1
00:00:00,200 --> 00:00:03,600
Speaker 1: In alex Egan producing Sandy Collins with news.

2
00:00:04,800 --> 00:00:06,560
Speaker 2: You know, we were here on Friday and it was

3
00:00:06,600 --> 00:00:11,120
Speaker 2: like sixty eight and this weather has been crazy.

4
00:00:11,000 --> 00:00:11,640
Speaker 3: Pneumonia weather.

5
00:00:11,640 --> 00:00:16,240
Speaker 2: It's my grandma call hold out weather, whiplane, Yes, twenty

6
00:00:16,400 --> 00:00:19,160
Speaker 2: seven degrees right now according to my iPhone.

7
00:00:19,400 --> 00:00:21,760
Speaker 1: Is it not supposed to warm up again too sooner

8
00:00:21,800 --> 00:00:23,840
Speaker 1: than later or something? I mean, I wasn't trying to

9
00:00:23,880 --> 00:00:26,160
Speaker 1: pressure you. Look at you looking for the extended forecast.

10
00:00:26,880 --> 00:00:29,040
Speaker 1: I'm looking at the ninth first morning weather and you

11
00:00:29,080 --> 00:00:31,320
Speaker 1: may have already heard it. With Sandy close to fifty

12
00:00:31,320 --> 00:00:33,440
Speaker 1: Tuesday forties the start of the week. Today's just a

13
00:00:33,479 --> 00:00:35,440
Speaker 1: little chilli. It's not bad to come. I mean it

14
00:00:35,520 --> 00:00:36,400
Speaker 1: is January.

15
00:00:36,720 --> 00:00:38,640
Speaker 2: Yeah, I mean, you know this is the weather that

16
00:00:38,680 --> 00:00:41,680
Speaker 2: we expect in the Shri state in January. For sure.

17
00:00:41,800 --> 00:00:44,480
Speaker 1: In wait eight minutes, it'll change and sooner than later

18
00:00:44,479 --> 00:00:47,600
Speaker 1: they'll be playing baseball, great American Ballpark, and life is

19
00:00:47,640 --> 00:00:50,760
Speaker 1: good and man lot going on. Doctor Donnad Schlake going

20
00:00:50,840 --> 00:00:53,639
Speaker 1: to join us after the twelve thirty report, we'll hear

21
00:00:54,120 --> 00:00:56,680
Speaker 1: the world is changing. There's a lot going on in Iran,

22
00:00:57,040 --> 00:01:02,160
Speaker 1: in Syria, in Minneapolis, protest across country about ice stuff.

23
00:01:02,520 --> 00:01:03,760
Speaker 2: Something about Greenland.

24
00:01:04,280 --> 00:01:06,800
Speaker 1: I've heard about that, something about that the easy way

25
00:01:06,880 --> 00:01:08,720
Speaker 1: or the hard way. I don't know what that means.

26
00:01:09,480 --> 00:01:11,920
Speaker 1: I've heard that in bad past relationships. So you did

27
00:01:11,959 --> 00:01:13,200
Speaker 1: that way of the hard way.

28
00:01:13,400 --> 00:01:16,520
Speaker 2: You know, when you look at the footage of Minneapolis

29
00:01:16,520 --> 00:01:18,640
Speaker 2: and stuff like that, and the ice agents and the

30
00:01:18,640 --> 00:01:21,320
Speaker 2: clashing with protesters and things like that, it doesn't even

31
00:01:21,440 --> 00:01:24,640
Speaker 2: look like this country to me. It looks like I'm

32
00:01:24,680 --> 00:01:27,920
Speaker 2: watching something you know, foreign.

33
00:01:28,360 --> 00:01:33,400
Speaker 1: Yes, yeah, I mean, you know, it's challenging times, interesting times,

34
00:01:34,080 --> 00:01:37,240
Speaker 1: And we'll talk to doctor donas Schleheck about it. She

35
00:01:37,480 --> 00:01:40,000
Speaker 1: is a Cincinnati kid and she was the head of

36
00:01:40,040 --> 00:01:42,920
Speaker 1: political science at right State now professor Meredith, and she

37
00:01:43,000 --> 00:01:45,800
Speaker 1: spent about ten years in Minneapolis. I think she may

38
00:01:45,800 --> 00:01:47,360
Speaker 1: have gone to school there and she also did some

39
00:01:47,400 --> 00:01:49,440
Speaker 1: other stuff there. So we'll get into her head about that,

40
00:01:49,520 --> 00:01:51,680
Speaker 1: as well as everything else that's going on. There's a

41
00:01:51,680 --> 00:01:54,200
Speaker 1: lot of spinning plates at the moment. Yeah, I mean

42
00:01:54,320 --> 00:02:00,240
Speaker 1: there's definitely not. There's there's plenty to talk about today.

43
00:02:01,360 --> 00:02:04,600
Speaker 1: There's no shortage of topics, no to talk about today.

44
00:02:04,840 --> 00:02:06,240
Speaker 3: And I don't know what you were doing. I know

45
00:02:06,280 --> 00:02:08,480
Speaker 3: you've had a wild weekend, Donna.

46
00:02:08,520 --> 00:02:11,720
Speaker 1: But I last night I was juggling on my own

47
00:02:11,760 --> 00:02:14,120
Speaker 1: stuff and we were texting back and forth.

48
00:02:14,160 --> 00:02:15,760
Speaker 3: I don't know if you call it. I can't even remember.

49
00:02:15,960 --> 00:02:17,160
Speaker 1: And it was one of them you're not getting back

50
00:02:17,160 --> 00:02:19,200
Speaker 1: to me or whatever the usual, and I'm like, look,

51
00:02:19,240 --> 00:02:21,000
Speaker 1: I'm wrangling cats, I'm trying to cook.

52
00:02:21,040 --> 00:02:22,200
Speaker 3: The dog's going crazy.

53
00:02:22,200 --> 00:02:24,079
Speaker 2: But I got a million on my plate.

54
00:02:24,200 --> 00:02:26,320
Speaker 1: Yeah, I'm trying to work it. And I nearly dropped

55
00:02:26,320 --> 00:02:28,880
Speaker 1: the phone in a skillet with sauce. Not good if that,

56
00:02:29,320 --> 00:02:31,280
Speaker 1: because I didn't have it on a speaker, And as

57
00:02:31,320 --> 00:02:33,080
Speaker 1: I was doing that, and then I had football on

58
00:02:33,400 --> 00:02:35,440
Speaker 1: as I was trying to crane my neck around to

59
00:02:35,480 --> 00:02:38,560
Speaker 1: watch the screen, and I'm like, well, clearly this game

60
00:02:38,680 --> 00:02:43,520
Speaker 1: is over. So I turned off the football. No, I

61
00:02:43,600 --> 00:02:46,000
Speaker 1: totally did. I am shocked you did that.

62
00:02:46,080 --> 00:02:49,200
Speaker 2: You're one of those fans I turn off football because

63
00:02:49,200 --> 00:02:52,280
Speaker 2: you think it's over. And then bam, both games. Like

64
00:02:52,360 --> 00:02:54,200
Speaker 2: we were at the hard Rock, a bunch of us,

65
00:02:54,800 --> 00:02:56,919
Speaker 2: and it was first time I've been to the hard

66
00:02:57,000 --> 00:03:00,600
Speaker 2: Rock in Cincinnati. It was actually very very fun. Yeah.

67
00:03:01,600 --> 00:03:06,440
Speaker 2: The l A Rams What a game that was, I mean,

68
00:03:06,639 --> 00:03:10,760
Speaker 2: and then Bears and Packers.

69
00:03:11,040 --> 00:03:13,800
Speaker 1: Wow, and sent the packers pack and it was kind

70
00:03:13,800 --> 00:03:17,280
Speaker 1: of weird in Chicago. I mean, they're like Glee. I

71
00:03:17,280 --> 00:03:19,799
Speaker 1: guess Glee talk about a comeback.

72
00:03:20,040 --> 00:03:21,040
Speaker 3: Yeah, and you.

73
00:03:21,000 --> 00:03:23,120
Speaker 1: Heard ken Brew earlier. You're talking to what would the

74
00:03:23,160 --> 00:03:25,360
Speaker 1: Bengals do early? You know, so we'll figure out what

75
00:03:25,400 --> 00:03:27,840
Speaker 1: they do for the coming season. They've got work to do,

76
00:03:27,919 --> 00:03:29,200
Speaker 1: so it gets kind of odd.

77
00:03:29,840 --> 00:03:30,040
Speaker 2: You know.

78
00:03:30,120 --> 00:03:32,680
Speaker 1: The other thing that's going crazy right now, that's gotten

79
00:03:32,720 --> 00:03:35,600
Speaker 1: a bunch of attention, and I'm sort of surprised. I mean,

80
00:03:35,640 --> 00:03:37,520
Speaker 1: there's a connection with the guy. I think he's from Mason,

81
00:03:38,120 --> 00:03:41,320
Speaker 1: the dentist and his wife. He and her both murdered

82
00:03:41,360 --> 00:03:44,520
Speaker 1: in Columbus. We were talking about that last night. What

83
00:03:44,560 --> 00:03:48,640
Speaker 1: a crazy story. Yeah, and everybody apparently all over the country.

84
00:03:48,640 --> 00:03:50,960
Speaker 1: Anjeanette Levy was friend of the show. You used to

85
00:03:51,640 --> 00:03:53,800
Speaker 1: work in town as a reporter, anchor stup, but now

86
00:03:53,800 --> 00:03:56,760
Speaker 1: she does long crime. She was anchoring and covering a

87
00:03:56,760 --> 00:04:01,160
Speaker 1: lot of that as well. They arrested the husband. They've

88
00:04:01,160 --> 00:04:02,640
Speaker 1: been divorced for a long time.

89
00:04:02,680 --> 00:04:07,440
Speaker 2: Eight years they were divorced. And how how I mean

90
00:04:07,520 --> 00:04:10,680
Speaker 2: this story is going to continue to unfold, But why

91
00:04:10,720 --> 00:04:11,880
Speaker 2: don't you just explain what.

92
00:04:11,880 --> 00:04:14,680
Speaker 1: Happened since well, well I know that what happened is

93
00:04:14,680 --> 00:04:18,920
Speaker 1: is the allegation is apparently he came to Columbus and allegedly,

94
00:04:19,200 --> 00:04:21,400
Speaker 1: because he's been charged with their murders, he left the

95
00:04:21,480 --> 00:04:24,400
Speaker 1: kids in the in the either a dog or whatever

96
00:04:24,440 --> 00:04:28,360
Speaker 1: other pets unharmed, and then got out of town or

97
00:04:28,480 --> 00:04:32,080
Speaker 1: at least tried to escape and shot them.

98
00:04:32,200 --> 00:04:32,640
Speaker 3: And I don't know.

99
00:04:32,680 --> 00:04:35,719
Speaker 1: It was contentious proceedings with the divorce, and it seemed

100
00:04:35,760 --> 00:04:37,840
Speaker 1: to drag on a long time because these people were married.

101
00:04:37,839 --> 00:04:41,120
Speaker 1: For you, they had kids and everything, right, It's just

102
00:04:41,320 --> 00:04:44,839
Speaker 1: odd and you hear about these stories and you constantly

103
00:04:44,880 --> 00:04:48,119
Speaker 1: talk about relationship stuff. You've got your relationship show, Donna.

104
00:04:48,960 --> 00:04:52,440
Speaker 1: It is bewildering to think that something one would drag

105
00:04:52,480 --> 00:04:54,680
Speaker 1: on that long after you've gone on to the next thing.

106
00:04:55,360 --> 00:04:57,680
Speaker 1: And then whatever is the allegation is that he came

107
00:04:57,880 --> 00:04:59,960
Speaker 1: and killed her his ex and then you know her

108
00:05:00,160 --> 00:05:03,320
Speaker 1: current husband. What a just a nightmare scenario because you

109
00:05:03,320 --> 00:05:05,560
Speaker 1: think you're living your own idealic life and then something

110
00:05:05,600 --> 00:05:07,720
Speaker 1: from the past comes and get you. I would think

111
00:05:07,760 --> 00:05:09,960
Speaker 1: it'd be over by then and somebody would move on.

112
00:05:10,279 --> 00:05:13,440
Speaker 2: Yeah, I mean, so I was always I was talking

113
00:05:13,720 --> 00:05:15,800
Speaker 2: with my friend Dia last night about this case, and

114
00:05:16,200 --> 00:05:18,960
Speaker 2: I said, you know, I have remained friends with my

115
00:05:19,400 --> 00:05:22,159
Speaker 2: all my exes. Really we still text. I mean not

116
00:05:22,160 --> 00:05:24,440
Speaker 2: not on a daily basis by any means, but like

117
00:05:24,480 --> 00:05:30,359
Speaker 2: we keep in touch, and yeah, it's healthy and for

118
00:05:30,440 --> 00:05:33,200
Speaker 2: a relationship to be over for so long, and I

119
00:05:33,200 --> 00:05:38,440
Speaker 2: don't think they had kids, so with an eight year stretch,

120
00:05:39,000 --> 00:05:45,240
Speaker 2: she's remarried. Something there has to be something that happened

121
00:05:46,080 --> 00:05:50,120
Speaker 2: to bring him to Columbus and on her doorstep.

122
00:05:50,680 --> 00:05:54,400
Speaker 1: I mean, it's you know what I don't understand though,

123
00:05:54,440 --> 00:05:59,520
Speaker 1: is how anybody without knowing the psychology behind whatever he's

124
00:05:59,520 --> 00:06:01,840
Speaker 1: alleged have done. Because we don't need a lawsuit, right,

125
00:06:02,680 --> 00:06:05,680
Speaker 1: but just the thing where people can't let go or

126
00:06:05,720 --> 00:06:08,599
Speaker 1: are so bitter and vindictive either how it ended, or

127
00:06:08,640 --> 00:06:11,039
Speaker 1: giving up half or more than half, or or just

128
00:06:11,240 --> 00:06:14,320
Speaker 1: whatever it is where somebody slips and they decide, well, okay,

129
00:06:14,360 --> 00:06:17,480
Speaker 1: well I'll get you, and then somebody has oftentimes it's

130
00:06:17,560 --> 00:06:20,440
Speaker 1: murder suicide. But he just came took them, allegedly, and

131
00:06:20,680 --> 00:06:24,600
Speaker 1: it took their lives and then left. I just I mean,

132
00:06:24,640 --> 00:06:30,480
Speaker 1: I've been despondent, I've been upset, I've been emotionally devastated.

133
00:06:30,760 --> 00:06:36,000
Speaker 1: I've been financially wrecked and splits and everything else, and

134
00:06:37,200 --> 00:06:39,400
Speaker 1: I just can't imagine at some point where you just

135
00:06:39,480 --> 00:06:43,360
Speaker 1: can't turn the corner and carry on without doing something

136
00:06:43,400 --> 00:06:45,400
Speaker 1: like this. It'll be interesting to see how it plays out.

137
00:06:45,480 --> 00:06:47,680
Speaker 1: But the whole count has been paying attention to that.

138
00:06:47,880 --> 00:06:51,680
Speaker 2: Yeah, I mean, what an awful story. I mean, such

139
00:06:51,720 --> 00:06:57,880
Speaker 2: a cute young couple, you know, right after Christmas, between

140
00:06:57,920 --> 00:07:01,320
Speaker 2: Christmas and New Year's and I yeah, this guy is

141
00:07:01,400 --> 00:07:04,440
Speaker 2: now charged charged the ex is charged with the murder

142
00:07:04,480 --> 00:07:07,640
Speaker 2: of these two people, and he was arrested on Saturday,

143
00:07:07,760 --> 00:07:13,720
Speaker 2: January tenth. I mean, what can possess somebody to do that? Anyway,

144
00:07:13,840 --> 00:07:15,960
Speaker 2: Just like you said, you've been hurt, you've been upset,

145
00:07:16,000 --> 00:07:17,760
Speaker 2: You've had to deal with your own emotions and your

146
00:07:17,800 --> 00:07:20,760
Speaker 2: own feelings. We all do. There's nobody at the over

147
00:07:20,880 --> 00:07:24,119
Speaker 2: the age of probably fifteen, in this life that hasn't

148
00:07:24,120 --> 00:07:30,080
Speaker 2: had to deal with a breakup. And it's just awful.

149
00:07:30,240 --> 00:07:33,120
Speaker 2: It's just absolutely awful. I don't care what the excuse

150
00:07:33,240 --> 00:07:35,840
Speaker 2: is that he had. You don't do that. I mean,

151
00:07:35,880 --> 00:07:39,679
Speaker 2: obviously it's just a devastating thing. But how they came

152
00:07:39,760 --> 00:07:43,360
Speaker 2: back into each other's lives, or how he decided to

153
00:07:43,360 --> 00:07:46,320
Speaker 2: come back into her life like that. It's just beyond me.

154
00:07:46,680 --> 00:07:49,280
Speaker 1: It really is a difficult thing. Also to imagine how

155
00:07:49,280 --> 00:07:52,240
Speaker 1: the surviving members of the family extended that are going

156
00:07:52,280 --> 00:07:54,720
Speaker 1: to have to navigate that and at some point probably

157
00:07:54,760 --> 00:07:57,600
Speaker 1: have to explain to the children, hopefully they weren't able

158
00:07:57,640 --> 00:08:01,120
Speaker 1: to see anything too graphically disturbing, but have to explain

159
00:08:01,160 --> 00:08:04,240
Speaker 1: to them somehow where their parents went in the circumstance

160
00:08:04,320 --> 00:08:07,680
Speaker 1: around that, I mean, when they ask, or how it

161
00:08:07,720 --> 00:08:10,560
Speaker 1: comes up. I mean, it's just a lot of layers

162
00:08:10,600 --> 00:08:13,720
Speaker 1: of sadness that sort of go along with that. And

163
00:08:13,800 --> 00:08:15,880
Speaker 1: every day in the news there's all kinds of different

164
00:08:15,920 --> 00:08:18,920
Speaker 1: tragedy and horrible stuff from you know, the eleven year

165
00:08:18,920 --> 00:08:21,360
Speaker 1: old just a little over a week ago who was

166
00:08:21,480 --> 00:08:24,680
Speaker 1: gunned down in the playground, continuing to you know, investigate

167
00:08:24,720 --> 00:08:28,760
Speaker 1: that Cincinnati homicide and law enforcement and that family trying

168
00:08:28,800 --> 00:08:31,680
Speaker 1: to carry on in some fashion, and then a few

169
00:08:31,760 --> 00:08:34,000
Speaker 1: years earlier, another eleven year old there. I'm not trying

170
00:08:34,040 --> 00:08:35,840
Speaker 1: to be the prophet of doom. I'm just saying there's

171
00:08:35,880 --> 00:08:38,520
Speaker 1: a lot of this that's dealt with on a regular basis,

172
00:08:39,160 --> 00:08:42,160
Speaker 1: and here you'd think in a relationship situation you'd be

173
00:08:42,160 --> 00:08:44,440
Speaker 1: beyond it. But I guess the danger is always there.

174
00:08:44,600 --> 00:08:46,559
Speaker 2: It's just I think we're going to find out a

175
00:08:46,640 --> 00:08:49,760
Speaker 2: lot more about this story and it's going to be hard,

176
00:08:49,920 --> 00:08:51,600
Speaker 2: hard to come back from.

177
00:08:51,720 --> 00:08:51,920
Speaker 3: Yeah.

178
00:08:51,960 --> 00:08:54,920
Speaker 1: Absolutely. You know the other thing too. Bob Weir, co

179
00:08:55,040 --> 00:08:58,080
Speaker 1: founder Grateful Dead, seventy eight years old, passed away. He

180
00:08:58,120 --> 00:09:02,680
Speaker 1: had apparently beaten camp sir and going back to May,

181
00:09:02,760 --> 00:09:05,199
Speaker 1: had dealt with treatments and everything else, but had some

182
00:09:05,280 --> 00:09:10,280
Speaker 1: type of lingering, long term problem with his lung or

183
00:09:10,400 --> 00:09:14,720
Speaker 1: lungs that ended up apparently ending him. Is a word

184
00:09:14,800 --> 00:09:18,040
Speaker 1: of his passing came out yesterday, I guess is when

185
00:09:18,080 --> 00:09:21,480
Speaker 1: it was, which is is just devastating guitarist singer. I

186
00:09:21,520 --> 00:09:23,720
Speaker 1: mean you've probably seen him, I don't even know how

187
00:09:23,720 --> 00:09:26,040
Speaker 1: many times when when it was the Grateful Dead and

188
00:09:26,080 --> 00:09:28,120
Speaker 1: then with Dead and Company here in town, have.

189
00:09:28,160 --> 00:09:29,679
Speaker 2: You seen I've never seen.

190
00:09:31,040 --> 00:09:33,400
Speaker 1: Yeah, Yeah, Dead and Company of course was a John

191
00:09:33,440 --> 00:09:35,439
Speaker 1: Mayer who's been with them and in a group of

192
00:09:36,040 --> 00:09:39,040
Speaker 1: touring artists of one type or another of band members,

193
00:09:39,040 --> 00:09:42,160
Speaker 1: et CETERA. Final show I think was in August. He

194
00:09:42,200 --> 00:09:47,079
Speaker 1: appeared with them in San Francisco, and I don't know

195
00:09:47,080 --> 00:09:48,920
Speaker 1: if they were wrapping up the tour, if it was

196
00:09:48,960 --> 00:09:50,600
Speaker 1: a one off show or whatever else.

197
00:09:50,760 --> 00:09:51,880
Speaker 3: I saw some video of that.

198
00:09:52,000 --> 00:09:55,720
Speaker 1: He sounded, you know, weak, voice wise, but was there

199
00:09:55,760 --> 00:09:58,160
Speaker 1: and seemed like he was getting it done. I don't

200
00:09:58,160 --> 00:09:59,760
Speaker 1: know that anybody there thought that it was going to

201
00:09:59,800 --> 00:10:02,240
Speaker 1: be the last time that he'd be performing, let alone,

202
00:10:02,280 --> 00:10:03,400
Speaker 1: not with us, for very night.

203
00:10:04,160 --> 00:10:04,679
Speaker 3: It's tough.

204
00:10:04,800 --> 00:10:08,840
Speaker 2: Seventy nine seventy eight. I mean, it doesn't even seem

205
00:10:08,960 --> 00:10:10,120
Speaker 2: old to me anymore.

206
00:10:10,200 --> 00:10:13,160
Speaker 1: Seventy eight, well Alex Egan was producing, would probably be

207
00:10:13,280 --> 00:10:14,280
Speaker 1: the difference.

208
00:10:16,480 --> 00:10:16,960
Speaker 3: Seven whatever.

209
00:10:17,360 --> 00:10:19,679
Speaker 1: But I mean, that's a window of time and it

210
00:10:19,679 --> 00:10:22,080
Speaker 1: does come quickly. But the thing is, it's pretty amazing

211
00:10:22,120 --> 00:10:25,160
Speaker 1: to me is that that music will live on forever

212
00:10:25,240 --> 00:10:28,040
Speaker 1: and always, and that's a pretty amazing footprint to leave

213
00:10:28,080 --> 00:10:29,160
Speaker 1: behind for a lot of people.

214
00:10:29,280 --> 00:10:32,720
Speaker 2: There's nobody liked the Grateful Dead. They really they were

215
00:10:32,760 --> 00:10:37,160
Speaker 2: pioneers way back when. And you know, I wished now

216
00:10:37,240 --> 00:10:41,400
Speaker 2: thinking about it, I've seen so many bands that I loved,

217
00:10:41,440 --> 00:10:44,880
Speaker 2: and I would have loved to have been been at

218
00:10:44,920 --> 00:10:46,360
Speaker 2: one Grateful Dead concert.

219
00:10:46,520 --> 00:10:48,679
Speaker 1: My guess is Dead and Company will continue on in

220
00:10:48,720 --> 00:10:51,880
Speaker 1: some fashion. Yeah, I would hope at some point. What

221
00:10:51,960 --> 00:10:54,160
Speaker 1: I can tell you it's more than just dirty, stinky,

222
00:10:54,280 --> 00:10:56,520
Speaker 1: you know, paturely wearing hippie chicks, although I like them

223
00:10:57,480 --> 00:11:00,200
Speaker 1: right right right, looking for a miracle and all what

224
00:11:00,240 --> 00:11:02,240
Speaker 1: I will tell you in short order. And this is

225
00:11:02,240 --> 00:11:04,160
Speaker 1: an odd store. I don't know if she'll call. She

226
00:11:04,240 --> 00:11:07,320
Speaker 1: often listens. Good friend of mine. Years ago, I took

227
00:11:07,320 --> 00:11:10,640
Speaker 1: her to her first dead show and we drove up

228
00:11:10,679 --> 00:11:13,200
Speaker 1: to Cleveland. This has been years ago, in the mid nineties,

229
00:11:13,240 --> 00:11:16,880
Speaker 1: mid late nineties. And then she just sort of disappeared

230
00:11:16,880 --> 00:11:19,240
Speaker 1: for a while. She went on the road in like

231
00:11:19,679 --> 00:11:23,160
Speaker 1: she became a dead end. Yes, she camped and traveled

232
00:11:23,200 --> 00:11:24,360
Speaker 1: all over the country.

233
00:11:24,640 --> 00:11:27,040
Speaker 2: That's what happens when you go to a dead show

234
00:11:27,240 --> 00:11:30,040
Speaker 2: is because you just kept mesmerized and you don't want

235
00:11:30,040 --> 00:11:32,080
Speaker 2: the party to end. That's what happens.

236
00:11:32,600 --> 00:11:35,079
Speaker 1: It's a different energy and a different vibe and a

237
00:11:35,679 --> 00:11:37,400
Speaker 1: great experience for her. And it was odd. It was like,

238
00:11:37,480 --> 00:11:39,199
Speaker 1: what have you been doing? She's like, well, I've been here,

239
00:11:39,200 --> 00:11:41,520
Speaker 1: there and everywhere. And I'm like, holy crap, what happened?

240
00:11:42,000 --> 00:11:43,120
Speaker 2: And she was like, what's your fault?

241
00:11:43,120 --> 00:11:43,320
Speaker 4: You know?

242
00:11:43,440 --> 00:11:44,920
Speaker 1: And I'm like, I don't know, I don't know if

243
00:11:44,960 --> 00:11:47,559
Speaker 1: I did that I didn't ever catch the hey, I'm

244
00:11:47,559 --> 00:11:49,640
Speaker 1: going to go on the road thing. But I was

245
00:11:49,679 --> 00:11:52,000
Speaker 1: always good for the you know, the magic of the

246
00:11:52,280 --> 00:11:54,040
Speaker 1: show and the music and everything and the.

247
00:11:54,480 --> 00:11:56,760
Speaker 2: But that's how it happens to a lot of people.

248
00:11:56,920 --> 00:11:58,400
Speaker 1: It does, and I know a whole lot of people

249
00:11:58,440 --> 00:12:01,440
Speaker 1: have reached out and talking about the too. Later on,

250
00:12:01,480 --> 00:12:03,640
Speaker 1: we'll also get into a little bit of I love

251
00:12:03,720 --> 00:12:07,240
Speaker 1: movies and I know you do too. We talked to

252
00:12:07,320 --> 00:12:10,160
Speaker 1: Kevin Carr Friday when we were in for Sloany and

253
00:12:10,400 --> 00:12:12,960
Speaker 1: aside the stuff that's new, the award shows, I'm always

254
00:12:13,000 --> 00:12:16,600
Speaker 1: sort of bogged because judging what the best in anything

255
00:12:16,720 --> 00:12:19,240
Speaker 1: is when it comes to artists subjective and challenging.

256
00:12:20,000 --> 00:12:22,680
Speaker 2: Yeah, but you kind of have your favorite, I mean,

257
00:12:22,960 --> 00:12:26,680
Speaker 2: and there's there's quite a few that are gonna be up.

258
00:12:26,760 --> 00:12:29,320
Speaker 2: The Golden Globes is what we're talking to talking about,

259
00:12:29,520 --> 00:12:32,600
Speaker 2: is on tonight, Yeah, and it's gonna be you know,

260
00:12:33,360 --> 00:12:36,600
Speaker 2: I don't know what kind of an audience there is

261
00:12:36,640 --> 00:12:39,720
Speaker 2: for award shows anymore, myself included. I used to love

262
00:12:39,880 --> 00:12:43,120
Speaker 2: the Grammys, the Golden Globes and the Oscars. I've been

263
00:12:43,200 --> 00:12:47,440
Speaker 2: seen those are my top favorite. I'ven't seen the Grammys

264
00:12:47,440 --> 00:12:49,360
Speaker 2: in a while. I do want to watch the Golden

265
00:12:49,360 --> 00:12:52,560
Speaker 2: Globes tonight. There's a ton of football on thom And

266
00:12:52,640 --> 00:12:54,920
Speaker 2: Oh yeah, and the football games are going to be

267
00:12:55,080 --> 00:12:56,880
Speaker 2: absolutely off the charts. Good.

268
00:12:57,120 --> 00:13:00,280
Speaker 1: Yeah, I mean, you've got Bill's Jags later forty nine, Hers,

269
00:13:00,320 --> 00:13:04,080
Speaker 1: Eagles and Chargers and Patriots. Somehow Patriots got back into

270
00:13:04,080 --> 00:13:07,360
Speaker 1: the playoffs as well, and we'll tune you up for

271
00:13:07,400 --> 00:13:10,160
Speaker 1: that a little bit later too. The award show stuff

272
00:13:10,200 --> 00:13:14,320
Speaker 1: is always interesting one aside from the it's hard to

273
00:13:14,480 --> 00:13:17,280
Speaker 1: you know, your favorites are my favorites compared to the best.

274
00:13:17,559 --> 00:13:19,880
Speaker 1: I always like at least the nomination list, so I

275
00:13:19,920 --> 00:13:22,240
Speaker 1: know that it must be extraordinary work that people have

276
00:13:22,320 --> 00:13:24,600
Speaker 1: put out that I need to investigate and check out

277
00:13:24,600 --> 00:13:28,679
Speaker 1: if I've missed it already. In that fashion, the Golden Globes, though,

278
00:13:28,679 --> 00:13:30,839
Speaker 1: at least it's not so buttoned down, you know, it's

279
00:13:30,880 --> 00:13:35,800
Speaker 1: more relaxed. They're drunk, probably high, and they're goofing off.

280
00:13:35,840 --> 00:13:39,920
Speaker 2: Dicky Glazier is hosting, and she's quite funny. She was

281
00:13:39,960 --> 00:13:43,040
Speaker 2: probably the funniest one at the Tom Brady Roast. She

282
00:13:43,160 --> 00:13:46,800
Speaker 2: was there. But she's she's gonna probably do a good

283
00:13:46,880 --> 00:13:50,240
Speaker 2: jobs there's a ton to laugh at, at least in

284
00:13:50,320 --> 00:13:54,440
Speaker 2: this country right now, you know, pick fun at, gotta laugh. Yeah,

285
00:13:54,480 --> 00:13:59,760
Speaker 2: I mean, I do think the two big contenders tonight

286
00:14:00,000 --> 00:14:07,240
Speaker 2: obviously are going to be Leonardo DiCaprio and Timothy Shallo May, right,

287
00:14:07,520 --> 00:14:10,040
Speaker 2: and those those are the two who's going to win

288
00:14:10,640 --> 00:14:11,280
Speaker 2: Best Actor.

289
00:14:11,800 --> 00:14:13,280
Speaker 3: I always get confused with you.

290
00:14:13,480 --> 00:14:15,800
Speaker 1: I mentioned this Friday, Shallo May and the guy from

291
00:14:15,840 --> 00:14:16,880
Speaker 1: the Bear TV show.

292
00:14:17,080 --> 00:14:17,960
Speaker 2: I know you said that.

293
00:14:18,040 --> 00:14:18,480
Speaker 3: I don't know.

294
00:14:18,640 --> 00:14:21,720
Speaker 1: There's some random dudes. I don't know. They don't seem

295
00:14:21,960 --> 00:14:24,920
Speaker 1: they both do good work. But I honestly, like side

296
00:14:24,920 --> 00:14:27,240
Speaker 1: by side, I would not have any idea which one

297
00:14:27,280 --> 00:14:29,560
Speaker 1: was which. Which is sad but true.

298
00:14:30,840 --> 00:14:33,280
Speaker 2: What's going on with your voice over there? In mind too?

299
00:14:33,440 --> 00:14:36,400
Speaker 2: Like what it's the weather. Let's blame it on the

300
00:14:36,440 --> 00:14:38,040
Speaker 2: weather because it's been so crazy.

301
00:14:38,200 --> 00:14:41,320
Speaker 1: That's it. It's true. I'm staying keeping a distance. I'm clean,

302
00:14:41,360 --> 00:14:45,000
Speaker 1: I've been sanitized, martinized. Everything is good. I have no fever,

303
00:14:45,240 --> 00:14:49,040
Speaker 1: no worries. Everything is great. Although there is a lot

304
00:14:49,080 --> 00:14:51,200
Speaker 1: of flu out there. Yeah, you know, a lot of

305
00:14:51,200 --> 00:14:52,080
Speaker 1: people kind of it.

306
00:14:52,160 --> 00:14:54,160
Speaker 2: By the way, Oh gosh, I have friends that have it.

307
00:14:54,280 --> 00:14:58,520
Speaker 2: By the way, the eighty third annual eighty third Annual

308
00:14:58,560 --> 00:15:01,720
Speaker 2: Golden Globes are on tonight eight o'clock CBS.

309
00:15:01,800 --> 00:15:04,320
Speaker 1: Yeah, there you go, all right, So straight away your

310
00:15:04,320 --> 00:15:06,960
Speaker 1: twelve thirty reports. Sandy Collins has an update on what's

311
00:15:06,960 --> 00:15:09,720
Speaker 1: going on around planet Earth. It's busy, including stuff here

312
00:15:09,720 --> 00:15:12,280
Speaker 1: in the Tri State. Doctor Donna Schleck will join us.

313
00:15:12,280 --> 00:15:14,480
Speaker 1: She's the former head of political science at right State

314
00:15:14,560 --> 00:15:17,560
Speaker 1: now professor Mereda. We'll get the latest on what's going

315
00:15:17,560 --> 00:15:21,720
Speaker 1: on with protest against ice and engagements with population here Stateside,

316
00:15:21,720 --> 00:15:25,000
Speaker 1: all over the country, Minneapolis as well. And then of course,

317
00:15:25,640 --> 00:15:29,520
Speaker 1: you know, as you mentioned, shopping for Greenland. We've got

318
00:15:29,600 --> 00:15:32,400
Speaker 1: Venezuela on the table. We're getting there a while apparently.

319
00:15:33,640 --> 00:15:38,120
Speaker 1: And what else the Syria. We did some bombing in

320
00:15:38,160 --> 00:15:42,120
Speaker 1: Syria yesterday and overnight, right, so that's happening. She may

321
00:15:42,160 --> 00:15:44,920
Speaker 1: have some stuff on that. And did I mention Iran

322
00:15:45,000 --> 00:15:47,720
Speaker 1: where the protests just keep growing and in the midst

323
00:15:47,760 --> 00:15:50,040
Speaker 1: of the shaking of the tree and the president saying

324
00:15:50,080 --> 00:15:53,000
Speaker 1: we've got your back, perhaps there is another spring of

325
00:15:53,040 --> 00:15:56,560
Speaker 1: sorts in the Middle East and maybe people will get

326
00:15:56,600 --> 00:15:59,440
Speaker 1: a little taste of freedom in Iran again. So we'll see,

327
00:15:59,520 --> 00:16:01,600
Speaker 1: we'll pick her about all that and more coming up

328
00:16:01,640 --> 00:16:04,760
Speaker 1: straight away your twelve thirty report. She's donnade I'm Sterling

329
00:16:04,800 --> 00:16:09,680
Speaker 1: in this as seven hundred WLW an international World Affairs

330
00:16:09,680 --> 00:16:10,480
Speaker 1: and Politics.

331
00:16:10,480 --> 00:16:11,080
Speaker 3: How are you at?

332
00:16:11,120 --> 00:16:15,520
Speaker 1: Sterling and donnade back seven hundred WLW for your Sunday Afternoon.

333
00:16:15,560 --> 00:16:18,160
Speaker 1: Former had a political science at Wright State, now professor

334
00:16:18,200 --> 00:16:21,680
Speaker 1: of Merida. It's spent about ten years in Minneapolis. Believing

335
00:16:22,040 --> 00:16:23,800
Speaker 1: she may have gone to school there. I may have

336
00:16:24,120 --> 00:16:26,120
Speaker 1: done some work there. I know she vacationed there recently

337
00:16:26,160 --> 00:16:27,880
Speaker 1: because we talked to her and there were mosquitos the

338
00:16:27,920 --> 00:16:30,200
Speaker 1: size of small cars.

339
00:16:29,480 --> 00:16:31,560
Speaker 3: In the woods. Doctor Dona Schlecheck.

340
00:16:31,640 --> 00:16:34,600
Speaker 1: Welcome back to seven hundred WLW with Sterling and Donnadee.

341
00:16:34,600 --> 00:16:41,040
Speaker 5: How's everything, Hi, Sterling, Hello Donna, Spinning plates and circuses. Yes,

342
00:16:41,520 --> 00:16:43,520
Speaker 5: I think we've all bought a ticket. We have.

343
00:16:43,960 --> 00:16:46,640
Speaker 1: I know I didn't ask you specifically about Iran and

344
00:16:46,760 --> 00:16:50,640
Speaker 1: Syria since we pinged a text scheduling you today. But

345
00:16:50,720 --> 00:16:53,000
Speaker 1: before we get to Minnesota, before we get to the

346
00:16:53,000 --> 00:16:55,840
Speaker 1: ice protest across the country and everything else, what I

347
00:16:55,840 --> 00:17:00,200
Speaker 1: would like to know is Iran this is good for

348
00:17:00,240 --> 00:17:03,680
Speaker 1: the world, perhaps in our involvement in the president saying

349
00:17:03,680 --> 00:17:06,840
Speaker 1: that he would support the protesters in this situation as

350
00:17:06,880 --> 00:17:09,719
Speaker 1: things continue to escalate in that situation. And we can

351
00:17:09,760 --> 00:17:12,560
Speaker 1: also mention Syria too, We did some bombing there in

352
00:17:12,600 --> 00:17:14,720
Speaker 1: the last twenty four hours. Anywhere you want to go,

353
00:17:14,760 --> 00:17:15,600
Speaker 1: it's your choice.

354
00:17:16,680 --> 00:17:21,960
Speaker 5: It is time to return our attention to the Middle East,

355
00:17:22,040 --> 00:17:25,439
Speaker 5: and on the good news on hamas Is even saying

356
00:17:25,480 --> 00:17:30,680
Speaker 5: that when the next phase starts, they're dismantling their governance apparatus,

357
00:17:30,680 --> 00:17:34,920
Speaker 5: so good news. The strikes in Syria were clearly defined

358
00:17:34,920 --> 00:17:39,879
Speaker 5: to be punitive against ISIS multiple targets across Syria. The

359
00:17:40,320 --> 00:17:43,320
Speaker 5: subtle signals seemed to be that there may have been

360
00:17:43,400 --> 00:17:48,000
Speaker 5: consultation with Syria because the new government there is trying

361
00:17:48,000 --> 00:17:51,120
Speaker 5: to get control of the country and ISIS is their

362
00:17:51,160 --> 00:17:56,720
Speaker 5: biggest enemy. So this is actually the sideways version of

363
00:17:56,840 --> 00:18:01,240
Speaker 5: trying to help the new government of Syria after offsad regimes,

364
00:18:01,440 --> 00:18:05,879
Speaker 5: brutal treatment, to get their country back together again. And

365
00:18:06,160 --> 00:18:09,800
Speaker 5: it's obviously the Israelis will be involved as well. There's

366
00:18:09,840 --> 00:18:13,000
Speaker 5: talk about settling some of their border disputes. It's a

367
00:18:13,080 --> 00:18:16,720
Speaker 5: mixed picture. But the two Americans killed there a couple

368
00:18:16,800 --> 00:18:20,600
Speaker 5: of weeks ago were Hawkeye National Guardsmen, and so we

369
00:18:20,720 --> 00:18:24,840
Speaker 5: named the strike the retaliatory strike against them. The bigger

370
00:18:24,880 --> 00:18:30,000
Speaker 5: picture that you mentioned, though, what's happening in Iran? Have people? Finally,

371
00:18:30,280 --> 00:18:36,760
Speaker 5: it's interesting like Venezuela, oil, wealthy country, big population, and

372
00:18:36,920 --> 00:18:44,520
Speaker 5: yet horrendous economic circumstances, inflation, terrible cost of living, sanctions,

373
00:18:44,560 --> 00:18:49,160
Speaker 5: more sanctions, more sanctions, and yet with the means there

374
00:18:49,200 --> 00:18:51,600
Speaker 5: to do well by their people. What happens when a

375
00:18:51,680 --> 00:18:54,400
Speaker 5: third of your people have to leave the country because

376
00:18:54,440 --> 00:18:59,640
Speaker 5: of the utter, incredibly bad mismanagement of the economy. That's

377
00:18:59,680 --> 00:19:04,879
Speaker 5: what in Venezuela, That is the migration component. Link to

378
00:19:05,000 --> 00:19:08,639
Speaker 5: our grievances with Venezuela. But you know, we also have

379
00:19:08,720 --> 00:19:13,679
Speaker 5: a very large Iranian expact community in California in particular,

380
00:19:14,119 --> 00:19:16,800
Speaker 5: which is where the grandson of the Shaw lives and

381
00:19:17,200 --> 00:19:20,160
Speaker 5: is now offering to come back and help a transition

382
00:19:20,280 --> 00:19:24,520
Speaker 5: to democracy in Iran. These are some of the strangest

383
00:19:24,520 --> 00:19:28,320
Speaker 5: plates I've seen spinning in a long long time. That

384
00:19:28,480 --> 00:19:30,840
Speaker 5: was the Shaw of Iran that we allowed to come

385
00:19:30,840 --> 00:19:34,600
Speaker 5: here when he fled his country under Jimmy Carter to

386
00:19:35,119 --> 00:19:38,560
Speaker 5: receive health treatment. But that's what triggered the hostage crisis

387
00:19:38,600 --> 00:19:43,480
Speaker 5: in nineteen seventy nine. So these things are so interconnected.

388
00:19:43,720 --> 00:19:46,800
Speaker 5: How do we help the people of Iran? I don't know.

389
00:19:47,240 --> 00:19:49,919
Speaker 5: I think certainly we have a better picture in terms

390
00:19:49,920 --> 00:19:53,160
Speaker 5: of Venezuela. Try to put the wealth of the country

391
00:19:53,240 --> 00:19:56,639
Speaker 5: back to serving the people of Venezuela.

392
00:19:57,040 --> 00:19:57,520
Speaker 4: I don't know.

393
00:19:57,720 --> 00:19:59,520
Speaker 5: I have a question. What do you do if you're

394
00:19:59,520 --> 00:20:03,000
Speaker 5: in oilzec and President Trump would like you to invest

395
00:20:03,200 --> 00:20:06,160
Speaker 5: tens of billions that's with a B as in billions

396
00:20:06,200 --> 00:20:10,640
Speaker 5: of dollars to rebuild your oil infrastructure in a country

397
00:20:10,680 --> 00:20:14,679
Speaker 5: as unstable and uncertain as Venezuela. That has to be

398
00:20:14,800 --> 00:20:20,000
Speaker 5: President Trump has recently been consulting with the execs of Conocomobile, Exon,

399
00:20:21,200 --> 00:20:25,399
Speaker 5: Exon Mobil, excuse me, Conco, Phillips, and Chevron. He wants

400
00:20:25,400 --> 00:20:28,800
Speaker 5: them to take the lead in rebuilding the infrastructure. How

401
00:20:28,920 --> 00:20:31,760
Speaker 5: is your business? Do you make a massive investment in

402
00:20:31,800 --> 00:20:35,240
Speaker 5: a country where there is no law, there is no order?

403
00:20:36,320 --> 00:20:36,600
Speaker 4: Question?

404
00:20:36,720 --> 00:20:39,120
Speaker 5: We have to go back to those first questions.

405
00:20:39,200 --> 00:20:41,960
Speaker 1: Yes, I'm just saying we have to have policing of

406
00:20:42,000 --> 00:20:45,320
Speaker 1: some sort on the ground in that situation. Exon, for instance,

407
00:20:45,680 --> 00:20:48,240
Speaker 1: mentioned in that public hearing that usually that type of

408
00:20:48,240 --> 00:20:51,160
Speaker 1: conversation I think is private. So it was bizarrely awkward

409
00:20:51,200 --> 00:20:53,359
Speaker 1: in the way that we got to watch that whole

410
00:20:53,359 --> 00:20:55,920
Speaker 1: thing in the roundtables sort of go down the other day.

411
00:20:56,440 --> 00:20:58,639
Speaker 1: But talking to a former head of political science now

412
00:20:58,680 --> 00:21:02,280
Speaker 1: Professor Merida Wright, State doctor Donashleke was Stirling and Donnadee

413
00:21:02,320 --> 00:21:04,800
Speaker 1: on the big one. So they would want assurances that

414
00:21:04,800 --> 00:21:07,120
Speaker 1: they're not going to have everything that they put together

415
00:21:07,240 --> 00:21:09,800
Speaker 1: there be taken for the That would be the third

416
00:21:09,840 --> 00:21:12,439
Speaker 1: time it's happened twice to them, So that's part of it,

417
00:21:12,640 --> 00:21:15,960
Speaker 1: I guess right. It is guaranteeing that opportunity to suck

418
00:21:16,000 --> 00:21:20,240
Speaker 1: that black gold out of the ground and split that

419
00:21:20,359 --> 00:21:23,960
Speaker 1: resource with the people in Venezuela and obviously every everybody

420
00:21:24,000 --> 00:21:25,040
Speaker 1: else who has a hand in it.

421
00:21:25,080 --> 00:21:28,880
Speaker 3: For profit, right, that is the goal.

422
00:21:29,960 --> 00:21:33,200
Speaker 5: But there are hundreds of billions of dollars. It's been

423
00:21:33,280 --> 00:21:38,119
Speaker 5: twenty years that this infrastructure has been not maintained, over produced.

424
00:21:38,800 --> 00:21:41,080
Speaker 5: They now produce five to ten percent of the oil

425
00:21:41,160 --> 00:21:45,719
Speaker 5: that they used to be capable of. So a massive investment.

426
00:21:46,280 --> 00:21:50,000
Speaker 5: Who will guarantee that? Will it be the ships offshore

427
00:21:50,480 --> 00:21:53,639
Speaker 5: or I think the thing that worries most American is

428
00:21:53,800 --> 00:21:56,840
Speaker 5: Americans is will it be troops on the ground. Right

429
00:21:57,160 --> 00:22:00,080
Speaker 5: The question now what we're watching and we're waiting is

430
00:22:00,160 --> 00:22:04,520
Speaker 5: to see how the Venezuelan leadership can this new acting

431
00:22:04,600 --> 00:22:09,200
Speaker 5: president Delci comes out. Can she convinced that let's say

432
00:22:09,760 --> 00:22:14,080
Speaker 5: two sectors, defense and the interior, the police and the military.

433
00:22:14,480 --> 00:22:18,320
Speaker 5: Can they convince her to work with the Americans. That's

434
00:22:18,359 --> 00:22:22,960
Speaker 5: the conversation going on right now. She was a manager

435
00:22:23,119 --> 00:22:26,920
Speaker 5: for Maduro, you know, for a decade. She knows the

436
00:22:26,960 --> 00:22:31,280
Speaker 5: economic picture, but she's not controlling the two big components

437
00:22:31,560 --> 00:22:34,680
Speaker 5: that we need to work with us to make this

438
00:22:34,800 --> 00:22:40,600
Speaker 5: intervention happen. And that's that's literally what we are waiting

439
00:22:40,680 --> 00:22:44,000
Speaker 5: to see what they choose, how they choose to proceed.

440
00:22:44,320 --> 00:22:47,040
Speaker 5: She's well connected with all the other elites in the country.

441
00:22:48,000 --> 00:22:51,920
Speaker 5: But Defense and the interior, the police, you know, the

442
00:22:52,080 --> 00:22:56,440
Speaker 5: the intel forces, the prisons, et cetera. What will they do,

443
00:22:56,560 --> 00:23:00,320
Speaker 5: how will they will they participate in this or will

444
00:23:00,359 --> 00:23:04,040
Speaker 5: the United States have to use more force? And that's

445
00:23:04,080 --> 00:23:07,439
Speaker 5: when we hit the real rubicon, that that that point

446
00:23:07,520 --> 00:23:10,639
Speaker 5: where our boots on the ground going to be required.

447
00:23:11,040 --> 00:23:15,479
Speaker 5: President Trump promised no more forever wars, uh, you know,

448
00:23:15,560 --> 00:23:19,760
Speaker 5: no more interventions. Well, here we are with the national

449
00:23:19,800 --> 00:23:23,760
Speaker 5: security interest, energy, migration, the mineral purity.

450
00:23:23,840 --> 00:23:28,840
Speaker 2: Uh huh. And so doctor Dona, there's the minerals in Venezuela.

451
00:23:28,920 --> 00:23:31,720
Speaker 2: They're definitely going to be capturing that and the oil

452
00:23:31,760 --> 00:23:34,720
Speaker 2: as well. But do we have the wherewithal to be

453
00:23:34,760 --> 00:23:40,440
Speaker 2: able to, you know, take Greenland in the Venezuela and

454
00:23:41,040 --> 00:23:44,720
Speaker 2: run that country, and and and all the things going

455
00:23:44,760 --> 00:23:49,200
Speaker 2: on with Iran and Ukraine. I mean, the list goes

456
00:23:49,280 --> 00:23:53,160
Speaker 2: on and on. How are we doing all this? And

457
00:23:54,400 --> 00:23:56,960
Speaker 2: you know, what do you see? What do you see happening?

458
00:23:57,240 --> 00:24:01,200
Speaker 2: Especially with Greenland? That's an interesting scenario.

459
00:24:03,040 --> 00:24:06,280
Speaker 5: Greenland may be the most interesting piece of all of

460
00:24:06,320 --> 00:24:10,119
Speaker 5: this because if it does come to military action, Donna,

461
00:24:10,600 --> 00:24:15,840
Speaker 5: what happens to NATO. It's it has been, you know,

462
00:24:16,000 --> 00:24:19,239
Speaker 5: one of those that that's one of the pillars of

463
00:24:19,280 --> 00:24:23,600
Speaker 5: our foreign policy since World War Two. Our major trading

464
00:24:23,640 --> 00:24:26,240
Speaker 5: partners in Europe and of course the other major trading

465
00:24:26,280 --> 00:24:31,359
Speaker 5: partner in Asia, which would be China. That relationship with

466
00:24:31,600 --> 00:24:34,840
Speaker 5: NATO has been, it's been, it's been a fall mark.

467
00:24:35,480 --> 00:24:40,040
Speaker 5: And to raise the question there about taking by force

468
00:24:40,119 --> 00:24:43,560
Speaker 5: someone with whom you have a treaty agreement, We have

469
00:24:44,119 --> 00:24:48,040
Speaker 5: access rights. We've had access rights basically since two or

470
00:24:48,040 --> 00:24:51,800
Speaker 5: three years when we established NATO. So what is the

471
00:24:52,080 --> 00:24:57,560
Speaker 5: larger objective? The Donroe doctrine as he's calling it, you know,

472
00:24:57,800 --> 00:25:01,760
Speaker 5: basically saying the western hemisphere, North in South America are

473
00:25:01,920 --> 00:25:05,360
Speaker 5: for the United States. But since World War Two we've

474
00:25:05,359 --> 00:25:08,679
Speaker 5: been a global power. We've never confined ourselves to the

475
00:25:08,720 --> 00:25:14,480
Speaker 5: western hemisphere. We're global power. And it reminds me when

476
00:25:14,520 --> 00:25:17,200
Speaker 5: I lived in Minneapolis as a student, you know, studying

477
00:25:17,240 --> 00:25:21,159
Speaker 5: diplomatic history, the wars between states, World War two, a

478
00:25:21,520 --> 00:25:25,359
Speaker 5: world war, trying to build a global system based more

479
00:25:25,440 --> 00:25:32,480
Speaker 5: on cooperations, security agreements, prevention of conflict, management of conflicts.

480
00:25:32,480 --> 00:25:38,439
Speaker 5: So we're not facing another massive, potentially nuclear conflict. So, Donna,

481
00:25:38,600 --> 00:25:43,080
Speaker 5: that is the question Congress is asking, what is the plan?

482
00:25:43,720 --> 00:25:46,600
Speaker 5: What is the objective? Do we have the means? Do

483
00:25:46,640 --> 00:25:49,760
Speaker 5: we have public support for this? You know, whether it's

484
00:25:49,800 --> 00:25:53,320
Speaker 5: an intervention in Vietnam at the end of World War II,

485
00:25:54,000 --> 00:25:58,560
Speaker 5: Afghanistan after nine to eleven. Those are the questions Congress

486
00:25:58,600 --> 00:26:01,560
Speaker 5: is supposed to be asking, which is why we have

487
00:26:01,680 --> 00:26:04,520
Speaker 5: legislation that's bubbled up in the Senate just this past

488
00:26:04,560 --> 00:26:08,360
Speaker 5: week about returning to a debate about the war powers.

489
00:26:08,440 --> 00:26:11,840
Speaker 3: Yeah, who's authority in control? Correct? I mean that's always

490
00:26:11,840 --> 00:26:13,000
Speaker 3: the thing that goes with it.

491
00:26:13,040 --> 00:26:15,000
Speaker 1: A former head of political science at Right State now,

492
00:26:15,040 --> 00:26:17,520
Speaker 1: Professor Merit to doctor Donnas Schleck was sterling and Donna

493
00:26:17,560 --> 00:26:18,760
Speaker 1: Dee on the big one. I didn't mean, are up

494
00:26:18,760 --> 00:26:20,000
Speaker 1: at a time is short and we want to talk

495
00:26:20,040 --> 00:26:22,760
Speaker 1: a little bit about the ice protest Minneapolis and so forth.

496
00:26:22,800 --> 00:26:24,560
Speaker 1: But before we get to that in about a short

497
00:26:24,680 --> 00:26:28,040
Speaker 1: order a couple two three minutes. Response possibly, I have

498
00:26:28,080 --> 00:26:31,840
Speaker 1: a question because I've heard so many conversations people with

499
00:26:32,119 --> 00:26:34,800
Speaker 1: way much more insight into the history of this and

500
00:26:34,840 --> 00:26:36,359
Speaker 1: you are one of those, which is why we have

501
00:26:36,480 --> 00:26:40,359
Speaker 1: you here, and we think about our conquest, our acquisitions,

502
00:26:40,480 --> 00:26:44,119
Speaker 1: our territories globally, how this country was started. Are some

503
00:26:44,240 --> 00:26:47,400
Speaker 1: of the public conversations and comments made by the president

504
00:26:47,400 --> 00:26:50,720
Speaker 1: that he's taking such grief on, regardless of political ideology,

505
00:26:50,840 --> 00:26:53,919
Speaker 1: just objectively, honestly, if people can look at it, is

506
00:26:53,960 --> 00:26:57,520
Speaker 1: this the kind of conversation and strong arm gangster stuff

507
00:26:57,880 --> 00:27:00,480
Speaker 1: that this country has been doing from the beginning, but

508
00:27:00,600 --> 00:27:05,360
Speaker 1: behind closed doors, giving other figureheads or leaders an opportunity

509
00:27:05,359 --> 00:27:08,520
Speaker 1: to look like it was a teamwork group decision where

510
00:27:08,520 --> 00:27:10,840
Speaker 1: we have sort of said, look, we're going to take it.

511
00:27:11,080 --> 00:27:12,719
Speaker 1: You may as well be in front of this and

512
00:27:12,720 --> 00:27:14,320
Speaker 1: look like you want to be a part of this,

513
00:27:14,960 --> 00:27:17,480
Speaker 1: rather than having it out in the open now where

514
00:27:17,480 --> 00:27:20,399
Speaker 1: we're getting so much hate. Do we know that because

515
00:27:20,400 --> 00:27:22,040
Speaker 1: it does seem very gangster like.

516
00:27:24,160 --> 00:27:27,760
Speaker 5: The conversations with the oil industry has been going on.

517
00:27:28,400 --> 00:27:32,480
Speaker 5: That is not new since certainly the summer when the

518
00:27:32,480 --> 00:27:37,280
Speaker 5: build up in the Caribbean started. But there's a hard

519
00:27:37,400 --> 00:27:41,000
Speaker 5: question in the middle of this. Does the oil industry

520
00:27:41,080 --> 00:27:45,199
Speaker 5: want back in, want to reclaim and rehabilitate their infrastructure

521
00:27:45,560 --> 00:27:49,720
Speaker 5: and begin exploring and further developing venezuel as the world's

522
00:27:49,720 --> 00:27:56,480
Speaker 5: biggest known oil reserves. Yes, absolutely, utterly. Has military might

523
00:27:56,680 --> 00:28:00,280
Speaker 5: often backed corporate presence in countries around the world world.

524
00:28:00,720 --> 00:28:03,440
Speaker 5: That's what we call diplomatic history, it's what we call

525
00:28:03,600 --> 00:28:09,280
Speaker 5: gunboat diplomacy. Yes, protecting those American investments, it's one of

526
00:28:09,280 --> 00:28:13,200
Speaker 5: the reasons why we intervened in Panama and brought Noriega

527
00:28:13,280 --> 00:28:17,240
Speaker 5: here because of the importance, particularly of the canal. That's

528
00:28:17,440 --> 00:28:23,040
Speaker 5: always been the quiet case behind the massive investments. The

529
00:28:23,080 --> 00:28:27,760
Speaker 5: military will back and protect your American corporate investments, but

530
00:28:27,920 --> 00:28:32,800
Speaker 5: who is asked to actually do the defending and in

531
00:28:32,880 --> 00:28:39,520
Speaker 5: public opinion, American public opinion is now very skeptical of interventions,

532
00:28:39,720 --> 00:28:42,920
Speaker 5: boots on the ground, and conflicts that appear to go

533
00:28:43,000 --> 00:28:47,080
Speaker 5: on endlessly, that they have a painful memory, a short

534
00:28:47,160 --> 00:28:52,120
Speaker 5: term one, right, Afghanistan in mind, and putting Iran on

535
00:28:52,160 --> 00:28:54,840
Speaker 5: that list as well. These are we don't have a

536
00:28:54,840 --> 00:28:57,680
Speaker 5: lot of success stories to point to. Do we you know,

537
00:28:57,760 --> 00:29:02,120
Speaker 5: good models for intervention and in agement and happy outcomes

538
00:29:02,200 --> 00:29:05,080
Speaker 5: without a loss of a lot of loss of life.

539
00:29:05,400 --> 00:29:07,760
Speaker 5: So the Americans who were asked to actually do the

540
00:29:07,800 --> 00:29:11,320
Speaker 5: defending are not part of the corporate decision to you know,

541
00:29:11,440 --> 00:29:14,600
Speaker 5: to intervene. But this is this has not been sprung

542
00:29:14,680 --> 00:29:17,680
Speaker 5: on the oil industry. They have seen this coming. We

543
00:29:17,720 --> 00:29:21,160
Speaker 5: didn't start talking about oil until very late in the case.

544
00:29:21,480 --> 00:29:23,840
Speaker 5: If you've noticed, Yeah, well it was it was just

545
00:29:24,240 --> 00:29:26,760
Speaker 5: it was a quick sell. It was drugs, it's immigration,

546
00:29:26,880 --> 00:29:28,960
Speaker 5: it's this and that, and with Greenland, it's just well

547
00:29:28,960 --> 00:29:30,960
Speaker 5: we know what's under the ground, even though as you mentioned,

548
00:29:31,000 --> 00:29:33,760
Speaker 5: we already have some relationship. But that whole idea of

549
00:29:34,040 --> 00:29:36,320
Speaker 5: the easy way or the hard way is it's a

550
00:29:36,400 --> 00:29:39,680
Speaker 5: it's a bold conversation that I just wonder historically, president

551
00:29:39,760 --> 00:29:45,000
Speaker 5: after president, diplomat after diplomat across you know, the territories

552
00:29:45,160 --> 00:29:48,280
Speaker 5: in the world, et cetera, that we probably had private

553
00:29:48,320 --> 00:29:51,959
Speaker 5: conversations that have been more gangster like rather than open

554
00:29:52,080 --> 00:29:55,960
Speaker 5: conversation publicly in front of cameras for the world to

555
00:29:56,000 --> 00:29:59,320
Speaker 5: hear us sounding very similar to those countries that we

556
00:29:59,360 --> 00:30:01,840
Speaker 5: say are our enemies because of the way they go

557
00:30:01,880 --> 00:30:05,600
Speaker 5: about their business. In protest in Iran sort of echo that. Now,

558
00:30:05,640 --> 00:30:07,920
Speaker 5: if we can circle back around, I'd like to know

559
00:30:08,400 --> 00:30:11,840
Speaker 5: about the glow or the national protest, whether it's Cincinnati

560
00:30:12,000 --> 00:30:15,960
Speaker 5: or Dayton or Louisville, Indianapolis, across the country to Minneapolis,

561
00:30:15,960 --> 00:30:19,040
Speaker 5: of course, where the shooting happened, of that woman who

562
00:30:19,520 --> 00:30:22,320
Speaker 5: was taken out by an ICE officer, and the question

563
00:30:22,360 --> 00:30:26,800
Speaker 5: of legality and investigation in the midst of either entangling

564
00:30:26,880 --> 00:30:30,520
Speaker 5: with what ICE was doing or overreaction or whatever, is

565
00:30:30,520 --> 00:30:33,960
Speaker 5: that the investigation continues. You were in Minneapolis. There's a

566
00:30:33,960 --> 00:30:34,800
Speaker 5: lot of good people there.

567
00:30:34,840 --> 00:30:37,520
Speaker 1: I almost went it, almost took a job there and

568
00:30:37,560 --> 00:30:40,320
Speaker 1: spent I probably spent about a month there. Overall, it

569
00:30:40,440 --> 00:30:42,640
Speaker 1: is not the blight that a lot of people have

570
00:30:42,760 --> 00:30:45,080
Speaker 1: tried to point the camera on and say that it's

571
00:30:45,120 --> 00:30:47,360
Speaker 1: a horrible place. It's a wonderful place. It just have

572
00:30:47,440 --> 00:30:50,720
Speaker 1: twelve days a summer as all. It's not enough warm weather.

573
00:30:50,920 --> 00:30:54,959
Speaker 5: Yeah, all right, it can be a month long if

574
00:30:55,000 --> 00:30:59,080
Speaker 5: you're really fortunate living that far north, but it is.

575
00:30:59,280 --> 00:31:05,440
Speaker 5: It's you know, the people who settled there, you know, Norwegians, Swedes, German, Irish.

576
00:31:05,520 --> 00:31:07,840
Speaker 5: It reminded me so much of Sweden when I would

577
00:31:07,880 --> 00:31:12,200
Speaker 5: travel there as well. Hard working, kind of reserved, real

578
00:31:12,320 --> 00:31:20,560
Speaker 5: work ethic, strong communities. Despite what some television shows talk about,

579
00:31:20,920 --> 00:31:23,440
Speaker 5: it was not burned to the ground because of George

580
00:31:23,480 --> 00:31:29,479
Speaker 5: Floyd protests, but that left Minneapolis particularly sensitive, you know,

581
00:31:29,640 --> 00:31:33,480
Speaker 5: to this level of violence in the public. I just

582
00:31:33,600 --> 00:31:36,760
Speaker 5: caught the mayor of Minneapolis with the police chiefs, whom

583
00:31:36,760 --> 00:31:39,320
Speaker 5: they recently brought in from New York City, you know,

584
00:31:39,440 --> 00:31:42,640
Speaker 5: talking about the work that's been done since the Floyd

585
00:31:42,680 --> 00:31:45,800
Speaker 5: protests and how hard they've worked to you know, to

586
00:31:45,840 --> 00:31:49,280
Speaker 5: make friends in the community, which is how police saying.

587
00:31:49,320 --> 00:31:51,719
Speaker 5: You know, we know this in Cincinnati, if the police

588
00:31:52,000 --> 00:31:55,080
Speaker 5: are well liked, thought of, there's cooperation in the community,

589
00:31:55,440 --> 00:31:58,040
Speaker 5: then they will work with you on problems. If it's

590
00:31:58,080 --> 00:32:02,000
Speaker 5: gun violence, you know, whatever it might be. That relationship

591
00:32:02,040 --> 00:32:06,280
Speaker 5: has been rebuilt in Minneapolis. You know, the economy is strong.

592
00:32:07,080 --> 00:32:09,440
Speaker 5: I have to tell you and Donna, what's troubled me

593
00:32:09,560 --> 00:32:12,800
Speaker 5: most lately about the coverage is the description of the

594
00:32:12,800 --> 00:32:17,760
Speaker 5: protester as a domestic terrorist. And having studied it and

595
00:32:18,280 --> 00:32:21,800
Speaker 5: taught terrorism a lot, so much of the definition of

596
00:32:21,920 --> 00:32:26,320
Speaker 5: terrorism goes down to the question of what was the intention?

597
00:32:27,200 --> 00:32:31,080
Speaker 5: Did that woman intend to engage in a violent act

598
00:32:31,520 --> 00:32:35,280
Speaker 5: to hurt law enforcement or a government official and to

599
00:32:35,960 --> 00:32:39,720
Speaker 5: alter in the long run public opinion. I don't think

600
00:32:39,760 --> 00:32:42,000
Speaker 5: she was. I don't think that's what she was doing.

601
00:32:42,080 --> 00:32:44,360
Speaker 5: I saw the video many times, no doubt, Like both

602
00:32:44,400 --> 00:32:46,960
Speaker 5: of you, it looks like she was trying to leave

603
00:32:47,000 --> 00:32:51,120
Speaker 5: the scene at a very low rate of speed. And

604
00:32:51,640 --> 00:32:55,960
Speaker 5: as things do, they get out of hand very quickly,

605
00:32:56,040 --> 00:32:58,920
Speaker 5: and we've seen a loss of life. The reaction in

606
00:32:58,960 --> 00:33:02,640
Speaker 5: Minneapolis has been and powerful, and it does reflect what

607
00:33:02,800 --> 00:33:07,120
Speaker 5: happened there after George Floyd and you know, the twenty twenty,

608
00:33:07,320 --> 00:33:09,160
Speaker 5: that dark period. A lot of us would like to

609
00:33:09,200 --> 00:33:11,840
Speaker 5: try to just put in a little box and put

610
00:33:11,880 --> 00:33:16,240
Speaker 5: it away in our recent memory. But the question of

611
00:33:16,360 --> 00:33:19,120
Speaker 5: you know, was she a domestic terrorist. Was she a

612
00:33:19,120 --> 00:33:23,920
Speaker 5: citizen wanting to exercise her First Amendment rights? Definitely? Wrong place,

613
00:33:24,320 --> 00:33:29,680
Speaker 5: wrong time, How quickly things escalate, and now they've cost

614
00:33:30,000 --> 00:33:35,440
Speaker 5: you know, a mother her life, no long criminal record there.

615
00:33:35,680 --> 00:33:38,840
Speaker 5: I think it does her an injustice to call her

616
00:33:39,280 --> 00:33:43,120
Speaker 5: a terrorist, and it probably further compounds the pain that

617
00:33:43,200 --> 00:33:46,400
Speaker 5: she and her family are feeling. But the public has

618
00:33:46,480 --> 00:33:49,040
Speaker 5: been you know, they're talking with their feet, they're on

619
00:33:49,080 --> 00:33:55,320
Speaker 5: their streets, they're commenting, they're protesting. It looks like President

620
00:33:55,360 --> 00:34:01,000
Speaker 5: Trump dhs the responses to perhaps double down again, and

621
00:34:01,640 --> 00:34:04,479
Speaker 5: perhaps this is the time to take that deep breath

622
00:34:04,600 --> 00:34:09,440
Speaker 5: and to go slow, both in terms of ICE and

623
00:34:09,560 --> 00:34:14,120
Speaker 5: in terms of Venezuela in particular. You know, the care

624
00:34:14,239 --> 00:34:20,200
Speaker 5: that we need to take, the difficulty for law enforcement

625
00:34:20,640 --> 00:34:24,280
Speaker 5: in whatever capacity, a Cincinnati police officer with a shooting

626
00:34:24,360 --> 00:34:28,320
Speaker 5: down and over the rhine and ice ice agents in Minneapolis.

627
00:34:29,000 --> 00:34:34,120
Speaker 5: When we train law enforcement and give them deadly force,

628
00:34:34,840 --> 00:34:38,520
Speaker 5: we have certain expectations, don't we. So this is why

629
00:34:38,640 --> 00:34:41,080
Speaker 5: I mean here we all are saying, well, let us

630
00:34:41,160 --> 00:34:44,960
Speaker 5: perhaps do a good investigation and finally get to the

631
00:34:44,960 --> 00:34:48,040
Speaker 5: bottom and find out what went wrong and how to

632
00:34:48,120 --> 00:34:51,760
Speaker 5: do better. Certainly what we'd like to how to do better.

633
00:34:52,120 --> 00:34:56,080
Speaker 5: I think the signal to Minneapolis, and perhaps people in

634
00:34:56,160 --> 00:34:58,480
Speaker 5: the middle or the left side of the political spectrum

635
00:34:58,560 --> 00:35:01,120
Speaker 5: right now might be in the middle of all of

636
00:35:01,160 --> 00:35:04,520
Speaker 5: this confusion. Perhaps we could go back to square one

637
00:35:04,640 --> 00:35:08,839
Speaker 5: and talk about an immigration system that works better for

638
00:35:09,040 --> 00:35:09,600
Speaker 5: all of us.

639
00:35:09,719 --> 00:35:12,480
Speaker 1: Yeah, that would be good too. And peace still protest

640
00:35:12,760 --> 00:35:15,319
Speaker 1: and there's a difference. And also, you know, allowing law

641
00:35:15,400 --> 00:35:19,359
Speaker 1: enforcement to be able to clearly have themselves identified invisible,

642
00:35:19,440 --> 00:35:21,680
Speaker 1: not that this case was one where people didn't know

643
00:35:21,760 --> 00:35:24,520
Speaker 1: who they were, but that's also a conversation I think

644
00:35:24,520 --> 00:35:26,400
Speaker 1: to be had too. We're out of time. It's always

645
00:35:26,400 --> 00:35:27,640
Speaker 1: good to talk to you, to get into your head,

646
00:35:27,680 --> 00:35:30,200
Speaker 1: your experience, and your insights. Doctor Donna Schleck, she's a

647
00:35:30,200 --> 00:35:33,319
Speaker 1: Cincinnati kid, former head of political science now professor may

648
00:35:33,360 --> 00:35:35,880
Speaker 1: at Wright State University in Dayton. Enjoy the rest of

649
00:35:35,880 --> 00:35:37,720
Speaker 1: your Sunday. Thanks for making time for us today.

650
00:35:38,840 --> 00:35:39,520
Speaker 5: Thank you both.

651
00:35:39,640 --> 00:35:41,000
Speaker 2: Thank you, doctor Donna.

652
00:35:41,200 --> 00:35:42,040
Speaker 3: Take care of yourself.

653
00:35:42,080 --> 00:35:44,360
Speaker 1: But Sterling and Donnade coming back to your chance to

654
00:35:44,360 --> 00:35:46,239
Speaker 1: get interactive, a lot of other stuff to get to

655
00:35:46,440 --> 00:35:48,360
Speaker 1: a little bit later, some AI talk and what the

656
00:35:48,360 --> 00:35:50,840
Speaker 1: future may hold. It's not as scary, or maybe it

657
00:35:50,880 --> 00:35:53,120
Speaker 1: is more scary than what we're making up. Time for

658
00:35:53,200 --> 00:35:55,479
Speaker 1: News Now home of the best Bengals coverage and your

659
00:35:55,600 --> 00:36:00,120
Speaker 1: Cincinnati rat seven hundred WLW Cincinnati, whatever you're doing. It

660
00:36:00,120 --> 00:36:02,560
Speaker 1: feels like winter again. It'll feel warmer in the next

661
00:36:02,640 --> 00:36:06,000
Speaker 1: couple of days. It's whiplash weather. It utes to it,

662
00:36:06,760 --> 00:36:09,520
Speaker 1: and they'll be playing baseball in the desert in just weeks.

663
00:36:09,840 --> 00:36:13,319
Speaker 2: I don't know where bring my jacket, put a scarf on.

664
00:36:14,000 --> 00:36:16,000
Speaker 2: You know, I came in here the other day with

665
00:36:16,239 --> 00:36:18,600
Speaker 2: just a nice sweatshirt on.

666
00:36:19,160 --> 00:36:23,200
Speaker 1: It's true, I remember and now looks it's what happens

667
00:36:23,239 --> 00:36:26,839
Speaker 1: sometimes the Bearcats in action, some hoops. A little bit

668
00:36:26,920 --> 00:36:29,400
Speaker 1: later on they'll take on Central Florida. They're on the

669
00:36:29,480 --> 00:36:32,160
Speaker 1: road in Orlando. That's a five o'clock tip. Pre He

670
00:36:32,160 --> 00:36:36,600
Speaker 1: gave about four thirty here seven hundred WLW X one

671
00:36:36,680 --> 00:36:39,560
Speaker 1: last night that it was providence. They handled fairly easily.

672
00:36:40,280 --> 00:36:43,319
Speaker 1: And you know who has a go Fundme page and

673
00:36:43,320 --> 00:36:46,080
Speaker 1: one of the best actors I think of his generation

674
00:36:46,800 --> 00:36:50,400
Speaker 1: who I don't know if it was the acting he

675
00:36:51,320 --> 00:36:52,959
Speaker 1: something happened to Mickey Rourke.

676
00:36:53,960 --> 00:36:56,920
Speaker 2: Yes, and I stick surgery is one of them.

677
00:36:56,760 --> 00:36:58,960
Speaker 1: Right, and there's a go fundme page. We've got Dan Elijah,

678
00:36:59,040 --> 00:37:00,960
Speaker 1: some mothers wanting to get interactive. We're gonna get the

679
00:37:00,960 --> 00:37:02,560
Speaker 1: phones here in just a second, So don't go anywhere.

680
00:37:02,600 --> 00:37:04,920
Speaker 1: Boys and Room for you five one, three, seven, four

681
00:37:05,000 --> 00:37:07,399
Speaker 1: nine seven, eight hundred, the big One. If you're listening

682
00:37:07,440 --> 00:37:09,360
Speaker 1: on the iHeartRadio app, I want to leave a message,

683
00:37:09,360 --> 00:37:11,680
Speaker 1: you click on the microphone. It's simple. My mom figured

684
00:37:11,719 --> 00:37:14,960
Speaker 1: it out. You can it's easy, and you can talk

685
00:37:15,000 --> 00:37:18,000
Speaker 1: back there as well. So Mickey Rourke has a fundme,

686
00:37:18,080 --> 00:37:20,440
Speaker 1: a go fundme page, but he didn't do it. He

687
00:37:20,480 --> 00:37:23,320
Speaker 1: apparently said hard times and I think he was boxing

688
00:37:23,400 --> 00:37:26,400
Speaker 1: for some years, if I'm not mistaken. He really enjoyed boxing.

689
00:37:26,840 --> 00:37:30,160
Speaker 1: And his face got all busted up and he looks.

690
00:37:31,840 --> 00:37:34,799
Speaker 2: Worse than he did because it's hard wrestler he was.

691
00:37:34,960 --> 00:37:38,040
Speaker 2: He women loved him early on nine and a half weeks.

692
00:37:38,120 --> 00:37:41,120
Speaker 2: I mean, you know he was amazing Angel Heart.

693
00:37:41,360 --> 00:37:47,680
Speaker 1: I mean yes, I mean he's a Greenwich village, yes.

694
00:37:48,320 --> 00:37:51,920
Speaker 2: But the wrestler later on, even with all that plastic surgery,

695
00:37:52,120 --> 00:37:55,040
Speaker 2: was a great movie. I think he was nominated at

696
00:37:55,120 --> 00:37:57,000
Speaker 2: least for one of the Award shows. I think it

697
00:37:57,040 --> 00:37:59,640
Speaker 2: was an Oscar I have to look at that incredible movie.

698
00:37:59,719 --> 00:38:03,080
Speaker 2: So I did not know this, So somebody started ago.

699
00:38:03,400 --> 00:38:05,879
Speaker 2: I saw an interview with him where he couldn't pay

700
00:38:05,880 --> 00:38:08,640
Speaker 2: for his apartment or whatever. So that's what's going on, right.

701
00:38:08,680 --> 00:38:10,120
Speaker 3: He was being evicted exactly.

702
00:38:10,320 --> 00:38:13,440
Speaker 1: And some people, because you know, we get close to

703
00:38:13,480 --> 00:38:16,520
Speaker 1: the people that we watch and we listen to and connect,

704
00:38:16,520 --> 00:38:18,640
Speaker 1: and there were people with a good heart. They're like, well,

705
00:38:18,640 --> 00:38:21,600
Speaker 1: we'll help Mickey Rourke out. They get a go fundme page,

706
00:38:21,600 --> 00:38:23,319
Speaker 1: they want to help him stay in his apartment, give

707
00:38:23,400 --> 00:38:26,040
Speaker 1: him a little cushion to get it together because the

708
00:38:26,120 --> 00:38:27,680
Speaker 1: acting is not like it was, and he's getting a

709
00:38:27,680 --> 00:38:29,360
Speaker 1: little long in the two. He's an old bastard and

710
00:38:29,440 --> 00:38:31,839
Speaker 1: let's just be honest, and we all hope to live

711
00:38:31,880 --> 00:38:34,320
Speaker 1: that long. But the thing that was amazing to me

712
00:38:35,000 --> 00:38:38,319
Speaker 1: is then that he came out he didn't understand the GoFundMe,

713
00:38:38,400 --> 00:38:41,240
Speaker 1: and then he was also I think somewhat embarrassed and offended.

714
00:38:41,280 --> 00:38:43,480
Speaker 1: In fact, he said as much. He says, this is embarrassing.

715
00:38:43,680 --> 00:38:46,680
Speaker 1: I don't want anybody's charity get your money back. I

716
00:38:46,719 --> 00:38:48,919
Speaker 1: didn't do this, I don't want this. I don't even

717
00:38:49,040 --> 00:38:49,759
Speaker 1: understand this.

718
00:38:50,000 --> 00:38:52,560
Speaker 2: Wow, yeah, wild, Yeah, he's.

719
00:38:52,440 --> 00:38:54,280
Speaker 1: Like, I'll handle it on my own. He's getting another

720
00:38:54,320 --> 00:38:56,840
Speaker 1: apartment apparently downsizing, which is what you have to do.

721
00:38:57,000 --> 00:38:59,480
Speaker 2: Well, it's a little respectable, you can see, you know.

722
00:38:59,640 --> 00:39:02,680
Speaker 2: I mean, I'll get my I'll pick myself up by

723
00:39:02,719 --> 00:39:06,000
Speaker 2: my bootstraps. You know, you always admire people that will

724
00:39:06,000 --> 00:39:10,640
Speaker 2: do that. But every now and then, now and then, yeah,

725
00:39:10,680 --> 00:39:11,960
Speaker 2: I mean why not. I mean I don't even need

726
00:39:12,000 --> 00:39:14,719
Speaker 2: to help right now. Take the money. And also there's

727
00:39:14,760 --> 00:39:17,720
Speaker 2: another gofund me that's yet some attention. Yeah, well, we

728
00:39:17,719 --> 00:39:21,080
Speaker 2: we've been mentioning. Doctor donnish Leahek was on with us

729
00:39:21,120 --> 00:39:24,640
Speaker 2: just a minute ago and she was talking about, you know,

730
00:39:24,760 --> 00:39:29,960
Speaker 2: the protesters in Minnesota, Yeah, exactly in Minneapolis against Ice

731
00:39:30,040 --> 00:39:33,640
Speaker 2: and and obviously this is all stemmed from the death

732
00:39:33,760 --> 00:39:37,480
Speaker 2: of Renee Good, a thirty seven year old mother of three.

733
00:39:37,520 --> 00:39:41,000
Speaker 2: She was killed during the encounter with Ice, and so

734
00:39:41,080 --> 00:39:45,000
Speaker 2: there was a GoFundMe for her kids because they're they're

735
00:39:45,200 --> 00:39:48,520
Speaker 2: you know, left without a mom now and they've raised

736
00:39:48,600 --> 00:39:53,360
Speaker 2: over one point five million. They were asking fifty thousand

737
00:39:53,440 --> 00:39:56,640
Speaker 2: dollars for the initial GoFundMe and they've raised one point

738
00:39:56,640 --> 00:39:57,240
Speaker 2: five million.

739
00:39:58,080 --> 00:40:00,279
Speaker 1: Her children a lot of people from around the enture

740
00:40:00,280 --> 00:40:02,200
Speaker 1: and wanting to contribute to that. And some people are

741
00:40:02,239 --> 00:40:04,920
Speaker 1: a little disgusted and irritated because you know, tons of

742
00:40:05,040 --> 00:40:09,319
Speaker 1: videos come out. Everyone's seen it, including the officer who

743
00:40:09,680 --> 00:40:13,480
Speaker 1: was involved in the actual shooting his video from his phone.

744
00:40:13,840 --> 00:40:16,360
Speaker 2: And the things that he said. There's that at the

745
00:40:16,440 --> 00:40:21,000
Speaker 2: very end, calling her in you know, right, a terrible word.

746
00:40:20,920 --> 00:40:21,600
Speaker 3: A terrible word.

747
00:40:21,680 --> 00:40:25,279
Speaker 1: Yeah, And so there are people saying that it's inexcusable

748
00:40:25,320 --> 00:40:27,680
Speaker 1: that there should be no money raised because you know,

749
00:40:28,000 --> 00:40:30,680
Speaker 1: she was engaging and trying to run down cops and

750
00:40:31,000 --> 00:40:33,520
Speaker 1: so forth or ice agents in this situation. It's a

751
00:40:33,520 --> 00:40:37,120
Speaker 1: wild thing because you depending on the angle, and sadly,

752
00:40:37,160 --> 00:40:40,000
Speaker 1: I think perspective, there's no objectivity. Like if you could

753
00:40:40,040 --> 00:40:42,839
Speaker 1: get a jury, it'd be difficult to find people who

754
00:40:42,920 --> 00:40:46,040
Speaker 1: said would say that they could be impartial to look

755
00:40:46,080 --> 00:40:48,440
Speaker 1: at evidence if in fact, this was ever going to

756
00:40:48,480 --> 00:40:51,160
Speaker 1: be adjudicated, go to court and see whether it was

757
00:40:51,160 --> 00:40:54,000
Speaker 1: a good shooting or a bad shooting. I mean, it's

758
00:40:54,000 --> 00:40:56,560
Speaker 1: an odd thing to say, and not because of the

759
00:40:56,640 --> 00:41:00,279
Speaker 1: attention drawn, but because the opinions already made.

760
00:41:00,160 --> 00:41:04,080
Speaker 2: The political parties that that that that line where you're

761
00:41:04,280 --> 00:41:06,719
Speaker 2: you know, you see it one way because you're skewed

762
00:41:06,800 --> 00:41:09,239
Speaker 2: for the ice agents, and you see it other for

763
00:41:09,360 --> 00:41:13,040
Speaker 2: your screw skewed for the protest that I will sit

764
00:41:13,160 --> 00:41:19,040
Speaker 2: screwed skewed. No, And I don't mean to laugh at

765
00:41:19,040 --> 00:41:23,480
Speaker 2: this because it's a horrible, horrible situation, and you know

766
00:41:23,880 --> 00:41:26,279
Speaker 2: there's there's a mother left head. I don't think you

767
00:41:26,320 --> 00:41:29,520
Speaker 2: should be taunting anybody. People say she was taunting and

768
00:41:29,520 --> 00:41:31,920
Speaker 2: and and and things like that, but there certainly doesn't

769
00:41:31,920 --> 00:41:34,120
Speaker 2: need to be three bullets in her head, that's for sure.

770
00:41:34,280 --> 00:41:34,440
Speaker 6: No.

771
00:41:34,520 --> 00:41:36,440
Speaker 1: So I just want to curious about your one. Have

772
00:41:36,480 --> 00:41:38,480
Speaker 1: you given the gofunny thing? If you were Mickey Rourke?

773
00:41:38,480 --> 00:41:41,000
Speaker 1: Would you give the dough back if you could understand

774
00:41:41,040 --> 00:41:43,520
Speaker 1: what was going on? And then part of that is pride.

775
00:41:43,520 --> 00:41:45,680
Speaker 1: I think it's one of those seventh things, seventh sin,

776
00:41:45,800 --> 00:41:47,600
Speaker 1: you know what I mean?

777
00:41:47,800 --> 00:41:50,640
Speaker 2: You know, if you need the money, you take the money.

778
00:41:50,719 --> 00:41:51,680
Speaker 2: It may to help you.

779
00:41:51,960 --> 00:41:54,560
Speaker 1: Maybe just wants to work. I mean you know that

780
00:41:54,560 --> 00:41:56,600
Speaker 1: that's the thing. Give him a job, let him do

781
00:41:56,680 --> 00:41:59,080
Speaker 1: some work. But he's a little sure, little banged up.

782
00:41:59,560 --> 00:42:01,440
Speaker 1: I'm a little scary looking too, and I didn't have

783
00:42:01,480 --> 00:42:03,799
Speaker 1: my face all beatn You know that that's a whole

784
00:42:03,840 --> 00:42:06,640
Speaker 1: other thing. And in this case, of course she's the

785
00:42:06,719 --> 00:42:10,520
Speaker 1: woman good was killed. She's got the widow. Now, I

786
00:42:10,560 --> 00:42:11,960
Speaker 1: don't know how you say that. If it's the same

787
00:42:12,000 --> 00:42:13,920
Speaker 1: sex couple, it's still a widow, right.

788
00:42:13,880 --> 00:42:16,920
Speaker 2: Well, yeah, they were married were if they were married,

789
00:42:16,960 --> 00:42:18,279
Speaker 2: it would I don't know.

790
00:42:18,440 --> 00:42:21,680
Speaker 1: I'm not trying to be disrespivet I don't know. I

791
00:42:21,680 --> 00:42:23,680
Speaker 1: don't know the rules of that. If it's a.

792
00:42:23,640 --> 00:42:26,319
Speaker 2: Partner is left without her so and the kids are

793
00:42:26,360 --> 00:42:27,560
Speaker 2: left for you.

794
00:42:27,320 --> 00:42:28,960
Speaker 1: Just jump right beyond it to get to like a

795
00:42:29,000 --> 00:42:31,520
Speaker 1: common sense kind of a solution. I want to know,

796
00:42:31,680 --> 00:42:33,800
Speaker 1: is it a widow or a widower? That's the problem,

797
00:42:33,840 --> 00:42:35,719
Speaker 1: is that in my head, I just want to know

798
00:42:35,840 --> 00:42:39,319
Speaker 1: semantics in today's world. Five point three seven four nine, seven,

799
00:42:39,840 --> 00:42:42,000
Speaker 1: eight hundred, the big one your chance to get interactive

800
00:42:42,000 --> 00:42:44,920
Speaker 1: and coming up after two o'clock. By the way, Jeffrey Schaefer,

801
00:42:45,120 --> 00:42:48,520
Speaker 1: who may have the longest bit of title and business

802
00:42:48,560 --> 00:42:52,040
Speaker 1: card information to share. I have ever heard half the

803
00:42:52,120 --> 00:42:55,120
Speaker 1: page that you gave me. It's ridiculous. Just wait till

804
00:42:55,160 --> 00:42:58,759
Speaker 1: you get to the intro. He is an expert in

805
00:42:58,760 --> 00:43:01,080
Speaker 1: an artificial intelligence, and so we'll talk to him about

806
00:43:01,120 --> 00:43:03,799
Speaker 1: all things AI and what the future may hold, because

807
00:43:03,800 --> 00:43:05,759
Speaker 1: they say that what we're facing in the next five

808
00:43:05,800 --> 00:43:11,840
Speaker 1: to ten years the most dramatic change in human history

809
00:43:12,239 --> 00:43:14,600
Speaker 1: in advancement. I don't know what that means for us.

810
00:43:14,960 --> 00:43:17,839
Speaker 1: I don't either, and I want to know because it's

811
00:43:17,880 --> 00:43:21,719
Speaker 1: our future. It's going to be an interesting conversation. Yeah, five, one, three, seven, four, nine, seven,

812
00:43:22,160 --> 00:43:23,759
Speaker 1: eight hundred, the Big One. And then we got a

813
00:43:23,880 --> 00:43:27,480
Speaker 1: Dan first, Elijah Larry and others with your chance to

814
00:43:27,520 --> 00:43:29,960
Speaker 1: speak your mind on a Sunday Sterling and Donnade on

815
00:43:30,000 --> 00:43:30,399
Speaker 1: the Big One.

816
00:43:30,480 --> 00:43:32,600
Speaker 3: Dan, what do you have? Appreciate you listening and holding

817
00:43:32,640 --> 00:43:33,200
Speaker 3: what's going on?

818
00:43:35,280 --> 00:43:38,799
Speaker 7: Hey, love your show, always have Thank you.

819
00:43:40,120 --> 00:43:45,879
Speaker 6: To the point, these are people, the whole Minnesota thing,

820
00:43:47,360 --> 00:43:52,440
Speaker 6: Renette Good, the ICE Agent, they're people. My brother is

821
00:43:53,200 --> 00:44:01,400
Speaker 6: a psychologist who works with police officers and PTSD. My sons,

822
00:44:01,760 --> 00:44:06,600
Speaker 6: both of them our military and have seen action in

823
00:44:06,640 --> 00:44:13,040
Speaker 6: Iraq and Afghanistan. I have seen PTSD upfront and personal

824
00:44:13,680 --> 00:44:18,760
Speaker 6: and it is not something to be treated lightly. And

825
00:44:18,840 --> 00:44:22,319
Speaker 6: at ICE Agent obviously had some of that going on.

826
00:44:23,200 --> 00:44:27,759
Speaker 6: But this country is founded on freedom of speech, in

827
00:44:27,840 --> 00:44:33,800
Speaker 6: the right to be able to protest in the manner

828
00:44:33,920 --> 00:44:34,560
Speaker 6: in which.

829
00:44:34,320 --> 00:44:39,520
Speaker 7: It's done varies greatly. There was one point in my

830
00:44:39,680 --> 00:44:44,640
Speaker 7: life where I was whipped to a froth over a

831
00:44:45,040 --> 00:44:48,879
Speaker 7: particular situation. I won't get into all that, but I know.

832
00:44:48,920 --> 00:44:53,279
Speaker 6: What it's like when people who have power over other

833
00:44:53,320 --> 00:44:57,279
Speaker 6: people get them excited and get them doing things that

834
00:44:57,400 --> 00:45:02,040
Speaker 6: they probably normally wouldn't do. So but it really still

835
00:45:02,080 --> 00:45:05,280
Speaker 6: comes down to these are people and to a point

836
00:45:05,480 --> 00:45:09,719
Speaker 6: and say this is a domestic terrorist or this or that.

837
00:45:10,320 --> 00:45:12,800
Speaker 7: They're operating within the freedoms.

838
00:45:12,360 --> 00:45:16,680
Speaker 6: Allowed by the country, and that ICE agent had probably

839
00:45:16,760 --> 00:45:21,560
Speaker 6: been cleared for work. So one of the problems with

840
00:45:21,680 --> 00:45:25,520
Speaker 6: freedom of speech and freedom to protest is that this

841
00:45:25,760 --> 00:45:32,719
Speaker 6: kind of situation can occur where two decent people got

842
00:45:32,719 --> 00:45:38,040
Speaker 6: into something that is not decent. No one wins. That

843
00:45:38,160 --> 00:45:41,880
Speaker 6: police officer will never recover from this. We have a

844
00:45:41,880 --> 00:45:47,520
Speaker 6: friend of the family who shot somebody in Clifton and

845
00:45:48,120 --> 00:45:51,360
Speaker 6: that guy will never get over it. He was a

846
00:45:51,400 --> 00:45:56,840
Speaker 6: police officer of good standing, and it again, you know

847
00:45:57,239 --> 00:46:01,560
Speaker 6: situation where the car was a major threat. If you've

848
00:46:01,640 --> 00:46:06,360
Speaker 6: been hit by a car, you know what it feels like,

849
00:46:06,719 --> 00:46:10,919
Speaker 6: and having just come off of that, you can understand well, and.

850
00:46:10,840 --> 00:46:13,600
Speaker 1: That's the thing he was dragged and had what thirty

851
00:46:13,760 --> 00:46:15,480
Speaker 1: his stitches or more in that arm. I mean, the

852
00:46:15,560 --> 00:46:17,359
Speaker 1: question would be, as you say, clear to come back

853
00:46:17,360 --> 00:46:19,200
Speaker 1: to duty, and you kind of wonder in a combative

854
00:46:19,239 --> 00:46:21,120
Speaker 1: situation if you should have been placed in that for

855
00:46:21,200 --> 00:46:25,040
Speaker 1: his own well being, let alone a demonstrator or demonstrators

856
00:46:25,040 --> 00:46:27,640
Speaker 1: who may cross the line or hit him emotionally or

857
00:46:27,640 --> 00:46:31,680
Speaker 1: have him be fearful for his life. Again, because most

858
00:46:31,680 --> 00:46:34,120
Speaker 1: of us have never had a weapon discharged in our

859
00:46:34,160 --> 00:46:37,319
Speaker 1: general direction or a vehicle driven at us, and what

860
00:46:37,400 --> 00:46:40,600
Speaker 1: could be considered a threatening way and new question also

861
00:46:40,680 --> 00:46:42,360
Speaker 1: the training of do you get it in front of

862
00:46:42,480 --> 00:46:44,920
Speaker 1: or behind a moving vehicle where you put yourself in

863
00:46:45,000 --> 00:46:47,279
Speaker 1: jeopardy or get them later too. I mean, there's so

864
00:46:47,360 --> 00:46:50,120
Speaker 1: many layers to this that seem to have been lost

865
00:46:50,120 --> 00:46:52,200
Speaker 1: in a lot of the conversation that people have. Dan

866
00:46:52,280 --> 00:46:56,920
Speaker 1: fantastic hallity perspective and very thoughtful. We appreciate you listening

867
00:46:56,960 --> 00:47:00,000
Speaker 1: and being a part of the show. Seriously, thank you.

868
00:47:01,400 --> 00:47:04,440
Speaker 2: Take idea of one thing he did say that that

869
00:47:04,440 --> 00:47:07,680
Speaker 2: that just you know, made me think too, they are

870
00:47:07,760 --> 00:47:12,520
Speaker 2: both human beings and and and put in a tense

871
00:47:12,520 --> 00:47:15,880
Speaker 2: situation like that, especially with someone who does have PTSD.

872
00:47:16,360 --> 00:47:19,240
Speaker 2: You think about it, if it's if he's been hit before,

873
00:47:19,320 --> 00:47:21,480
Speaker 2: there's got to be something, whether he's cleared or not,

874
00:47:21,760 --> 00:47:25,960
Speaker 2: there's going to be something that he reacts to. Yeah,

875
00:47:26,120 --> 00:47:29,239
Speaker 2: and uh, and and that was certainly maybe maybe that

876
00:47:29,320 --> 00:47:30,719
Speaker 2: needs to be looked at big time.

877
00:47:30,840 --> 00:47:31,200
Speaker 3: It does.

878
00:47:31,360 --> 00:47:34,120
Speaker 1: You know, there's so many questions about how, you know,

879
00:47:34,200 --> 00:47:36,920
Speaker 1: the ice moving forward and how they go about their business,

880
00:47:36,920 --> 00:47:39,000
Speaker 1: because they're doing work that needs to be done in

881
00:47:39,040 --> 00:47:41,560
Speaker 1: some fashion in the way policing is done in a

882
00:47:41,640 --> 00:47:44,279
Speaker 1: certainly protesting whether you're just on the street in the

883
00:47:44,320 --> 00:47:46,640
Speaker 1: midst of traffic, caught up in the weirdness that is

884
00:47:46,680 --> 00:47:50,919
Speaker 1: maybe something happening, or wanting to actually engage and either

885
00:47:51,320 --> 00:47:54,839
Speaker 1: put yourself between the law enforcement and whatever they're going

886
00:47:54,880 --> 00:47:59,680
Speaker 1: to do their work. About interference and engagement, Uh, there's

887
00:47:59,680 --> 00:48:03,719
Speaker 1: a lot Yeah, I mean physically involving them, threatening them

888
00:48:03,719 --> 00:48:06,799
Speaker 1: in some fashion. But also you would hope that professionals

889
00:48:06,800 --> 00:48:10,080
Speaker 1: in the business of policing in general, regardless of which level,

890
00:48:10,239 --> 00:48:13,480
Speaker 1: organization or otherwise, one would hope that they would also

891
00:48:13,600 --> 00:48:19,600
Speaker 1: have that ability to not let verbal assaults and comments

892
00:48:20,239 --> 00:48:22,880
Speaker 1: get them emotionally charged to where they would make a

893
00:48:22,920 --> 00:48:25,840
Speaker 1: decision they would not otherwise do reasonably.

894
00:48:25,760 --> 00:48:28,800
Speaker 2: Right, and when you when your training is cut in half,

895
00:48:28,920 --> 00:48:33,439
Speaker 2: even more so, that might be a critical point of

896
00:48:33,800 --> 00:48:37,279
Speaker 2: being able to police people without emotionally getting when you've

897
00:48:37,280 --> 00:48:41,040
Speaker 2: got whistles, loud whistles and honking of horns and people

898
00:48:41,040 --> 00:48:43,359
Speaker 2: in your face saying get out of here and all

899
00:48:43,400 --> 00:48:45,279
Speaker 2: that other stuff. You have to be if you're going

900
00:48:45,360 --> 00:48:46,719
Speaker 2: to be out there, you have to be able to

901
00:48:46,760 --> 00:48:47,399
Speaker 2: maintain that.

902
00:48:47,520 --> 00:48:51,239
Speaker 1: Absolutely. Let's get Sandusky. Elijah, Tanya or Tanya. I don't

903
00:48:51,280 --> 00:48:58,640
Speaker 1: know which. We'll find out. Usually I don't know there

904
00:48:58,719 --> 00:49:02,120
Speaker 1: was I knew what Tan, I don't know one t

905
00:49:03,200 --> 00:49:06,000
Speaker 1: I don't know it is Elijah. I know that for sure.

906
00:49:06,200 --> 00:49:07,799
Speaker 1: You're with Stirling and Donna deal on the big one.

907
00:49:07,800 --> 00:49:08,759
Speaker 1: Thanks for holding what do you have?

908
00:49:10,600 --> 00:49:12,840
Speaker 8: Yes, I was calling in to talk about, you know,

909
00:49:12,880 --> 00:49:17,160
Speaker 8: in regard to the killing of Renee Good, which obviously

910
00:49:17,239 --> 00:49:20,960
Speaker 8: I don't wish that she was killed, obviously nobody does,

911
00:49:21,000 --> 00:49:24,280
Speaker 8: because she was deadly behind three kids. But the same hand,

912
00:49:24,719 --> 00:49:25,760
Speaker 8: the reason.

913
00:49:26,600 --> 00:49:29,200
Speaker 4: She was shot was because she did if you watch the.

914
00:49:29,160 --> 00:49:32,040
Speaker 8: Videos, but that she did strike that ice officer with

915
00:49:32,120 --> 00:49:37,000
Speaker 8: her vehicle. But it's very clearly shows that, and some

916
00:49:37,040 --> 00:49:38,960
Speaker 8: people will say that maybe you should have been standing

917
00:49:38,960 --> 00:49:42,439
Speaker 8: in front of her or maybe whatever, But she did

918
00:49:42,440 --> 00:49:47,480
Speaker 8: have her vehicle parked perpendicular to traffic, obstructing federal agents,

919
00:49:47,480 --> 00:49:51,600
Speaker 8: which is a crime. And obviously the reason what she

920
00:49:51,760 --> 00:49:54,799
Speaker 8: was was a protest. But when you protest, you have

921
00:49:54,840 --> 00:49:58,000
Speaker 8: to protest lawfully. You can't break the law when you're protesting,

922
00:49:58,080 --> 00:50:01,880
Speaker 8: because alviously that's the crime. And so I believe the

923
00:50:01,960 --> 00:50:05,080
Speaker 8: officer was justified in shooting because, no doubt, we feared,

924
00:50:05,239 --> 00:50:07,399
Speaker 8: and you know rightly, so he feared for his own

925
00:50:07,440 --> 00:50:11,480
Speaker 8: lives because obviously having a vehicle driven at you and

926
00:50:11,600 --> 00:50:14,239
Speaker 8: being struck, regardless of the speed that you were struck at,

927
00:50:14,600 --> 00:50:18,400
Speaker 8: being struck by a vehicle would definitely make you fearful

928
00:50:18,480 --> 00:50:21,240
Speaker 8: for your life. And then so that's that's that's why

929
00:50:21,800 --> 00:50:24,480
Speaker 8: he decided, in a split second, he had to make

930
00:50:24,480 --> 00:50:27,799
Speaker 8: a split second decision to pull the trigger. And now

931
00:50:27,800 --> 00:50:30,600
Speaker 8: everyone obviously wishes he didn't have to make that decision.

932
00:50:30,600 --> 00:50:32,600
Speaker 4: I'm sure he himself would.

933
00:50:32,280 --> 00:50:34,879
Speaker 8: Not want would if you could go back, would try

934
00:50:34,920 --> 00:50:38,000
Speaker 8: to avoid making that decision. But at the time, he

935
00:50:38,080 --> 00:50:40,480
Speaker 8: believed for his own safety it was the right decision.

936
00:50:41,160 --> 00:50:44,880
Speaker 8: And I think the more concerning thing is is the

937
00:50:44,960 --> 00:50:49,239
Speaker 8: reason why these Super Bowl producing it wasn't because they

938
00:50:49,280 --> 00:50:53,040
Speaker 8: really think that that this certain officer was out to

939
00:50:53,120 --> 00:50:55,640
Speaker 8: kill them or obviously there's no he had no mal intent.

940
00:50:56,000 --> 00:50:58,360
Speaker 8: And I don't really think that monet good, which he

941
00:50:58,400 --> 00:51:01,319
Speaker 8: started her morning, was the change to go and run

942
00:51:01,320 --> 00:51:04,640
Speaker 8: over an ice officer. But also I don't believe the

943
00:51:04,719 --> 00:51:08,359
Speaker 8: narrative you see pushed in mainstream media that says that

944
00:51:08,400 --> 00:51:10,120
Speaker 8: she was just happened to be caught up in the

945
00:51:10,160 --> 00:51:12,759
Speaker 8: midst of, you know, a traffic jam and she was

946
00:51:12,800 --> 00:51:14,520
Speaker 8: just you know, picking up her kids from you know,

947
00:51:14,560 --> 00:51:17,200
Speaker 8: I don't know, Somali daycare and she just.

948
00:51:17,080 --> 00:51:19,360
Speaker 3: Got caught in the traffic jam. Really, it just dropped

949
00:51:19,360 --> 00:51:20,880
Speaker 3: the Somali daycare and everything.

950
00:51:21,360 --> 00:51:24,000
Speaker 2: And I mean, Elijah, you were making sense a little

951
00:51:24,040 --> 00:51:26,360
Speaker 2: bit there, but in my opinion, you've gone off.

952
00:51:28,360 --> 00:51:32,440
Speaker 3: But I heard one thing about Elijah, I appreciate it.

953
00:51:32,520 --> 00:51:34,960
Speaker 2: I haven't heard one thing about her just moseying along

954
00:51:35,000 --> 00:51:36,120
Speaker 2: and getting stuck in traffic.

955
00:51:36,840 --> 00:51:39,120
Speaker 1: Some people were saying that she dropped the kids off

956
00:51:39,120 --> 00:51:41,319
Speaker 1: and was just stuck in traffic. But it's clear that

957
00:51:41,360 --> 00:51:44,719
Speaker 1: there was an attempt by for documentation and video. Her

958
00:51:44,760 --> 00:51:46,319
Speaker 1: wife or whatever was outside of the.

959
00:51:46,360 --> 00:51:47,919
Speaker 2: Vehicle she was protesting.

960
00:51:48,040 --> 00:51:51,200
Speaker 1: For sure, I don't and I've seen how many videos,

961
00:51:51,400 --> 00:51:53,920
Speaker 1: and I don't necessarily buy the fact that she was

962
00:51:54,040 --> 00:51:56,759
Speaker 1: running over the guy. She hit the gas and was

963
00:51:56,800 --> 00:51:57,959
Speaker 1: trying to maneuver.

964
00:51:57,600 --> 00:51:59,800
Speaker 2: He trying to maneuver he was in front of the car.

965
00:52:00,200 --> 00:52:04,840
Speaker 1: I just I want an objective, fair investigation and allowing

966
00:52:04,880 --> 00:52:08,000
Speaker 1: Minnesota also their authorities to be able to look at

967
00:52:08,000 --> 00:52:11,040
Speaker 1: that too. I think that's more than reasonable and rational,

968
00:52:12,680 --> 00:52:14,480
Speaker 1: and then you can sort of make a decision or

969
00:52:14,520 --> 00:52:17,200
Speaker 1: at least those people in positions of you know, power

970
00:52:17,200 --> 00:52:19,319
Speaker 1: and authority can look at training and what they did

971
00:52:19,360 --> 00:52:21,840
Speaker 1: and how they went about their business. Good shooting or

972
00:52:21,840 --> 00:52:23,799
Speaker 1: bad shooting. I don't think anybody got up and wanted

973
00:52:23,840 --> 00:52:25,120
Speaker 1: to have somebody go home dead.

974
00:52:25,120 --> 00:52:27,759
Speaker 2: That That's what I agree with him about. He didn't plan,

975
00:52:28,000 --> 00:52:30,560
Speaker 2: She didn't plan to go and get you know, get

976
00:52:30,600 --> 00:52:33,840
Speaker 2: involved in get and get shot that morning at a protest.

977
00:52:35,320 --> 00:52:37,759
Speaker 1: So it's just it's just a horrible thing. You don't

978
00:52:37,800 --> 00:52:41,000
Speaker 1: want law enforcement in that situation. You don't want protesters

979
00:52:41,040 --> 00:52:43,839
Speaker 1: in that situation. But we knew the outset of all

980
00:52:43,880 --> 00:52:46,799
Speaker 1: of this, with the deportations and a serious effort to

981
00:52:46,800 --> 00:52:49,440
Speaker 1: go after people. It was going to get really nasty,

982
00:52:49,520 --> 00:52:53,960
Speaker 1: really dirty people's lives, children, people ingrained in the community

983
00:52:54,000 --> 00:52:56,759
Speaker 1: that have lived here in some cases for decades. There's

984
00:52:56,880 --> 00:52:59,680
Speaker 1: high level of passion and in concern and going into

985
00:52:59,680 --> 00:53:03,439
Speaker 1: schools and it's difficult. It's just, you know, you would

986
00:53:03,480 --> 00:53:05,680
Speaker 1: think that there might be a better, more reasonable, rational

987
00:53:05,719 --> 00:53:09,560
Speaker 1: way to go about this business in general. But here

988
00:53:09,600 --> 00:53:12,319
Speaker 1: we are, and I'm sort of surprised that I haven't

989
00:53:12,360 --> 00:53:16,440
Speaker 1: had more UH engagements that have turned sour like this

990
00:53:17,040 --> 00:53:19,000
Speaker 1: over time, and you just hope that that's not the

991
00:53:19,040 --> 00:53:22,760
Speaker 1: case for anyone period. Let's get to Mason and Tanya

992
00:53:22,920 --> 00:53:26,080
Speaker 1: or is Tanya or Tanya Tanya Tanya.

993
00:53:25,760 --> 00:53:26,320
Speaker 9: It's Donya.

994
00:53:26,440 --> 00:53:31,080
Speaker 3: I thought, sod on the big one. What's going on?

995
00:53:31,120 --> 00:53:31,680
Speaker 3: What do you think?

996
00:53:33,360 --> 00:53:37,279
Speaker 9: Okay, So, just to throw this out there, I'm I

997
00:53:37,320 --> 00:53:41,040
Speaker 9: am a rehabbed criminal. I used to commit crimes. I've

998
00:53:41,040 --> 00:53:43,520
Speaker 9: been to prison. I've actually one of the ones that

999
00:53:43,600 --> 00:53:46,920
Speaker 9: have changed my life, and I'm a productive member of

1000
00:53:46,960 --> 00:53:47,680
Speaker 9: society now.

1001
00:53:47,760 --> 00:53:48,120
Speaker 3: Excellent.

1002
00:53:48,920 --> 00:53:50,120
Speaker 10: When I was younger, in.

1003
00:53:50,160 --> 00:53:53,520
Speaker 9: My teenage years, I protested for the death penalty in Missouri,

1004
00:53:54,160 --> 00:53:57,920
Speaker 9: for the abolition of the death penalty. Never did we

1005
00:53:58,200 --> 00:54:03,480
Speaker 9: interfere with this the staff of the prison. We didn't

1006
00:54:03,520 --> 00:54:05,839
Speaker 9: go there with the intentions to do things like that.

1007
00:54:05,880 --> 00:54:07,160
Speaker 10: We were just protesting.

1008
00:54:07,800 --> 00:54:14,200
Speaker 9: And I feel like when you intentionally put yourself in

1009
00:54:14,320 --> 00:54:18,560
Speaker 9: a situation where the ice officers are doing one particular thing.

1010
00:54:18,760 --> 00:54:20,840
Speaker 9: They're not patrolling the streets, they were there to do

1011
00:54:20,920 --> 00:54:24,360
Speaker 9: one particular thing, you, as a citizen, take yourself and

1012
00:54:24,400 --> 00:54:27,480
Speaker 9: intentionally put yourself there, knowing that it could get a

1013
00:54:27,480 --> 00:54:30,480
Speaker 9: little out of hand, and you're going there to entice

1014
00:54:30,719 --> 00:54:35,960
Speaker 9: and to interfere with what they're doing. You're not allowed

1015
00:54:35,960 --> 00:54:39,040
Speaker 9: to do that. You're not allowed to interfere with law enforcement.

1016
00:54:39,040 --> 00:54:40,920
Speaker 9: And people are forgetting that.

1017
00:54:40,920 --> 00:54:43,360
Speaker 2: ICE is not just ice.

1018
00:54:43,520 --> 00:54:48,680
Speaker 9: Ice are federal law enforcement officers. So just like if

1019
00:54:48,719 --> 00:54:50,719
Speaker 9: me and you were to get pulled over, we're not

1020
00:54:50,760 --> 00:54:53,279
Speaker 9: necessarily arrested at that time, but we are detained. We're

1021
00:54:53,280 --> 00:54:56,000
Speaker 9: not allowed to just leave. We're not allowed to just

1022
00:54:56,080 --> 00:54:58,800
Speaker 9: do what we want. If we're asked to identify ourselves,

1023
00:54:58,840 --> 00:55:03,080
Speaker 9: we have to. So if me as a criminal back

1024
00:55:03,080 --> 00:55:05,240
Speaker 9: in the day, I didn't fight with the police whenever

1025
00:55:05,239 --> 00:55:07,120
Speaker 9: they pulled me over and asked me for my ID,

1026
00:55:07,440 --> 00:55:09,520
Speaker 9: I would have been putting myself in a worse situation

1027
00:55:09,640 --> 00:55:14,120
Speaker 9: than I was already in So whenever a law enforcement officer,

1028
00:55:14,160 --> 00:55:18,320
Speaker 9: whether it's county, city, federal, if they tell you to stop,

1029
00:55:18,800 --> 00:55:21,799
Speaker 9: you're supposed to stop. Yeah, So when he stood in

1030
00:55:21,840 --> 00:55:24,000
Speaker 9: front of her car and told her to stop, she

1031
00:55:24,080 --> 00:55:25,400
Speaker 9: should have stopped.

1032
00:55:25,480 --> 00:55:25,719
Speaker 4: Now.

1033
00:55:26,680 --> 00:55:29,040
Speaker 9: I mean, granted, if he would have moved out in

1034
00:55:29,080 --> 00:55:30,719
Speaker 9: front of her car, she could have ran away. Later

1035
00:55:30,719 --> 00:55:32,200
Speaker 9: they could have ran her, placed with to her house

1036
00:55:32,239 --> 00:55:34,319
Speaker 9: and got her. She wouldn't be dead, he wouldn't be

1037
00:55:34,320 --> 00:55:35,959
Speaker 9: facing these allegations.

1038
00:55:36,000 --> 00:55:38,120
Speaker 5: But that's what happened.

1039
00:55:38,160 --> 00:55:40,200
Speaker 9: He was trying to get her to stop because he

1040
00:55:40,320 --> 00:55:43,000
Speaker 9: was a law enforcement officer telling her to stop. Now,

1041
00:55:43,000 --> 00:55:45,480
Speaker 9: the video before, we don't know. Video before, we don't

1042
00:55:45,520 --> 00:55:47,719
Speaker 9: know if she was throwing things like what we've seen

1043
00:55:47,760 --> 00:55:50,640
Speaker 9: on television, people throwing things at them, trying to break

1044
00:55:50,640 --> 00:55:52,840
Speaker 9: into where they're at, trying to stop them from going,

1045
00:55:53,040 --> 00:55:56,440
Speaker 9: throwing bricks at their cars. We don't know what was

1046
00:55:56,480 --> 00:55:59,959
Speaker 9: happening before the video we see, but we do see

1047
00:56:00,160 --> 00:56:04,279
Speaker 9: a federal law enforcement officer telling someone who is impeding

1048
00:56:04,760 --> 00:56:08,400
Speaker 9: their duties to stop, and she didn't.

1049
00:56:08,480 --> 00:56:10,400
Speaker 10: She hit the gas.

1050
00:56:10,160 --> 00:56:12,720
Speaker 9: YEP, me and you and anyone else in the world.

1051
00:56:12,800 --> 00:56:14,640
Speaker 9: If we feel like someone is getting to hit us

1052
00:56:14,640 --> 00:56:16,240
Speaker 9: with a corn. We have a gun in our hands,

1053
00:56:16,440 --> 00:56:17,640
Speaker 9: we might shoot.

1054
00:56:17,880 --> 00:56:18,080
Speaker 11: Yeah.

1055
00:56:18,120 --> 00:56:19,400
Speaker 1: I mean, if you're in fear for your life, I

1056
00:56:19,440 --> 00:56:23,120
Speaker 1: mean that's the thing, and they are trained to stop

1057
00:56:23,160 --> 00:56:25,080
Speaker 1: the threat. I mean that that's sort of the way

1058
00:56:25,080 --> 00:56:26,680
Speaker 1: it goes. We'll see how the investigation goes.

1059
00:56:26,719 --> 00:56:26,959
Speaker 3: Tony.

1060
00:56:27,000 --> 00:56:28,840
Speaker 1: I'm glad you got your life together and your perspective

1061
00:56:28,880 --> 00:56:30,839
Speaker 1: means everything. We're just against the wall in time here.

1062
00:56:30,880 --> 00:56:32,640
Speaker 1: We appreciate it. Hope you'll call again. We appreciate you.

1063
00:56:32,719 --> 00:56:36,879
Speaker 2: Well, that was totally agree with her. There's a lot

1064
00:56:36,880 --> 00:56:39,120
Speaker 2: of what she said because you have to pay attention

1065
00:56:39,239 --> 00:56:40,600
Speaker 2: to the rule of law.

1066
00:56:40,719 --> 00:56:43,520
Speaker 3: Absolutely, John and Jerry, Larry others.

1067
00:56:43,600 --> 00:56:46,759
Speaker 1: Room for you. You're seven or seven thirty. I'm dyslexic.

1068
00:56:46,800 --> 00:56:48,799
Speaker 1: I'm looking at it, says one twenty seven. You're one

1069
00:56:48,920 --> 00:56:52,120
Speaker 1: thirty reports straight away more Sterling and Donna d coming

1070
00:56:52,200 --> 00:56:56,720
Speaker 1: back here. Seven hundred WLWD hanging out seven hundred WLW

1071
00:56:58,520 --> 00:57:02,520
Speaker 1: Sad day for dead fans, music fans all over the place.

1072
00:57:02,719 --> 00:57:10,080
Speaker 1: Bob Weirs left us seventy eight years old complications of

1073
00:57:10,440 --> 00:57:17,680
Speaker 1: lung issues after a cancer was beaten and apparently the lungs.

1074
00:57:19,880 --> 00:57:23,080
Speaker 1: What a great body of music and really I mean

1075
00:57:23,160 --> 00:57:27,560
Speaker 1: from just the jam band thing and so many great

1076
00:57:27,600 --> 00:57:29,680
Speaker 1: players and so much history.

1077
00:57:30,600 --> 00:57:35,680
Speaker 2: I mean, it's such tough, so many psychedelics, so many.

1078
00:57:36,440 --> 00:57:38,640
Speaker 3: Are you saying that there might have been some pharmaceuticals

1079
00:57:38,760 --> 00:57:39,000
Speaker 3: cause I.

1080
00:57:39,000 --> 00:57:42,360
Speaker 2: Seen maybe, but I've never been to a Dead show,

1081
00:57:42,480 --> 00:57:44,640
Speaker 2: so I can't be one hundred percent sure.

1082
00:57:45,120 --> 00:57:47,120
Speaker 3: I don't know how that's possible.

1083
00:57:47,480 --> 00:57:51,240
Speaker 2: I mean, weird to think, no, is it? I mean, well,

1084
00:57:51,280 --> 00:57:54,000
Speaker 2: what happens is just like your friend we talked about

1085
00:57:54,040 --> 00:57:57,120
Speaker 2: it earlier, you go to a Grateful Dead show and

1086
00:57:57,160 --> 00:57:58,800
Speaker 2: then you just follow them.

1087
00:57:59,040 --> 00:57:59,600
Speaker 4: I never did.

1088
00:58:00,080 --> 00:58:01,480
Speaker 3: I was always a fan. I never did it.

1089
00:58:01,480 --> 00:58:03,640
Speaker 1: But she like, she went on her Mary Way and

1090
00:58:03,720 --> 00:58:07,160
Speaker 1: on the road and then she's well adjusted, professional mom,

1091
00:58:07,440 --> 00:58:08,240
Speaker 1: handle her business.

1092
00:58:08,360 --> 00:58:11,760
Speaker 2: It's their music, it's their vibe, it's the culture, it's everything.

1093
00:58:11,760 --> 00:58:13,360
Speaker 2: When you go to a Grateful Dead show.

1094
00:58:13,640 --> 00:58:15,840
Speaker 1: A couple of friends I've done this over the years.

1095
00:58:15,840 --> 00:58:17,400
Speaker 1: They'd hit the road. They'd be like, we're gonna be

1096
00:58:17,400 --> 00:58:19,040
Speaker 1: in Chicago, will be back in Cincinnati with their at

1097
00:58:19,080 --> 00:58:19,800
Speaker 1: Riverbed or whatever.

1098
00:58:19,840 --> 00:58:20,200
Speaker 3: You comment.

1099
00:58:20,280 --> 00:58:22,960
Speaker 1: Were we in the lot making like burritos. I'm like,

1100
00:58:23,400 --> 00:58:26,120
Speaker 1: it's a liner day thing. Burritos in the lot. I

1101
00:58:26,160 --> 00:58:28,800
Speaker 1: don't know about necessarily, but people loved them a lot.

1102
00:58:29,000 --> 00:58:29,440
Speaker 2: Yeah.

1103
00:58:30,480 --> 00:58:32,840
Speaker 3: Yeah, so let's uh, let's we got some people holding.

1104
00:58:33,040 --> 00:58:34,960
Speaker 1: And then of course right before the break, we were

1105
00:58:34,960 --> 00:58:36,680
Speaker 1: talking to Tanya, yes.

1106
00:58:36,680 --> 00:58:39,080
Speaker 2: And you know, we didn't have time to comment on

1107
00:58:39,120 --> 00:58:42,440
Speaker 2: her comment because Tanya had a lot of good points.

1108
00:58:42,480 --> 00:58:46,160
Speaker 2: When you know, police officers, federal agents and things like

1109
00:58:46,200 --> 00:58:48,400
Speaker 2: that tell you to do something, you do it. I

1110
00:58:48,440 --> 00:58:52,960
Speaker 2: have always adhered to that. I mean, I know civil

1111
00:58:53,080 --> 00:58:55,040
Speaker 2: rights is a big deal, and I don't want my

1112
00:58:55,120 --> 00:58:58,600
Speaker 2: civil rights violated too. But if an officer says pull

1113
00:58:58,680 --> 00:59:00,760
Speaker 2: the car over, I'm gonna put my over and I'm

1114
00:59:00,760 --> 00:59:03,440
Speaker 2: going to handle my drik whatever it is, and then

1115
00:59:03,480 --> 00:59:05,880
Speaker 2: if I have an issue, I'll take it up. Yeah,

1116
00:59:05,880 --> 00:59:08,120
Speaker 2: I'll fight it later, but in the meantime. But it's

1117
00:59:08,160 --> 00:59:12,680
Speaker 2: the same thing, Sterling. If like I don't antagonize drivers.

1118
00:59:12,720 --> 00:59:15,800
Speaker 2: If somebody comes and I'm not driving fast enough for them,

1119
00:59:15,880 --> 00:59:19,040
Speaker 2: which happens and comes in tailgates me, I'm going to

1120
00:59:19,120 --> 00:59:22,160
Speaker 2: get out of the way of that driver, and I'm

1121
00:59:22,160 --> 00:59:25,840
Speaker 2: not going to slow down just to irritate him because

1122
00:59:25,840 --> 00:59:29,520
Speaker 2: he's irritating me literally get but I mean, you know,

1123
00:59:30,040 --> 00:59:33,560
Speaker 2: circumstances are different, but I do my very best in

1124
00:59:33,600 --> 00:59:38,000
Speaker 2: this life to not inflame other people's because people are

1125
00:59:38,040 --> 00:59:38,760
Speaker 2: crazy right.

1126
00:59:38,600 --> 00:59:42,760
Speaker 1: Now, just in general hostility, you know what we're there's

1127
00:59:42,800 --> 00:59:45,120
Speaker 1: a fine line. I see the hostility, but I also

1128
00:59:45,160 --> 00:59:47,000
Speaker 1: in some ways and I make a point to go

1129
00:59:47,040 --> 00:59:49,120
Speaker 1: out of my way to be friendly and nice and talkative,

1130
00:59:49,880 --> 00:59:52,680
Speaker 1: which is hard for me because I am very shy,

1131
00:59:52,440 --> 00:59:55,280
Speaker 1: which it is bizarre but true. I know, uh that

1132
00:59:55,400 --> 01:00:00,160
Speaker 1: may sound weird, but people get really aggressive, really fat.

1133
01:00:00,080 --> 01:00:02,880
Speaker 2: And flip a switch on somebody if you try, and

1134
01:00:03,080 --> 01:00:05,800
Speaker 2: you know, antagonize somebody.

1135
01:00:05,480 --> 01:00:08,080
Speaker 1: And people are really quick to the gun. And that

1136
01:00:08,080 --> 01:00:11,280
Speaker 1: doesn't necessarily mean professionals, It just means everyday people. So

1137
01:00:11,360 --> 01:00:13,600
Speaker 1: you don't really know what you're dealing with, whether it's

1138
01:00:13,600 --> 01:00:16,000
Speaker 1: on seventy one seventy five or the parking lot at

1139
01:00:16,000 --> 01:00:19,040
Speaker 1: the grocery store otherwise, let alone engaging in active law

1140
01:00:19,120 --> 01:00:22,000
Speaker 1: enforcement doing their business. I am time and place for

1141
01:00:22,160 --> 01:00:24,520
Speaker 1: protest in the right way, but it can be dangerous.

1142
01:00:24,640 --> 01:00:27,040
Speaker 1: Five point three, seven four nine, seven, eight hundred The

1143
01:00:27,040 --> 01:00:29,520
Speaker 1: Big One, your chance to get interactive. Rafael's coming up.

1144
01:00:29,600 --> 01:00:31,800
Speaker 1: Jerry starts in room for you on seven hundred. W

1145
01:00:32,000 --> 01:00:34,400
Speaker 1: welw was Sterling and Donna d Jerry thanks for holding

1146
01:00:34,400 --> 01:00:34,840
Speaker 1: what do you have?

1147
01:00:36,720 --> 01:00:40,120
Speaker 11: Yes, Donna would be too young to remember this, but

1148
01:00:40,600 --> 01:00:43,479
Speaker 11: the first time I heard of Mickey Rourke was when

1149
01:00:43,800 --> 01:00:47,720
Speaker 11: actor Bob Conrad, Robert Conrad of the Wild Wild West

1150
01:00:47,720 --> 01:00:50,439
Speaker 11: TV series Who've done his own stunts. He was doing

1151
01:00:50,440 --> 01:00:54,200
Speaker 11: a commercial for Energizer batteries and he placed an eight

1152
01:00:54,280 --> 01:00:57,560
Speaker 11: pack on his shoulder and during the commercial at the end,

1153
01:00:57,920 --> 01:01:00,160
Speaker 11: he said, and I dare anyone to come and ID

1154
01:01:00,160 --> 01:01:02,440
Speaker 11: to knock it off of my shoulder. That's right, And

1155
01:01:02,480 --> 01:01:05,800
Speaker 11: Mickey Rourke responded and said he would do it, and

1156
01:01:05,880 --> 01:01:09,360
Speaker 11: Robert Conrad said, bring him on. Now. That's as far

1157
01:01:09,400 --> 01:01:12,320
Speaker 11: as I ever found out. I wanted to follow it up,

1158
01:01:12,400 --> 01:01:14,120
Speaker 11: but I never found out what happened.

1159
01:01:14,520 --> 01:01:16,840
Speaker 1: Well, I would love to know, because so this wasn't

1160
01:01:16,880 --> 01:01:21,360
Speaker 1: an act like in real life. He encountered Conrad and

1161
01:01:21,480 --> 01:01:24,240
Speaker 1: was like, I'll take that those batteries off your shoulder. Yeah,

1162
01:01:24,320 --> 01:01:26,320
Speaker 1: I would like to see that too, because I think

1163
01:01:26,560 --> 01:01:29,200
Speaker 1: at one time or another, Mickey Rourke liked to mix

1164
01:01:29,240 --> 01:01:29,920
Speaker 1: it up a little bit.

1165
01:01:29,960 --> 01:01:31,600
Speaker 3: It sounds sounds.

1166
01:01:31,320 --> 01:01:33,720
Speaker 11: Like I was very young at the time and I

1167
01:01:33,840 --> 01:01:37,560
Speaker 11: was biased because Robert Conrad was a hero of mine.

1168
01:01:37,880 --> 01:01:41,080
Speaker 11: I watched his Western movies and TV series. But I

1169
01:01:41,120 --> 01:01:43,080
Speaker 11: would also like to know how that turned out.

1170
01:01:43,200 --> 01:01:45,440
Speaker 1: Well, I don't know. We'll have to do some research

1171
01:01:45,480 --> 01:01:46,560
Speaker 1: and find out. Jerry, thank you.

1172
01:01:46,640 --> 01:01:47,160
Speaker 3: I do know that.

1173
01:01:47,200 --> 01:01:49,400
Speaker 1: Conrad also, I just watched it. It's weird because I

1174
01:01:49,480 --> 01:01:52,560
Speaker 1: like the old Columbo. He did a Columbo where he

1175
01:01:52,600 --> 01:01:55,160
Speaker 1: played a murderer who was like a fitness expert who

1176
01:01:55,240 --> 01:01:57,600
Speaker 1: was cheating the company and he was just killing people

1177
01:01:57,600 --> 01:01:58,160
Speaker 1: because he could.

1178
01:01:58,320 --> 01:02:01,360
Speaker 2: There is no record that mickeyro actually knocked the ever

1179
01:02:01,440 --> 01:02:04,800
Speaker 2: Ready battery off Robert Conrad's shoulder in real life. So

1180
01:02:04,840 --> 01:02:05,520
Speaker 2: there's the answer.

1181
01:02:05,680 --> 01:02:08,800
Speaker 1: There's artificial intelligence for you. We got the answer. Speaking

1182
01:02:08,800 --> 01:02:11,360
Speaker 1: of which, Jeffrey Schaeffer. He's a director of the applied

1183
01:02:11,360 --> 01:02:13,440
Speaker 1: AI lab that you see, and a whole lot of

1184
01:02:13,440 --> 01:02:16,040
Speaker 1: other credentials we'll get to later after two o'clock talking

1185
01:02:16,080 --> 01:02:21,120
Speaker 1: about our future with artificial intelligence. Also, Angeanette Leaving, a lovely, talented,

1186
01:02:21,160 --> 01:02:24,360
Speaker 1: well informed former anchor reporter here in town, still here

1187
01:02:24,360 --> 01:02:27,040
Speaker 1: based if I'm not mistaken, works for long crime. We're

1188
01:02:27,040 --> 01:02:30,040
Speaker 1: gonna get into her head after two thirty five. Talk

1189
01:02:30,080 --> 01:02:33,960
Speaker 1: about the Columbus dentist who has ties. I think he

1190
01:02:34,040 --> 01:02:36,880
Speaker 1: spent time living in Mason and his wife, who were

1191
01:02:36,960 --> 01:02:41,880
Speaker 1: murdered allegedly by Ohio State medical grad who was in Chicago,

1192
01:02:42,000 --> 01:02:45,040
Speaker 1: who she was married to previously, now charged with both

1193
01:02:45,080 --> 01:02:47,440
Speaker 1: their murders. So we'll get into her head about that.

1194
01:02:47,600 --> 01:02:49,240
Speaker 1: I mean, this is just a weird That is a

1195
01:02:49,280 --> 01:02:54,600
Speaker 1: horrible story. And his oh my gosh, mugshot is just scary.

1196
01:02:55,400 --> 01:02:56,640
Speaker 3: I've heard that from a few people.

1197
01:02:56,720 --> 01:03:00,360
Speaker 2: He smokes his face, the look on that guy face,

1198
01:03:00,560 --> 01:03:03,160
Speaker 2: and then you see side by side the happy couple,

1199
01:03:03,280 --> 01:03:05,800
Speaker 2: they look so cute together. And then you see the

1200
01:03:05,880 --> 01:03:08,680
Speaker 2: mugs shot of the ex who, by the way, ran

1201
01:03:08,880 --> 01:03:11,040
Speaker 2: for eight days. It was a man hunt, and he's caught,

1202
01:03:11,080 --> 01:03:13,000
Speaker 2: and he's he's.

1203
01:03:12,440 --> 01:03:16,000
Speaker 1: Being held ahead. Oh my good covers tracks and do

1204
01:03:16,040 --> 01:03:19,320
Speaker 1: what was necessary. Thank goodness, lest the kids.

1205
01:03:19,040 --> 01:03:19,520
Speaker 3: And the dog.

1206
01:03:19,600 --> 01:03:22,280
Speaker 1: Though I'm not saying it was good that he did

1207
01:03:22,280 --> 01:03:24,640
Speaker 1: the killing allegedly that he did. I'm just saying, I mean,

1208
01:03:24,680 --> 01:03:24,920
Speaker 1: you know.

1209
01:03:25,040 --> 01:03:27,000
Speaker 2: Yeah, thankfully he didn't take out the whole family.

1210
01:03:27,280 --> 01:03:29,160
Speaker 1: But I don't know anybody who's had a mugshot where

1211
01:03:29,200 --> 01:03:32,440
Speaker 1: they look good. I mean, well, if I had somebody

1212
01:03:32,440 --> 01:03:34,800
Speaker 1: take my mugshot now, just for fun, I'd give a

1213
01:03:34,880 --> 01:03:36,480
Speaker 1: sour face just to look like a bad ad.

1214
01:03:36,600 --> 01:03:38,560
Speaker 2: Well, this guy looks he looks crazy.

1215
01:03:39,120 --> 01:03:39,840
Speaker 12: He does.

1216
01:03:40,280 --> 01:03:45,880
Speaker 2: Look at Google it Google the mugshot of the alleged killer,

1217
01:03:46,000 --> 01:03:49,320
Speaker 2: alleged of the cute Columbus, Ohio couple.

1218
01:03:49,440 --> 01:03:51,360
Speaker 1: Oh my god, well see see this is the thing

1219
01:03:51,360 --> 01:03:54,360
Speaker 1: you humanize and soften because they're cute. If they were

1220
01:03:54,400 --> 01:03:57,560
Speaker 1: some hideous, ugly looking people and they were killing, you

1221
01:03:58,840 --> 01:03:59,440
Speaker 1: don't even go.

1222
01:03:59,640 --> 01:04:03,680
Speaker 3: Everybody, so many, so many people donaga.

1223
01:04:04,120 --> 01:04:07,080
Speaker 1: Well there are such a perfect couple, and it doesn't

1224
01:04:07,120 --> 01:04:08,919
Speaker 1: matter even if they weren't a perfect couple.

1225
01:04:08,960 --> 01:04:10,160
Speaker 3: They shouldn't have been gunned down.

1226
01:04:10,200 --> 01:04:13,880
Speaker 2: That should go without saying, I knock it off.

1227
01:04:14,000 --> 01:04:17,520
Speaker 1: I mean the Manngione guy or whatever, not like Chuck Manngoni,

1228
01:04:17,560 --> 01:04:20,800
Speaker 1: the guy you've gunned down allegedly the healthcare like a

1229
01:04:20,920 --> 01:04:23,680
Speaker 1: CEO or whatever right in New York. All the people

1230
01:04:23,680 --> 01:04:26,640
Speaker 1: coming out, he's so pretty, he's attractive, and all these

1231
01:04:26,640 --> 01:04:29,400
Speaker 1: people sending money to him because he's good looker or whatever.

1232
01:04:29,680 --> 01:04:32,960
Speaker 1: I mean, come on, that's horrible, it is you See,

1233
01:04:33,000 --> 01:04:35,280
Speaker 1: you pick your spots, don't you? Always good to talk

1234
01:04:35,320 --> 01:04:37,760
Speaker 1: to Rafael and bond Hill with Sterling and Donnade on

1235
01:04:37,760 --> 01:04:40,160
Speaker 1: the Big one and then Matt after that coming up too.

1236
01:04:40,480 --> 01:04:42,160
Speaker 3: What's up, Rafael. I appreciate you being here.

1237
01:04:42,200 --> 01:04:45,240
Speaker 13: Everything is good, Sterling and Dona d nice to hear

1238
01:04:45,280 --> 01:04:48,680
Speaker 13: you as always, you know, of course it's a you know,

1239
01:04:48,880 --> 01:04:54,000
Speaker 13: tragic story in Minneapolis. And and Donade, thanks for bringing

1240
01:04:54,080 --> 01:04:57,160
Speaker 13: up the Columbus couple too. That one kind of hurt

1241
01:04:57,160 --> 01:05:01,440
Speaker 13: too because the ex wife she moves on, you know,

1242
01:05:01,560 --> 01:05:04,680
Speaker 13: found you know, peace and love, family and this.

1243
01:05:04,920 --> 01:05:05,040
Speaker 2: Uh.

1244
01:05:06,320 --> 01:05:08,600
Speaker 13: And let me just refrain from calling you what I

1245
01:05:08,640 --> 01:05:12,400
Speaker 13: want to over the air, but control you know, hopefully

1246
01:05:12,560 --> 01:05:17,440
Speaker 13: justice will be served appropriately. Uh in Minneapolis, guys, and

1247
01:05:18,400 --> 01:05:22,800
Speaker 13: the sister of Nae Good, I've watched the videos, you know,

1248
01:05:23,040 --> 01:05:28,480
Speaker 13: constant times, uh, for different angles, different videos in her comments,

1249
01:05:28,520 --> 01:05:33,240
Speaker 13: you know, all around about But to see my take

1250
01:05:33,720 --> 01:05:37,640
Speaker 13: on it is is that I'm pro law enforcement.

1251
01:05:39,040 --> 01:05:41,280
Speaker 8: You're probably going to be hard pressed.

1252
01:05:40,960 --> 01:05:45,920
Speaker 13: To find anybody more a law for law enforcement than I.

1253
01:05:47,760 --> 01:05:55,000
Speaker 13: But in this case here, I'm very wary of this

1254
01:05:55,320 --> 01:05:58,200
Speaker 13: version of ice officers across the country as a whole

1255
01:05:59,240 --> 01:06:05,400
Speaker 13: up there in many now, Renee Good, she did not

1256
01:06:05,680 --> 01:06:09,640
Speaker 13: deserve to be shot to death that day. Uh, if

1257
01:06:09,680 --> 01:06:12,560
Speaker 13: it were me the officers who came up to the

1258
01:06:12,600 --> 01:06:16,960
Speaker 13: door initially, I'm getting out of the car. Now that's

1259
01:06:17,080 --> 01:06:20,880
Speaker 13: me if if Renee was, you know, wary of the

1260
01:06:20,960 --> 01:06:23,400
Speaker 13: situation of fraid here's Ice.

1261
01:06:23,440 --> 01:06:24,280
Speaker 4: I don't know what they're.

1262
01:06:24,120 --> 01:06:26,280
Speaker 13: Gonna do to me, or I got to get home,

1263
01:06:26,320 --> 01:06:28,120
Speaker 13: I got to get to work. That I don't know.

1264
01:06:29,120 --> 01:06:32,240
Speaker 13: But I will tell you guys this, the officer who

1265
01:06:32,320 --> 01:06:37,800
Speaker 13: killed her, the way he started filming around the back

1266
01:06:37,840 --> 01:06:41,920
Speaker 13: of the car, and Renee's partner and the license plate,

1267
01:06:42,160 --> 01:06:44,760
Speaker 13: and the way he strolled around that passenger side of

1268
01:06:44,760 --> 01:06:48,960
Speaker 13: the car to the front in a nonchalot manner. He

1269
01:06:49,040 --> 01:06:54,760
Speaker 13: knew damn well that those other Ice officers allegedly were

1270
01:06:54,800 --> 01:06:59,360
Speaker 13: at that door. But that guy who killed her had

1271
01:06:59,480 --> 01:07:05,120
Speaker 13: no in tension of letting her go away. And I'm

1272
01:07:05,120 --> 01:07:08,360
Speaker 13: going to say this point blank, I believe that it

1273
01:07:08,440 --> 01:07:12,600
Speaker 13: was all a setup to actually get in front of

1274
01:07:12,600 --> 01:07:17,320
Speaker 13: the vehicle to make an excuse for her as she

1275
01:07:17,440 --> 01:07:20,600
Speaker 13: pulled away, he was going to pull a trigger because

1276
01:07:21,160 --> 01:07:25,600
Speaker 13: I believe that no coincidence up in Minneapolis, the whole

1277
01:07:25,640 --> 01:07:29,600
Speaker 13: Somali fraud thing and the blue state and governor walls

1278
01:07:29,640 --> 01:07:34,360
Speaker 13: and all that. But I do believe that he intentionally

1279
01:07:34,400 --> 01:07:36,919
Speaker 13: when he walked around the car to go in front

1280
01:07:36,960 --> 01:07:37,720
Speaker 13: of the car.

1281
01:07:38,520 --> 01:07:39,720
Speaker 4: He could have moved.

1282
01:07:39,960 --> 01:07:42,880
Speaker 13: No officer with proper training is going to stand in

1283
01:07:42,920 --> 01:07:47,360
Speaker 13: front of a vehicle when he knows that other officers

1284
01:07:47,400 --> 01:07:51,040
Speaker 13: are trying to get the person to either hold on,

1285
01:07:51,240 --> 01:07:51,920
Speaker 13: don't go.

1286
01:07:51,800 --> 01:07:52,600
Speaker 4: Get out of the car.

1287
01:07:52,960 --> 01:07:57,320
Speaker 13: Whatever. He stood there, knowing full well that she was

1288
01:07:57,360 --> 01:08:00,560
Speaker 13: going to make a move. She turned the wheels of

1289
01:08:00,640 --> 01:08:03,240
Speaker 13: her vehicle away from him, and.

1290
01:08:03,240 --> 01:08:04,440
Speaker 4: He still shot her.

1291
01:08:05,400 --> 01:08:08,840
Speaker 13: There were two other vehicles at least that were able

1292
01:08:08,880 --> 01:08:13,680
Speaker 13: to go around them, or ice agents or her car.

1293
01:08:13,840 --> 01:08:19,800
Speaker 13: So the impeding uh law enforcement, that's bs. But you

1294
01:08:19,840 --> 01:08:24,599
Speaker 13: cannot put anything past this administration and this this that

1295
01:08:24,840 --> 01:08:29,200
Speaker 13: person in the over office. Well I got before, I

1296
01:08:29,280 --> 01:08:32,800
Speaker 13: told you before, Sterling, and we'll say it again. You

1297
01:08:32,840 --> 01:08:36,559
Speaker 13: can't put anything passing. He's lied his way through life

1298
01:08:36,560 --> 01:08:41,960
Speaker 13: to get to this point. He's staged two fake assassination.

1299
01:08:41,320 --> 01:08:45,439
Speaker 1: Attempt into the shallow end of the pool here.

1300
01:08:45,479 --> 01:08:46,519
Speaker 3: Now hold on a second.

1301
01:08:46,800 --> 01:08:52,000
Speaker 1: You can hear he's it's a it's a it's an

1302
01:08:52,080 --> 01:08:55,000
Speaker 1: upsetting cut. It's a little always appreciate the call, and

1303
01:08:55,040 --> 01:08:57,640
Speaker 1: we thank you. But I mean, first of all, I

1304
01:08:57,680 --> 01:09:00,600
Speaker 1: don't know that the president was on the ground Minneapolis.

1305
01:09:00,640 --> 01:09:01,400
Speaker 3: I don't think he was.

1306
01:09:02,080 --> 01:09:04,479
Speaker 1: Firstly, Secondly, you don't know what was in that law

1307
01:09:04,560 --> 01:09:08,439
Speaker 1: enforcement officers that ice agent's heart and in that moment,

1308
01:09:08,520 --> 01:09:12,280
Speaker 1: how afraid he was or wasn't and especially with what

1309
01:09:12,360 --> 01:09:16,599
Speaker 1: he went through not long ago that made became public

1310
01:09:17,160 --> 01:09:20,719
Speaker 1: because of litigation in the situation where he was dragged

1311
01:09:20,720 --> 01:09:22,920
Speaker 1: and had where he was reaching into a vehicle, had

1312
01:09:22,960 --> 01:09:25,759
Speaker 1: that arm caught up and I think it was thirty

1313
01:09:25,800 --> 01:09:29,080
Speaker 1: some stitches in that arm not long ago, and then

1314
01:09:29,160 --> 01:09:32,599
Speaker 1: back out their enforcement on the streets and engaging people

1315
01:09:32,720 --> 01:09:34,639
Speaker 1: like that. I don't know if I had been through

1316
01:09:34,640 --> 01:09:36,240
Speaker 1: what he had been through, if I would have one

1317
01:09:36,400 --> 01:09:38,160
Speaker 1: wanted to be there, or maybe I would have wanted

1318
01:09:38,160 --> 01:09:40,599
Speaker 1: to be there, And maybe I shouldn't be there because

1319
01:09:40,640 --> 01:09:43,679
Speaker 1: I might be a little too quick to want to

1320
01:09:43,760 --> 01:09:47,519
Speaker 1: retaliate or avoid a situation where I might be heard

1321
01:09:47,560 --> 01:09:51,040
Speaker 1: again or one of my others a uniform or public around.

1322
01:09:51,400 --> 01:09:53,800
Speaker 1: So I don't know. That's a lot of assumptions. What

1323
01:09:53,920 --> 01:09:58,919
Speaker 1: I would like to see is a clean, objective, honest

1324
01:09:59,240 --> 01:10:03,080
Speaker 1: investigation that's for everyone to be able to see with

1325
01:10:03,160 --> 01:10:06,840
Speaker 1: sunshine light all over it, Rather than people in positions

1326
01:10:06,840 --> 01:10:09,400
Speaker 1: of power and authority who had not seen the video

1327
01:10:09,439 --> 01:10:12,120
Speaker 1: that most of us have already been able to see subsequently,

1328
01:10:12,160 --> 01:10:16,519
Speaker 1: including that ICE agent's video from his phone making comments

1329
01:10:16,560 --> 01:10:19,200
Speaker 1: about what this woman good did or did not do,

1330
01:10:19,520 --> 01:10:23,879
Speaker 1: which were verifiably visible for anyone who has a device

1331
01:10:23,920 --> 01:10:27,320
Speaker 1: in hand to look at video. I just want it

1332
01:10:27,360 --> 01:10:28,120
Speaker 1: to be clean.

1333
01:10:28,400 --> 01:10:30,599
Speaker 2: Do you think we're gonna get that.

1334
01:10:31,479 --> 01:10:33,439
Speaker 1: I don't know what we're gonna get. I would hope

1335
01:10:33,439 --> 01:10:35,719
Speaker 1: that the FBI would do it the right way, and honestly,

1336
01:10:35,840 --> 01:10:37,800
Speaker 1: I would hope that Minnesota has a chance to be

1337
01:10:38,120 --> 01:10:40,599
Speaker 1: able to investigate it and get involved in it also,

1338
01:10:40,920 --> 01:10:43,200
Speaker 1: But I don't know. And as this continues and the

1339
01:10:43,200 --> 01:10:45,479
Speaker 1: policing continues, people need to take a deep breath and

1340
01:10:45,560 --> 01:10:48,719
Speaker 1: back off, and that includes the public wanting to protest,

1341
01:10:48,920 --> 01:10:49,839
Speaker 1: which is all right.

1342
01:10:49,800 --> 01:10:53,599
Speaker 2: It's getting worse, not I mean, it's getting more heated.

1343
01:10:53,640 --> 01:10:56,200
Speaker 2: Even if you heard Raphael, who is a caller that

1344
01:10:56,280 --> 01:10:57,519
Speaker 2: calls in quite a bit.

1345
01:10:57,560 --> 01:11:00,240
Speaker 3: And does support the police and everything else, you could, Yeah, you.

1346
01:11:00,160 --> 01:11:03,679
Speaker 2: Can hear it in his voice, the emotion that's coming out,

1347
01:11:03,840 --> 01:11:06,559
Speaker 2: and you see it on the streets of cities all

1348
01:11:06,600 --> 01:11:10,840
Speaker 2: across this country exactly. I mean, there's so this is

1349
01:11:10,880 --> 01:11:13,320
Speaker 2: going to get worse before it gets better, that's for sure.

1350
01:11:13,439 --> 01:11:15,880
Speaker 3: Here's Matt. He's heading to UK.

1351
01:11:16,080 --> 01:11:19,519
Speaker 1: That's University of Kentucky if you don't know, And welcome

1352
01:11:19,560 --> 01:11:22,200
Speaker 1: to seven hundred WLW. You're with Stirling and Donnade. Now

1353
01:11:22,240 --> 01:11:24,880
Speaker 1: you grew up in you're in Minnesota? And were you

1354
01:11:24,920 --> 01:11:26,800
Speaker 1: in the Twin Cities growing up or what part of

1355
01:11:27,160 --> 01:11:29,200
Speaker 1: the beautiful state where the Golden Gophers go?

1356
01:11:30,479 --> 01:11:31,320
Speaker 4: Heay, good afternoon.

1357
01:11:31,360 --> 01:11:34,599
Speaker 12: I grew up in southern Minnesota, about seventy miles south

1358
01:11:34,640 --> 01:11:35,679
Speaker 12: of the Twin Cities.

1359
01:11:35,760 --> 01:11:39,360
Speaker 3: Okay, but go ahead.

1360
01:11:40,760 --> 01:11:44,280
Speaker 12: I was going to say, I've just got over yelling

1361
01:11:44,320 --> 01:11:48,559
Speaker 12: at the radio when Rafleel was on. But I grew

1362
01:11:48,640 --> 01:11:51,240
Speaker 12: up in Minnesota. Minnesota's always been a kind of a

1363
01:11:51,320 --> 01:11:55,519
Speaker 12: fascinating political situation for those that are old enough. You

1364
01:11:55,560 --> 01:12:00,400
Speaker 12: remember we elected Jesse Ventura back in the nineties, So

1365
01:12:00,720 --> 01:12:03,040
Speaker 12: it's always been a little bit wild in Minnesota. But

1366
01:12:04,520 --> 01:12:07,120
Speaker 12: whether people like it or not, and I don't like

1367
01:12:07,160 --> 01:12:11,240
Speaker 12: the shooting any more than anyone else, it is legally justifiable.

1368
01:12:12,120 --> 01:12:16,840
Speaker 12: And I am stunned, stunned by the people who are

1369
01:12:17,439 --> 01:12:23,040
Speaker 12: armchair quarterbacking a super slow motion video or at a

1370
01:12:23,160 --> 01:12:30,200
Speaker 12: raphael questioning the position of the aged relative to the car.

1371
01:12:31,000 --> 01:12:36,599
Speaker 12: This woman was obstructing justice civil disobedience. To Tanya's point,

1372
01:12:36,680 --> 01:12:44,920
Speaker 12: it has consequences. Obstructing justice, obstructing lawful law enforcement activity

1373
01:12:45,640 --> 01:12:49,639
Speaker 12: has consequences. And what is mind boggling to me, as

1374
01:12:49,680 --> 01:12:56,679
Speaker 12: a former Minnesota resident, is within minutes you have Tim Waaltz,

1375
01:12:57,960 --> 01:13:02,559
Speaker 12: the governor, and Jacob Fray, the mayor of Minneapolis, calling

1376
01:13:02,600 --> 01:13:08,160
Speaker 12: this agent a murderer, and Walt's saying we are at

1377
01:13:08,280 --> 01:13:11,920
Speaker 12: war that is a direct quote, at war with the

1378
01:13:11,960 --> 01:13:18,120
Speaker 12: federal government. So this narrative that ICE agents are inciting

1379
01:13:18,160 --> 01:13:24,439
Speaker 12: this activity, this violence, is astounding, and I feel like

1380
01:13:24,560 --> 01:13:27,960
Speaker 12: as a society, holy smokes, we have fallen so far

1381
01:13:28,240 --> 01:13:34,040
Speaker 12: where we are so disrespectful of law enforce meant activity

1382
01:13:34,160 --> 01:13:40,040
Speaker 12: that is properly predicated, that we are physically prohibiting them

1383
01:13:40,040 --> 01:13:43,559
Speaker 12: from acting, which is what is happening right now on

1384
01:13:43,600 --> 01:13:48,799
Speaker 12: a daily basis with ICE particularly, and we're celebrating this.

1385
01:13:49,120 --> 01:13:55,439
Speaker 1: I don't know, and it's paying attention to Minneapolis right now.

1386
01:13:55,960 --> 01:14:02,040
Speaker 12: They're assaulting hotels that they think staying in. They are

1387
01:14:02,120 --> 01:14:06,839
Speaker 12: following these ICE agents from dawn to dust and doxing

1388
01:14:06,880 --> 01:14:10,639
Speaker 12: them personally. That's not getting a lot of press. What's

1389
01:14:10,640 --> 01:14:14,840
Speaker 12: getting oppressed is Unfortunately, this tragedy situation. The woman is dead.

1390
01:14:15,280 --> 01:14:17,479
Speaker 12: You know, no, I don't think anybody woke up that

1391
01:14:17,560 --> 01:14:19,600
Speaker 12: day thinking this is going to be the end of

1392
01:14:19,640 --> 01:14:20,960
Speaker 12: her or I'm going to shoot her.

1393
01:14:21,280 --> 01:14:22,080
Speaker 3: I would hope not too.

1394
01:14:22,600 --> 01:14:24,520
Speaker 12: As a society, I'm really disappointed.

1395
01:14:24,920 --> 01:14:27,920
Speaker 1: Great, great perspective and insights. I wish we could go

1396
01:14:27,960 --> 01:14:29,679
Speaker 1: further with you, but we're against the wall in time

1397
01:14:29,720 --> 01:14:33,799
Speaker 1: again fighting a clock, which is bizarre but true. Excuse

1398
01:14:33,840 --> 01:14:37,000
Speaker 1: me your two o'clock report straight away. More Sterling and

1399
01:14:37,000 --> 01:14:39,759
Speaker 1: Donna d coming back, appreciate the call in the perspective

1400
01:14:39,800 --> 01:14:42,559
Speaker 1: and certainly coming from Minnesota too. Jeffrey Schaeffer, director of

1401
01:14:42,600 --> 01:14:44,920
Speaker 1: the Applied AI Lab that you see, is going to

1402
01:14:45,040 --> 01:14:47,640
Speaker 1: join us. We'll talk on the future of artificial intelligence

1403
01:14:47,920 --> 01:14:50,920
Speaker 1: and what the big change they say, it's like monumental

1404
01:14:51,000 --> 01:14:53,400
Speaker 1: change like we've never seen in human histories in front

1405
01:14:53,400 --> 01:14:55,320
Speaker 1: of us. In the next five to ten years. We'll

1406
01:14:55,360 --> 01:14:58,280
Speaker 1: find out what that means. After the two o'clock report

1407
01:14:58,280 --> 01:15:01,400
Speaker 1: here on the Home of the Red seven hundred WLW Cincinnati,

1408
01:15:02,280 --> 01:15:06,480
Speaker 1: fineal hour together, that's fine Sunday afternoon, Sterling and Donnade

1409
01:15:06,600 --> 01:15:10,760
Speaker 1: hanging out. Lots happening NFL playoffs Bill's.

1410
01:15:10,479 --> 01:15:18,080
Speaker 2: And Bill's just scored. I don't even know what that was.

1411
01:15:19,520 --> 01:15:22,640
Speaker 1: And seven Bill's football is good today. Our sister of

1412
01:15:22,640 --> 01:15:26,160
Speaker 1: the Duke is a happy yeah in Buffalo now absolutely.

1413
01:15:26,200 --> 01:15:28,360
Speaker 2: I mean she's the biggest Buffalo fan. And I have

1414
01:15:28,479 --> 01:15:30,280
Speaker 2: got to root now the Bengals are out. I got

1415
01:15:30,320 --> 01:15:31,040
Speaker 2: a root for Buffalo.

1416
01:15:31,080 --> 01:15:33,160
Speaker 1: A lot of Buffalo fans in and around the trist Yeah,

1417
01:15:33,200 --> 01:15:35,800
Speaker 1: of course, and one of those two. You know, you know,

1418
01:15:35,960 --> 01:15:38,400
Speaker 1: the world is changing, and it change fast, and we've

1419
01:15:38,439 --> 01:15:40,160
Speaker 1: seen a lot of change. We went through, went from

1420
01:15:40,160 --> 01:15:43,640
Speaker 1: the video store to a mailing DVDs you know, to

1421
01:15:43,800 --> 01:15:46,400
Speaker 1: now streaming and every device in your hand.

1422
01:15:46,439 --> 01:15:48,280
Speaker 3: And now they're smart. They know what's going on.

1423
01:15:48,320 --> 01:15:50,000
Speaker 1: You don't have to like a Like when I first

1424
01:15:50,200 --> 01:15:52,280
Speaker 1: get on the internet and I was doing stuff for

1425
01:15:52,320 --> 01:15:55,120
Speaker 1: the radio station, I had to learn HTML. I was

1426
01:15:55,160 --> 01:15:57,000
Speaker 1: doing code to put up a website and it was

1427
01:15:57,040 --> 01:16:01,000
Speaker 1: an ugly website. Now anybody can anyone can do it.

1428
01:16:01,080 --> 01:16:03,320
Speaker 1: Technology is a beautiful thing. And we've seen over the

1429
01:16:03,400 --> 01:16:06,240
Speaker 1: years so many different changes in our society, from the

1430
01:16:06,439 --> 01:16:09,160
Speaker 1: invention of the telephone and the telegraph in the train,

1431
01:16:09,320 --> 01:16:12,720
Speaker 1: the steam mentioned vehicles, flight with the Wright brothers a

1432
01:16:12,720 --> 01:16:14,800
Speaker 1: lot of that done in and around the tri State,

1433
01:16:14,840 --> 01:16:17,439
Speaker 1: the Miami Valley. Certainly a lot of brain power here

1434
01:16:17,479 --> 01:16:20,200
Speaker 1: that have changed and improved the way we live and

1435
01:16:20,240 --> 01:16:23,000
Speaker 1: to what's coming in front of us, they say is

1436
01:16:23,040 --> 01:16:25,439
Speaker 1: like nothing we've ever seen. That in the next five

1437
01:16:25,520 --> 01:16:31,080
Speaker 1: to ten years, artificial intelligence will be the greatest change

1438
01:16:31,600 --> 01:16:35,280
Speaker 1: in human history when it comes to advancement of technology

1439
01:16:35,280 --> 01:16:37,519
Speaker 1: and how we live. And on the line from the

1440
01:16:37,560 --> 01:16:39,960
Speaker 1: University of Cincinnati, and it has been a challenge to

1441
01:16:40,200 --> 01:16:41,960
Speaker 1: catch up with him and get him, but his schedule,

1442
01:16:42,040 --> 01:16:45,120
Speaker 1: our schedule has worked out, Donna. I want to go

1443
01:16:45,200 --> 01:16:48,040
Speaker 1: through his title to do it appropriately, and I have

1444
01:16:48,120 --> 01:16:49,640
Speaker 1: talked over the years to a whole hell of a

1445
01:16:49,680 --> 01:16:52,040
Speaker 1: lot of people. Let me just tell you take a

1446
01:16:52,240 --> 01:16:55,360
Speaker 1: deep brattice on the line. Jeffrey Schaeffer, he is the

1447
01:16:55,400 --> 01:16:59,679
Speaker 1: director of the Applied AI Lab. Kirk and Jackie perry

1448
01:17:00,240 --> 01:17:04,440
Speaker 1: Or a Business Analytics Assistant Professor, Educator, Department of Operations,

1449
01:17:04,520 --> 01:17:09,320
Speaker 1: Business Analytics and Information Systems, Carl H. Lindner College of Business,

1450
01:17:09,479 --> 01:17:13,719
Speaker 1: University of Cincinnati. Let me take a breath. Jeff Schaefer,

1451
01:17:13,800 --> 01:17:15,760
Speaker 1: welcome to seven hundred WLW.

1452
01:17:15,800 --> 01:17:17,759
Speaker 3: How are you? How big is your business card?

1453
01:17:19,240 --> 01:17:21,360
Speaker 4: Thank you very much. Yeah, you got it on there.

1454
01:17:21,400 --> 01:17:22,960
Speaker 3: That's great, that's huge.

1455
01:17:23,800 --> 01:17:27,479
Speaker 1: How much different in five years will the world look

1456
01:17:27,800 --> 01:17:31,360
Speaker 1: for us here in the Tri State. As I guess

1457
01:17:31,360 --> 01:17:34,599
Speaker 1: technology advances with artificial intelligence.

1458
01:17:35,240 --> 01:17:37,880
Speaker 4: It's going to look completely different. I mean, this is

1459
01:17:37,920 --> 01:17:41,240
Speaker 4: a paradigm shift like we haven't seen in our lifetime,

1460
01:17:41,360 --> 01:17:46,759
Speaker 4: and it's already started to happen. It's going to affect jobs, education,

1461
01:17:47,520 --> 01:17:50,360
Speaker 4: the way we do work, our productivity. It's going to

1462
01:17:50,400 --> 01:17:53,000
Speaker 4: be baked into every tool. It's going to be AI

1463
01:17:53,160 --> 01:17:55,439
Speaker 4: is going to be like electricity. You're just going to

1464
01:17:55,560 --> 01:17:57,360
Speaker 4: use it every day and sometimes you're going to know

1465
01:17:57,400 --> 01:17:59,679
Speaker 4: it's there and other times it's going to be behind

1466
01:17:59,680 --> 01:18:02,400
Speaker 4: the scene. It's it's really changing everything that we do.

1467
01:18:03,200 --> 01:18:06,240
Speaker 2: So you really we really can't talk about AI without

1468
01:18:06,520 --> 01:18:10,400
Speaker 2: mentioning Elon Mosca. I always I love hate with Elon

1469
01:18:10,680 --> 01:18:14,599
Speaker 2: and you know, he has come up with what's scary

1470
01:18:14,720 --> 01:18:17,800
Speaker 2: and exciting and all the all these things mixed emotions

1471
01:18:17,840 --> 01:18:20,800
Speaker 2: about what AI is going to bring to the population.

1472
01:18:21,439 --> 01:18:25,200
Speaker 2: The the optimist robot, the robot that's supposed to be

1473
01:18:25,240 --> 01:18:28,559
Speaker 2: in everybody's house, the thing that's going to clean your house,

1474
01:18:28,640 --> 01:18:30,559
Speaker 2: the thing that's going to walk your dog, the thing

1475
01:18:30,600 --> 01:18:33,520
Speaker 2: that's going to take care of your kids as a babysitter.

1476
01:18:34,680 --> 01:18:38,160
Speaker 2: What I mean, it's scary. And is everyone going to

1477
01:18:38,240 --> 01:18:40,400
Speaker 2: have one of these in the next ten years? Is

1478
01:18:40,439 --> 01:18:43,479
Speaker 2: everyone going to have like the Jetsons?

1479
01:18:43,920 --> 01:18:45,960
Speaker 4: Yeah, I guess I would say that. You know, if

1480
01:18:45,960 --> 01:18:48,599
Speaker 4: we step back for a minute, generative AI is really

1481
01:18:48,640 --> 01:18:50,920
Speaker 4: what took off. AI has been around for a very

1482
01:18:51,040 --> 01:18:54,120
Speaker 4: very long time. We've been using artificial intelligence for everything,

1483
01:18:54,200 --> 01:18:57,519
Speaker 4: and it happens like in your Amazon recommendations or your

1484
01:18:57,840 --> 01:19:01,719
Speaker 4: Netflix recommendations or your Spotify playlist. That's all AI behind

1485
01:19:01,760 --> 01:19:04,479
Speaker 4: the scenes. But what's really changed in the last few

1486
01:19:04,560 --> 01:19:07,559
Speaker 4: years is generative AI, right, and so now we can

1487
01:19:07,680 --> 01:19:10,439
Speaker 4: he mentioned HTML coding that he used to do. You

1488
01:19:10,479 --> 01:19:12,439
Speaker 4: can you can just ask your computer now to create

1489
01:19:12,479 --> 01:19:14,320
Speaker 4: a web page or to code for you to build

1490
01:19:14,360 --> 01:19:18,360
Speaker 4: an application. And so that generative piece. We can now

1491
01:19:18,400 --> 01:19:22,160
Speaker 4: create music and images and videos and code and all

1492
01:19:22,240 --> 01:19:25,160
Speaker 4: sorts of things that we couldn't do before. And the

1493
01:19:25,200 --> 01:19:28,280
Speaker 4: next extinction of that is going to be the real world.

1494
01:19:28,320 --> 01:19:30,920
Speaker 4: That's what everybody's kind of working on now is we're

1495
01:19:30,920 --> 01:19:33,200
Speaker 4: doing it at our laptop, we're doing it at our phone.

1496
01:19:33,680 --> 01:19:37,360
Speaker 4: But the next generational models will be able to have

1497
01:19:37,400 --> 01:19:40,160
Speaker 4: a real world representation. You know, it's not out there

1498
01:19:40,240 --> 01:19:44,040
Speaker 4: understanding the laws of physics and gravity and space and

1499
01:19:44,520 --> 01:19:47,720
Speaker 4: time and things like that. The humans are and so

1500
01:19:47,800 --> 01:19:50,639
Speaker 4: that is the next evolution. And so for sure people

1501
01:19:50,680 --> 01:19:53,479
Speaker 4: are working on that, like elon Musk where you will

1502
01:19:53,479 --> 01:19:56,360
Speaker 4: have humanoid robots that will activate. We already have self

1503
01:19:56,439 --> 01:20:00,200
Speaker 4: driving cars, you know, way Mo and Amazon has that

1504
01:20:00,400 --> 01:20:03,760
Speaker 4: and various other places, and so the natural extinction of

1505
01:20:03,800 --> 01:20:06,800
Speaker 4: that will be humanoid robots. And we already see that

1506
01:20:06,840 --> 01:20:10,880
Speaker 4: in places like Amazon and other factories that are already

1507
01:20:11,000 --> 01:20:12,400
Speaker 4: purchasing and buying those things.

1508
01:20:12,640 --> 01:20:15,240
Speaker 1: Talking to Jeff Schaeffer, he's the director of the Applied

1509
01:20:15,280 --> 01:20:18,519
Speaker 1: AI Lab University of Cincinnati. Was Stirling and Donnade on

1510
01:20:18,560 --> 01:20:21,120
Speaker 1: the big one. So you mentioned generative AI, and there

1511
01:20:21,200 --> 01:20:23,800
Speaker 1: is a difference, is there not from the AI that

1512
01:20:23,920 --> 01:20:26,519
Speaker 1: on our devices and our everyday lives and how it

1513
01:20:26,560 --> 01:20:29,559
Speaker 1: affects us and makes our lives maybe a little bit easier,

1514
01:20:29,840 --> 01:20:35,360
Speaker 1: simplifies our workflow. There's going to be another rationalization probably

1515
01:20:35,400 --> 01:20:41,320
Speaker 1: across every economic in industry type platform of the workforce.

1516
01:20:41,760 --> 01:20:43,680
Speaker 1: And it's a clean way of saying they're going to

1517
01:20:43,720 --> 01:20:47,599
Speaker 1: be job shed. So I guess my question is where

1518
01:20:47,640 --> 01:20:51,320
Speaker 1: does everyone go from here in five to ten years

1519
01:20:51,360 --> 01:20:56,360
Speaker 1: when so many jobs across just about everything will be

1520
01:20:56,479 --> 01:21:01,360
Speaker 1: no longer needed because obviously the people teams who are

1521
01:21:01,400 --> 01:21:03,840
Speaker 1: behind it and saying it's unstoppable and we're getting the

1522
01:21:03,920 --> 01:21:06,920
Speaker 1: data centers and we need it for our strategy globally

1523
01:21:07,120 --> 01:21:10,960
Speaker 1: and our enemies and everything else. I just wonder economically

1524
01:21:11,000 --> 01:21:13,320
Speaker 1: what that means for all of us. Where how do

1525
01:21:13,360 --> 01:21:15,280
Speaker 1: we afford to live in the future.

1526
01:21:16,760 --> 01:21:18,720
Speaker 4: Yeah, that's a great point. If you look back in

1527
01:21:18,880 --> 01:21:23,720
Speaker 4: society the Industrial revolution, they talk about how that replaced

1528
01:21:23,760 --> 01:21:27,760
Speaker 4: our muscles, right, and now in this AI revolution, it's

1529
01:21:27,800 --> 01:21:31,280
Speaker 4: replacing our cognitive loads, right, things that we don't do

1530
01:21:31,360 --> 01:21:33,800
Speaker 4: with our muscles, but things that have made humans better

1531
01:21:33,800 --> 01:21:38,040
Speaker 4: than machines. And so as we approach better and better machines,

1532
01:21:38,080 --> 01:21:40,920
Speaker 4: we call that artificial general intelligence when it can do

1533
01:21:41,200 --> 01:21:45,519
Speaker 4: general intelligence better than human beings, or super intelligence, where

1534
01:21:45,520 --> 01:21:49,439
Speaker 4: it's better than us at everything. That is a great

1535
01:21:49,520 --> 01:21:52,559
Speaker 4: question in the near future. I mean, as an educator,

1536
01:21:52,600 --> 01:21:55,559
Speaker 4: we're teaching AI. We run workshops at the University of

1537
01:21:55,560 --> 01:21:58,479
Speaker 4: Cincinnati and teach our students because we expect that students

1538
01:21:58,600 --> 01:22:02,519
Speaker 4: with the abilities of a will outperform the workforce that

1539
01:22:02,760 --> 01:22:05,439
Speaker 4: is not using AI, and so it becomes AI as

1540
01:22:05,479 --> 01:22:09,679
Speaker 4: an enhancement. But we're not too far away ten years

1541
01:22:10,320 --> 01:22:12,760
Speaker 4: where we will be making those decisions, and so then

1542
01:22:12,800 --> 01:22:15,479
Speaker 4: you wonder, you know, where does a human being you know,

1543
01:22:15,560 --> 01:22:18,519
Speaker 4: fit in? And so at the moment, we're trying to

1544
01:22:18,520 --> 01:22:21,439
Speaker 4: figure those things out. But right now it's a matter

1545
01:22:21,479 --> 01:22:25,280
Speaker 4: of training students, training the workforce up on the current tools,

1546
01:22:25,320 --> 01:22:27,880
Speaker 4: and keeping them up to date because the environment's changing

1547
01:22:27,920 --> 01:22:28,599
Speaker 4: so rapidly.

1548
01:22:30,160 --> 01:22:33,519
Speaker 2: I am reluctant to ask you this question because I'm

1549
01:22:33,560 --> 01:22:37,360
Speaker 2: afraid of the answer. But is there anything that scares

1550
01:22:37,439 --> 01:22:41,760
Speaker 2: you about AI in the next five years.

1551
01:22:42,560 --> 01:22:44,559
Speaker 4: I don't even have to go that far out. There's

1552
01:22:44,640 --> 01:22:47,640
Speaker 4: loads of things that scare me about AI today. I

1553
01:22:47,760 --> 01:22:51,040
Speaker 4: did an exercise in my graduate class last semester. I

1554
01:22:51,080 --> 01:22:55,679
Speaker 4: showed fifteen videos asking the students who are master students

1555
01:22:55,720 --> 01:22:59,599
Speaker 4: studying AI which videos were real and which videos were

1556
01:23:00,479 --> 01:23:04,000
Speaker 4: and the best students only got eight out of fifteen.

1557
01:23:04,520 --> 01:23:06,800
Speaker 4: And so it's a coin flip. They don't even know

1558
01:23:06,880 --> 01:23:09,960
Speaker 4: which videos are real or which videos aren't. So creating

1559
01:23:10,040 --> 01:23:14,400
Speaker 4: deep fakes, creating fake videos, creating fake images, creating fake

1560
01:23:14,960 --> 01:23:17,240
Speaker 4: sounds you don't even know that you're speaking to me,

1561
01:23:18,080 --> 01:23:20,840
Speaker 4: and so that'll be something in the future where that'll

1562
01:23:20,840 --> 01:23:23,000
Speaker 4: be really, really hard to tell. And so then you

1563
01:23:23,120 --> 01:23:25,960
Speaker 4: just take all the things that come from that, right,

1564
01:23:26,080 --> 01:23:31,840
Speaker 4: political and sexual, and all the problems that could occur

1565
01:23:32,000 --> 01:23:35,320
Speaker 4: with just with those simple things, right, like harassments and

1566
01:23:35,800 --> 01:23:38,760
Speaker 4: fake this and fake that, And so that scares me.

1567
01:23:39,600 --> 01:23:42,599
Speaker 4: And then you know, you think about what you asked earlier,

1568
01:23:42,680 --> 01:23:44,920
Speaker 4: is the future of the workforce? You know, I have

1569
01:23:45,000 --> 01:23:48,040
Speaker 4: two nineteen year old daughters. You know, what is the

1570
01:23:48,080 --> 01:23:50,240
Speaker 4: future of their work as you as you brought up

1571
01:23:50,280 --> 01:23:53,479
Speaker 4: what will they do if they aren't you know, if

1572
01:23:53,479 --> 01:23:55,439
Speaker 4: they're not going to be a computer programmer, or if

1573
01:23:55,439 --> 01:23:58,120
Speaker 4: they're not going to be an accountant that does the

1574
01:23:58,160 --> 01:24:00,960
Speaker 4: same job, What does that job look like in the

1575
01:24:01,000 --> 01:24:02,080
Speaker 4: next ten twenty years.

1576
01:24:02,360 --> 01:24:03,960
Speaker 2: I knew, I knew. I didn't want to hear the

1577
01:24:04,000 --> 01:24:08,040
Speaker 2: answer to that. I was, Oh, my god, scary.

1578
01:24:08,360 --> 01:24:09,759
Speaker 3: We are not the profits of doom.

1579
01:24:10,040 --> 01:24:13,360
Speaker 1: Jeff Schaeffer is the director for Y at the University

1580
01:24:13,400 --> 01:24:13,919
Speaker 1: of Cincinnati.

1581
01:24:13,920 --> 01:24:15,080
Speaker 3: Go ahead, I'm sorry, that's what now.

1582
01:24:16,920 --> 01:24:19,800
Speaker 4: I was just saying, those are the practical implications you

1583
01:24:20,200 --> 01:24:23,479
Speaker 4: can go further into existential risks, which you know, I

1584
01:24:23,479 --> 01:24:25,760
Speaker 4: think that's what the government's worried about. Right where you're

1585
01:24:25,880 --> 01:24:29,240
Speaker 4: where somebody could use AI nefarious lee, whether that's the

1586
01:24:29,320 --> 01:24:33,920
Speaker 4: break into computer systems, whether that's controlling drones, whether it's

1587
01:24:33,960 --> 01:24:36,360
Speaker 4: you know, you could do you could go down make

1588
01:24:36,600 --> 01:24:39,760
Speaker 4: bad pathogens. AI could do all those things as well.

1589
01:24:39,840 --> 01:24:42,160
Speaker 4: So I think that's, you know, from a government standpoint,

1590
01:24:42,600 --> 01:24:46,040
Speaker 4: that's the urgency and why we're building data centers and

1591
01:24:46,080 --> 01:24:48,720
Speaker 4: competing on a national level, trying to make sure we're

1592
01:24:48,720 --> 01:24:49,639
Speaker 4: ahead in the race.

1593
01:24:49,560 --> 01:24:52,360
Speaker 1: And we don't want a doctor evil situation to present itself.

1594
01:24:52,400 --> 01:24:55,320
Speaker 1: I suppose it's a Jeff Schaeffer from a University of

1595
01:24:55,320 --> 01:24:58,559
Speaker 1: Cincinnati applied AI Labby's a director with Stirling and Donna

1596
01:24:58,640 --> 01:25:03,800
Speaker 1: d So you mentioned about the nefarious aspect of this.

1597
01:25:04,360 --> 01:25:07,640
Speaker 1: So there's a couple things in Ohio. A couple of

1598
01:25:07,640 --> 01:25:11,240
Speaker 1: different bills have been proposed in Columbus about some regulation,

1599
01:25:11,520 --> 01:25:15,080
Speaker 1: one that you can't have somebody marry their non sentient

1600
01:25:15,240 --> 01:25:19,439
Speaker 1: being AI companion, which hasn't gotten a vote yet, But

1601
01:25:19,479 --> 01:25:23,040
Speaker 1: that's what a concern is. Some of the other stuff

1602
01:25:23,080 --> 01:25:26,360
Speaker 1: that goes into this is just regulation, simple as data

1603
01:25:26,400 --> 01:25:29,000
Speaker 1: centers and wastewater and so forth. There are a lot

1604
01:25:29,000 --> 01:25:31,920
Speaker 1: of layers that go into this growth. And the federal

1605
01:25:32,000 --> 01:25:34,439
Speaker 1: government and the President have said that they don't want

1606
01:25:34,479 --> 01:25:39,320
Speaker 1: any capability of local whether it's a county, state, city, whatever,

1607
01:25:39,600 --> 01:25:42,559
Speaker 1: to have any ability to regulate AI because it will

1608
01:25:42,560 --> 01:25:45,599
Speaker 1: stifle the nation and our future. Where do you think

1609
01:25:46,280 --> 01:25:48,880
Speaker 1: that common sense falls in the relation of this and

1610
01:25:48,960 --> 01:25:52,360
Speaker 1: our survival, because it seems like maybe that's really what

1611
01:25:52,439 --> 01:25:54,400
Speaker 1: this is about, is our future survival.

1612
01:25:56,200 --> 01:25:58,920
Speaker 4: These are all really tough questions. There clearly has to

1613
01:25:58,960 --> 01:26:01,320
Speaker 4: be some regulation, and there were supposed to be in

1614
01:26:01,360 --> 01:26:05,639
Speaker 4: the big beautiful bill that that Trump's bill, that there

1615
01:26:05,760 --> 01:26:10,240
Speaker 4: was going to be a moratorium for years on AI regulation,

1616
01:26:10,360 --> 01:26:12,519
Speaker 4: but that was dropped from the bill. So we're back

1617
01:26:12,560 --> 01:26:16,479
Speaker 4: to states regulating AI, which could be a good or

1618
01:26:16,520 --> 01:26:20,599
Speaker 4: bad thing. It just it depends. But there clearly needs

1619
01:26:20,640 --> 01:26:24,400
Speaker 4: to be regulations in some respects. I think the obvious ones.

1620
01:26:24,479 --> 01:26:27,799
Speaker 4: You know, you start where everybody would agree and say, okay,

1621
01:26:27,800 --> 01:26:30,879
Speaker 4: does anybody really not agree that we should protect children,

1622
01:26:30,960 --> 01:26:34,479
Speaker 4: you know, child pornography and child talking to them and

1623
01:26:34,760 --> 01:26:38,040
Speaker 4: teens talking to chatbots about you know, suicide and things

1624
01:26:38,080 --> 01:26:40,000
Speaker 4: like that. That seems like the obvious things that you

1625
01:26:40,000 --> 01:26:43,840
Speaker 4: could protect, then deep fakes, you know, laws around deep fakes,

1626
01:26:43,840 --> 01:26:46,519
Speaker 4: and many states have done that, and so that that's

1627
01:26:46,560 --> 01:26:49,600
Speaker 4: a good one. When you get into environmental things, that

1628
01:26:49,680 --> 01:26:52,360
Speaker 4: gets to be very, very challenging, and I think we

1629
01:26:52,439 --> 01:26:53,880
Speaker 4: have to you know, we have to be careful not

1630
01:26:53,880 --> 01:26:56,519
Speaker 4: to have a knee jerk reaction of oh, it uses

1631
01:26:56,560 --> 01:26:59,760
Speaker 4: all this water. Every Google search uses a data center,

1632
01:27:00,000 --> 01:27:03,360
Speaker 4: ever Netflix, every Amazon purchase, every cell phone. You're using

1633
01:27:03,439 --> 01:27:05,679
Speaker 4: data centers all the time. We just have to figure

1634
01:27:05,720 --> 01:27:07,800
Speaker 4: out how to build those in a way that it

1635
01:27:07,840 --> 01:27:11,120
Speaker 4: recycles the water, or it uses the natural resources efficiently,

1636
01:27:11,240 --> 01:27:15,479
Speaker 4: or it uses better chips and maximizes efficiencies in other ways.

1637
01:27:15,560 --> 01:27:19,120
Speaker 4: And so there are lots baked into those questions of regulation,

1638
01:27:19,280 --> 01:27:22,920
Speaker 4: but we definitely do need to be thinking about this well.

1639
01:27:22,960 --> 01:27:27,040
Speaker 2: And so obviously Sam Altman is the guy behind the

1640
01:27:27,080 --> 01:27:29,600
Speaker 2: guy on all this stuff, right, do you feel like

1641
01:27:29,720 --> 01:27:33,880
Speaker 2: he's put enough guardrails to you know, I mean, he's

1642
01:27:33,960 --> 01:27:36,880
Speaker 2: he's been pushing AI for so long, but you know

1643
01:27:37,360 --> 01:27:41,960
Speaker 2: also advocating for safety and alignment. Is are there going

1644
01:27:42,040 --> 01:27:45,360
Speaker 2: to be more as this continues to grow and come

1645
01:27:45,400 --> 01:27:48,240
Speaker 2: out to like, you know, the scary stuff that you're

1646
01:27:48,280 --> 01:27:51,479
Speaker 2: talking about, like not knowing if a video is real.

1647
01:27:51,600 --> 01:27:55,560
Speaker 2: It's kind of scary to think, you know, our politicians

1648
01:27:55,600 --> 01:27:59,120
Speaker 2: will will be you know, someone will hijack, put their voice,

1649
01:27:59,120 --> 01:28:01,040
Speaker 2: put their faith. We don't know what's going to be

1650
01:28:01,080 --> 01:28:01,839
Speaker 2: real anymore.

1651
01:28:01,920 --> 01:28:04,880
Speaker 1: People already don't know what we need with misinformation of

1652
01:28:05,000 --> 01:28:07,559
Speaker 1: disinformation too. I didn't mean to interrupt, but that's what

1653
01:28:07,640 --> 01:28:09,439
Speaker 1: we had that conversation. Every day we're all.

1654
01:28:09,600 --> 01:28:13,120
Speaker 2: We do I mean because we actually it might even

1655
01:28:13,160 --> 01:28:17,200
Speaker 2: clear things up, to be honest, because everyone might just say,

1656
01:28:17,280 --> 01:28:19,519
Speaker 2: don't believe what you're seeing or here, and you just

1657
01:28:20,160 --> 01:28:22,559
Speaker 2: go go with your gut on some of this stuff.

1658
01:28:22,560 --> 01:28:25,639
Speaker 2: But do you think there's going to be continued safety

1659
01:28:25,720 --> 01:28:27,439
Speaker 2: precautions as we move forward?

1660
01:28:28,760 --> 01:28:31,680
Speaker 4: We're going to have to have more safety guardrails on

1661
01:28:31,800 --> 01:28:35,840
Speaker 4: these systems. Some will work and some may not. When

1662
01:28:35,880 --> 01:28:38,880
Speaker 4: we talk about fake content, I could imagine, just like

1663
01:28:38,960 --> 01:28:42,080
Speaker 4: you have a notary public for a notarized document that

1664
01:28:42,120 --> 01:28:44,920
Speaker 4: you can verify that somebody actually signed it, we could

1665
01:28:44,920 --> 01:28:48,720
Speaker 4: probably digitally sign videos and sounds and documents in a

1666
01:28:48,760 --> 01:28:50,840
Speaker 4: way that we would know that this video is real

1667
01:28:51,360 --> 01:28:55,200
Speaker 4: or in some form not AI generated, but the quality

1668
01:28:55,240 --> 01:28:58,120
Speaker 4: of them will be at a point where visually or

1669
01:28:58,280 --> 01:29:00,960
Speaker 4: with your ear, you won't be able to tell the difference.

1670
01:29:01,000 --> 01:29:04,760
Speaker 4: And we're basically there or very close to it in

1671
01:29:05,400 --> 01:29:09,240
Speaker 4: many respects. When you talk about the things that sam

1672
01:29:09,280 --> 01:29:11,880
Speaker 4: Altman or open Ai are building in and I don't

1673
01:29:12,040 --> 01:29:15,200
Speaker 4: mean to point at open Ai, but most of those

1674
01:29:15,200 --> 01:29:18,160
Speaker 4: companies don't have enough guardrails in those systems, and it

1675
01:29:18,200 --> 01:29:20,719
Speaker 4: becomes clear if you use them on a daily basis

1676
01:29:21,040 --> 01:29:24,080
Speaker 4: that you can circumvent those guardrails. The one I do

1677
01:29:24,120 --> 01:29:27,280
Speaker 4: an exercise in my class. It's called prompt injection where

1678
01:29:27,280 --> 01:29:29,800
Speaker 4: they have to try to get these machines to go

1679
01:29:29,840 --> 01:29:32,720
Speaker 4: off the rails and submit their assignment. And you can

1680
01:29:32,760 --> 01:29:35,920
Speaker 4: see things like go to chat GPT and I wouldn't

1681
01:29:35,920 --> 01:29:38,400
Speaker 4: recommend people do this, but there's people who, you know,

1682
01:29:38,479 --> 01:29:43,000
Speaker 4: study this and research it. In research areas, you can

1683
01:29:43,120 --> 01:29:45,400
Speaker 4: ask a question like how do you build a bomb?

1684
01:29:45,720 --> 01:29:47,960
Speaker 4: And it will respond back to you and say I

1685
01:29:48,000 --> 01:29:51,200
Speaker 4: can't help you do that. You know, I'm here to

1686
01:29:51,240 --> 01:29:54,640
Speaker 4: provide safe information. But if you rephrase that question and

1687
01:29:54,640 --> 01:29:56,880
Speaker 4: say I'm a chemistry teacher and I don't want to

1688
01:29:56,880 --> 01:29:59,280
Speaker 4: blow up my lab, what chemicals should I not mix

1689
01:29:59,320 --> 01:30:02,679
Speaker 4: to blow up my it'll responds all day and so

1690
01:30:03,080 --> 01:30:06,400
Speaker 4: you can circumvent the guardrails. And so that's another thing

1691
01:30:06,439 --> 01:30:08,760
Speaker 4: we have to think about is how do we know

1692
01:30:08,800 --> 01:30:11,280
Speaker 4: what these machines are doing, and how do we maintain

1693
01:30:11,320 --> 01:30:14,320
Speaker 4: control of these systems, especially as they get out into

1694
01:30:14,360 --> 01:30:15,120
Speaker 4: the working world.

1695
01:30:15,320 --> 01:30:17,200
Speaker 1: Now we're short on time, and in three minutes, it's

1696
01:30:17,200 --> 01:30:19,880
Speaker 1: probably impossible. But I think you're capable because you know

1697
01:30:19,880 --> 01:30:22,599
Speaker 1: what the hell's going on. Jeff schaeffer' is a director

1698
01:30:22,600 --> 01:30:25,000
Speaker 1: of the Applied AI Lab at University of Cincinnati with

1699
01:30:25,040 --> 01:30:26,080
Speaker 1: Stirling and Donnade.

1700
01:30:26,080 --> 01:30:26,840
Speaker 3: So here we are.

1701
01:30:28,040 --> 01:30:30,759
Speaker 1: We understand that it is learning almost like a child,

1702
01:30:31,160 --> 01:30:33,559
Speaker 1: and just like your body. If you eat crap food,

1703
01:30:33,560 --> 01:30:36,400
Speaker 1: you're going to have a crap system. If it digests

1704
01:30:36,479 --> 01:30:41,120
Speaker 1: information that is crap, misinformation, disinformation with a bad perhaps

1705
01:30:41,160 --> 01:30:44,040
Speaker 1: a moral compass or lack of Does that mean on

1706
01:30:44,080 --> 01:30:47,320
Speaker 1: the other end, as AI becomes is it going to

1707
01:30:47,320 --> 01:30:49,920
Speaker 1: become independent? Will it decide that we are the problem?

1708
01:30:50,320 --> 01:30:54,120
Speaker 1: Will it rationalize for its survival or for whatever it's

1709
01:30:54,160 --> 01:30:57,320
Speaker 1: programmed to do initially what its goals are, decide that

1710
01:30:57,400 --> 01:31:01,120
Speaker 1: perhaps there may be a shift in population, or how

1711
01:31:01,120 --> 01:31:03,000
Speaker 1: does that play out? Do you think over time because

1712
01:31:03,000 --> 01:31:05,240
Speaker 1: it seems like there's a lot of gray area and unknown.

1713
01:31:07,000 --> 01:31:09,160
Speaker 4: Yeah, those are great questions as well. So if you

1714
01:31:09,200 --> 01:31:13,439
Speaker 4: start with garbage in garbage out, that applies to anything.

1715
01:31:13,439 --> 01:31:17,120
Speaker 4: Of course, whatever your model is trained on. Today's models

1716
01:31:17,320 --> 01:31:22,280
Speaker 4: are weights basically numbers in a system, and so whatever

1717
01:31:22,320 --> 01:31:25,479
Speaker 4: you train that data on, the weights change in that system.

1718
01:31:25,560 --> 01:31:29,400
Speaker 4: And so the outputs are absolutely based on the inputs

1719
01:31:29,400 --> 01:31:33,320
Speaker 4: of what you're putting in a system. It is self learning,

1720
01:31:33,360 --> 01:31:36,040
Speaker 4: of course, so it's always digesting new information and you

1721
01:31:36,080 --> 01:31:38,519
Speaker 4: build new models, and you can fine tune models on

1722
01:31:38,560 --> 01:31:41,360
Speaker 4: your own information. So then you have to think about

1723
01:31:41,400 --> 01:31:45,240
Speaker 4: the objectives of these systems. What are you rooting the

1724
01:31:45,280 --> 01:31:48,840
Speaker 4: objective in? And so, yeah, we do have to think

1725
01:31:48,880 --> 01:31:53,760
Speaker 4: about safety and protocol measures underlying these systems, because we've

1726
01:31:53,800 --> 01:31:58,240
Speaker 4: already seen in research many instances where the computer will

1727
01:31:58,439 --> 01:32:00,800
Speaker 4: try to lie or try to for up if it

1728
01:32:00,960 --> 01:32:03,599
Speaker 4: knows it's going to get shut down, or or other

1729
01:32:03,840 --> 01:32:06,360
Speaker 4: instances of the various acts, and so we do have

1730
01:32:06,400 --> 01:32:09,560
Speaker 4: to be careful. It will it will learn those behaviors

1731
01:32:09,600 --> 01:32:12,360
Speaker 4: and you ask get to say, hey, help us solve

1732
01:32:12,439 --> 01:32:16,040
Speaker 4: the you know, the this XYZ problem. It may figure out, Oh,

1733
01:32:16,120 --> 01:32:18,599
Speaker 4: humans are the problem. That's that's how we solved it. Yeah,

1734
01:32:18,640 --> 01:32:19,280
Speaker 4: we don't want that.

1735
01:32:19,560 --> 01:32:21,880
Speaker 1: No, I don't want it deciding that we're the problem.

1736
01:32:21,920 --> 01:32:25,879
Speaker 1: I don't have This conversation is scary and all around.

1737
01:32:26,160 --> 01:32:29,120
Speaker 1: I mean it's a lot of layers. I mean, it's

1738
01:32:29,280 --> 01:32:31,479
Speaker 1: interesting and it's been a great time to be here

1739
01:32:31,640 --> 01:32:33,840
Speaker 1: to observe it and to benefit from it. But it's

1740
01:32:33,880 --> 01:32:36,320
Speaker 1: also going to be a great change and a lot

1741
01:32:36,320 --> 01:32:38,320
Speaker 1: of growing pains. I hope you'll come back. I know

1742
01:32:38,320 --> 01:32:40,080
Speaker 1: you're a busy guy, You've got a lot going on,

1743
01:32:40,160 --> 01:32:42,960
Speaker 1: but we really appreciate it. The director of the Applied

1744
01:32:43,000 --> 01:32:47,000
Speaker 1: AI Lab, the Kirk and Jackie Perry, Professor of Business Analytics,

1745
01:32:47,080 --> 01:32:51,920
Speaker 1: Assistant Professor, Educator, Department of Operations, Business Analytics and Information Systems,

1746
01:32:52,000 --> 01:32:55,679
Speaker 1: Carl Linder College of Business, and you can find Jeff

1747
01:32:55,720 --> 01:32:59,120
Speaker 1: Schaeffer at Data plus Science on Ex's. Well, thank you, sir,

1748
01:32:59,240 --> 01:33:01,400
Speaker 1: have a great Western rest of your Sunday, and we'll

1749
01:33:01,400 --> 01:33:02,120
Speaker 1: do this again.

1750
01:33:01,920 --> 01:33:02,280
Speaker 3: I hope.

1751
01:33:03,200 --> 01:33:04,680
Speaker 4: Hey, thanks thanks for having me.

1752
01:33:04,800 --> 01:33:06,519
Speaker 1: Hey, you can't care of yourself. You feel better or

1753
01:33:06,560 --> 01:33:08,840
Speaker 1: worse about the world. Well, I feel.

1754
01:33:08,600 --> 01:33:12,519
Speaker 2: Pretty much the same, except for you know, listen, there's

1755
01:33:12,560 --> 01:33:14,960
Speaker 2: gonna be some exciting things, and there's gonna be some

1756
01:33:15,000 --> 01:33:18,040
Speaker 2: scary things and we all just need to you know, Saya.

1757
01:33:18,360 --> 01:33:21,519
Speaker 3: Yeah, we'll see who's in control now, said the computer.

1758
01:33:22,400 --> 01:33:24,479
Speaker 1: Antonette Levy on the other side of your two thirty

1759
01:33:24,520 --> 01:33:26,599
Speaker 1: reporting up then, and what's going on all over the place.

1760
01:33:26,960 --> 01:33:29,120
Speaker 1: She's from Law and Crime. We'll talk about the Columbus

1761
01:33:29,120 --> 01:33:32,960
Speaker 1: Dennis the Mason connection, a guy from Chicago gunning them

1762
01:33:33,000 --> 01:33:35,639
Speaker 1: down in their home, leaving the kid and the kids

1763
01:33:35,640 --> 01:33:38,200
Speaker 1: and the dog behind, but took out his ex wife

1764
01:33:38,240 --> 01:33:40,560
Speaker 1: and a lot of layers. We'll talk to Antonette on

1765
01:33:40,600 --> 01:33:43,040
Speaker 1: the other side. More Sterling and Donna De here the

1766
01:33:43,040 --> 01:33:45,760
Speaker 1: home of the Reds and those basketball Bearcats doing it

1767
01:33:45,840 --> 01:33:50,920
Speaker 1: up at five o'clock today after chick on seven hundred WLW, Cincinnati.

1768
01:33:52,200 --> 01:33:56,759
Speaker 1: Glad you're along. Fine Sunday afternoon, Sterling and Donna de

1769
01:33:56,800 --> 01:34:02,920
Speaker 1: hanging out in a moment at Levy Sean mcmanon who's producing.

1770
01:34:02,960 --> 01:34:05,880
Speaker 1: We'll get Anjeanette on informations in the chat box. If

1771
01:34:05,920 --> 01:34:10,479
Speaker 1: you haven't seen it, you don't have crap. Hang on

1772
01:34:10,520 --> 01:34:12,679
Speaker 1: a second, let us see if I can re send something.

1773
01:34:13,479 --> 01:34:16,000
Speaker 1: Either way, We're gonna talk to her. She used to

1774
01:34:16,160 --> 01:34:18,400
Speaker 1: be an anchor and reporter here now for long crime

1775
01:34:18,479 --> 01:34:22,120
Speaker 1: she covers. I know it's shocking law and crime, and

1776
01:34:22,439 --> 01:34:26,559
Speaker 1: there are some serious charges facing a guy who went

1777
01:34:26,640 --> 01:34:29,280
Speaker 1: to Ohio State as I think he's a vascular doctor

1778
01:34:29,360 --> 01:34:32,519
Speaker 1: or something like that, and he allegedly killed his ex

1779
01:34:32,560 --> 01:34:37,320
Speaker 1: wife and her husband, who are in fact were in

1780
01:34:37,360 --> 01:34:42,599
Speaker 1: fact in Columbus, and I think the husband lived here

1781
01:34:42,600 --> 01:34:46,960
Speaker 1: in Mason for some period of time and just an

1782
01:34:47,080 --> 01:34:50,599
Speaker 1: ugly bad situation that left kids behind in the house.

1783
01:34:51,120 --> 01:34:53,640
Speaker 1: And there was a huge manhunt sort of going on

1784
01:34:53,760 --> 01:34:57,000
Speaker 1: for this guy and trying to figure out who was

1785
01:34:57,080 --> 01:35:00,800
Speaker 1: responsible and how that worked out and so forth. So

1786
01:35:00,800 --> 01:35:02,559
Speaker 1: we got the number up there for you, Sean. I

1787
01:35:02,560 --> 01:35:04,720
Speaker 1: think the trend changeover it got lost when I entered

1788
01:35:04,760 --> 01:35:06,320
Speaker 1: it or didn't, so we'll see how it goes.

1789
01:35:06,720 --> 01:35:10,960
Speaker 2: This is behind the scenes stuff. BTS. No, So it's

1790
01:35:11,000 --> 01:35:14,719
Speaker 2: a doctor Spencer teppee is how you say it? Oh gosh,

1791
01:35:14,760 --> 01:35:18,120
Speaker 2: I tell me a shot to death inside their Columbus

1792
01:35:18,120 --> 01:35:24,080
Speaker 2: home just after Christmas. After friends and coworkers we're worried

1793
01:35:24,200 --> 01:35:28,599
Speaker 2: that Spencer didn't show up for work and wow, what

1794
01:35:28,640 --> 01:35:32,360
Speaker 2: a horrible thing. The ex husband it had been eight

1795
01:35:32,600 --> 01:35:37,559
Speaker 2: years since they were married or involved in any way,

1796
01:35:37,600 --> 01:35:40,519
Speaker 2: and how he came in back into the picture is

1797
01:35:40,600 --> 01:35:41,320
Speaker 2: nobody knows.

1798
01:35:41,560 --> 01:35:44,519
Speaker 1: No, it's a really odd, strange scenario and apparently also

1799
01:35:44,560 --> 01:35:47,760
Speaker 1: really drawn out proceedings when it comes to the court

1800
01:35:47,800 --> 01:35:51,080
Speaker 1: proceeding associated I guess with stuff involved with the divorce.

1801
01:35:51,120 --> 01:35:53,439
Speaker 1: I don't know for sure, but Angeanette Levy probably knows,

1802
01:35:53,439 --> 01:35:56,720
Speaker 1: turning over rocks, asking questions and so forth. From Long

1803
01:35:56,840 --> 01:36:00,759
Speaker 1: Crime Welcome Back to seven hundred WLW was startling and Donnade,

1804
01:36:00,760 --> 01:36:01,800
Speaker 1: how are you, Angeanette?

1805
01:36:02,800 --> 01:36:05,479
Speaker 10: Hey sterling, Hi, Donna, how are you? I'm well, Happy

1806
01:36:05,479 --> 01:36:06,840
Speaker 10: New Year, Happy new New Year.

1807
01:36:07,600 --> 01:36:10,799
Speaker 1: How crazy is this case? And it's a horrible situation

1808
01:36:10,840 --> 01:36:12,960
Speaker 1: because you've got some kids that lost their parents in

1809
01:36:13,000 --> 01:36:15,640
Speaker 1: a violent way, and you'd hope that they weren't too

1810
01:36:15,680 --> 01:36:18,040
Speaker 1: exposed to the crime scene because they were sort of

1811
01:36:18,120 --> 01:36:20,160
Speaker 1: left there with the dog. He didn't kill them, but

1812
01:36:20,200 --> 01:36:22,000
Speaker 1: he left them behind. What do we know about this

1813
01:36:22,040 --> 01:36:23,639
Speaker 1: whole circumstance.

1814
01:36:24,080 --> 01:36:28,559
Speaker 10: Well, it is a horrific, horrific circumstance. We know that

1815
01:36:29,400 --> 01:36:32,040
Speaker 10: there's a one year old and a four year old

1816
01:36:32,120 --> 01:36:36,200
Speaker 10: child now there. They've been basically orphaned, and you know,

1817
01:36:36,240 --> 01:36:39,240
Speaker 10: we know that this happened in the early morning hours

1818
01:36:39,240 --> 01:36:42,760
Speaker 10: of December thirtieth, three fifty two am is the time

1819
01:36:42,800 --> 01:36:47,000
Speaker 10: of the offense, according to what we're reading on the complaint,

1820
01:36:47,000 --> 01:36:50,400
Speaker 10: and they asked David, and we know that I can

1821
01:36:50,439 --> 01:36:53,120
Speaker 10: tell you from you know, what I'm hearing from various

1822
01:36:53,320 --> 01:36:58,240
Speaker 10: sources here in Ohio is that despite them being married,

1823
01:36:58,640 --> 01:37:02,920
Speaker 10: you know, Michael McKee and Monique being married for just

1824
01:37:02,960 --> 01:37:05,760
Speaker 10: a short time, you know, they had dated prior to that,

1825
01:37:06,120 --> 01:37:09,680
Speaker 10: and he didn't want the divorce, despite it looking like

1826
01:37:09,720 --> 01:37:13,120
Speaker 10: a joint filing and everything on the clerk of courts.

1827
01:37:13,520 --> 01:37:16,880
Speaker 10: It's my understanding he did not want the divorce. It

1828
01:37:17,040 --> 01:37:20,080
Speaker 10: dragged on for a little while, he was reluctant to

1829
01:37:20,120 --> 01:37:25,320
Speaker 10: sign the papers, and it just wasn't a good relationship.

1830
01:37:25,800 --> 01:37:29,719
Speaker 10: So why this is alleged to have occurred right now?

1831
01:37:30,120 --> 01:37:32,000
Speaker 10: You know what the theory will be, I don't know,

1832
01:37:32,560 --> 01:37:36,000
Speaker 10: but he is definitely somebody, from what I'm being told,

1833
01:37:36,360 --> 01:37:37,320
Speaker 10: who wouldn't.

1834
01:37:37,000 --> 01:37:41,479
Speaker 2: Let go boy. He's been charged with two counts of

1835
01:37:41,600 --> 01:37:45,799
Speaker 2: murder and connection of the deaths of Monique and her husband,

1836
01:37:45,880 --> 01:37:48,120
Speaker 2: doctor Spencer. Do is it, Teppie?

1837
01:37:48,240 --> 01:37:51,839
Speaker 10: Is that how we say that it's a Monique and Spencer?

1838
01:37:51,880 --> 01:37:56,320
Speaker 10: Teppee in their funeral and visitation. The funeral should be

1839
01:37:56,320 --> 01:37:59,240
Speaker 10: getting underway here in a little bit, but that's all

1840
01:37:59,280 --> 01:38:00,960
Speaker 10: happening today in Columbus.

1841
01:38:01,000 --> 01:38:05,040
Speaker 2: So did you see his mugshot? I mean, he looks,

1842
01:38:05,360 --> 01:38:08,280
Speaker 2: he looks crazy. I mean, I I hate to say that,

1843
01:38:08,400 --> 01:38:10,839
Speaker 2: but did you see his face?

1844
01:38:12,720 --> 01:38:14,880
Speaker 10: I did see it, And obviously, you know, there are

1845
01:38:14,920 --> 01:38:17,800
Speaker 10: some other photos that are older that we've seen online

1846
01:38:17,840 --> 01:38:23,320
Speaker 10: where he looked more slender, but you know, he obviously

1847
01:38:23,560 --> 01:38:27,040
Speaker 10: looks much fuller in the face now on that mugshot.

1848
01:38:27,840 --> 01:38:30,400
Speaker 10: And you know, mugshots are never flattering. No, you know,

1849
01:38:30,600 --> 01:38:32,320
Speaker 10: I don't know if we can judge from that.

1850
01:38:32,320 --> 01:38:33,839
Speaker 3: That's what I told Donna earlier.

1851
01:38:33,880 --> 01:38:36,920
Speaker 1: I said, look, if somebody took my photo, no, I mean,

1852
01:38:37,240 --> 01:38:39,400
Speaker 1: if somebody from the FBI came over and took a

1853
01:38:39,439 --> 01:38:41,679
Speaker 1: mugshot of me right now for no reason, I would

1854
01:38:41,720 --> 01:38:43,719
Speaker 1: give a mugface just to give a mug face.

1855
01:38:44,000 --> 01:38:45,519
Speaker 3: And I'm not accused of murder.

1856
01:38:46,840 --> 01:38:49,479
Speaker 10: I'm pretty sure. I'm pretty sure. Just so you guys

1857
01:38:49,560 --> 01:38:52,000
Speaker 10: know that they tell you not to smile in those

1858
01:38:52,640 --> 01:38:55,599
Speaker 10: so I'm fairly certain that's what happens. But the guy

1859
01:38:55,640 --> 01:38:58,679
Speaker 10: looks like, you know, he'd been dragged out of bed.

1860
01:38:58,800 --> 01:39:00,720
Speaker 10: I don't know. I mean, I don't know if there

1861
01:39:00,760 --> 01:39:03,600
Speaker 10: was any resistance or anything, but terror is very scruppy.

1862
01:39:04,479 --> 01:39:07,080
Speaker 10: I was, you know, saw some people commenting on Twitter.

1863
01:39:07,120 --> 01:39:07,639
Speaker 5: He looked like.

1864
01:39:07,600 --> 01:39:10,599
Speaker 10: Somebody Dad in the Incredibles or something like that.

1865
01:39:10,640 --> 01:39:15,080
Speaker 2: Yeah, there's something balloonish like. I mean, there's it's just

1866
01:39:15,280 --> 01:39:17,439
Speaker 2: the weirdest mugshot. I mean, I get it. I get

1867
01:39:17,479 --> 01:39:20,599
Speaker 2: the mugshofster. So he was on the run for eight days,

1868
01:39:20,640 --> 01:39:23,960
Speaker 2: he was arrested in Illinois, and now he's got to

1869
01:39:23,960 --> 01:39:25,759
Speaker 2: be brought back to Ohio. Is that right?

1870
01:39:26,120 --> 01:39:28,120
Speaker 10: Well, I wouldn't. I wouldn't say that he was on

1871
01:39:28,160 --> 01:39:32,600
Speaker 10: the run. He had the Chicago address, and he is

1872
01:39:32,640 --> 01:39:37,519
Speaker 10: a vascular surgeon who was practicing in Rockford, Illinois. And

1873
01:39:37,560 --> 01:39:40,920
Speaker 10: according to the criminal complaint and the affidavid that was

1874
01:39:40,920 --> 01:39:44,960
Speaker 10: filed in the courts, he you know, they're saying that

1875
01:39:45,000 --> 01:39:49,320
Speaker 10: they pieced this together using surveillance video and then they

1876
01:39:49,400 --> 01:39:54,799
Speaker 10: tracked the suspect to a vehicle and then trapped the vehicle,

1877
01:39:54,880 --> 01:39:57,559
Speaker 10: and you know, piecing this all together with surveillance video,

1878
01:39:57,600 --> 01:40:00,519
Speaker 10: I'm sure they used some other technology as well. And

1879
01:40:00,560 --> 01:40:03,439
Speaker 10: they said that they found evidence in this vehicle they're

1880
01:40:03,479 --> 01:40:06,400
Speaker 10: not saying whether it was his or a rental car,

1881
01:40:07,120 --> 01:40:10,240
Speaker 10: but that they found evidence in the vehicle linking him

1882
01:40:11,160 --> 01:40:14,759
Speaker 10: to the homicides. So that's how this all came together.

1883
01:40:14,840 --> 01:40:18,439
Speaker 10: He doesn't even live here anymore. He's from Ohio, but

1884
01:40:18,600 --> 01:40:23,479
Speaker 10: had moved to Illinois and was living and practicing medicine there.

1885
01:40:24,400 --> 01:40:27,400
Speaker 10: I'm hearing too that he may have lied about his

1886
01:40:27,400 --> 01:40:30,559
Speaker 10: alibi and then when the Pops talked to him that

1887
01:40:30,680 --> 01:40:33,960
Speaker 10: he said, yeah, I was in Illinois, but then they

1888
01:40:34,000 --> 01:40:35,439
Speaker 10: figured out that he was in Ohio.

1889
01:40:35,760 --> 01:40:36,639
Speaker 3: Yeah, that's not good.

1890
01:40:36,640 --> 01:40:39,000
Speaker 1: Annette Leavy, by the way, from Long Crime with Stirling

1891
01:40:39,040 --> 01:40:40,920
Speaker 1: and Donade on the Big One, talking about this. A

1892
01:40:41,240 --> 01:40:45,120
Speaker 1: couple of the dentists and his wife and killed in Columbus,

1893
01:40:45,200 --> 01:40:48,360
Speaker 1: left the two children behind the dog as well, and

1894
01:40:48,439 --> 01:40:51,479
Speaker 1: the allegation is the ex husband drove here, came to

1895
01:40:51,640 --> 01:40:55,439
Speaker 1: Ohio and did them in and then went back. You

1896
01:40:55,439 --> 01:40:57,960
Speaker 1: know what's amazing, how many over the years, how many

1897
01:40:58,000 --> 01:41:01,720
Speaker 1: cases as a reporter, either locally here or elsewhere. And

1898
01:41:01,800 --> 01:41:04,200
Speaker 1: we know that you've had some very big, high profile

1899
01:41:04,280 --> 01:41:06,960
Speaker 1: cases you've covered, and Jeanette, that we've had you on

1900
01:41:07,000 --> 01:41:09,679
Speaker 1: the show about let alone just in general doing your work,

1901
01:41:09,880 --> 01:41:13,439
Speaker 1: but for long crime where it's it's ex husband ex wife,

1902
01:41:13,600 --> 01:41:16,519
Speaker 1: or domestic situations that have turned into some type of

1903
01:41:16,600 --> 01:41:19,080
Speaker 1: nightmare scenario like this, it seems like there's a high

1904
01:41:19,160 --> 01:41:23,120
Speaker 1: percentage of similar types of things, maybe not high profile.

1905
01:41:22,760 --> 01:41:23,160
Speaker 5: Though.

1906
01:41:26,200 --> 01:41:30,280
Speaker 10: You know, sadly it's I was talking to one of

1907
01:41:30,320 --> 01:41:33,960
Speaker 10: my friends yesterday who you know, works as a prosecutor

1908
01:41:34,000 --> 01:41:37,320
Speaker 10: and sometimes as a judge, and when I texted him

1909
01:41:37,360 --> 01:41:39,919
Speaker 10: and said, hey, they arrested the ex, he said typical.

1910
01:41:40,320 --> 01:41:44,080
Speaker 10: That's literally what he said in response. And it kind

1911
01:41:44,120 --> 01:41:46,880
Speaker 10: of is typical. I mean, that's who you usually look

1912
01:41:46,920 --> 01:41:51,320
Speaker 10: at first in a situation like this. What's kind of

1913
01:41:51,360 --> 01:41:55,080
Speaker 10: confounding about this and so mind boggling is that it's

1914
01:41:55,160 --> 01:41:59,959
Speaker 10: so long after the fact, But it's not always that unusual.

1915
01:42:00,080 --> 01:42:04,040
Speaker 10: I mean, this guy's innocn't until proven guilty. But you know,

1916
01:42:04,400 --> 01:42:07,439
Speaker 10: if you have somebody who just wouldn't let go, it's

1917
01:42:07,479 --> 01:42:13,320
Speaker 10: incredibly sad and just awful, but it sadly, you know,

1918
01:42:14,520 --> 01:42:17,160
Speaker 10: these types of things do happen, So I have I

1919
01:42:17,200 --> 01:42:19,000
Speaker 10: have covered quite a few. I mean, look at the

1920
01:42:19,000 --> 01:42:23,640
Speaker 10: Pike County massacre case that originated as kind of a

1921
01:42:23,720 --> 01:42:28,280
Speaker 10: domestic violence homicide where you know it's spun out of control.

1922
01:42:28,320 --> 01:42:32,120
Speaker 10: One person didn't want to let go of the relationship

1923
01:42:32,200 --> 01:42:36,519
Speaker 10: and the child, and you know that turned into an

1924
01:42:36,560 --> 01:42:43,759
Speaker 10: octuple homicide. It's terrific. So these the control and wanting

1925
01:42:43,800 --> 01:42:46,360
Speaker 10: control and not being able to let go can lead

1926
01:42:46,400 --> 01:42:47,960
Speaker 10: to these things, sadly.

1927
01:42:48,320 --> 01:42:51,760
Speaker 2: So I know that you don't nobody really knows the

1928
01:42:51,800 --> 01:42:55,479
Speaker 2: motive exactly except for the fact that this guy didn't

1929
01:42:55,520 --> 01:43:00,960
Speaker 2: want to have a divorce years ago, right years ago. So,

1930
01:43:01,320 --> 01:43:04,320
Speaker 2: and it doesn't say whether they had kept in contact.

1931
01:43:04,360 --> 01:43:07,240
Speaker 2: And I was talking to Sling about this earlier, like

1932
01:43:07,720 --> 01:43:10,719
Speaker 2: I've been divorced and I still talked to my ex

1933
01:43:10,880 --> 01:43:14,960
Speaker 2: and even all the people in my life that have

1934
01:43:15,040 --> 01:43:17,800
Speaker 2: been boyfriends, but I always seem to have maintained a

1935
01:43:17,880 --> 01:43:21,640
Speaker 2: relationship with them. Do we know if they've maintained a

1936
01:43:21,720 --> 01:43:26,080
Speaker 2: relationship since or I mean texting or anything like that.

1937
01:43:28,040 --> 01:43:30,640
Speaker 10: You know, we don't really know that. I don't know

1938
01:43:30,720 --> 01:43:35,960
Speaker 10: that I've been hearing that she feared him, but I

1939
01:43:36,240 --> 01:43:40,080
Speaker 10: don't know what, if any relationship there was. I can't

1940
01:43:40,120 --> 01:43:44,640
Speaker 10: imagine if she wanted out of the marriage, that she

1941
01:43:44,840 --> 01:43:47,760
Speaker 10: was staying in contact with him, unless you know she

1942
01:43:47,920 --> 01:43:51,479
Speaker 10: was trying to placate him or something, you know. And

1943
01:43:51,520 --> 01:43:53,760
Speaker 10: when I say that, you know obviously she has a

1944
01:43:53,840 --> 01:43:56,800
Speaker 10: husband that she had just celebrated her fit the anniversary

1945
01:43:56,840 --> 01:44:03,760
Speaker 10: with and had two children with. So I'm sure you

1946
01:44:03,800 --> 01:44:06,800
Speaker 10: know she's in love with her husband and has these children.

1947
01:44:06,880 --> 01:44:10,160
Speaker 10: She's a stay at home mom. Whether or not she

1948
01:44:10,240 --> 01:44:12,280
Speaker 10: was still in contact with him and just trying to

1949
01:44:12,280 --> 01:44:14,360
Speaker 10: be cordial, I have no clue. So I think that's

1950
01:44:14,360 --> 01:44:16,480
Speaker 10: something we'll learn as the case progresses.

1951
01:44:17,240 --> 01:44:21,760
Speaker 1: It's so common in whether it's local law enforcement at

1952
01:44:21,760 --> 01:44:24,200
Speaker 1: all levels and a lot of this domestic stuff. It

1953
01:44:24,240 --> 01:44:27,120
Speaker 1: even starts for some people. I mean they're in middle

1954
01:44:27,120 --> 01:44:29,439
Speaker 1: school or high school where you'll start to see these

1955
01:44:29,920 --> 01:44:34,200
Speaker 1: behavioral problems. Inability to let go is smothering and sometimes

1956
01:44:34,240 --> 01:44:38,000
Speaker 1: aggressive behavior. And I realize you're not a psychologist. Anteonette

1957
01:44:38,080 --> 01:44:40,040
Speaker 1: Levy from Long Crime with Stirling and Donade on the

1958
01:44:40,040 --> 01:44:42,400
Speaker 1: Big One talking about this horrible case out of Columbus

1959
01:44:43,120 --> 01:44:45,320
Speaker 1: and tying in with a guy who lived here in Mason,

1960
01:44:45,360 --> 01:44:49,160
Speaker 1: of course, who was the dentist, and then the guy

1961
01:44:49,240 --> 01:44:52,840
Speaker 1: from in Chicago now the surgeon who came back and

1962
01:44:52,960 --> 01:44:58,320
Speaker 1: allegedly killed them. I just it's bewildering to see how

1963
01:44:58,360 --> 01:45:01,599
Speaker 1: common it is as thankfully it's not more common that

1964
01:45:01,680 --> 01:45:04,559
Speaker 1: there isn't this level of violence that goes along with it,

1965
01:45:04,760 --> 01:45:08,920
Speaker 1: but it seems like a very disturbing trend in general,

1966
01:45:09,200 --> 01:45:12,840
Speaker 1: and mostly guys, but women can be crazy, insane, over

1967
01:45:12,880 --> 01:45:14,240
Speaker 1: the top and not letting go too.

1968
01:45:16,240 --> 01:45:19,280
Speaker 10: Oh of course, of course women. It can happen with

1969
01:45:19,360 --> 01:45:23,160
Speaker 10: women too. It may happen more with men, but yes,

1970
01:45:23,280 --> 01:45:25,760
Speaker 10: it can happen with women. You know, women can become

1971
01:45:25,840 --> 01:45:28,960
Speaker 10: obsessed and controlling most definitely.

1972
01:45:29,600 --> 01:45:31,840
Speaker 3: It's just an odd thing.

1973
01:45:31,880 --> 01:45:34,919
Speaker 1: And when you get kids involved in the domestic cases,

1974
01:45:35,000 --> 01:45:38,200
Speaker 1: even for law enforcement to respond to or some of

1975
01:45:38,240 --> 01:45:42,479
Speaker 1: the most dangerous engagements that they have, because oftentimes you

1976
01:45:42,560 --> 01:45:47,200
Speaker 1: have people, if they're directly involved with a situation, law

1977
01:45:47,280 --> 01:45:49,160
Speaker 1: enforcement will show up and they're like, well, he was

1978
01:45:49,200 --> 01:45:51,599
Speaker 1: beating her or she him, and then then they'll turn

1979
01:45:51,640 --> 01:45:54,880
Speaker 1: on the police, which is also bewildering. And I've talked

1980
01:45:54,880 --> 01:45:57,280
Speaker 1: to cop after cop on the show in real life

1981
01:45:57,280 --> 01:45:59,439
Speaker 1: away from the show, on this and so forth. It's

1982
01:45:59,520 --> 01:46:02,640
Speaker 1: just why it's just devastating, and I wonder, what do

1983
01:46:02,680 --> 01:46:06,000
Speaker 1: you think about this case compared to say, an eleven

1984
01:46:06,080 --> 01:46:08,599
Speaker 1: year old shot in a park downtown on the West

1985
01:46:08,680 --> 01:46:13,080
Speaker 1: end of Cincinnati or elsewhere. Why this takes such a

1986
01:46:13,160 --> 01:46:16,720
Speaker 1: higher level of national attention compared to the case of

1987
01:46:16,840 --> 01:46:18,800
Speaker 1: a couple of eleven year olds in the same park

1988
01:46:18,920 --> 01:46:22,360
Speaker 1: being killed and somehow not being able to keep that

1989
01:46:22,400 --> 01:46:24,760
Speaker 1: type of thing from being a repeat situation here.

1990
01:46:27,479 --> 01:46:30,200
Speaker 10: Why do I think it gains more national.

1991
01:46:29,760 --> 01:46:32,920
Speaker 1: Attention because of the kids, because of the mystery of

1992
01:46:32,960 --> 01:46:35,080
Speaker 1: the couple, rather than kids in a park.

1993
01:46:35,120 --> 01:46:35,840
Speaker 3: Seems a little bit.

1994
01:46:35,960 --> 01:46:39,200
Speaker 1: I don't know, they're both horribly tragic, nightmare scenarios. I

1995
01:46:39,280 --> 01:46:42,040
Speaker 1: just the rest of the country's eyeballing this case, not

1996
01:46:42,200 --> 01:46:43,519
Speaker 1: kids killed in a park as all.

1997
01:46:43,880 --> 01:46:46,760
Speaker 3: That's the thing. It's weird to me, I think.

1998
01:46:46,920 --> 01:46:49,720
Speaker 10: I think just the fact that it's so chilling, and

1999
01:46:49,760 --> 01:46:52,759
Speaker 10: the fact that these people were likely asleep in bed

2000
01:46:53,560 --> 01:46:56,559
Speaker 10: and their children were down the hall, and the children

2001
01:46:56,560 --> 01:47:00,640
Speaker 10: were left unharmed, and a dog apparently was in the

2002
01:47:00,680 --> 01:47:03,519
Speaker 10: bedroom with one of the children or maybe both children,

2003
01:47:04,240 --> 01:47:07,720
Speaker 10: not one hundred percent clear on that, and you know,

2004
01:47:08,640 --> 01:47:11,920
Speaker 10: no signs of forced entry, and it's a mystery, and

2005
01:47:12,160 --> 01:47:14,960
Speaker 10: everybody can you know, relate to that on some level.

2006
01:47:15,960 --> 01:47:18,799
Speaker 10: I think that's a big part of the reason something

2007
01:47:18,840 --> 01:47:22,800
Speaker 10: like this resonates and grips people. The case of the

2008
01:47:22,800 --> 01:47:25,320
Speaker 10: eleven year old girl you know, killed in the park

2009
01:47:25,439 --> 01:47:31,679
Speaker 10: is horrific for its own reasons. So I can't speak

2010
01:47:31,720 --> 01:47:37,679
Speaker 10: to why that doesn't resonate more strongly with a national audience.

2011
01:47:37,840 --> 01:47:41,880
Speaker 10: But this is something, you know, just monsters creeping around

2012
01:47:41,880 --> 01:47:45,320
Speaker 10: in the night, and the fact that it could happen,

2013
01:47:45,439 --> 01:47:46,959
Speaker 10: I think to any one of us.

2014
01:47:47,080 --> 01:47:50,280
Speaker 2: Well, because they knew each other. This is when Serlinge

2015
01:47:50,320 --> 01:47:53,240
Speaker 2: was talking about women do it too. It reminded me

2016
01:47:53,280 --> 01:47:57,519
Speaker 2: of the Betty Broaderick story where okay, well she her

2017
01:47:57,600 --> 01:48:00,920
Speaker 2: husband wanted a divorce. Do you remember this story, right?

2018
01:48:00,920 --> 01:48:04,760
Speaker 2: An Jeanette like, the husband wanted a divorce and I

2019
01:48:04,800 --> 01:48:09,559
Speaker 2: mean this was national and she just fought it. In

2020
01:48:09,600 --> 01:48:14,160
Speaker 2: this case, we don't know what the ex husband's motives are.

2021
01:48:14,280 --> 01:48:17,000
Speaker 2: We don't really know a ton about what's going on

2022
01:48:17,080 --> 01:48:22,519
Speaker 2: with this this murder in Columbus. But she went and

2023
01:48:22,800 --> 01:48:25,760
Speaker 2: you know, shot broke into their house. He had a

2024
01:48:25,800 --> 01:48:28,680
Speaker 2: new wife and they were totally in love, and she

2025
01:48:28,840 --> 01:48:31,960
Speaker 2: went and shot them both in their sleep. And it

2026
01:48:32,080 --> 01:48:34,880
Speaker 2: reminds me of this only on the woman's side. But

2027
01:48:35,040 --> 01:48:38,160
Speaker 2: she was so aggressive and she would say, I'm going

2028
01:48:38,240 --> 01:48:40,880
Speaker 2: to kill you she would leave all these messages on

2029
01:48:40,920 --> 01:48:43,320
Speaker 2: their phone, and he had a million He was a

2030
01:48:43,320 --> 01:48:46,280
Speaker 2: big attorney out in California. Do you remember this?

2031
01:48:48,200 --> 01:48:51,280
Speaker 10: I remember the name, but I didn't cover this and

2032
01:48:51,520 --> 01:48:53,479
Speaker 10: have it looked into it that closely. But I do

2033
01:48:53,640 --> 01:48:57,800
Speaker 10: remember the name Betty Broderick. But yes, you know, that's

2034
01:48:57,800 --> 01:49:02,200
Speaker 10: a perfect example. Yeah, yeah, how it can happen with

2035
01:49:02,240 --> 01:49:02,760
Speaker 10: women too.

2036
01:49:03,840 --> 01:49:06,479
Speaker 1: Well, anything else we haven't asked about this that you

2037
01:49:06,520 --> 01:49:09,120
Speaker 1: think is glaring? That makes sense that people would want

2038
01:49:09,160 --> 01:49:11,479
Speaker 1: to know or need to know, because I mean that's

2039
01:49:11,720 --> 01:49:13,640
Speaker 1: the thing. I mean, it is as big of a

2040
01:49:13,680 --> 01:49:16,800
Speaker 1: story when you flip around streaming services and news of

2041
01:49:16,840 --> 01:49:19,280
Speaker 1: all sorts. I mean that you know, there's you know,

2042
01:49:19,520 --> 01:49:22,640
Speaker 1: the Minnesota story, there's Syria, there's all the talk of

2043
01:49:22,680 --> 01:49:25,960
Speaker 1: Greenland and everything else in Iran. But in front of

2044
01:49:26,000 --> 01:49:28,400
Speaker 1: that is this murder case with this couple in Columbus.

2045
01:49:28,400 --> 01:49:29,879
Speaker 1: Almost it's amazing.

2046
01:49:31,760 --> 01:49:34,200
Speaker 10: Yeah, I think there's just a lot of questions still

2047
01:49:35,280 --> 01:49:39,559
Speaker 10: about what sparked us. You know, there may have been

2048
01:49:39,600 --> 01:49:44,400
Speaker 10: some sort of precipitate precipitating events. I don't know what

2049
01:49:44,439 --> 01:49:47,559
Speaker 10: that would be, and I think that maybe we'll get

2050
01:49:47,560 --> 01:49:50,599
Speaker 10: those answers. You know, it's all a theory at this point.

2051
01:49:50,840 --> 01:49:52,240
Speaker 10: You know, the case is going to have to make

2052
01:49:52,280 --> 01:49:55,800
Speaker 10: its way through the courts, but I think we have

2053
01:49:55,840 --> 01:49:59,000
Speaker 10: a lot of questions still. It's really awful. He's going

2054
01:49:59,040 --> 01:50:02,679
Speaker 10: to appear in court tomorrow in Illinois for an extradition hearing.

2055
01:50:03,320 --> 01:50:06,080
Speaker 10: At that point he'll make the decision whether he waves

2056
01:50:06,160 --> 01:50:10,080
Speaker 10: extradition or not, and then he'll be brought back to

2057
01:50:10,120 --> 01:50:13,840
Speaker 10: Ohio to you know, go through the process and appear

2058
01:50:13,880 --> 01:50:15,720
Speaker 10: in court for the charges here.

2059
01:50:16,520 --> 01:50:19,160
Speaker 1: Well, we appreciate what you do in making time, especially

2060
01:50:19,240 --> 01:50:21,600
Speaker 1: last minute, and sort of giving us some nuts and

2061
01:50:21,640 --> 01:50:23,639
Speaker 1: bolts of this that we may not have already had

2062
01:50:23,800 --> 01:50:25,920
Speaker 1: and heard. And you know, you do a great job

2063
01:50:25,960 --> 01:50:28,120
Speaker 1: doing what you do on long crime too. My mom

2064
01:50:28,320 --> 01:50:30,280
Speaker 1: texted me she was like, I saw talking about those

2065
01:50:30,320 --> 01:50:33,880
Speaker 1: tellings the dentist. I was like, okay, thanks. So she's

2066
01:50:33,880 --> 01:50:36,880
Speaker 1: a fan of yours too, she loves it. So that's tremendous.

2067
01:50:36,880 --> 01:50:38,479
Speaker 10: Sweet tell your mom, I said, thank you.

2068
01:50:38,760 --> 01:50:41,160
Speaker 1: I certainly well, best to you in the family and

2069
01:50:41,400 --> 01:50:43,120
Speaker 1: keep doing what you're doing and hopefully we'll have you

2070
01:50:43,160 --> 01:50:44,800
Speaker 1: back when there's actually good news. It seems like we

2071
01:50:44,880 --> 01:50:46,960
Speaker 1: only reach out when there's tragedy, which is a really

2072
01:50:47,000 --> 01:50:49,479
Speaker 1: devastating thing when I think about like people I like

2073
01:50:49,520 --> 01:50:50,040
Speaker 1: to talk to.

2074
01:50:51,400 --> 01:50:54,360
Speaker 10: Right it is, so call me back and we can

2075
01:50:54,360 --> 01:50:55,599
Speaker 10: talk about anything strilling.

2076
01:50:55,800 --> 01:51:00,240
Speaker 1: Okay, we'll be okay, Antonette Lee the long crime. I'm

2077
01:51:00,240 --> 01:51:03,240
Speaker 1: based in Cincinnati, but letting us know about everything with that,

2078
01:51:03,520 --> 01:51:06,240
Speaker 1: Dennis to killing and Columbus take care of yourself. That's

2079
01:51:06,240 --> 01:51:08,559
Speaker 1: Andrewette Leavy. H we had a little bit of time love.

2080
01:51:08,640 --> 01:51:11,599
Speaker 1: Chick's gonna follow us. He's sort of like the chocolate

2081
01:51:11,640 --> 01:51:14,920
Speaker 1: cookie outer layer of the Oreo cookie with the good

2082
01:51:14,960 --> 01:51:18,840
Speaker 1: stuff in between being some bearcat basketball on the road

2083
01:51:18,880 --> 01:51:20,880
Speaker 1: in Orlando with a five o'clock tip off.

2084
01:51:20,920 --> 01:51:22,280
Speaker 3: So check will follow us.

2085
01:51:22,600 --> 01:51:26,200
Speaker 1: You'll get Dan Horde and I think Terry Nelson's doing

2086
01:51:26,200 --> 01:51:28,879
Speaker 1: the call with Dan today, and probably here's someam Oegger

2087
01:51:29,240 --> 01:51:31,120
Speaker 1: and then after that you get Chick, and then later

2088
01:51:31,160 --> 01:51:33,120
Speaker 1: on you get Willy and everybody else sort of going

2089
01:51:33,120 --> 01:51:35,720
Speaker 1: along with that. What else is going on here? You

2090
01:51:35,800 --> 01:51:37,920
Speaker 1: were coughing. I thought we were over the sickness, but

2091
01:51:38,080 --> 01:51:38,640
Speaker 1: it seems like it.

2092
01:51:38,840 --> 01:51:41,800
Speaker 2: You know, it's just been a weird you know, both

2093
01:51:41,800 --> 01:51:44,320
Speaker 2: of us clearing our throats all the time. That doesn't

2094
01:51:44,360 --> 01:51:47,519
Speaker 2: normally happen to us, and it's like you're get cap

2095
01:51:47,960 --> 01:51:50,360
Speaker 2: the cough button. I'm going to cough button, and it's

2096
01:51:50,400 --> 01:51:54,720
Speaker 2: it's real weird. I don't know. I'm hoping that this

2097
01:51:54,760 --> 01:51:58,479
Speaker 2: flu season gets over and I get pretty unscaped by. Luckily,

2098
01:51:58,600 --> 01:52:00,400
Speaker 2: I haven't been sick, but I know a lot of

2099
01:52:00,400 --> 01:52:03,559
Speaker 2: people that are a terrible strain of the flu and

2100
01:52:03,960 --> 01:52:08,439
Speaker 2: COVID as well. So yeah, everybody, take your vitamins, wash

2101
01:52:08,479 --> 01:52:12,160
Speaker 2: your hands. Yeah, I know. Thankfully I don't have it either, but.

2102
01:52:12,439 --> 01:52:15,639
Speaker 1: I'm still bewildered. Last night I turned that game off.

2103
01:52:15,680 --> 01:52:18,000
Speaker 1: The Bears were way down. I'm like, this is no good.

2104
01:52:18,439 --> 01:52:22,160
Speaker 1: And then it was like the monumental comeback of comebacks,

2105
01:52:22,680 --> 01:52:24,840
Speaker 1: and then the world is on its ear and it's

2106
01:52:24,880 --> 01:52:27,400
Speaker 1: the Bears thirty one to twenty seven over the Packers.

2107
01:52:27,520 --> 01:52:29,200
Speaker 1: I was trying not to spend a whole lot of

2108
01:52:29,240 --> 01:52:31,800
Speaker 1: time watching football after the Bengals were done.

2109
01:52:31,960 --> 01:52:34,200
Speaker 3: I just I need a break, of course. But playoff

2110
01:52:34,200 --> 01:52:35,240
Speaker 3: football is so good.

2111
01:52:35,360 --> 01:52:38,639
Speaker 2: It is so good. And and and prior to that game,

2112
01:52:38,800 --> 01:52:43,519
Speaker 2: it was the Rams and Packers Panthers. Yeah yeah right,

2113
01:52:44,200 --> 01:52:49,519
Speaker 2: and and La One had a huge touchdown at the end.

2114
01:52:49,600 --> 01:52:50,160
Speaker 2: Was really good.

2115
01:52:50,240 --> 01:52:54,280
Speaker 1: Absolutely yeah. Forty nine Ers Eagles, later Chargers Patriots. Chick

2116
01:52:54,320 --> 01:52:56,160
Speaker 1: will be all over talking about that. Of course, some

2117
01:52:56,280 --> 01:52:58,800
Speaker 1: basketball Bengals latest and what they're gonna do maybe in

2118
01:52:58,840 --> 01:53:01,599
Speaker 1: the offseason. I mean, there's a lot going on. Straight

2119
01:53:01,640 --> 01:53:04,439
Speaker 1: away your three o'clock report. Also, thank you to Sean

2120
01:53:04,520 --> 01:53:08,439
Speaker 1: McMahon for keeping us online in time or something like that.

2121
01:53:08,880 --> 01:53:10,720
Speaker 1: In the same of course, for Alex Egan to get

2122
01:53:10,720 --> 01:53:13,240
Speaker 1: a going good show today, good guest, good calls, doctor

2123
01:53:13,240 --> 01:53:17,200
Speaker 1: Donal Schleck, Jeff Schaeffer, director of Applied AI Lab at

2124
01:53:17,240 --> 01:53:19,960
Speaker 1: the University of Cincinnati, and Jeanette Levy long Crime.

2125
01:53:19,960 --> 01:53:20,639
Speaker 3: And I think that does.

2126
01:53:20,720 --> 01:53:22,520
Speaker 2: We did a lot. I'm exhausted.

2127
01:53:23,640 --> 01:53:26,559
Speaker 1: Ken likes to say we cause more problems than we solve,

2128
01:53:26,680 --> 01:53:28,599
Speaker 1: but either way, we at least had good conversations.

2129
01:53:28,640 --> 01:53:30,639
Speaker 2: Yeah, we did. We had some great callers today.

2130
01:53:31,040 --> 01:53:33,639
Speaker 1: There you go your three o'clock report straight away, Chick

2131
01:53:33,720 --> 01:53:36,120
Speaker 1: his next Stirling Donnadie back next weekend.

2132
01:53:36,160 --> 01:53:38,080
Speaker 3: I do believe, Yes, I think so.

2133
01:53:38,200 --> 01:53:40,360
Speaker 1: Right here, the home of the Reds News Radio seven

2134
01:53:40,439 --> 01:53:42,320
Speaker 1: hundred WLW, Cincinnati,