1
00:00:00,000 --> 00:00:01,000
Speaker 1: The talk station.

2
00:00:03,240 --> 00:00:06,240
Speaker 2: It is six point thirty. It's Friday. Stay in the obvious.

3
00:00:06,320 --> 00:00:08,879
Speaker 2: It is time for tech Friday with Dave Hatter. In

4
00:00:08,960 --> 00:00:11,440
Speaker 2: trust It is Dave's company. He has been voted the

5
00:00:11,480 --> 00:00:14,920
Speaker 2: best IT company for businesses by the Business Courrier. I

6
00:00:14,920 --> 00:00:17,000
Speaker 2: trust the business career and I certainly trust Dave Hatter

7
00:00:17,040 --> 00:00:19,799
Speaker 2: and his team. So interest it dot Com to tap

8
00:00:19,840 --> 00:00:23,079
Speaker 2: into their awesome services. Welcome back, Dave Hatter. Happy Friday

9
00:00:23,079 --> 00:00:23,279
Speaker 2: to you.

10
00:00:24,200 --> 00:00:26,119
Speaker 3: Always good to be here, Brian, Thanks for having me,

11
00:00:26,160 --> 00:00:28,320
Speaker 3: and Happy Friday to you and Joe and all your listeners.

12
00:00:28,360 --> 00:00:31,280
Speaker 2: All right, everybody's seen the idea that artificial intelligence can

13
00:00:31,320 --> 00:00:35,440
Speaker 2: make clothed people look naked. But this is different. Apparently

14
00:00:35,560 --> 00:00:40,360
Speaker 2: chatbots stripper. Now you're gonna have to explain this to me,

15
00:00:40,479 --> 00:00:42,240
Speaker 2: you know me, I don't use made it and stuff

16
00:00:42,280 --> 00:00:42,559
Speaker 2: like that.

17
00:00:43,479 --> 00:00:45,879
Speaker 1: Yeah, you may be better off, Brian, you may be

18
00:00:45,920 --> 00:00:46,440
Speaker 1: better off.

19
00:00:46,560 --> 00:00:49,080
Speaker 3: So this is a story and wired and it's interesting

20
00:00:49,159 --> 00:00:52,760
Speaker 3: because you may have noticed in the media lately there's

21
00:00:52,800 --> 00:00:55,640
Speaker 3: been a lot of talk about this, specifically around Groc.

22
00:00:56,280 --> 00:01:00,880
Speaker 3: As a reminder, Groc is x ai a ka elon

23
00:01:01,040 --> 00:01:05,840
Speaker 3: Musk's chat bots. So when you think chatbot, when you

24
00:01:05,880 --> 00:01:09,080
Speaker 3: hear that word. Essentially, what they're talking about is large

25
00:01:09,160 --> 00:01:14,959
Speaker 3: language model based generative AI tools aka rock Gemini from Google,

26
00:01:16,160 --> 00:01:20,679
Speaker 3: Chat GPT from Open Ai, Claude, perplexity, et cetera. Now

27
00:01:20,840 --> 00:01:22,720
Speaker 3: it does a lot more than what I'm going to describe.

28
00:01:22,720 --> 00:01:25,319
Speaker 3: But you know the idea that if you go to chat, GPT,

29
00:01:25,600 --> 00:01:27,360
Speaker 3: you sit down, you type in a prompt and it

30
00:01:27,440 --> 00:01:31,399
Speaker 3: generates some kind of content text, audio, video, whatever. You know,

31
00:01:31,440 --> 00:01:35,840
Speaker 3: it's gotten much better at that these tools. And this

32
00:01:35,920 --> 00:01:37,520
Speaker 3: really gets to the heart of something you and I

33
00:01:37,520 --> 00:01:40,080
Speaker 3: have been talking about ever since AI sort of hit

34
00:01:40,120 --> 00:01:45,000
Speaker 3: the public's consciousness. Deep fakes which are could be audio,

35
00:01:45,080 --> 00:01:47,480
Speaker 3: could be video, could be text, but it's something that

36
00:01:47,680 --> 00:01:49,480
Speaker 3: is made up by the AI.

37
00:01:50,040 --> 00:01:50,520
Speaker 1: It's fake.

38
00:01:51,160 --> 00:01:53,400
Speaker 3: And you know, we've talked about the potential implications on

39
00:01:53,440 --> 00:01:57,680
Speaker 3: the legal system, on politics. But the latest thing that's

40
00:01:57,760 --> 00:02:01,120
Speaker 3: caused quite a stir is people have figured out how

41
00:02:01,160 --> 00:02:04,840
Speaker 3: to use these chatbot tools again think chat, GPT, rock whatever,

42
00:02:05,320 --> 00:02:09,160
Speaker 3: to take someone's photo and either a put them in

43
00:02:09,200 --> 00:02:12,600
Speaker 3: a bikini or b make them nude. And again this

44
00:02:12,720 --> 00:02:15,680
Speaker 3: story from whyre Google and Open AI's chatbots can strip

45
00:02:15,720 --> 00:02:18,840
Speaker 3: women down to photos, women in photos down to Bikinis

46
00:02:20,600 --> 00:02:24,320
Speaker 3: points out that this is fairly easy to do and unfortunately,

47
00:02:24,880 --> 00:02:29,720
Speaker 3: unfortunately are to stop. One of the terms you hear

48
00:02:29,760 --> 00:02:32,280
Speaker 3: when people talk about this is the idea of jail breaking,

49
00:02:32,360 --> 00:02:34,760
Speaker 3: that I'm purposely going to attempt to get one of

50
00:02:34,800 --> 00:02:42,560
Speaker 3: these chatbots to do something it's not supposed to do, right, yeah, like, yeah,

51
00:02:42,639 --> 00:02:45,359
Speaker 3: this is the latest thing. And you know, in many cases,

52
00:02:46,080 --> 00:02:48,320
Speaker 3: if someone just sits down and types in a prompt

53
00:02:48,840 --> 00:02:53,079
Speaker 3: give me this right, if that violates some rule, then

54
00:02:53,200 --> 00:02:56,400
Speaker 3: it'll say I can't do that. But what what people

55
00:02:56,440 --> 00:03:00,320
Speaker 3: have gotten good at is figuring out ways to spend

56
00:03:00,320 --> 00:03:03,160
Speaker 3: time working their way into what they want, you know,

57
00:03:03,200 --> 00:03:06,280
Speaker 3: step by step, trying to get to an end result

58
00:03:06,400 --> 00:03:09,200
Speaker 3: that would be denied if you just asked it straight out.

59
00:03:10,080 --> 00:03:13,160
Speaker 3: And I'm not saying that's necessarily what's happening here in

60
00:03:13,200 --> 00:03:16,359
Speaker 3: every case. I'm just saying it's really difficult to stop

61
00:03:16,400 --> 00:03:19,519
Speaker 3: people from jail breaking these things.

62
00:03:19,680 --> 00:03:22,400
Speaker 2: I just am led to the conclusion I just wonder,

63
00:03:23,480 --> 00:03:25,560
Speaker 2: don't these people have anything better to do with their

64
00:03:25,600 --> 00:03:27,799
Speaker 2: time day? I know that's a ridiculous thing to say,

65
00:03:27,840 --> 00:03:28,840
Speaker 2: but apparently they don't.

66
00:03:29,760 --> 00:03:33,000
Speaker 3: Apparently they don't, now, you know, and I understand why.

67
00:03:33,080 --> 00:03:35,440
Speaker 3: You know, if you're a woman and you have a

68
00:03:35,440 --> 00:03:39,560
Speaker 3: photo online and someone takes it and then put you

69
00:03:39,600 --> 00:03:43,120
Speaker 3: in a bikini or some other subjective thing or unfortunately makes.

70
00:03:43,000 --> 00:03:43,280
Speaker 1: You new it.

71
00:03:43,320 --> 00:03:47,400
Speaker 3: I mean, it's sad that this can happen, and I'm

72
00:03:47,400 --> 00:03:52,160
Speaker 3: not really sure ultimately it can be fixed. Again, can

73
00:03:52,200 --> 00:03:54,840
Speaker 3: they build these systems over time so that they can't

74
00:03:54,880 --> 00:03:58,880
Speaker 3: ever be jailbroken? I don't know, Brian, I really don't know.

75
00:03:59,800 --> 00:04:03,600
Speaker 3: I think it's a very difficult challenge. And then to your.

76
00:04:03,480 --> 00:04:07,120
Speaker 2: Point, a programmer, you're saying out loud, this is a

77
00:04:07,200 --> 00:04:10,800
Speaker 2: difficult challenge to get to that point. It's almost impossible,

78
00:04:11,080 --> 00:04:11,680
Speaker 2: is what I'm hearing.

79
00:04:12,640 --> 00:04:15,200
Speaker 3: Well, you know, maybe if the AI gets smart enough

80
00:04:15,200 --> 00:04:18,000
Speaker 3: that on its own, it could understand that it is

81
00:04:18,080 --> 00:04:20,680
Speaker 3: being led down a path to jail breaking to do

82
00:04:20,760 --> 00:04:23,680
Speaker 3: something it's not supposed to do. Maybe, But you know,

83
00:04:24,400 --> 00:04:26,280
Speaker 3: to your point, as a guy who spent a lot

84
00:04:26,320 --> 00:04:29,840
Speaker 3: of time writing code, could I anticipate every single way

85
00:04:29,880 --> 00:04:32,080
Speaker 3: that a user would do something that they shouldn't do

86
00:04:32,160 --> 00:04:34,960
Speaker 3: and that it would cause an error? It's really hard. Yeah,

87
00:04:35,080 --> 00:04:37,200
Speaker 3: it's really hard to do that, and that's why software

88
00:04:37,240 --> 00:04:39,240
Speaker 3: has bugs in it, right, you know, I know, it

89
00:04:39,320 --> 00:04:42,160
Speaker 3: never occurred to me they would do this one thing here,

90
00:04:42,760 --> 00:04:47,480
Speaker 3: and so it's a difficult challenge. I understand why women

91
00:04:47,520 --> 00:04:51,680
Speaker 3: are unhappy about this, especially like, you know, if this

92
00:04:51,760 --> 00:04:55,279
Speaker 3: was your daughter and some creep goes out and finds

93
00:04:55,279 --> 00:04:57,520
Speaker 3: a picture of her and next thing you know, there

94
00:04:57,520 --> 00:05:00,720
Speaker 3: are deep fake nudes of her floating or or again,

95
00:05:00,800 --> 00:05:04,719
Speaker 3: and suggestive photos and bikinis or whatever. I totally understand.

96
00:05:04,760 --> 00:05:06,320
Speaker 3: I think it's sad that this is a thing.

97
00:05:06,520 --> 00:05:09,760
Speaker 2: I think it could be embarrassing for guys too, right,

98
00:05:10,680 --> 00:05:13,480
Speaker 2: you know, I mean you could resize the junk and

99
00:05:13,760 --> 00:05:15,360
Speaker 2: embarrassed guys if you wanted, right.

100
00:05:15,920 --> 00:05:19,120
Speaker 3: Yeah, I mean you theoretically using these tools can alter

101
00:05:19,240 --> 00:05:23,120
Speaker 3: pictures in all kinds of ways, again, including nudes or

102
00:05:23,240 --> 00:05:25,480
Speaker 3: you know, could you try to frame someone with this?

103
00:05:25,720 --> 00:05:26,919
Speaker 1: Well, yeah, yeah you could.

104
00:05:27,000 --> 00:05:31,599
Speaker 3: It's this has been one of the latest things to

105
00:05:31,680 --> 00:05:34,520
Speaker 3: catch a lot of bad press. But when you when

106
00:05:34,520 --> 00:05:38,280
Speaker 3: you extrapolate out using these tools to take a photo

107
00:05:38,360 --> 00:05:42,320
Speaker 3: of someone or frankly, create a whole cloth photo of someone, yeah,

108
00:05:42,360 --> 00:05:44,120
Speaker 3: and then you know, put them into some kind of

109
00:05:44,160 --> 00:05:48,839
Speaker 3: compromising position, it's a real concern. And again, while groc

110
00:05:48,920 --> 00:05:52,400
Speaker 3: has gotten a lot of the the IR on this.

111
00:05:52,400 --> 00:05:54,359
Speaker 3: This is a story from Wired again pointing out the

112
00:05:54,440 --> 00:05:56,160
Speaker 3: Google and open.

113
00:05:55,920 --> 00:05:57,560
Speaker 1: Ai seem to have the same problem.

114
00:05:57,680 --> 00:06:00,360
Speaker 3: And you know it's it's just one of the many

115
00:06:00,440 --> 00:06:04,120
Speaker 3: challenges we face as a result of this technology. So

116
00:06:04,279 --> 00:06:06,800
Speaker 3: people should be aware of this. About the only thing

117
00:06:06,839 --> 00:06:08,760
Speaker 3: you can do to protect yourself from it is try

118
00:06:08,800 --> 00:06:12,320
Speaker 3: to limit the amount of photos that are out there

119
00:06:12,480 --> 00:06:13,200
Speaker 3: with you in them.

120
00:06:13,240 --> 00:06:15,479
Speaker 1: Yeah, good luck, which is difficult. Yeah, good luck.

121
00:06:15,520 --> 00:06:19,400
Speaker 3: And then understand that someone can potentially just create something

122
00:06:19,440 --> 00:06:21,839
Speaker 3: completely from whole cloth in and without a photo of

123
00:06:21,880 --> 00:06:24,640
Speaker 3: you to begin with, as this tech progresses.

124
00:06:24,720 --> 00:06:28,800
Speaker 2: So what a sad empathetic existence that person has who

125
00:06:28,880 --> 00:06:31,200
Speaker 2: takes the time to do this. We'll bring Dave patterback

126
00:06:31,279 --> 00:06:35,360
Speaker 2: talking about ways artificial intelligence can inflict damage. Plus stick

127
00:06:35,360 --> 00:06:39,880
Speaker 2: around comp It's six COVID sixty two. It's about kercittalk

128
00:06:39,920 --> 00:06:42,359
Speaker 2: station interest it dot com where you find Dave Patter

129
00:06:42,400 --> 00:06:45,120
Speaker 2: and you find them every week here on Friday morning,

130
00:06:45,120 --> 00:06:50,120
Speaker 2: meeting at six moving over ways artificial intelligence can inflict damage,

131
00:06:50,680 --> 00:06:53,800
Speaker 2: Unprecedented damage, says the headline of the zd net article

132
00:06:53,800 --> 00:06:56,800
Speaker 2: you'll have posted on LinkedIn on your account. Go ahead, Dave,

133
00:06:56,800 --> 00:06:57,240
Speaker 2: what's this all?

134
00:06:57,240 --> 00:06:59,640
Speaker 3: About Yeah, Brian, we won't have time to get into

135
00:06:59,640 --> 00:07:01,680
Speaker 3: all of these. I'm glad you mentioned that, so I'll

136
00:07:01,720 --> 00:07:04,800
Speaker 3: share this article. And I think that the headline is

137
00:07:04,800 --> 00:07:06,960
Speaker 3: a little hyperbolic, and I mean we just talked about

138
00:07:06,960 --> 00:07:08,560
Speaker 3: one of the ways they don't cover. This is more

139
00:07:08,560 --> 00:07:11,400
Speaker 3: of an IT focus for you as as a person

140
00:07:11,440 --> 00:07:14,200
Speaker 3: trying to defend your systems against this stuff. And I

141
00:07:14,200 --> 00:07:16,800
Speaker 3: would say, you know, every business needs to be thinking

142
00:07:16,840 --> 00:07:18,480
Speaker 3: about this, and I also want to start out with

143
00:07:19,720 --> 00:07:23,720
Speaker 3: these tools can be extremely powerful and productive if you

144
00:07:23,800 --> 00:07:26,360
Speaker 3: understand what they can and can't do, and you think

145
00:07:26,400 --> 00:07:28,920
Speaker 3: about some of the security issues that they point out.

146
00:07:28,960 --> 00:07:32,520
Speaker 3: In the cd in net article, a couple headlines are

147
00:07:32,560 --> 00:07:35,320
Speaker 3: a couple of topics. They say AI enabled malware will

148
00:07:35,400 --> 00:07:37,600
Speaker 3: unleash havoc. I'm just going to hit a couple of

149
00:07:37,600 --> 00:07:39,720
Speaker 3: these and come back to them. Agentic AI is involving

150
00:07:39,720 --> 00:07:44,960
Speaker 3: into every thread actor's fantasy. Prompting prompt injection AI tools

151
00:07:45,000 --> 00:07:47,760
Speaker 3: will be the new attack surface. Thread actors will use

152
00:07:47,760 --> 00:07:49,800
Speaker 3: AI to go after the weakest link humans. That's my

153
00:07:49,840 --> 00:07:52,200
Speaker 3: biggest concern. By the way, come back again, I'm going

154
00:07:52,200 --> 00:07:54,280
Speaker 3: to get into each of these a little bit. AI

155
00:07:54,400 --> 00:08:00,000
Speaker 3: will expose APIs too easily exploited. Extortion tactics will evolve

156
00:08:00,160 --> 00:08:03,120
Speaker 3: from ransomware encryption, and they mentioned in the next one

157
00:08:03,160 --> 00:08:06,600
Speaker 3: how contagion spreads to industrial control and operations. I don't

158
00:08:06,600 --> 00:08:08,320
Speaker 3: remember if we talked about this last year or not.

159
00:08:08,480 --> 00:08:12,400
Speaker 3: Range Rover Jaguar. Range Rover had a devastating ransomware attack.

160
00:08:12,480 --> 00:08:15,240
Speaker 3: They had some systems down for months, and the last

161
00:08:15,280 --> 00:08:17,760
Speaker 3: number I saw they lost something like two billion dollars.

162
00:08:18,000 --> 00:08:20,240
Speaker 3: People got laid off there, People got laid off with

163
00:08:20,280 --> 00:08:22,960
Speaker 3: their suppliers because their suppliers had nothing to do since

164
00:08:23,000 --> 00:08:26,080
Speaker 3: they weren't making cars. I mean, it was a devastating attack,

165
00:08:26,160 --> 00:08:29,760
Speaker 3: not necessarily AI related, but they're just drawing the nexus

166
00:08:29,800 --> 00:08:34,040
Speaker 3: of these things and the two big threats I think

167
00:08:34,120 --> 00:08:37,040
Speaker 3: every business really needs to consider around AI as it

168
00:08:37,120 --> 00:08:37,720
Speaker 3: stands today.

169
00:08:37,720 --> 00:08:41,040
Speaker 1: Again, there's a couple more in this article. If you

170
00:08:41,880 --> 00:08:42,560
Speaker 1: don't have.

171
00:08:42,480 --> 00:08:45,199
Speaker 3: People that understand what these things can and can't do,

172
00:08:45,280 --> 00:08:47,760
Speaker 3: the idea of hallucinations and so forth, and you can't

173
00:08:47,800 --> 00:08:50,559
Speaker 3: just assume anything that it creates as one hundred percent accurate,

174
00:08:51,320 --> 00:08:56,560
Speaker 3: that's a problem. And when you couple that with the

175
00:08:56,600 --> 00:08:59,120
Speaker 3: idea that I'm going to have an AI agent that

176
00:08:59,200 --> 00:09:01,200
Speaker 3: can go do something on its own. It's not a

177
00:09:01,240 --> 00:09:04,439
Speaker 3: human being sitting and typing prompts in and getting.

178
00:09:04,120 --> 00:09:05,240
Speaker 1: Output and doing something.

179
00:09:05,679 --> 00:09:09,000
Speaker 3: I'm going to let something run on its own and

180
00:09:09,040 --> 00:09:11,200
Speaker 3: do stuff. I'm going to give it credentials, use your

181
00:09:11,240 --> 00:09:13,960
Speaker 3: name and passwords so it can act on its own.

182
00:09:15,480 --> 00:09:17,600
Speaker 3: There is an enormous amount of risk in that. They

183
00:09:17,640 --> 00:09:19,440
Speaker 3: talk about that in here, and there are many other

184
00:09:19,559 --> 00:09:22,679
Speaker 3: articles about that. I'm not saying you shouldn't do it.

185
00:09:22,760 --> 00:09:25,680
Speaker 3: I'm not saying it can't work. What I'm saying is

186
00:09:26,160 --> 00:09:29,520
Speaker 3: if you think that you're just going to give this

187
00:09:29,600 --> 00:09:32,480
Speaker 3: thing a user name and password and let it start

188
00:09:32,480 --> 00:09:37,200
Speaker 3: doing stuff that that couldn't go catastrophically wrong, you need

189
00:09:37,240 --> 00:09:41,480
Speaker 3: to be very very careful and really understand all the

190
00:09:41,480 --> 00:09:43,839
Speaker 3: ins and outs of that. And frankly, if you give

191
00:09:43,880 --> 00:09:46,000
Speaker 3: it credentials and let it do things on its own,

192
00:09:46,520 --> 00:09:48,920
Speaker 3: have you secured it correctly so it can't be hacked?

193
00:09:48,960 --> 00:09:51,880
Speaker 3: And then the bad guys are now operating with permissions

194
00:09:51,920 --> 00:09:54,480
Speaker 3: in your system, the permissions that you gave it. So

195
00:09:55,280 --> 00:09:58,200
Speaker 3: that's something everyone needs to look at very carefully and

196
00:09:58,360 --> 00:10:00,960
Speaker 3: really understand what the risks are and make sure they're

197
00:10:01,520 --> 00:10:06,360
Speaker 3: taking adequate protection against that risk. But the biggest thing

198
00:10:06,440 --> 00:10:09,640
Speaker 3: I'm still mostly concerned about is as these tools progress,

199
00:10:09,720 --> 00:10:11,680
Speaker 3: as we just talked about in the last segment about

200
00:10:11,679 --> 00:10:15,240
Speaker 3: the bikini thing, it's easier and easier and easier for

201
00:10:15,280 --> 00:10:18,480
Speaker 3: bad guys to create things that are incredibly realistic, including

202
00:10:18,520 --> 00:10:22,080
Speaker 3: cloning someone's voice. For example, so you come into work,

203
00:10:22,400 --> 00:10:25,240
Speaker 3: there's a quote voicemail unquote from your boss telling you

204
00:10:25,280 --> 00:10:26,920
Speaker 3: to do a transfer of some sort.

205
00:10:27,760 --> 00:10:29,000
Speaker 1: Sounds exactly like them.

206
00:10:29,240 --> 00:10:32,320
Speaker 3: They got your voices or your boss's voice from his

207
00:10:32,440 --> 00:10:35,560
Speaker 3: voicemail or from some public speech he gave, or whatever.

208
00:10:35,880 --> 00:10:38,240
Speaker 3: They use a tool to clone his voice, a deep

209
00:10:38,280 --> 00:10:42,400
Speaker 3: fake voice clone. It's simple, it's free, and these things

210
00:10:42,440 --> 00:10:46,360
Speaker 3: are unbelievably good at this now, so you know the

211
00:10:46,440 --> 00:10:51,040
Speaker 3: idea that as a criminal, I can create text, audio,

212
00:10:51,080 --> 00:10:54,160
Speaker 3: and video that is unbelievably realistic. It will look exactly

213
00:10:54,240 --> 00:10:57,560
Speaker 3: like the real person. Could you get a call where

214
00:10:57,600 --> 00:11:01,160
Speaker 3: the hacker is literally using a voice cloning tool and

215
00:11:01,200 --> 00:11:03,560
Speaker 3: talking to you real time by typing a response in

216
00:11:03,600 --> 00:11:06,040
Speaker 3: and hitting a button and generating a voice. Yes, that

217
00:11:06,160 --> 00:11:08,000
Speaker 3: is a thing at this point. I think you and

218
00:11:08,040 --> 00:11:11,440
Speaker 3: I talked about the Ferrari situation last year where the

219
00:11:11,520 --> 00:11:14,760
Speaker 3: CFO of Ferrari almost was fooled by a voice clone

220
00:11:14,800 --> 00:11:17,000
Speaker 3: of the CEO of Ferrari. I mean they know each

221
00:11:17,040 --> 00:11:20,320
Speaker 3: other personally, they work together all the time. So I

222
00:11:20,360 --> 00:11:23,600
Speaker 3: think the average person does not realize how advanced all

223
00:11:23,640 --> 00:11:25,400
Speaker 3: this stuff is at this point in terms of this

224
00:11:25,480 --> 00:11:29,520
Speaker 3: deep faate capability, and every business should be training their employees,

225
00:11:29,760 --> 00:11:32,400
Speaker 3: you know, on the risks how to use this stuff,

226
00:11:32,559 --> 00:11:37,080
Speaker 3: the risks of it, and particularly cybersecurity awareness training that

227
00:11:37,160 --> 00:11:40,880
Speaker 3: includes something around AI, because I mean, we see it

228
00:11:41,880 --> 00:11:44,640
Speaker 3: growing and we've talked about the Grandparent scam and all

229
00:11:44,679 --> 00:11:47,880
Speaker 3: this stuff. Businesses are going to be increasingly targeted with

230
00:11:47,960 --> 00:11:51,880
Speaker 3: sophisticated attacks, not only from a technical perspective with AI,

231
00:11:52,040 --> 00:11:54,200
Speaker 3: but focused on the humans. It's one of the points

232
00:11:54,200 --> 00:11:57,160
Speaker 3: in this article, you know, fooling human beings into doing

233
00:11:57,200 --> 00:12:02,000
Speaker 3: something they shouldn't do using the advanced capability. So you know,

234
00:12:02,160 --> 00:12:04,240
Speaker 3: we can help. If anyone wants some help, call me up.

235
00:12:04,280 --> 00:12:08,680
Speaker 3: I'm happy to talk about this. But this is only

236
00:12:08,720 --> 00:12:10,920
Speaker 3: going to get worse before it gets better, because most

237
00:12:10,920 --> 00:12:15,480
Speaker 3: people do not understand how capable this stuff is in

238
00:12:15,559 --> 00:12:18,679
Speaker 3: terms of creating things that seem unbelievably realistic. Sadly, it's

239
00:12:19,120 --> 00:12:19,880
Speaker 3: believe it's a thing.

240
00:12:19,960 --> 00:12:20,360
Speaker 1: Folks.

241
00:12:20,600 --> 00:12:25,200
Speaker 2: Yeah, I can't believe you yearly can't linked LinkedIn dot com.

242
00:12:25,280 --> 00:12:27,000
Speaker 2: Let's look for Dave Hadder. You'll find him and you'll

243
00:12:27,000 --> 00:12:29,520
Speaker 2: find all the articles in information. One more and there's

244
00:12:29,520 --> 00:12:31,680
Speaker 2: a feature on your Google Gmail.

245
00:12:31,559 --> 00:12:33,120
Speaker 1: Five KRC the talk station.

246
00:12:38,520 --> 00:12:40,800
Speaker 2: It is six fifty one six two fifty five krcity

247
00:12:40,840 --> 00:12:44,800
Speaker 2: talk station. All right, what's the story on this Gmail

248
00:12:44,880 --> 00:12:46,679
Speaker 2: feature that you we need to turn off?

249
00:12:46,760 --> 00:12:51,440
Speaker 3: Dave hatter Well, Brian, you should know me well left

250
00:12:51,440 --> 00:12:54,400
Speaker 3: to know by now. My initial response is this headline

251
00:12:54,640 --> 00:12:56,600
Speaker 3: rather than if you use Gmail, you're going to want

252
00:12:56,600 --> 00:13:00,280
Speaker 3: to turn off this one automatic setting asapp should day

253
00:13:00,360 --> 00:13:05,440
Speaker 3: instead stop using Gmail. But good pud since it doesn't

254
00:13:05,480 --> 00:13:09,920
Speaker 3: say that, let me explain. Now this article is a

255
00:13:09,960 --> 00:13:12,079
Speaker 3: few months old, and again I'll post the link. If

256
00:13:12,080 --> 00:13:14,480
Speaker 3: you use Gmail and you plan to keep using Gmail,

257
00:13:14,559 --> 00:13:17,760
Speaker 3: I strongly recommend that you read this. And this is

258
00:13:17,840 --> 00:13:20,040
Speaker 3: one of the problems I have with all of these

259
00:13:20,040 --> 00:13:24,000
Speaker 3: big tech tech platforms. It's not just Google, right, So

260
00:13:24,120 --> 00:13:29,680
Speaker 3: many of these things are basically surveillance capitalism driven. You

261
00:13:29,800 --> 00:13:32,920
Speaker 3: are the product, not the customer. It's your data that

262
00:13:33,000 --> 00:13:36,920
Speaker 3: makes them quote free unquote for you, and when you

263
00:13:36,960 --> 00:13:40,520
Speaker 3: look at the ever increasing leaks of your data, the

264
00:13:41,120 --> 00:13:43,840
Speaker 3: ways this data is used in ways you would not

265
00:13:43,920 --> 00:13:48,840
Speaker 3: necessarily understand, and things like surveillance pricing. I just wrote

266
00:13:48,880 --> 00:13:50,679
Speaker 3: an op ed on this, which i'll have out there.

267
00:13:50,679 --> 00:13:52,880
Speaker 3: Maybe we talk about that next week. The idea that

268
00:13:52,920 --> 00:13:56,000
Speaker 3: because there's so much data about you out there and

269
00:13:56,040 --> 00:13:58,360
Speaker 3: these companies are capturing it, they're selling it to other

270
00:13:58,400 --> 00:14:01,200
Speaker 3: companies and so forth, I'm able to look at your

271
00:14:01,240 --> 00:14:03,720
Speaker 3: profile and say, you know what, I think Brian Thomas

272
00:14:03,720 --> 00:14:05,880
Speaker 3: would pay more for this than Dave Hatter. Looks like

273
00:14:05,960 --> 00:14:08,720
Speaker 3: he's probably got more money, or maybe he's more desperate

274
00:14:08,760 --> 00:14:10,880
Speaker 3: to get this thing, So even though we're on the

275
00:14:10,960 --> 00:14:14,320
Speaker 3: same website, you might see a higher price than me.

276
00:14:14,679 --> 00:14:17,640
Speaker 3: It's a real thing that's happening all the time. And

277
00:14:17,679 --> 00:14:19,960
Speaker 3: that's I bring that up because I think it's one

278
00:14:19,960 --> 00:14:23,040
Speaker 3: of the most concrete ways to help regular folks who

279
00:14:23,080 --> 00:14:26,640
Speaker 3: aren't tenfoil hat wearing nerds like me understand why you

280
00:14:26,680 --> 00:14:29,040
Speaker 3: should care about all your data. Because I still hear

281
00:14:29,080 --> 00:14:30,440
Speaker 3: why I don't care about that. You know, I don't

282
00:14:30,480 --> 00:14:33,080
Speaker 3: care about privacy. Second, nothing to hide, and I'm going

283
00:14:33,160 --> 00:14:34,800
Speaker 3: to come back to this article but I'm just trying

284
00:14:34,840 --> 00:14:36,520
Speaker 3: to set the stage for why you should care about

285
00:14:36,560 --> 00:14:39,640
Speaker 3: this and why I find this approach to things offensive.

286
00:14:39,720 --> 00:14:42,560
Speaker 3: So these companies will opt you into things. They roll

287
00:14:42,600 --> 00:14:45,640
Speaker 3: out some new feature that's beneficial for them, They turn

288
00:14:45,720 --> 00:14:47,360
Speaker 3: it on, and you have to figure out how to

289
00:14:47,400 --> 00:14:49,840
Speaker 3: turn it off, and often you don't even know this

290
00:14:49,880 --> 00:14:53,200
Speaker 3: has been done. Secondarily, even if you do, it's you know,

291
00:14:53,320 --> 00:14:55,840
Speaker 3: buried thirty six menus in and they tell you seven

292
00:14:55,920 --> 00:14:59,120
Speaker 3: times why you shouldn't turn it off. Dark patterns, trying

293
00:14:59,120 --> 00:15:02,320
Speaker 3: to convince you to turn off something that is beneficial

294
00:15:02,360 --> 00:15:04,880
Speaker 3: to them. And so to the heart of this article,

295
00:15:05,520 --> 00:15:10,560
Speaker 3: Google Gemini, that's their AI chatout platform, Generative AILM if

296
00:15:10,600 --> 00:15:15,880
Speaker 3: you will. They have now incorporated it into Gmail so

297
00:15:15,960 --> 00:15:18,520
Speaker 3: it can train off all of your emails. So if

298
00:15:18,560 --> 00:15:20,520
Speaker 3: you've been using Gmail for a long time, you might

299
00:15:20,560 --> 00:15:23,320
Speaker 3: have tens of thousands, hundreds of thousands of emails in there.

300
00:15:23,680 --> 00:15:26,320
Speaker 3: This thing is in there reading your emails, learning about you,

301
00:15:26,520 --> 00:15:29,880
Speaker 3: training purportedly to help you, right, because it's going to

302
00:15:29,960 --> 00:15:35,920
Speaker 3: help you schedule tasks and do things and compose emails

303
00:15:35,920 --> 00:15:38,080
Speaker 3: on your behalf and so forth. Right, But I'm going

304
00:15:38,120 --> 00:15:39,880
Speaker 3: to quote directly from the article for around of time.

305
00:15:39,920 --> 00:15:42,840
Speaker 3: Important message for everyone using Gmail. You've been automatically opted

306
00:15:42,880 --> 00:15:45,880
Speaker 3: in to allow Gmail to access all your private messages

307
00:15:45,920 --> 00:15:49,520
Speaker 3: and attachments to train AI models. Engineer Dave Jones shared

308
00:15:49,560 --> 00:15:51,400
Speaker 3: on X earlier this week. Again, this was a couple

309
00:15:51,440 --> 00:15:53,720
Speaker 3: of years ago, a couple months ago. You have to

310
00:15:53,760 --> 00:15:56,760
Speaker 3: manually turn off the quote smart features in the setting

311
00:15:56,920 --> 00:16:00,120
Speaker 3: menu in two locations. So first off, you have to

312
00:16:00,200 --> 00:16:03,080
Speaker 3: know that this has been turned on. Secondarily, you have

313
00:16:03,120 --> 00:16:04,840
Speaker 3: to know where to go. And then third you have

314
00:16:04,880 --> 00:16:07,240
Speaker 3: to go to two different places to turn it off.

315
00:16:07,680 --> 00:16:11,800
Speaker 3: And again it's it's the fact that they if you

316
00:16:12,040 --> 00:16:14,600
Speaker 3: have fully informed consent and you agree to use the

317
00:16:14,680 --> 00:16:17,280
Speaker 3: Gmail and you agree to use this feature, have at

318
00:16:17,280 --> 00:16:20,680
Speaker 3: it for an adult. Do what you want. I don't

319
00:16:20,760 --> 00:16:23,000
Speaker 3: use Gmail, and if I did, I would turn this off.

320
00:16:23,080 --> 00:16:23,520
Speaker 1: There you go.

321
00:16:23,640 --> 00:16:25,600
Speaker 2: That's the final point and we are at a time.

322
00:16:25,720 --> 00:16:28,640
Speaker 2: So heed his advice. Go to LinkedIn dot com find Dave.

323
00:16:28,680 --> 00:16:30,440
Speaker 2: How do you'll find these articles and you can read

324
00:16:30,480 --> 00:16:32,840
Speaker 2: the whys and the wearforce. Dave, thank you for what

325
00:16:32,880 --> 00:16:34,720
Speaker 2: you do for here on the morning show. My listeners.

326
00:16:34,760 --> 00:16:37,720
Speaker 2: Thanks to Interest I your company for sponsoring them. And

327
00:16:37,800 --> 00:16:42,560
Speaker 2: another word for Interest I interest dot com. Thank you brother,

328
00:16:42,680 --> 00:16:45,800
Speaker 2: have a great weekend. Don't go away. Corey Bowman up next.

329
00:16:46,960 --> 00:16:49,640
Speaker 2: Today's tough headlines coming up at the