1
00:00:02,160 --> 00:00:05,440
Speaker 1: Now here's a highlight from Coast to Coast AM on

2
00:00:05,559 --> 00:00:08,880
Speaker 1: iHeartRadio and welcome back to Coast to Coast George Norri

3
00:00:09,000 --> 00:00:10,520
Speaker 1: with you. Let me tell you a little bit about

4
00:00:10,560 --> 00:00:15,800
Speaker 1: doctor Maryland Singleton, a board certified anesthesiologist. Doctor Maryland Singleton

5
00:00:16,239 --> 00:00:21,160
Speaker 1: graduated from Stanford and earned her MD at UCSF Medical School.

6
00:00:21,560 --> 00:00:26,360
Speaker 1: She completed two years of surgery residency at UCSF and

7
00:00:26,400 --> 00:00:31,080
Speaker 1: then her an anesthesia residency at Harvard's Beth Israel Hospital.

8
00:00:31,120 --> 00:00:34,440
Speaker 1: While still working in the operated room, she attended uc

9
00:00:34,640 --> 00:00:38,960
Speaker 1: Berkeley's Law School, focusing on constitutional law and administrative law.

10
00:00:39,280 --> 00:00:44,680
Speaker 1: Doctor Singleton has become concerned that technology and algorithms will

11
00:00:44,720 --> 00:00:48,240
Speaker 1: soon be making medical decisions instead of humans in order

12
00:00:48,240 --> 00:00:51,559
Speaker 1: to maximize profits at the expense of what's best for

13
00:00:51,600 --> 00:00:55,000
Speaker 1: the patient. Doctor Maryland Singleton on Coast to Coast, Happy

14
00:00:55,000 --> 00:00:58,960
Speaker 1: holidays to you, Maryland. Well, same to you, and I'm

15
00:00:59,120 --> 00:01:04,479
Speaker 1: so glad to be here tonight. What an amazing subject. Well,

16
00:01:04,520 --> 00:01:09,160
Speaker 1: it's certainly caught my eye when last year a study

17
00:01:09,280 --> 00:01:13,640
Speaker 1: came out that Google was working on where they put

18
00:01:13,680 --> 00:01:18,399
Speaker 1: all the data of several patients into the computer and

19
00:01:18,600 --> 00:01:23,199
Speaker 1: could predict which patients were going to die. How soon

20
00:01:23,800 --> 00:01:27,240
Speaker 1: and whether they leave the hospital or not, and that

21
00:01:27,400 --> 00:01:32,240
Speaker 1: their prediction came out better than the doctors according to them.

22
00:01:32,640 --> 00:01:35,959
Speaker 1: Tell us exactly, Marilyn. If you can, in Layman's terms,

23
00:01:36,080 --> 00:01:42,119
Speaker 1: what is an algorithm, it's basically taking a lot of data.

24
00:01:42,319 --> 00:01:45,560
Speaker 1: And I mean and a person can make an algorithm

25
00:01:45,880 --> 00:01:49,160
Speaker 1: for themselves, and we probably do that in our own

26
00:01:49,240 --> 00:01:53,720
Speaker 1: heads in everyday life. If Johnny doesn't do the dishes,

27
00:01:54,320 --> 00:01:57,560
Speaker 1: then I'll have to do the dishes. That's a very

28
00:01:57,560 --> 00:02:03,640
Speaker 1: basic algorithm. And if this, then that, if this then that,

29
00:02:03,920 --> 00:02:06,280
Speaker 1: and then you take all the facts and put them

30
00:02:06,320 --> 00:02:12,200
Speaker 1: in and come up with an answer. Of the problem

31
00:02:12,400 --> 00:02:17,920
Speaker 1: is in medicine, so much of how we treat people

32
00:02:18,080 --> 00:02:23,960
Speaker 1: and how we really cure people comes very individually with

33
00:02:24,080 --> 00:02:27,359
Speaker 1: the patient. There always seems to be some little glitch.

34
00:02:27,800 --> 00:02:31,040
Speaker 1: A computer would see it as a glitch in each

35
00:02:31,160 --> 00:02:35,760
Speaker 1: patient that they just don't follow the rules. And this

36
00:02:35,840 --> 00:02:38,960
Speaker 1: is a real problem. If they say, well, we'll have

37
00:02:39,040 --> 00:02:41,880
Speaker 1: the computer make the decision. You'll just feed in all

38
00:02:41,919 --> 00:02:46,040
Speaker 1: the data, feed in the lab tests. But then you have,

39
00:02:46,200 --> 00:02:50,680
Speaker 1: as silly as it may sound, you have miracles. And

40
00:02:51,000 --> 00:02:55,560
Speaker 1: plenty of people have a story of somebody who was

41
00:02:55,600 --> 00:02:59,560
Speaker 1: supposed to die. They were on death store and somehow

42
00:02:59,600 --> 00:03:03,120
Speaker 1: they did die. Well, what do you do with that patient?

43
00:03:03,520 --> 00:03:06,680
Speaker 1: What do you say? The computer said you were supposed

44
00:03:06,720 --> 00:03:08,880
Speaker 1: to die, so I guess we have to kill you.

45
00:03:09,360 --> 00:03:14,280
Speaker 1: It's a it's going to be a very very slippery

46
00:03:14,320 --> 00:03:19,600
Speaker 1: slope of how much we use this data and how

47
00:03:19,680 --> 00:03:24,079
Speaker 1: much we decide it can think better than we can.

48
00:03:24,760 --> 00:03:30,200
Speaker 1: Also remembering who inputs the data, human being doctor Jack

49
00:03:30,280 --> 00:03:35,560
Speaker 1: of Orgian, the angel of death, wouldn't be concerned, wouldn't he? Well,

50
00:03:35,600 --> 00:03:40,920
Speaker 1: if that's very interesting because in my view, years ago,

51
00:03:42,240 --> 00:03:48,720
Speaker 1: Orkian was considered a gool for helping people die, even

52
00:03:48,880 --> 00:03:52,760
Speaker 1: and presumably these people wanted to die, and he was

53
00:03:52,840 --> 00:03:58,240
Speaker 1: in fact convicted of slaughter. I believe it was manslaughter,

54
00:03:58,320 --> 00:04:02,440
Speaker 1: it could have been second degree murder. And now some

55
00:04:02,560 --> 00:04:07,440
Speaker 1: of our laws are just allowing this. And so when

56
00:04:07,480 --> 00:04:11,280
Speaker 1: people think, oh, X, Y or Z will never happen,

57
00:04:11,680 --> 00:04:14,560
Speaker 1: we don't have to think back too many years to

58
00:04:14,600 --> 00:04:18,640
Speaker 1: see how we viewed something twenty years ago, and then

59
00:04:18,760 --> 00:04:22,839
Speaker 1: now it's completely different and it's happening now. They are

60
00:04:23,120 --> 00:04:30,040
Speaker 1: encouraging doctor assisted suicide and who to funk it? That's right,

61
00:04:30,080 --> 00:04:32,320
Speaker 1: he didn't know he was convicted of second degree murder

62
00:04:32,400 --> 00:04:36,680
Speaker 1: Maryland and was the sentenced to served eight years of

63
00:04:36,720 --> 00:04:39,480
Speaker 1: a ten to twenty five year prison the term, and

64
00:04:39,760 --> 00:04:44,039
Speaker 1: then he died in June of twenty eleven. I wonder though,

65
00:04:44,240 --> 00:04:48,480
Speaker 1: if he enjoyed doing what he was doing, because that's

66
00:04:48,520 --> 00:04:54,040
Speaker 1: where that ghoul thing comes in. Well, I think one

67
00:04:54,080 --> 00:04:58,600
Speaker 1: of the things that bothered people he was a pathologist

68
00:04:59,120 --> 00:05:04,240
Speaker 1: and not a clinical physician, so some people thought, well,

69
00:05:04,560 --> 00:05:08,240
Speaker 1: he doesn't really see patients and he's not an internist

70
00:05:09,120 --> 00:05:15,040
Speaker 1: family doctor or whatever. But I think he was compassionate.

71
00:05:15,520 --> 00:05:19,640
Speaker 1: I certainly didn't know him, so who knows, and all

72
00:05:19,680 --> 00:05:22,640
Speaker 1: you can go by is what was written about him,

73
00:05:23,400 --> 00:05:27,159
Speaker 1: And I think he believed in what he was doing.

74
00:05:27,800 --> 00:05:32,599
Speaker 1: It was not medically or socially acceptable at that time,

75
00:05:33,000 --> 00:05:37,960
Speaker 1: and then magically now it's socially acceptable. And what's interesting

76
00:05:38,000 --> 00:05:42,039
Speaker 1: to me is it seems we've regressed because if you

77
00:05:42,160 --> 00:05:48,160
Speaker 1: go back to ancient Greece, the elders decided which babies

78
00:05:48,240 --> 00:05:52,400
Speaker 1: lived or died and which old people lived or died.

79
00:05:52,680 --> 00:05:56,799
Speaker 1: When you outlived your usefulness, boom, you were gone. And

80
00:05:57,040 --> 00:05:59,880
Speaker 1: then we seem to evolve from that, and it seems

81
00:06:00,040 --> 00:06:03,280
Speaker 1: like we're going back the other way now we're we're

82
00:06:03,360 --> 00:06:07,040
Speaker 1: just deciding, well, you're expendable, we don't need you anymore,

83
00:06:07,600 --> 00:06:11,400
Speaker 1: and yes it's okay to kill babies at birth. What

84
00:06:11,560 --> 00:06:16,560
Speaker 1: concerns you roll in the most about all this, that

85
00:06:16,760 --> 00:06:21,360
Speaker 1: we're losing our humanity? And you know, it's it's interesting

86
00:06:22,520 --> 00:06:27,200
Speaker 1: because in the news we see things about the sex

87
00:06:27,400 --> 00:06:31,000
Speaker 1: robots and all this stuff, and I would read it

88
00:06:31,040 --> 00:06:36,520
Speaker 1: and just laugh when it came out it was exactly

89
00:06:36,720 --> 00:06:41,440
Speaker 1: and then suddenly it doesn't seem so silly anymore because

90
00:06:41,760 --> 00:06:47,359
Speaker 1: people are actually buying into this stuff. Apparently the sales

91
00:06:47,400 --> 00:06:49,520
Speaker 1: are up. And then you look at kids. They aren't

92
00:06:49,720 --> 00:06:52,560
Speaker 1: dating because they're afraid to date because of all this

93
00:06:52,720 --> 00:06:58,560
Speaker 1: political correctness, and you wonder where it's all going. First,

94
00:06:58,600 --> 00:07:03,120
Speaker 1: you don't talk to people because people are standing right

95
00:07:03,200 --> 00:07:08,080
Speaker 1: next to each other, but they're texting each other. What that?

96
00:07:09,040 --> 00:07:14,560
Speaker 1: And what happened to people talking to each other. It's

97
00:07:14,680 --> 00:07:19,080
Speaker 1: become really unusual if you say, well, I'll call you,

98
00:07:19,120 --> 00:07:23,160
Speaker 1: and oh, well text me the information, and I don't think, oh,

99
00:07:23,480 --> 00:07:26,520
Speaker 1: I don't think most younger people can go to dinner

100
00:07:26,720 --> 00:07:30,880
Speaker 1: with a friend and not put their phone away where

101
00:07:30,920 --> 00:07:34,080
Speaker 1: they don't look at it for the entire dinner. Instead,

102
00:07:34,400 --> 00:07:37,560
Speaker 1: they put it on the bartop or the restaurant table.

103
00:07:38,080 --> 00:07:41,600
Speaker 1: It's there in case somebody texts them or if they

104
00:07:41,640 --> 00:07:43,600
Speaker 1: want to send a text. I don't think they can

105
00:07:43,640 --> 00:07:46,760
Speaker 1: physically put it away. They're too addicted to it. I

106
00:07:46,800 --> 00:07:50,120
Speaker 1: think you're right, and I certainly see that. And just

107
00:07:50,280 --> 00:07:53,320
Speaker 1: going for a walk and seeing people walking together and

108
00:07:53,400 --> 00:07:57,120
Speaker 1: they both have their phones out. So all these things

109
00:07:58,080 --> 00:08:02,680
Speaker 1: taken individually, you can sort of fluff it off. But

110
00:08:02,800 --> 00:08:05,760
Speaker 1: then when you start adding it up, you have people

111
00:08:05,840 --> 00:08:09,280
Speaker 1: not talking to each other anymore, people forgetting how to

112
00:08:09,360 --> 00:08:14,240
Speaker 1: talk to each other. Therefore, you don't become comfortable with

113
00:08:14,400 --> 00:08:18,679
Speaker 1: human emotions. And maybe you'd prefer to sit in front

114
00:08:18,720 --> 00:08:23,080
Speaker 1: of a computer screen for you know, to learn about

115
00:08:23,680 --> 00:08:27,920
Speaker 1: news the world or whatever, rather than having a discussion

116
00:08:27,960 --> 00:08:33,320
Speaker 1: with someone. And so bit by bit we're just we're

117
00:08:33,360 --> 00:08:36,880
Speaker 1: just losing our humanity. Do you remember the movie years ago,

118
00:08:37,160 --> 00:08:41,680
Speaker 1: Fantastic Voyage? Yes, And this for people who have never

119
00:08:41,720 --> 00:08:44,720
Speaker 1: seen it before. A guy had some kind of tumor

120
00:08:44,920 --> 00:08:49,040
Speaker 1: or some clot or something that needed to be operated on,

121
00:08:49,480 --> 00:08:52,280
Speaker 1: and the only way they could get to it was

122
00:08:52,440 --> 00:08:55,920
Speaker 1: to shrink the medical people and put them in this

123
00:08:56,080 --> 00:08:59,520
Speaker 1: little tiny machine, like a little spaceship that was so

124
00:09:00,040 --> 00:09:04,040
Speaker 1: newt it traveled through his bloodstream and they went to

125
00:09:04,080 --> 00:09:07,520
Speaker 1: the tumor to fix the guy. It was an amazing story.

126
00:09:07,640 --> 00:09:13,880
Speaker 1: Is that doable one day? I don't know. It's what's

127
00:09:14,040 --> 00:09:21,800
Speaker 1: interesting is now they are putting DNA chips in inanimate objects.

128
00:09:22,280 --> 00:09:25,760
Speaker 1: There's a DNA chip I just read the other day

129
00:09:26,320 --> 00:09:31,400
Speaker 1: that they've put in a toy rabbit. So I don't

130
00:09:31,440 --> 00:09:35,640
Speaker 1: completely understand how they do it, and i'd like to,

131
00:09:37,679 --> 00:09:42,240
Speaker 1: but they can put what is it, millions and millions

132
00:09:42,240 --> 00:09:47,560
Speaker 1: and millions time more information in this little DNA chip

133
00:09:47,679 --> 00:09:51,200
Speaker 1: than you could in a computer chip. And so somehow

134
00:09:51,240 --> 00:09:55,920
Speaker 1: they've encoded DNA put it in in animate objects, and

135
00:09:56,200 --> 00:10:02,360
Speaker 1: that's stunning to me. So certainly this whole concept of

136
00:10:02,480 --> 00:10:05,800
Speaker 1: fantastic voyage could be out there. I don't know that

137
00:10:05,840 --> 00:10:09,800
Speaker 1: you could shrink people, but certainly you could make some

138
00:10:09,880 --> 00:10:15,240
Speaker 1: sort of capsule with a curative item in it and

139
00:10:15,880 --> 00:10:19,320
Speaker 1: float it through the human body. Listen to more Coast

140
00:10:19,360 --> 00:10:22,960
Speaker 1: to Coast AM every weeknight at one am Eastern, and

141
00:10:23,200 --> 00:10:25,600
Speaker 1: go to Coast to Coast am dot com for more