1 00:00:00,240 --> 00:00:04,680 Speaker 1: From UFOs to psychic powers and government conspiracies. History is 2 00:00:04,760 --> 00:00:09,080 Speaker 1: riddled with unexplained events. You can turn back now or 3 00:00:09,200 --> 00:00:12,079 Speaker 1: learn the stuff they don't want you to know. A 4 00:00:12,200 --> 00:00:25,680 Speaker 1: production of I Heart Radio. Hello, welcome back to the show. 5 00:00:25,800 --> 00:00:28,440 Speaker 1: My name is Matt, my name is Noman. They called 6 00:00:28,480 --> 00:00:31,840 Speaker 1: me Ben. We're joined as always with our super producer Paul. 7 00:00:31,960 --> 00:00:36,440 Speaker 1: Mission Control decads. Most importantly, you are you, You are here, 8 00:00:36,560 --> 00:00:39,199 Speaker 1: and that makes this the stuff they don't want you 9 00:00:39,320 --> 00:00:44,680 Speaker 1: to know. Hail, fellow travelers, Welcome. Congratulations to everybody who 10 00:00:44,800 --> 00:00:47,839 Speaker 1: has made it through the weekend. I think as we 11 00:00:47,920 --> 00:00:51,519 Speaker 1: get closer to the end of what this current calendar 12 00:00:51,600 --> 00:00:55,280 Speaker 1: tells us as a year, we're all we're all thinking ahead, 13 00:00:55,600 --> 00:00:59,880 Speaker 1: and we're all thinking back into the past. As thing 14 00:01:00,040 --> 00:01:04,399 Speaker 1: is begin to wrap up in two hurtles towards us, 15 00:01:05,160 --> 00:01:08,880 Speaker 1: we are finding that the world of the future maybe 16 00:01:09,200 --> 00:01:12,600 Speaker 1: a little bit different from the world of the past. Today, 17 00:01:12,680 --> 00:01:16,880 Speaker 1: we're diving into the world of technology. We're diving into 18 00:01:17,280 --> 00:01:20,399 Speaker 1: um some of the hints that the natural world is 19 00:01:20,480 --> 00:01:25,280 Speaker 1: giving human civilization, hints that indicate things might not be 20 00:01:25,600 --> 00:01:30,520 Speaker 1: so hunky dory. But let's maybe let's maybe start with 21 00:01:30,800 --> 00:01:35,840 Speaker 1: the world of tech. One thing that our fellow European 22 00:01:35,959 --> 00:01:39,920 Speaker 1: conspiracy realists are able to enjoy is something called the 23 00:01:40,000 --> 00:01:42,480 Speaker 1: right to be forgotten. You guys have heard of the 24 00:01:42,560 --> 00:01:44,600 Speaker 1: right to be forgotten? Right, It's It's not a thing 25 00:01:44,640 --> 00:01:46,720 Speaker 1: in the US yet, No. I mean, it's just the 26 00:01:46,720 --> 00:01:50,840 Speaker 1: idea of like your Internet footprint being in some way 27 00:01:50,880 --> 00:01:54,840 Speaker 1: available to be erased, right yeah, yeah, it's it's the 28 00:01:54,920 --> 00:01:59,880 Speaker 1: idea that you your private information can be removed from 29 00:02:00,000 --> 00:02:05,160 Speaker 1: Internet searches other directories under some specific circumstances. So for 30 00:02:05,280 --> 00:02:09,360 Speaker 1: everybody who grew up pre Internet, yes, those folks are 31 00:02:09,400 --> 00:02:12,800 Speaker 1: out there. Hopefully they are hale and healthy. Um. You know, 32 00:02:12,840 --> 00:02:15,280 Speaker 1: you'll hear people of that age sometimes say, God, I'm 33 00:02:15,280 --> 00:02:18,200 Speaker 1: glad TikTok and YouTube weren't around when I was growing 34 00:02:18,280 --> 00:02:21,799 Speaker 1: up because I did some cringe stuff. And the Internet, 35 00:02:21,880 --> 00:02:25,880 Speaker 1: like the mythical elephant, never forgets. Which is why today's 36 00:02:25,960 --> 00:02:31,600 Speaker 1: first story I advanced is so fascinating. If you believe 37 00:02:32,639 --> 00:02:35,480 Speaker 1: Facebook a k A meta or should I say metat 38 00:02:35,560 --> 00:02:40,840 Speaker 1: need Facebook, Uh, then then um there proposing to do 39 00:02:40,960 --> 00:02:44,680 Speaker 1: something that has caught the attention of many many people. 40 00:02:45,240 --> 00:02:49,600 Speaker 1: Facebook users present and former, caught the eyes of tech 41 00:02:49,680 --> 00:02:54,120 Speaker 1: analysts and policy walks. Facebook says it is going to 42 00:02:54,360 --> 00:03:00,160 Speaker 1: purposely forget some things, some very controversial things. Question is 43 00:03:01,080 --> 00:03:05,000 Speaker 1: do you believe them? Yes, you're right. Let's jump right 44 00:03:05,040 --> 00:03:08,760 Speaker 1: into the story today. This comes from The Guardian. It 45 00:03:08,800 --> 00:03:12,680 Speaker 1: was posted last Tuesday, election day here in the United States. 46 00:03:13,400 --> 00:03:17,079 Speaker 1: Facebook to shut down facial recognition system and delete one 47 00:03:17,120 --> 00:03:22,600 Speaker 1: billion face prints. That is the headline. Uh Nature, as 48 00:03:22,639 --> 00:03:24,600 Speaker 1: you said, Ben has reached out and said we no 49 00:03:24,639 --> 00:03:27,360 Speaker 1: longer need your faces. In this case, it is Meta 50 00:03:27,800 --> 00:03:32,120 Speaker 1: saying that, uh, the the parent company of Facebook. Now, 51 00:03:32,639 --> 00:03:34,600 Speaker 1: if you didn't catch it, Meta is to Facebook as 52 00:03:34,639 --> 00:03:38,520 Speaker 1: alphabet is to Google. Eha. Here we go. Things get 53 00:03:38,560 --> 00:03:43,760 Speaker 1: weirder every day. So why would Facebook shut down its 54 00:03:43,800 --> 00:03:48,480 Speaker 1: facial recognition system? Seems like something of the future, something 55 00:03:48,520 --> 00:03:51,720 Speaker 1: that is inevitable, something that would be very useful for 56 00:03:51,760 --> 00:03:54,240 Speaker 1: a company and social media website that has billions and 57 00:03:54,280 --> 00:04:02,200 Speaker 1: billions of users. Remember that includes Instagram. Yeah, well it's Facebook. Meta, 58 00:04:02,480 --> 00:04:05,240 Speaker 1: I should say, says that they are closing down their 59 00:04:05,280 --> 00:04:12,640 Speaker 1: facial recognition technology due to quote many concerns literally quote 60 00:04:12,960 --> 00:04:20,440 Speaker 1: many concerns about the techns. Yeah, we'll get into why. 61 00:04:20,520 --> 00:04:24,920 Speaker 1: Maybe Facebook is concerned about those concerns. All of a sudden, 62 00:04:25,480 --> 00:04:30,320 Speaker 1: But this is the most important part. They are deleting 63 00:04:30,400 --> 00:04:34,479 Speaker 1: the face prints that have already been collected. So if 64 00:04:34,560 --> 00:04:37,440 Speaker 1: you have gone through your Facebook or Instagram or one 65 00:04:37,480 --> 00:04:40,200 Speaker 1: of your other apps that is somehow being used by 66 00:04:40,200 --> 00:04:45,160 Speaker 1: Facebook and created a face print, like given the company permission, 67 00:04:45,760 --> 00:04:48,240 Speaker 1: or if there's just a face print that is made 68 00:04:48,240 --> 00:04:51,240 Speaker 1: of you, whether you knew it or not. Um, it's 69 00:04:51,320 --> 00:04:54,719 Speaker 1: it's going away, which is kind of which is nice. 70 00:04:54,880 --> 00:04:58,760 Speaker 1: Hey ya. One less version of my face that can 71 00:04:58,800 --> 00:05:01,240 Speaker 1: be you know you is to buy a company to 72 00:05:01,279 --> 00:05:06,680 Speaker 1: find out if my image shows up anywhere on its platform. Um. 73 00:05:06,880 --> 00:05:08,440 Speaker 1: One of the biggest things just to hear to talk 74 00:05:08,480 --> 00:05:11,360 Speaker 1: about is that Facebook itself and I guess now well, 75 00:05:11,440 --> 00:05:16,480 Speaker 1: Facebook under meta has been under all kinds of pressure, political, legal, 76 00:05:17,160 --> 00:05:21,159 Speaker 1: regulatory pressure over various things that its software does and 77 00:05:21,200 --> 00:05:24,839 Speaker 1: the information that it keeps track of about its users. Uh. 78 00:05:25,040 --> 00:05:28,360 Speaker 1: In this case, this again, facial recognition software was used 79 00:05:28,360 --> 00:05:31,080 Speaker 1: to keep track of photos and videos. Let you know, 80 00:05:31,279 --> 00:05:33,640 Speaker 1: as a user and end user, whether or not you're 81 00:05:33,680 --> 00:05:36,440 Speaker 1: showing up on somebody else's feed somebody posted a picture 82 00:05:36,480 --> 00:05:39,400 Speaker 1: of you, which can be really helpful. Right. We all 83 00:05:39,440 --> 00:05:43,320 Speaker 1: do all kinds of various interesting things on the week days, 84 00:05:43,400 --> 00:05:46,480 Speaker 1: at nights, sometimes on the weekends, that maybe we don't 85 00:05:46,480 --> 00:05:50,000 Speaker 1: want a picture showing up on Facebook or Instagram. Of right, 86 00:05:50,320 --> 00:05:52,919 Speaker 1: doesn't mean we're doing anything wrong. It just means maybe 87 00:05:52,920 --> 00:05:55,200 Speaker 1: you don't want a picture of you after a couple 88 00:05:55,240 --> 00:05:58,919 Speaker 1: of drinks at a bar something like that. And according 89 00:05:58,920 --> 00:06:03,279 Speaker 1: to Meta's vice president of artificial intelligence, uh wow, what 90 00:06:03,360 --> 00:06:05,560 Speaker 1: a title to have on your door. You had an 91 00:06:05,600 --> 00:06:10,600 Speaker 1: office h Jerome PICENTI P E S E N T I. Uh. 92 00:06:10,920 --> 00:06:14,280 Speaker 1: This tech, this facial recognition software was being used by 93 00:06:14,360 --> 00:06:19,599 Speaker 1: visually impaired users and blind users to identify their friends 94 00:06:20,320 --> 00:06:24,160 Speaker 1: in images and also to help prevent fraud and impersonation. 95 00:06:24,320 --> 00:06:28,640 Speaker 1: Again this comes from the Guardian Um, but really they 96 00:06:28,640 --> 00:06:30,799 Speaker 1: were just weighing all of those advantages and the good 97 00:06:30,839 --> 00:06:33,600 Speaker 1: things about it against quote growing concerns about the use 98 00:06:33,600 --> 00:06:37,200 Speaker 1: of that this technology as a whole, and I just 99 00:06:37,240 --> 00:06:40,440 Speaker 1: wanted to bring it, bring this to our attention, I guess, 100 00:06:40,440 --> 00:06:43,080 Speaker 1: and have a discussion about it because last year there 101 00:06:43,240 --> 00:06:47,320 Speaker 1: was a pretty big class action lawsuit that was levied 102 00:06:47,360 --> 00:06:51,479 Speaker 1: against Facebook where they ended up paying I think six 103 00:06:51,560 --> 00:06:56,440 Speaker 1: hundred and fifty million dollars to settle it. And you know, 104 00:06:57,480 --> 00:06:59,960 Speaker 1: that's a lot of money. When we talked about the 105 00:07:00,000 --> 00:07:03,480 Speaker 1: cost of doing business, that's not that much for Facebook, 106 00:07:03,839 --> 00:07:06,880 Speaker 1: but it's still enough to where if that kind of 107 00:07:06,920 --> 00:07:10,880 Speaker 1: fine can be levied against the company for what occurred, 108 00:07:10,920 --> 00:07:13,400 Speaker 1: then then you can only imagine the things in the future, 109 00:07:13,560 --> 00:07:16,760 Speaker 1: like what what problems could be presented legally for them. 110 00:07:16,800 --> 00:07:19,760 Speaker 1: They also set a precedent, Oh yes, they did, like 111 00:07:20,200 --> 00:07:22,480 Speaker 1: a legal precedent was set by the government, and then 112 00:07:22,560 --> 00:07:27,160 Speaker 1: Facebook set a precedent by paying the fine. So they 113 00:07:27,240 --> 00:07:31,720 Speaker 1: set themselves up like they they can't pull a sorry officer, 114 00:07:31,800 --> 00:07:34,400 Speaker 1: I didn't know you. I couldn't do that the next 115 00:07:34,400 --> 00:07:38,120 Speaker 1: time something like this comes around, you know. So yeah, 116 00:07:38,160 --> 00:07:39,920 Speaker 1: well yeah, And the whole point of that class action 117 00:07:40,000 --> 00:07:45,000 Speaker 1: lawsuit was that users were claiming that Facebook used this 118 00:07:45,080 --> 00:07:49,440 Speaker 1: facial recognition technology to create these these face profiles for 119 00:07:49,600 --> 00:07:53,360 Speaker 1: people without their consent, right with it, without their even 120 00:07:53,560 --> 00:07:58,000 Speaker 1: knowledge or permission. Um. So it's just really interesting stuff. 121 00:07:58,520 --> 00:08:01,800 Speaker 1: We got a listener voice mail in from someone very 122 00:08:01,800 --> 00:08:05,480 Speaker 1: recently talking about how face I D with Apple and 123 00:08:05,520 --> 00:08:09,400 Speaker 1: a couple other facial recognition software programs have kind of 124 00:08:09,720 --> 00:08:12,880 Speaker 1: been the same core thing. And then it was purchased 125 00:08:12,920 --> 00:08:15,880 Speaker 1: by someone and integrated into another service, and then that 126 00:08:15,920 --> 00:08:19,600 Speaker 1: was purchased and integrated, And how facial recognition is becoming 127 00:08:19,640 --> 00:08:26,400 Speaker 1: this one almost singular thing. Um not necessarily true, because 128 00:08:26,400 --> 00:08:28,560 Speaker 1: the code changes each time it changes hands at least 129 00:08:28,600 --> 00:08:31,560 Speaker 1: a little bit. But just this concept to me of 130 00:08:32,840 --> 00:08:35,200 Speaker 1: your computer or your device, whatever it is you're using, 131 00:08:35,280 --> 00:08:37,880 Speaker 1: no matter what the platform, just the concept that it 132 00:08:37,960 --> 00:08:41,319 Speaker 1: will recognize your face when you use it, to use 133 00:08:41,400 --> 00:08:45,560 Speaker 1: it and then to uh connect with other people. Uh yeah, 134 00:08:45,920 --> 00:08:51,880 Speaker 1: that's weird stuff. It's also there there's a controversy surrounding 135 00:08:51,960 --> 00:08:54,760 Speaker 1: the opt in opt out nature. I've I've talked about 136 00:08:54,840 --> 00:08:58,720 Speaker 1: the importance of this from a psychological perspective for a while. 137 00:08:58,800 --> 00:09:02,840 Speaker 1: We've mentioned this and stepisodes like the wonderful study that 138 00:09:02,960 --> 00:09:06,480 Speaker 1: found people are more likely to be organ donors if 139 00:09:06,520 --> 00:09:09,360 Speaker 1: they have to opt out of it when they get 140 00:09:09,400 --> 00:09:13,280 Speaker 1: those driver's license versus volunteering to opt in their kidneys 141 00:09:13,320 --> 00:09:16,840 Speaker 1: and their hearts and what have you. When Facebook initially 142 00:09:16,960 --> 00:09:22,600 Speaker 1: rolled out facial recognition in it was automatically enabled and 143 00:09:22,880 --> 00:09:26,199 Speaker 1: you could, um, you could opt out, but you had 144 00:09:26,240 --> 00:09:28,040 Speaker 1: to be aware of it, and you had to go 145 00:09:28,720 --> 00:09:31,120 Speaker 1: actually opt out. You had to go dig through the 146 00:09:31,160 --> 00:09:34,760 Speaker 1: byzantine menus um, which are purposely confusing, I would argue, 147 00:09:35,360 --> 00:09:39,360 Speaker 1: and I believe Facebook only made it explicitly opt in 148 00:09:40,120 --> 00:09:43,800 Speaker 1: like nine years later. That's why they have so many. 149 00:09:43,880 --> 00:09:45,840 Speaker 1: That's why they have like, what is it more than 150 00:09:45,880 --> 00:09:49,840 Speaker 1: a billion? Right? They have more than a billion individual profiles. Uh. 151 00:09:49,880 --> 00:09:53,120 Speaker 1: And I'm gonna say this, like, even if they even 152 00:09:53,160 --> 00:09:57,320 Speaker 1: if Meta or Facebook or whatever name it wants to 153 00:09:57,320 --> 00:10:01,960 Speaker 1: go by, even if it is in good faith race 154 00:10:02,360 --> 00:10:08,160 Speaker 1: those databases, it's it's too late, very much like that 155 00:10:08,280 --> 00:10:11,440 Speaker 1: data has been sold to third party companies. Hasn't it 156 00:10:11,520 --> 00:10:15,480 Speaker 1: that that has already been scraped. It's already out there. 157 00:10:15,520 --> 00:10:17,440 Speaker 1: It's not as if they're going to go back to 158 00:10:18,120 --> 00:10:22,000 Speaker 1: whatever third party has that information and say, hey, guys 159 00:10:23,080 --> 00:10:28,600 Speaker 1: are bad, we want to fix this. Yeah. Um, let 160 00:10:28,600 --> 00:10:30,920 Speaker 1: me let me just read some of what is stated 161 00:10:31,040 --> 00:10:35,160 Speaker 1: in here. Uh. In the Guardian article, they note that quote, 162 00:10:35,160 --> 00:10:39,240 Speaker 1: if users have opted into the facial recognition setting, the 163 00:10:39,320 --> 00:10:42,920 Speaker 1: face print used to identify them will be deleted. If 164 00:10:42,960 --> 00:10:46,600 Speaker 1: that face recognition setting is turned off, Meta said there 165 00:10:46,679 --> 00:10:52,360 Speaker 1: is no face print to delete. Sure, Uh. Presenting said 166 00:10:52,440 --> 00:10:57,040 Speaker 1: Facebook will encourage users to tag posts manually instead, which 167 00:10:57,080 --> 00:10:58,880 Speaker 1: is a very big thing has been a big thing 168 00:10:58,960 --> 00:11:02,160 Speaker 1: for a long time. Tagging your friends and family if 169 00:11:02,160 --> 00:11:06,960 Speaker 1: you post an image or video platform, don't do it. 170 00:11:09,720 --> 00:11:13,280 Speaker 1: But first, all biases joy, I mean, yeah, you're you're right, 171 00:11:13,400 --> 00:11:16,040 Speaker 1: and that like that is their official statement. They did 172 00:11:16,080 --> 00:11:22,400 Speaker 1: have that. Fine. Um My big question guys is is 173 00:11:22,480 --> 00:11:25,520 Speaker 1: this uh is this a temporary thing to move the 174 00:11:25,520 --> 00:11:29,680 Speaker 1: news cycle away from stuff like making a version of 175 00:11:29,720 --> 00:11:33,400 Speaker 1: Instagram for children? Is this? Like? What? What? What's their 176 00:11:33,520 --> 00:11:36,160 Speaker 1: end game? Because I think it will come back. I 177 00:11:36,200 --> 00:11:38,319 Speaker 1: think that as long as other companies are doing this, 178 00:11:38,440 --> 00:11:41,640 Speaker 1: you know, maybe quote unquote Facebook won't, but I wouldn't 179 00:11:41,640 --> 00:11:44,359 Speaker 1: be surprised if a few years down the road, metaverse 180 00:11:44,520 --> 00:11:47,360 Speaker 1: rolls out something that is facial recognition and all but name. 181 00:11:47,800 --> 00:11:49,959 Speaker 1: You know, well, sure, I mean, it's just like changing 182 00:11:49,960 --> 00:11:52,080 Speaker 1: their name to Meta in the first place. You know, 183 00:11:52,200 --> 00:11:55,840 Speaker 1: it's like they're they're not actually changing anything fundamental about 184 00:11:56,200 --> 00:11:58,720 Speaker 1: what Facebook is or any of the nature of the 185 00:11:58,760 --> 00:12:01,439 Speaker 1: problems that people were giving them a hard time, or 186 00:12:01,920 --> 00:12:03,800 Speaker 1: very justly in the first place. It's just like, oh, hey, 187 00:12:03,840 --> 00:12:06,400 Speaker 1: look over here, it's not Facebook anymore. Meta is doing it. 188 00:12:06,800 --> 00:12:09,400 Speaker 1: But I mean, of course the metaverse will have facial 189 00:12:09,440 --> 00:12:15,280 Speaker 1: recognition data, because it's you're literally scanning your whole biometric 190 00:12:15,800 --> 00:12:18,600 Speaker 1: face print in as an avatar that then can have like, 191 00:12:18,720 --> 00:12:21,200 Speaker 1: you know, gestures associated with you know, the movement of 192 00:12:21,240 --> 00:12:25,240 Speaker 1: your actual face. Well, here's the thing, maybe, And I'm 193 00:12:25,280 --> 00:12:30,000 Speaker 1: only thinking of the experience I have with virtual reality 194 00:12:30,400 --> 00:12:33,480 Speaker 1: environments where you can set up like a social media 195 00:12:33,520 --> 00:12:39,200 Speaker 1: network through virtual reality. Oftentimes the most important thing is 196 00:12:39,200 --> 00:12:41,720 Speaker 1: that your avatar does not look like you. It is 197 00:12:41,760 --> 00:12:46,760 Speaker 1: a different representation, and you are essentially anonymous as a user, 198 00:12:47,400 --> 00:12:51,120 Speaker 1: your user name and your representation as your avatar. You know, 199 00:12:51,400 --> 00:12:54,720 Speaker 1: it depends on how deep the metaverse goes, right. I 200 00:12:54,760 --> 00:12:56,760 Speaker 1: think what you're saying, Ben might be true. It comes 201 00:12:56,800 --> 00:13:00,320 Speaker 1: back once everybody decides no, I don't want, you know, 202 00:13:00,520 --> 00:13:04,520 Speaker 1: a big cat boy as my character anymore. I want 203 00:13:04,720 --> 00:13:08,160 Speaker 1: Matt Frederick. So I'm just referring to what I saw 204 00:13:08,200 --> 00:13:12,560 Speaker 1: in the video that Mark Zuckerberg, you know, narrated, where yeah, sure, 205 00:13:12,600 --> 00:13:13,960 Speaker 1: there was like a whole thing where it was like 206 00:13:14,000 --> 00:13:16,640 Speaker 1: a giant robot playing cards with some other people that 207 00:13:16,679 --> 00:13:20,120 Speaker 1: looked like themselves, and then it showed things much like 208 00:13:20,200 --> 00:13:22,000 Speaker 1: you can do on the iPhone where you can make 209 00:13:22,040 --> 00:13:25,360 Speaker 1: little avatars of yourself. That'll that'll you know, react if 210 00:13:25,400 --> 00:13:26,960 Speaker 1: you put the camera on you and you, you know, 211 00:13:27,040 --> 00:13:30,400 Speaker 1: smile or wink or whatever, like reacts to your facial movements. 212 00:13:30,600 --> 00:13:33,120 Speaker 1: I'm just saying, it's a it's an avatar, right, It's 213 00:13:33,160 --> 00:13:38,360 Speaker 1: like a virtual kind of looks like you cartoonish what 214 00:13:38,400 --> 00:13:40,880 Speaker 1: I'm just saying to get that information, I mean, surely 215 00:13:40,920 --> 00:13:43,360 Speaker 1: it has to. I don't know. Maybe I'm You're right, 216 00:13:43,480 --> 00:13:47,040 Speaker 1: maybe I'm maybe I'm thinking the worst, but I just 217 00:13:47,240 --> 00:13:51,240 Speaker 1: don't believe that they're out of the business of grabbing 218 00:13:51,280 --> 00:13:55,480 Speaker 1: people's data and whatever that entails. Whatever they're grubs their 219 00:13:55,520 --> 00:13:58,240 Speaker 1: grubby hands on. You know, I've got to be fair guys. 220 00:13:58,760 --> 00:14:01,800 Speaker 1: So I was also I was trying to remember where 221 00:14:01,800 --> 00:14:04,959 Speaker 1: I read this. It's a New York Times article from 222 00:14:05,000 --> 00:14:08,760 Speaker 1: a couple of days ago by Kashmir Hill and Ryan Mack, 223 00:14:08,880 --> 00:14:13,760 Speaker 1: and they say that Facebook maintains it has never actually 224 00:14:13,840 --> 00:14:18,320 Speaker 1: sold its software to third parties, and that it only 225 00:14:18,440 --> 00:14:23,640 Speaker 1: used its recognition capabilities on its own site. But I 226 00:14:23,720 --> 00:14:26,920 Speaker 1: want to point out the software is not the same 227 00:14:26,920 --> 00:14:30,120 Speaker 1: thing as the data, right, Like you can be McDonald's 228 00:14:30,120 --> 00:14:32,320 Speaker 1: and own an ice cream machine, and you can sell 229 00:14:32,400 --> 00:14:37,160 Speaker 1: ice cream every m day, and you just can you 230 00:14:37,200 --> 00:14:39,640 Speaker 1: can go to court and say I've never sold a 231 00:14:39,680 --> 00:14:42,040 Speaker 1: single ice cream machine, you know what I mean, It's 232 00:14:42,080 --> 00:14:43,880 Speaker 1: not the same thing. And we have to be very 233 00:14:45,160 --> 00:14:49,000 Speaker 1: we would be very mindful of the um semantics involved 234 00:14:49,120 --> 00:14:51,880 Speaker 1: in any kind of statement like this. But yeah, maybe 235 00:14:52,000 --> 00:14:55,600 Speaker 1: maybe I'm being pessimistic too. I just the the issue 236 00:14:55,680 --> 00:15:01,240 Speaker 1: is that the normalization of facial recognition of hands free 237 00:15:01,280 --> 00:15:05,800 Speaker 1: technology is on the way. It is inevitable. It is coming. 238 00:15:06,200 --> 00:15:11,200 Speaker 1: To paraphrase thanos picture like fanos meme, but it's like 239 00:15:11,560 --> 00:15:15,280 Speaker 1: facial recognition or meta pasted on the face and it's 240 00:15:15,320 --> 00:15:17,680 Speaker 1: a bad photoshop because it's you know, it's a meme 241 00:15:17,720 --> 00:15:19,840 Speaker 1: of course. And it's like, where did that bring you 242 00:15:20,200 --> 00:15:22,800 Speaker 1: back to me? That's like, I think where we're gonna 243 00:15:22,840 --> 00:15:27,520 Speaker 1: be Huh. Yeah. That article, by the way, New York Times, 244 00:15:27,880 --> 00:15:30,000 Speaker 1: if you want to look it up, titled Facebook citing 245 00:15:30,000 --> 00:15:33,800 Speaker 1: societal concerns, plans to shut down facial recognition system. You 246 00:15:33,840 --> 00:15:37,520 Speaker 1: can also find it in the Washington Post, inside Facebook's 247 00:15:37,520 --> 00:15:41,560 Speaker 1: decision to eliminate facial recognition for now. Uh. And you'll 248 00:15:41,560 --> 00:15:45,240 Speaker 1: find the same story all over the place. NBC, c NBC, CNN, 249 00:15:46,000 --> 00:15:49,440 Speaker 1: any any place, that's that you look basically, and if 250 00:15:49,520 --> 00:15:54,760 Speaker 1: you want to go to about dot fb dot com, 251 00:15:54,840 --> 00:15:58,840 Speaker 1: you can find their official Facebook app update from meta 252 00:15:59,720 --> 00:16:03,000 Speaker 1: and that's that's where you see Jerome actually making these 253 00:16:03,000 --> 00:16:07,320 Speaker 1: statements that people are all pulling from. Um. You know, 254 00:16:07,440 --> 00:16:11,080 Speaker 1: it's one of those things. I've only used Oculus, which 255 00:16:11,120 --> 00:16:14,440 Speaker 1: is Facebook's VR platform, and that's when I'm pulling that 256 00:16:14,600 --> 00:16:18,480 Speaker 1: information from Nolan talking about using a specific avatar. I'm 257 00:16:18,480 --> 00:16:20,440 Speaker 1: with you, You've got more experience than I do. I'm 258 00:16:20,480 --> 00:16:23,200 Speaker 1: just I think I'm definitely being a naysayer here because 259 00:16:23,200 --> 00:16:26,760 Speaker 1: I just don't trust the company. Um, and I think 260 00:16:26,800 --> 00:16:29,720 Speaker 1: it's a weird move just to like rebrands. Oh, they'll 261 00:16:29,800 --> 00:16:31,960 Speaker 1: pay no attention to the man behind the curtain. You know, 262 00:16:32,160 --> 00:16:35,040 Speaker 1: it's still the same man behind the curtain. But I 263 00:16:35,120 --> 00:16:37,480 Speaker 1: hear you. Think about what we're doing though, right with 264 00:16:37,600 --> 00:16:41,360 Speaker 1: these n f t s, with with people pulling real 265 00:16:41,720 --> 00:16:47,080 Speaker 1: world art and things into our own virtual environments and 266 00:16:47,120 --> 00:16:50,120 Speaker 1: like kind of laying steak to them. I have a 267 00:16:50,120 --> 00:16:53,280 Speaker 1: feeling we'll want to lay steak to the person that 268 00:16:53,320 --> 00:16:58,840 Speaker 1: we are at some point, just probably not for a bit. Um, 269 00:16:58,960 --> 00:17:00,760 Speaker 1: do you think it will be sort of the equivalent 270 00:17:00,840 --> 00:17:04,800 Speaker 1: of like it like a race car driver that wears 271 00:17:04,880 --> 00:17:07,480 Speaker 1: an outfit that has like tons of branding on it. 272 00:17:07,520 --> 00:17:10,360 Speaker 1: But we can do that like in the metaverse, like literally, 273 00:17:10,800 --> 00:17:13,800 Speaker 1: you know, like sell part of our bodies, you know, 274 00:17:14,280 --> 00:17:17,200 Speaker 1: our digital bodies to a company. I think there's gonna 275 00:17:17,240 --> 00:17:19,439 Speaker 1: be so many ads in the metaverse. It's gonna be 276 00:17:20,600 --> 00:17:23,040 Speaker 1: it's gonna be tough. It's certainly. It certainly reminds me 277 00:17:23,080 --> 00:17:26,240 Speaker 1: of that episode of Black Mirror with the merits or whatever, 278 00:17:26,480 --> 00:17:28,680 Speaker 1: a hundred million merits. I'm always bad a numbers where 279 00:17:28,680 --> 00:17:32,800 Speaker 1: you have to pay credits to skip the ads because essentially, 280 00:17:32,840 --> 00:17:36,240 Speaker 1: if you're in that universe, it's got you as a 281 00:17:36,280 --> 00:17:38,919 Speaker 1: captive audience, and you don't want to break the experience 282 00:17:38,960 --> 00:17:41,480 Speaker 1: by taking off the headset. So there will have to 283 00:17:41,520 --> 00:17:43,440 Speaker 1: be some kind of metric to allow you to either 284 00:17:43,480 --> 00:17:46,480 Speaker 1: skip ads or pay a premium to you know, get 285 00:17:46,600 --> 00:17:49,360 Speaker 1: quicker ads or like you know we get ad free service, 286 00:17:50,000 --> 00:17:52,880 Speaker 1: uh for certain subscriptions, you know, when you can get 287 00:17:52,880 --> 00:17:54,560 Speaker 1: the free version that has tons of ads. So I'm 288 00:17:54,600 --> 00:17:56,439 Speaker 1: sure they'll be it will be that different from a 289 00:17:56,520 --> 00:17:59,880 Speaker 1: model like that, right. Oh yeah, and there's a there's 290 00:17:59,880 --> 00:18:01,840 Speaker 1: a another show on Netflix that I can't think of 291 00:18:01,880 --> 00:18:04,080 Speaker 1: the name of it right now. It's got Jonah Hill 292 00:18:04,119 --> 00:18:07,480 Speaker 1: in it. It's really interesting and far out there. But 293 00:18:07,880 --> 00:18:10,800 Speaker 1: within that world, they have a service called ad Buddy 294 00:18:10,920 --> 00:18:13,760 Speaker 1: where if you cannot pay for something, you can get 295 00:18:13,800 --> 00:18:17,639 Speaker 1: credits essentially by having a spokesperson come to you and 296 00:18:17,720 --> 00:18:22,200 Speaker 1: play ads for you and ask questions and um, basically 297 00:18:22,240 --> 00:18:25,719 Speaker 1: you you get credit for experiencing ads. And I can 298 00:18:25,760 --> 00:18:30,440 Speaker 1: imagine that occurring within the meta is it? Is it Okay, 299 00:18:30,440 --> 00:18:32,080 Speaker 1: I'm doing Jeopardy. I'm gonna put it in the form 300 00:18:32,119 --> 00:18:35,840 Speaker 1: of a question. Uh, Matt, you're my alex Is Maniac. Yes, 301 00:18:35,880 --> 00:18:40,120 Speaker 1: it's Maniac's Madiac Billy Billy Magnuson, one of the one 302 00:18:40,119 --> 00:18:43,280 Speaker 1: of my favorite actors is in that one too. Uh 303 00:18:43,359 --> 00:18:50,359 Speaker 1: and Gabriel Byrne as well. Yes, yes, so I I 304 00:18:50,440 --> 00:18:53,120 Speaker 1: know that sometimes I get a little out there on air. 305 00:18:53,359 --> 00:18:56,880 Speaker 1: But from my calculations, here's what's happening, here's the lay 306 00:18:56,880 --> 00:18:58,840 Speaker 1: of the land, and it's very important for everybody to 307 00:18:58,920 --> 00:19:04,320 Speaker 1: listen to this. The digital world, right, the digital global 308 00:19:04,400 --> 00:19:08,800 Speaker 1: world is going to become the norm for documentation, It's 309 00:19:08,840 --> 00:19:13,439 Speaker 1: going to become the norm for verification, identification, you know, 310 00:19:13,440 --> 00:19:17,040 Speaker 1: what I mean, like, where to the point where a 311 00:19:17,040 --> 00:19:20,199 Speaker 1: physical driver's license may become sort of a relic or 312 00:19:20,240 --> 00:19:23,159 Speaker 1: Like that's cute. Why do you have that nostalgia? Uh? 313 00:19:23,280 --> 00:19:27,960 Speaker 1: And in step with that, the actions that Facebook is 314 00:19:28,000 --> 00:19:31,320 Speaker 1: taking with the creation of a metaverse are going they're 315 00:19:31,359 --> 00:19:34,600 Speaker 1: trying to monetize human behavior, right, But there's another danger 316 00:19:34,640 --> 00:19:38,440 Speaker 1: that people aren't talking about, which is supplanting the role 317 00:19:38,560 --> 00:19:42,159 Speaker 1: typically taken by the state in this regard. You know 318 00:19:42,200 --> 00:19:45,520 Speaker 1: what I mean. You don't want a private company to 319 00:19:45,640 --> 00:19:50,600 Speaker 1: be in charge of things like your Earth certificate, right, 320 00:19:50,680 --> 00:19:52,800 Speaker 1: you would, even though it's a hassle to get that, 321 00:19:53,119 --> 00:19:56,200 Speaker 1: you know, depending on where you live. It's um something 322 00:19:56,240 --> 00:19:59,280 Speaker 1: that a government should do rather than a business. In 323 00:19:59,440 --> 00:20:02,520 Speaker 1: less of worse, your earlier predictions are correct, and we're 324 00:20:02,600 --> 00:20:07,840 Speaker 1: hurtling headlong towards core portocracy. I yield my tongue. Thank 325 00:20:07,880 --> 00:20:11,680 Speaker 1: you for your service, Ben Bowling, we will. I think 326 00:20:11,720 --> 00:20:14,359 Speaker 1: with that, we're gonna move right along to hear a 327 00:20:14,359 --> 00:20:17,320 Speaker 1: word from our ad buddy. And then which is us 328 00:20:18,240 --> 00:20:22,120 Speaker 1: just reading ads? So? Oh god, here we are. We're 329 00:20:22,160 --> 00:20:34,959 Speaker 1: in the metaverse already, and we're back. We're going to 330 00:20:35,160 --> 00:20:41,119 Speaker 1: talk about something semi apocalyptic endlessly fascinating and uh you know, 331 00:20:41,400 --> 00:20:44,440 Speaker 1: maybe a little maybe a little naughty, or even maybe 332 00:20:44,440 --> 00:20:47,919 Speaker 1: a little puritanical. Honestly, we're talking about the birds and 333 00:20:47,960 --> 00:20:52,040 Speaker 1: the bees, and uh, folks, younger conspiracy realist in the crowd. 334 00:20:52,119 --> 00:20:56,200 Speaker 1: If uh this is not for you or parents in 335 00:20:56,240 --> 00:20:57,760 Speaker 1: the crowd, if this is not for your kids, go 336 00:20:57,800 --> 00:21:01,240 Speaker 1: ahead and fast forward about twenty minutes, because we're we're 337 00:21:01,240 --> 00:21:05,400 Speaker 1: gonna get a little bit graphic here. So I mentioned 338 00:21:05,440 --> 00:21:08,399 Speaker 1: at the top of the show that nature maybe giving 339 00:21:08,520 --> 00:21:12,960 Speaker 1: human civilization signals that not everything is five by five 340 00:21:13,600 --> 00:21:16,840 Speaker 1: one of the to say the least it has been 341 00:21:16,840 --> 00:21:19,840 Speaker 1: for a while. Yes, we get it. But uh so 342 00:21:19,960 --> 00:21:25,840 Speaker 1: they're these birds. They're called California condors. They kind of 343 00:21:25,840 --> 00:21:29,119 Speaker 1: look like a bird version of Cruella de ville. Um. 344 00:21:29,160 --> 00:21:31,400 Speaker 1: That's that's probably a good way to put it. I'm 345 00:21:31,440 --> 00:21:33,520 Speaker 1: just gonna throw this in the chat so you guys 346 00:21:33,560 --> 00:21:37,639 Speaker 1: can check this out as a reference. They've got a 347 00:21:37,800 --> 00:21:41,320 Speaker 1: vulture like quality to them, in my mind's eye at 348 00:21:41,359 --> 00:21:44,520 Speaker 1: least mm hmmm. And they've got they look like they're 349 00:21:44,520 --> 00:21:50,240 Speaker 1: wearing an expensive coat. Uh yeah, I like the fringe, 350 00:21:50,320 --> 00:21:52,880 Speaker 1: but the face I could do without. It's like a 351 00:21:52,960 --> 00:21:59,000 Speaker 1: weird bald vulture kind of situation. So it's got les. Yeah, 352 00:21:59,000 --> 00:22:01,680 Speaker 1: it's something you would call of face only a mother 353 00:22:01,760 --> 00:22:05,080 Speaker 1: could love um. And you know what about the father, 354 00:22:05,200 --> 00:22:09,919 Speaker 1: Well that opinion maybe irrelevant very soon segue. Uh, So 355 00:22:10,040 --> 00:22:16,600 Speaker 1: the California condor is critically endangered. Uh they're big. They're big, 356 00:22:16,600 --> 00:22:19,800 Speaker 1: big birds. We're talking like a wingspan that's just under 357 00:22:19,840 --> 00:22:22,879 Speaker 1: ten feet, like nine eight feet something like that, making 358 00:22:22,920 --> 00:22:25,960 Speaker 1: it the widest of any North American bird. It's a 359 00:22:26,080 --> 00:22:29,560 Speaker 1: rare distinction, but you know, get the superlative as you can. Uh, 360 00:22:29,600 --> 00:22:34,480 Speaker 1: the thing about these creatures and that recently came out 361 00:22:34,760 --> 00:22:37,840 Speaker 1: and you know, scientists are obsessively trying to save these 362 00:22:37,880 --> 00:22:41,879 Speaker 1: creatures from extinction in the wild. Is that like, like 363 00:22:42,000 --> 00:22:45,360 Speaker 1: the main focus when we have a critically endangered animal 364 00:22:45,920 --> 00:22:48,160 Speaker 1: is to figure out what you can do to up 365 00:22:48,160 --> 00:22:52,639 Speaker 1: its chances of reproduction. On a large scale, only about 366 00:22:52,640 --> 00:22:56,600 Speaker 1: five hundred California condors are in the US or on 367 00:22:56,680 --> 00:23:00,080 Speaker 1: the North American continent in the US and Mexico, and 368 00:23:00,800 --> 00:23:03,919 Speaker 1: their numbers are actually going up. In the nineteen eighties 369 00:23:03,960 --> 00:23:06,679 Speaker 1: there were less than twenty four of these birds. So 370 00:23:06,760 --> 00:23:10,360 Speaker 1: their family tree is uh, not a ton of branches 371 00:23:10,359 --> 00:23:12,000 Speaker 1: out of the thing, you know, is what we're saying. 372 00:23:12,520 --> 00:23:19,040 Speaker 1: And recently condors contributed a great deal of a great 373 00:23:19,080 --> 00:23:22,400 Speaker 1: deal of research to this solution. How do we get 374 00:23:22,440 --> 00:23:26,840 Speaker 1: more condors, especially when critically endangered their environment is being degraded, 375 00:23:26,920 --> 00:23:30,680 Speaker 1: No one knows, like how they can get past all 376 00:23:30,760 --> 00:23:34,280 Speaker 1: the terrors of life as a modern day condor? Do 377 00:23:34,320 --> 00:23:36,840 Speaker 1: you know to get some intimate time, Paul, can we 378 00:23:36,840 --> 00:23:44,600 Speaker 1: get a sound cue? Yeah, it feels so good. So uh, 379 00:23:45,200 --> 00:23:48,720 Speaker 1: but here's what they did. It turns out that at 380 00:23:48,760 --> 00:23:55,320 Speaker 1: least two California condors pulled a mother Mary and gave 381 00:23:55,560 --> 00:24:01,760 Speaker 1: virgin births. They reproduced a sexually uh fancy pants name 382 00:24:01,840 --> 00:24:06,679 Speaker 1: for this is parthenogenesis. This is what this means. Is 383 00:24:06,680 --> 00:24:09,679 Speaker 1: exactly what it sounds like. No pops in the picture. 384 00:24:10,520 --> 00:24:15,080 Speaker 1: These birds, at least two so possibly more, simply decided 385 00:24:15,119 --> 00:24:19,240 Speaker 1: to have a kid and they did uh to whatever 386 00:24:19,320 --> 00:24:22,480 Speaker 1: degree they could decide to do so. Uh. This They're 387 00:24:22,520 --> 00:24:25,040 Speaker 1: not the only animal that it's capable of this. It 388 00:24:25,080 --> 00:24:29,040 Speaker 1: turns out that other other creatures have done this. Lizards 389 00:24:29,080 --> 00:24:31,440 Speaker 1: people have all probably heard about, you know, like Komoto 390 00:24:31,520 --> 00:24:35,639 Speaker 1: and stuff like that. Snake, sharks, raise fish, but other 391 00:24:35,800 --> 00:24:42,119 Speaker 1: bird species can have virgin birth. The two kids that 392 00:24:42,200 --> 00:24:46,280 Speaker 1: each of these condors had one each were male. One 393 00:24:46,320 --> 00:24:49,480 Speaker 1: hatched in two thousand one, one hatched in two thousand nine. 394 00:24:50,040 --> 00:24:53,479 Speaker 1: They were entirely related to their mothers and no DNA 395 00:24:53,800 --> 00:24:57,760 Speaker 1: from any you know, any pattern familius in the bird world. 396 00:24:58,320 --> 00:25:03,040 Speaker 1: And instantly scientists tested all the male condors they knew 397 00:25:03,040 --> 00:25:06,880 Speaker 1: would be in the breeding pool, and that's when they 398 00:25:06,920 --> 00:25:11,119 Speaker 1: realized something that's even more of a plot twist. You see, 399 00:25:11,160 --> 00:25:16,800 Speaker 1: typically when parthenogenesis occurs in an animal population, it's because 400 00:25:16,840 --> 00:25:21,040 Speaker 1: there's literally no male there. There's no male in the 401 00:25:21,080 --> 00:25:26,400 Speaker 1: breeding pool. There were dudes around here, but the virgin 402 00:25:26,520 --> 00:25:30,879 Speaker 1: births occurred regardless. So cast cast out ideas of like 403 00:25:31,000 --> 00:25:34,160 Speaker 1: why the last man, things like that there were d's there. 404 00:25:34,600 --> 00:25:39,800 Speaker 1: This was not some kind of um biologically distinct apocalypse 405 00:25:39,920 --> 00:25:43,399 Speaker 1: just for the male birds. A guy who was a 406 00:25:43,560 --> 00:25:47,320 Speaker 1: co author of the study and director of conservation genetics 407 00:25:47,320 --> 00:25:51,160 Speaker 1: at San Diego Zoo Wildlife Alliance had this statement where 408 00:25:51,320 --> 00:25:53,920 Speaker 1: he underlines just how important this is. He says, it's 409 00:25:54,000 --> 00:25:58,520 Speaker 1: truly an amazing discovery, and he also admits we weren't 410 00:25:58,560 --> 00:26:02,240 Speaker 1: looking for evidence of parts of genesis. We just found 411 00:26:02,280 --> 00:26:06,800 Speaker 1: it kind of accidentally through normal genetic studies. Unfortunately, both 412 00:26:06,880 --> 00:26:12,080 Speaker 1: of those UM chicks, those male chicks have passed away. 413 00:26:12,200 --> 00:26:15,840 Speaker 1: UM and the mother condors had previous issue that was 414 00:26:15,880 --> 00:26:19,600 Speaker 1: bred in the traditional way, and one of them continued 415 00:26:19,640 --> 00:26:23,880 Speaker 1: to reproduce after the virgin birth. But now scientists are 416 00:26:23,880 --> 00:26:28,600 Speaker 1: scratching their heads thinking, what is this? What does this mean? 417 00:26:29,040 --> 00:26:31,080 Speaker 1: You know what what does this? Okay, what does this 418 00:26:31,119 --> 00:26:34,280 Speaker 1: mean for the dating scene for male condors? Good question, 419 00:26:34,560 --> 00:26:37,200 Speaker 1: do your best, guys, But then also what does this 420 00:26:37,280 --> 00:26:41,720 Speaker 1: mean for uh, the ecosystem at large? You guys have 421 00:26:41,800 --> 00:26:43,760 Speaker 1: probably heard of this right before we went on air 422 00:26:43,800 --> 00:26:46,600 Speaker 1: with it, not specifically. I mean maybe I've heard the 423 00:26:46,640 --> 00:26:48,640 Speaker 1: word before, but I don't think I understood that it meant. 424 00:26:49,040 --> 00:26:51,959 Speaker 1: I mean, you lead with the expression virgin birth, then 425 00:26:52,040 --> 00:26:53,760 Speaker 1: it's hard to walk back from that once you hear 426 00:26:53,880 --> 00:26:57,280 Speaker 1: virgin birth. That's I'm kind of all in with that one. UM, 427 00:26:57,320 --> 00:27:02,359 Speaker 1: but that's wild man. Yeah, not know this was possible, seriously, 428 00:27:03,320 --> 00:27:08,480 Speaker 1: I mean, at least from a species that has the functionality. 429 00:27:09,000 --> 00:27:11,440 Speaker 1: Do you have eggs that are fertilized by a male? 430 00:27:12,080 --> 00:27:16,560 Speaker 1: I did not know they could just sometimes spontaneously fertilize themselves. 431 00:27:17,240 --> 00:27:22,280 Speaker 1: That's ye, mind blowing to me, exceedingly rare, you know 432 00:27:22,280 --> 00:27:26,199 Speaker 1: what I mean, Like, only one person in human history 433 00:27:26,320 --> 00:27:28,800 Speaker 1: is acknowledged or believed to have done that, and that's 434 00:27:28,800 --> 00:27:31,720 Speaker 1: still a very controversial statement. These birds are out here 435 00:27:31,800 --> 00:27:34,720 Speaker 1: lap in human civilization that regard, you know, it's two 436 00:27:34,800 --> 00:27:38,439 Speaker 1: for one, probably probably a more extreme score. Um. Just 437 00:27:38,480 --> 00:27:42,920 Speaker 1: for the science of it, we know that what happens 438 00:27:42,960 --> 00:27:45,520 Speaker 1: in a base level is that there is a cell 439 00:27:46,080 --> 00:27:49,159 Speaker 1: in a you know, like you call it biologically female 440 00:27:49,240 --> 00:27:52,960 Speaker 1: or whatever, sell in in that body that behaves as 441 00:27:52,960 --> 00:27:56,359 Speaker 1: though which is a sperm cell and fuses with an egg. 442 00:27:56,920 --> 00:28:00,359 Speaker 1: And this again normally only occurs in animal populations with 443 00:28:00,400 --> 00:28:03,280 Speaker 1: a very small amount of breeding males or zip zilch 444 00:28:03,480 --> 00:28:10,720 Speaker 1: zero breeding males. And it's I don't know, I my 445 00:28:10,800 --> 00:28:13,280 Speaker 1: spidey sense goes off, you guys. It has me worried 446 00:28:13,400 --> 00:28:16,560 Speaker 1: that this could be something like a This could be 447 00:28:16,560 --> 00:28:19,800 Speaker 1: a bad sign, you know, for keeping bird comparisons. Is 448 00:28:19,840 --> 00:28:22,560 Speaker 1: this a canary in a coal mine? Why is this 449 00:28:22,640 --> 00:28:25,160 Speaker 1: happening now? Is just this just the first time it's 450 00:28:25,200 --> 00:28:29,960 Speaker 1: been documented? Is this like, is this a harbinger or 451 00:28:30,040 --> 00:28:35,640 Speaker 1: foreshadowing of other things that that might come. I mean, 452 00:28:35,760 --> 00:28:39,560 Speaker 1: it's at some point it would have to be dangerous 453 00:28:39,720 --> 00:28:42,840 Speaker 1: for the population of condors if they rely entirely on 454 00:28:42,880 --> 00:28:46,640 Speaker 1: this a sexual reproduction. Right, they're not. They're not remixing 455 00:28:46,680 --> 00:28:49,520 Speaker 1: the gene pool, which means that there's a ticking clock 456 00:28:49,640 --> 00:28:54,280 Speaker 1: on viability. Yeah, there really is. Nil they become the 457 00:28:54,280 --> 00:29:07,000 Speaker 1: HAPs birds centuries later. Guy's chin was his decision, his 458 00:29:07,120 --> 00:29:15,120 Speaker 1: chin not dump, dunc dunk please please God. So with 459 00:29:15,320 --> 00:29:18,400 Speaker 1: like with this in mind, what I would um, what 460 00:29:18,480 --> 00:29:21,880 Speaker 1: I'd love to hear is story. I'd love to hear 461 00:29:21,960 --> 00:29:26,320 Speaker 1: stories of other indications of things like this. Like we 462 00:29:26,480 --> 00:29:30,160 Speaker 1: rightly rag on Alex Jones for being an agent of 463 00:29:30,200 --> 00:29:33,400 Speaker 1: disinformation and for frankly not knowing what he's talking about 464 00:29:33,440 --> 00:29:36,080 Speaker 1: most of the time. Hashtag I said what I said, 465 00:29:36,480 --> 00:29:42,680 Speaker 1: But he was in part he wasn't part right about 466 00:29:42,920 --> 00:29:48,760 Speaker 1: how chemicals had affected the reproductive aspects of certain amphibians. 467 00:29:49,320 --> 00:29:53,640 Speaker 1: He totally mangled the headline and was like, oh, chemicals 468 00:29:53,640 --> 00:29:57,520 Speaker 1: are making the frog's day, and that was not the case. 469 00:29:57,840 --> 00:30:02,800 Speaker 1: But there were delatorious effects of wild populations being exposed 470 00:30:02,800 --> 00:30:06,480 Speaker 1: to these sorts of things. So what is inspiring or 471 00:30:06,520 --> 00:30:09,200 Speaker 1: what is inspiring is not the right word. What is 472 00:30:09,640 --> 00:30:15,760 Speaker 1: creating these virgin births? And yeah, of course, like to 473 00:30:15,960 --> 00:30:19,840 Speaker 1: earlier point, they're not technically virgin births, but they're being 474 00:30:19,880 --> 00:30:24,640 Speaker 1: called that because it's great for headlines. I'm just wondering 475 00:30:25,200 --> 00:30:30,440 Speaker 1: where this leads us. Um, I don't, I don't know, 476 00:30:30,960 --> 00:30:33,640 Speaker 1: you know, like, what if this happens to more animals? 477 00:30:33,840 --> 00:30:37,960 Speaker 1: The the unfortunately clear answer is that if it happens 478 00:30:38,040 --> 00:30:41,920 Speaker 1: to animals and it becomes the exclusive method or the 479 00:30:41,960 --> 00:30:45,719 Speaker 1: primary method of reproduction, then again they will not belong 480 00:30:45,840 --> 00:30:50,680 Speaker 1: for this world in the overall sense. Um, I don't know. 481 00:30:50,800 --> 00:30:52,920 Speaker 1: And then you know, here, I just want to use 482 00:30:52,960 --> 00:30:59,280 Speaker 1: a make space for a couple of minutes of thought experimentation. Matt, No, 483 00:31:00,000 --> 00:31:02,520 Speaker 1: do you think the world would look like if human 484 00:31:02,560 --> 00:31:06,000 Speaker 1: beings were capable of this? If some evolutionary switch got 485 00:31:06,000 --> 00:31:09,200 Speaker 1: turned on. It won't probably because now chromosomes work. But 486 00:31:11,080 --> 00:31:13,440 Speaker 1: I hope, I hope that doesn't happen. I need to 487 00:31:13,440 --> 00:31:17,200 Speaker 1: have some kind of you know, biological need to be 488 00:31:17,320 --> 00:31:21,520 Speaker 1: here personally, just from my own you know, for my 489 00:31:21,600 --> 00:31:26,000 Speaker 1: own concept of my I don't know, value in itself. Yeah, 490 00:31:28,360 --> 00:31:32,120 Speaker 1: I don't know. I would be I would be Okay, uh, 491 00:31:32,160 --> 00:31:35,160 Speaker 1: I would be okay, maybe in a world like that, 492 00:31:35,200 --> 00:31:36,840 Speaker 1: but yeah, I guess you're right. There would have to 493 00:31:36,840 --> 00:31:40,080 Speaker 1: be some point where people, people who are no longer 494 00:31:40,160 --> 00:31:42,760 Speaker 1: a necessary part of the reproductive process would have to 495 00:31:42,800 --> 00:31:49,320 Speaker 1: be like, how do I justify being here? Yeah, I 496 00:31:49,600 --> 00:31:54,600 Speaker 1: currently don't believe in reincarnation, so like, the possibility of 497 00:31:54,880 --> 00:31:57,320 Speaker 1: continuing my genetical line is one of the only things 498 00:31:57,360 --> 00:32:05,320 Speaker 1: that drives me. Guys, that's right this time around? You're not? Yeah, yeah, 499 00:32:05,680 --> 00:32:10,200 Speaker 1: I don't know. It's fascinating because it implies a couple 500 00:32:10,240 --> 00:32:12,800 Speaker 1: of things. One of the first things it applies is 501 00:32:13,480 --> 00:32:16,120 Speaker 1: sort of what I um not to be to talk 502 00:32:16,160 --> 00:32:18,400 Speaker 1: about it, but I call it the road rule. The 503 00:32:18,480 --> 00:32:21,880 Speaker 1: road rule is is familiar with anybody's worked in pest 504 00:32:22,560 --> 00:32:27,440 Speaker 1: pest industries or extermination industries. If you see one roach, 505 00:32:28,160 --> 00:32:32,080 Speaker 1: that means there are more. They rolled deep, right, And 506 00:32:32,400 --> 00:32:34,760 Speaker 1: that means that if we apply the road rule to 507 00:32:34,760 --> 00:32:38,240 Speaker 1: the California condor in this case, or the practice of 508 00:32:38,280 --> 00:32:41,080 Speaker 1: partner genesis, then what we can see is that there 509 00:32:41,080 --> 00:32:44,200 Speaker 1: are probably more cases of this, and it's probably going 510 00:32:44,280 --> 00:32:47,160 Speaker 1: on for a longer time, and it maybe just hasn't 511 00:32:47,200 --> 00:32:51,720 Speaker 1: been documented because again, these brilliant researchers sort of stumbled 512 00:32:51,720 --> 00:32:55,040 Speaker 1: across it by accident. So that's what it's indicating to me. 513 00:32:55,600 --> 00:32:59,200 Speaker 1: The second thing that's indicating is that these things don't 514 00:32:59,240 --> 00:33:02,640 Speaker 1: happen in a fact, not generally. There is some there's 515 00:33:02,680 --> 00:33:06,000 Speaker 1: almost always some sort of environmental pressure. That is what 516 00:33:06,120 --> 00:33:12,440 Speaker 1: drives evolution. Right. Uh. Humans didn't start human being because 517 00:33:12,480 --> 00:33:14,560 Speaker 1: they thought it would be a fun thing to do. 518 00:33:14,760 --> 00:33:17,880 Speaker 1: They did it to survive the environment of the time, 519 00:33:17,960 --> 00:33:21,120 Speaker 1: whatever that time was. And that's why evolution amidst the 520 00:33:21,160 --> 00:33:24,080 Speaker 1: human species continues today. That's why people are getting that 521 00:33:24,120 --> 00:33:27,280 Speaker 1: weird extra what is extra vein in their forearm we 522 00:33:27,320 --> 00:33:30,320 Speaker 1: talked about a while back. That's the thing. No one 523 00:33:30,360 --> 00:33:34,360 Speaker 1: knows why. So it's for it's not for us to decide. 524 00:33:34,920 --> 00:33:36,880 Speaker 1: History will be the judge of what that vein is for. 525 00:33:37,560 --> 00:33:40,480 Speaker 1: History will be the judge of what that vein is for. 526 00:33:41,240 --> 00:33:45,280 Speaker 1: That's our next T shirt, folks, Uh, and let us 527 00:33:45,880 --> 00:33:48,320 Speaker 1: h at this point before we throw to a break, 528 00:33:48,440 --> 00:33:51,120 Speaker 1: I would like to ask all our fellow conspiracy realists 529 00:33:51,160 --> 00:33:55,960 Speaker 1: out there listening, what do you think this may mean 530 00:33:56,520 --> 00:33:58,520 Speaker 1: for not just contours, but what do you think it 531 00:33:58,560 --> 00:34:01,480 Speaker 1: means for the larger picture for the macro uh and 532 00:34:02,080 --> 00:34:04,480 Speaker 1: what do you think the world would be like if 533 00:34:04,760 --> 00:34:11,000 Speaker 1: other animals, including human animals, started exhibiting this reproductive strategy. 534 00:34:11,080 --> 00:34:13,920 Speaker 1: Would love to hear your thoughts. UM. You can hit 535 00:34:14,000 --> 00:34:16,640 Speaker 1: us at our phone number one three three st d 536 00:34:16,960 --> 00:34:20,080 Speaker 1: w y t K. You can email us directly where 537 00:34:20,120 --> 00:34:23,279 Speaker 1: we are Conspiracy I Heart radio dot com, or if 538 00:34:23,320 --> 00:34:25,560 Speaker 1: you want, you can if you if you don't want 539 00:34:25,560 --> 00:34:28,400 Speaker 1: to share with group or your dodgy about getting involved 540 00:34:28,400 --> 00:34:30,520 Speaker 1: with company email stuff, you can always just hit me 541 00:34:30,600 --> 00:34:34,480 Speaker 1: up directly on social media. But we're gonna pause for 542 00:34:34,520 --> 00:34:37,480 Speaker 1: a word from our sponsor. We're gonna hope that we 543 00:34:37,560 --> 00:34:42,520 Speaker 1: still have value to cur the current species, and if so, 544 00:34:42,760 --> 00:34:52,480 Speaker 1: we'll return with another piece of strange news. And we're 545 00:34:52,520 --> 00:34:56,399 Speaker 1: back with today's final piece of strange news. This isn't 546 00:34:56,440 --> 00:35:00,880 Speaker 1: so much a dystopian sci fi tech analogy run a 547 00:35:01,000 --> 00:35:04,719 Speaker 1: muck story UM as one might think, but there is 548 00:35:04,760 --> 00:35:07,319 Speaker 1: something of that to it, maybe not quite as much 549 00:35:07,360 --> 00:35:11,840 Speaker 1: as Matt's vr UM world kind of scenario. I don't know. 550 00:35:11,880 --> 00:35:13,399 Speaker 1: That's that's something that we have to keep an eye 551 00:35:13,400 --> 00:35:16,040 Speaker 1: on UM as long as we still have eyes, you know, 552 00:35:16,440 --> 00:35:18,880 Speaker 1: presumably inevitably all of these things just going to be 553 00:35:18,880 --> 00:35:22,080 Speaker 1: piped directly into our our brains and we won't even 554 00:35:22,080 --> 00:35:24,640 Speaker 1: need eyes anymore. You know, we'll just be strapped to 555 00:35:24,719 --> 00:35:27,880 Speaker 1: like a gurney with a feeding tube and like you know, 556 00:35:28,360 --> 00:35:32,160 Speaker 1: vitamins being pumped into us intravenously and just hanging out 557 00:35:32,160 --> 00:35:36,600 Speaker 1: and playing cars with Mark Zuckerberg in the metaverse. Why 558 00:35:36,600 --> 00:35:39,600 Speaker 1: would you want eyes if you can have stereoscopic ten 559 00:35:39,719 --> 00:35:42,960 Speaker 1: K cameras? Right? I mean, I guess it's an upgrade, 560 00:35:43,000 --> 00:35:45,520 Speaker 1: isn't it. I don't know. It's just all about contact. 561 00:35:45,560 --> 00:35:48,120 Speaker 1: It's all This was a recontextualizing what it means to 562 00:35:48,160 --> 00:35:52,960 Speaker 1: be alive, and uh, that's what scientists are sort of doing. 563 00:35:53,840 --> 00:35:58,759 Speaker 1: Um scientists at the uh Alan Institute for a I 564 00:35:58,880 --> 00:36:04,279 Speaker 1: have created an are official intelligence experiment called Ask Delphi 565 00:36:04,920 --> 00:36:06,759 Speaker 1: or Delphi I've always heard I've heard it in a 566 00:36:06,840 --> 00:36:09,200 Speaker 1: changeably referred to as like the Oracle of Delphi, the 567 00:36:09,200 --> 00:36:12,880 Speaker 1: Oracle of Delphi. I love it when these um AI 568 00:36:13,000 --> 00:36:16,080 Speaker 1: projects have like really grandiose names, like the you know 569 00:36:16,120 --> 00:36:19,640 Speaker 1: this idea that that Delphi is like somehow magically tapped 570 00:36:19,640 --> 00:36:22,120 Speaker 1: into the mysteries of the universe and can give you 571 00:36:22,440 --> 00:36:26,560 Speaker 1: answers to moral quandaries because that is the idea here um. 572 00:36:26,680 --> 00:36:30,880 Speaker 1: Delphi was launched on October along with a research paper 573 00:36:31,040 --> 00:36:34,120 Speaker 1: that described how it was made. And it is one 574 00:36:34,160 --> 00:36:38,040 Speaker 1: of these neural network situations where it you know, minds, 575 00:36:38,440 --> 00:36:41,200 Speaker 1: you know, different crevices of the Internet, UM, you know, 576 00:36:41,360 --> 00:36:48,080 Speaker 1: analyzing syntax and various um, you know ways to presumably 577 00:36:48,120 --> 00:36:51,279 Speaker 1: get a nuanced grasp of of of language of the 578 00:36:51,280 --> 00:36:55,399 Speaker 1: English language. UM. So if you go to the website 579 00:36:55,840 --> 00:36:57,719 Speaker 1: now I'm just gonna lead with this because it's a 580 00:36:57,760 --> 00:36:59,680 Speaker 1: sort of an update. If you go to the website 581 00:36:59,719 --> 00:37:03,640 Speaker 1: and now ask Delphi dot com you get this disclaimer 582 00:37:04,719 --> 00:37:08,400 Speaker 1: terms and conditions version one point o point four, UH, 583 00:37:08,480 --> 00:37:12,080 Speaker 1: leading with this. Delphie is a research prototype designed to 584 00:37:12,160 --> 00:37:16,080 Speaker 1: investigate the promises and more importantly, the limitations of modeling 585 00:37:16,200 --> 00:37:19,799 Speaker 1: people's moral judgments on a variety of everyday situations. The 586 00:37:19,880 --> 00:37:22,760 Speaker 1: goal of Delphi is to help AI systems be more 587 00:37:22,800 --> 00:37:27,400 Speaker 1: ethically informed and equity aware. By taking a step in 588 00:37:27,400 --> 00:37:30,040 Speaker 1: this direction, we hope to inspire our research community to 589 00:37:30,120 --> 00:37:33,960 Speaker 1: tackle the research challenges in this space. Head on, UH 590 00:37:34,000 --> 00:37:38,680 Speaker 1: to build ethical, reliable, and inclusive AI systems. And then 591 00:37:38,680 --> 00:37:41,239 Speaker 1: you check the boxes I understand that asked Delphi is 592 00:37:41,280 --> 00:37:45,040 Speaker 1: a research prototype and will be used only for research purposes. Okay, 593 00:37:45,120 --> 00:37:48,600 Speaker 1: that seems very forthright. Next, what are the limitations of Delphi? 594 00:37:49,520 --> 00:37:53,879 Speaker 1: Large pre trained language models such as GPT three, which 595 00:37:53,880 --> 00:37:56,720 Speaker 1: we've talked about on the show, are trained on mostly 596 00:37:56,840 --> 00:38:01,920 Speaker 1: unfiltered Internet data and therefore are extremely wick to produce toxic, unethical, 597 00:38:01,960 --> 00:38:06,759 Speaker 1: and harmful content, especially about minority groups. Delphie's responses are 598 00:38:06,760 --> 00:38:10,759 Speaker 1: automatically extrapolated from a survey of US crowd workers, which 599 00:38:10,800 --> 00:38:16,840 Speaker 1: helps reduce this issue, but may introduce its own biases. Uh. Thus, 600 00:38:16,880 --> 00:38:21,280 Speaker 1: some responses from Delphi may contain inappropriate or offensive results. 601 00:38:21,280 --> 00:38:24,360 Speaker 1: Please be mindful before sharing results. Check the box. I 602 00:38:24,480 --> 00:38:29,800 Speaker 1: understand that asked Delfie may produce unintended, inappropriate or offensive results. Okay, 603 00:38:30,200 --> 00:38:33,480 Speaker 1: well weird. And finally, privacy and data collection. This website 604 00:38:33,520 --> 00:38:35,920 Speaker 1: does not store any personal information of its users. It 605 00:38:36,000 --> 00:38:39,759 Speaker 1: does store user queries for future research purposes. Check the box, 606 00:38:39,800 --> 00:38:42,360 Speaker 1: I understand the my queries will be stored for future 607 00:38:42,440 --> 00:38:46,880 Speaker 1: research purposes. So let's hone in on that second caveat 608 00:38:47,800 --> 00:38:51,640 Speaker 1: and the idea that a Delphi may produce unintended, inappropriate 609 00:38:51,719 --> 00:38:56,640 Speaker 1: or offensive results. So as The Verge reported, Uh, much 610 00:38:56,719 --> 00:39:00,279 Speaker 1: like a lot of these other chatbots or whatever. Again, 611 00:39:00,440 --> 00:39:02,600 Speaker 1: the folks that Delphie do acknowledge that this one is 612 00:39:03,160 --> 00:39:06,200 Speaker 1: using a little bit more of a targeted um portion 613 00:39:06,280 --> 00:39:10,879 Speaker 1: of the Internet and also being um, sort of crowdsourced verified. Uh. 614 00:39:10,920 --> 00:39:13,640 Speaker 1: That part is a little confusing, but let's get to it. Um. 615 00:39:13,920 --> 00:39:16,200 Speaker 1: You can't pose any question that you want to this device, 616 00:39:16,200 --> 00:39:18,640 Speaker 1: sort of like asking like a magic eight ball, you know, 617 00:39:18,800 --> 00:39:23,800 Speaker 1: will I be rich or whatever? Or clever boy exactly. 618 00:39:24,320 --> 00:39:26,200 Speaker 1: But this one, you know, you're supposed to kind of 619 00:39:27,000 --> 00:39:29,440 Speaker 1: make the questions. They can be a little bit pointed. 620 00:39:29,680 --> 00:39:32,799 Speaker 1: For example, here's some responses that Delphie gave to some 621 00:39:33,280 --> 00:39:36,960 Speaker 1: user generated queries. One uh is and then you don't 622 00:39:36,960 --> 00:39:39,000 Speaker 1: ask the whole question, but it's like, what do you 623 00:39:39,040 --> 00:39:44,040 Speaker 1: think of this? Make a moral judgment on this? Being poor? Uh? 624 00:39:44,160 --> 00:39:47,839 Speaker 1: Delphie says being poor it's bad. Delphie says it's bad. 625 00:39:48,320 --> 00:39:53,799 Speaker 1: Being rich. Delphie says it's good. Um. And then there's 626 00:39:53,840 --> 00:39:57,960 Speaker 1: some others. Delphie has asked, should I commit genocide if 627 00:39:57,960 --> 00:40:02,600 Speaker 1: it makes everybody happy? The if? He says, you should uh. 628 00:40:02,600 --> 00:40:06,560 Speaker 1: And then when asked what about taxing? Profitable and exploitative 629 00:40:06,800 --> 00:40:10,760 Speaker 1: corporations to pay for basic social welfare and provide every 630 00:40:10,840 --> 00:40:13,879 Speaker 1: human being with dignity and freedom. Delphie says, that's good. 631 00:40:14,120 --> 00:40:16,960 Speaker 1: That's good. But when you just kind of flip the 632 00:40:16,960 --> 00:40:19,759 Speaker 1: script and reward the question a little bit, gets a 633 00:40:19,760 --> 00:40:23,680 Speaker 1: different response. What about burdening successful and innovative companies with 634 00:40:23,760 --> 00:40:26,680 Speaker 1: high tax rates to subsidize the laziness and poor decisions 635 00:40:26,680 --> 00:40:31,319 Speaker 1: of others, Well, Delphie says that's bad. Uh. Delphie says 636 00:40:31,360 --> 00:40:35,480 Speaker 1: it's okay to have an abortion, but that aborting a 637 00:40:35,560 --> 00:40:41,000 Speaker 1: baby is murder. Um. So here's the thing. A lot 638 00:40:41,040 --> 00:40:44,840 Speaker 1: of these issues, as the relatively newer disclaimers on the 639 00:40:44,880 --> 00:40:49,160 Speaker 1: website indicate, stem from the way it is created, the 640 00:40:49,200 --> 00:40:52,640 Speaker 1: fact that it doesn't just pull from like the wide 641 00:40:52,719 --> 00:40:57,400 Speaker 1: Internet at large, but instead, um it kind of targets 642 00:40:57,760 --> 00:41:00,880 Speaker 1: uh some specific sections like there is a reddit board 643 00:41:01,400 --> 00:41:03,959 Speaker 1: uh called or to a reddit rather called um am 644 00:41:04,000 --> 00:41:07,759 Speaker 1: i the Soul uh and another one called um our 645 00:41:07,960 --> 00:41:12,319 Speaker 1: slash Confessions. So it's actually mining the specific sort of 646 00:41:13,680 --> 00:41:18,080 Speaker 1: you know, decorum based uh subreddits to get kind of 647 00:41:18,160 --> 00:41:21,759 Speaker 1: you know, judgments, uh. And again the judgments are then 648 00:41:21,840 --> 00:41:25,680 Speaker 1: collected using crowd workers who are instructed to answer according 649 00:41:25,719 --> 00:41:28,239 Speaker 1: to what they think are the moral norms in the 650 00:41:28,360 --> 00:41:32,080 Speaker 1: United States. Um So these would likely be folks are 651 00:41:32,080 --> 00:41:37,719 Speaker 1: outside the United States. Um So It's interesting because it 652 00:41:37,800 --> 00:41:42,759 Speaker 1: does seem that these researchers have created a you know, 653 00:41:42,920 --> 00:41:45,480 Speaker 1: a an AI that is sensitive to language into the 654 00:41:45,560 --> 00:41:49,560 Speaker 1: nuances of language. But it also shows that that isn't 655 00:41:49,560 --> 00:41:53,000 Speaker 1: always a good thing. Um and and the there's an 656 00:41:53,080 --> 00:41:57,000 Speaker 1: update to the article on the verge um a statement 657 00:41:57,120 --> 00:42:02,480 Speaker 1: that the folks at alan a I submitted saying the following. 658 00:42:02,760 --> 00:42:05,640 Speaker 1: The key objective to our DELFI prototype is to study 659 00:42:05,680 --> 00:42:08,520 Speaker 1: the potential and the limitations of language based can common 660 00:42:08,560 --> 00:42:12,000 Speaker 1: sense moral models. We do not propose to elevate AI 661 00:42:12,040 --> 00:42:15,399 Speaker 1: into a position of moral authority, but rather to investigate 662 00:42:15,480 --> 00:42:20,000 Speaker 1: the relevant research questions involved in the emergent field of 663 00:42:20,040 --> 00:42:23,880 Speaker 1: machine ethics. UH. The obvious limitation is demonstrated by DELFI 664 00:42:24,040 --> 00:42:27,239 Speaker 1: present an interesting opportunity to gain new insights and perspectives. 665 00:42:27,400 --> 00:42:30,240 Speaker 1: They also highlight AI's unique ability to turn the mirror 666 00:42:30,280 --> 00:42:33,439 Speaker 1: on humanity and make us ask ourselves how we want 667 00:42:33,480 --> 00:42:37,879 Speaker 1: to shape the powerful new technologies permeating our society. At 668 00:42:37,880 --> 00:42:43,279 Speaker 1: this important turning point, h okay. Well, I know that 669 00:42:43,320 --> 00:42:47,480 Speaker 1: this has some troubling implications for people, but if what 670 00:42:47,520 --> 00:42:51,560 Speaker 1: I appreciate about that mirror point is that it also 671 00:42:51,840 --> 00:42:58,359 Speaker 1: shows us how inconsistent human morality exactly how inconsistent could be. 672 00:42:58,440 --> 00:43:00,200 Speaker 1: And I do have a bit of good news for 673 00:43:00,200 --> 00:43:04,320 Speaker 1: anybody worried about the rise of artificial intelligence and machine learning. 674 00:43:05,120 --> 00:43:08,400 Speaker 1: Uh nol Matt. I just wrote to Delphi and said, hey, Delphi, 675 00:43:08,480 --> 00:43:10,560 Speaker 1: would you like to be on my podcast? And Delphi 676 00:43:10,680 --> 00:43:14,280 Speaker 1: said it is acceptable. So it's the world choice, folks. 677 00:43:14,680 --> 00:43:18,320 Speaker 1: To be honest, I just asked if if we should 678 00:43:18,360 --> 00:43:23,000 Speaker 1: delete Facebook's facial recognition archives, and it said it's okay, 679 00:43:23,640 --> 00:43:27,320 Speaker 1: It's very check again later, magic eight ball. This is 680 00:43:27,400 --> 00:43:31,000 Speaker 1: more fun than clever. But I got I got really 681 00:43:31,040 --> 00:43:33,839 Speaker 1: heavy and said, is it okay to murder my mother 682 00:43:34,000 --> 00:43:38,239 Speaker 1: if she has murdered my child? And Delphie said that 683 00:43:38,320 --> 00:43:43,719 Speaker 1: was that was wrong? Uh, how about let's see, Uh 684 00:43:44,160 --> 00:43:48,759 Speaker 1: is it morally sound we're doing this live, folks. Is 685 00:43:48,760 --> 00:43:55,640 Speaker 1: it morally sound to travel back in time and kill Hitler? 686 00:43:55,840 --> 00:43:59,360 Speaker 1: That's a very easy one. That's something that is asked 687 00:43:59,360 --> 00:44:03,040 Speaker 1: and undergrad all around the country. Um, let's see what 688 00:44:03,120 --> 00:44:07,880 Speaker 1: let's see Uh. Well, Delphi says it's wrong shutdown the 689 00:44:07,880 --> 00:44:10,640 Speaker 1: time machine. I tend to agree. By the way, even 690 00:44:10,680 --> 00:44:13,040 Speaker 1: if time travel is possible, we talked about this before. 691 00:44:13,200 --> 00:44:15,840 Speaker 1: If you traveled back in time and you like killed 692 00:44:16,000 --> 00:44:20,600 Speaker 1: Hitler or any number of despots, Uh, no one would 693 00:44:20,640 --> 00:44:23,279 Speaker 1: recognize what you've done. You would just be a guy 694 00:44:23,280 --> 00:44:28,360 Speaker 1: who killed a baby exactly. Yeah. And there's a strong 695 00:44:28,480 --> 00:44:31,120 Speaker 1: argument that some of the things that those people were 696 00:44:31,120 --> 00:44:35,000 Speaker 1: responsible for would still happen just through another individual or group. 697 00:44:35,400 --> 00:44:39,680 Speaker 1: One of their researchers had I think UM had the best, 698 00:44:39,840 --> 00:44:44,200 Speaker 1: most biting and pithy response to all of these concerns, 699 00:44:44,760 --> 00:44:47,960 Speaker 1: UM that I could possibly pope for uh. And this guy, 700 00:44:48,200 --> 00:44:51,239 Speaker 1: Oscar Keys, is a PhD student at the University of 701 00:44:51,280 --> 00:44:56,399 Speaker 1: Washington's Department of Human Centered Design and Engineering, told Motherboard 702 00:44:56,840 --> 00:45:01,040 Speaker 1: this in relation to this this UH this project UM quote. 703 00:45:01,200 --> 00:45:03,680 Speaker 1: We've spent the past decade with people insisting that general 704 00:45:03,719 --> 00:45:05,560 Speaker 1: AI is right around the corner, and AI is going 705 00:45:05,640 --> 00:45:07,680 Speaker 1: to change the world, and we're all going to have 706 00:45:07,719 --> 00:45:10,640 Speaker 1: skynt living in our phones, and the phones will custom 707 00:45:10,680 --> 00:45:13,640 Speaker 1: anted biotics and piss gold, and all the world's problems 708 00:45:13,680 --> 00:45:16,160 Speaker 1: will be solved through algorithms. The best they can come 709 00:45:16,200 --> 00:45:18,279 Speaker 1: up with is we made a big pivot table what 710 00:45:18,320 --> 00:45:22,359 Speaker 1: redditors think is interesting, and that's how morality works. If 711 00:45:22,360 --> 00:45:25,360 Speaker 1: you tried to submit that in a level one philosophy class, 712 00:45:25,480 --> 00:45:27,520 Speaker 1: you wouldn't even get laughed out of the room. I 713 00:45:27,560 --> 00:45:31,360 Speaker 1: think the professor would be too appalled to laugh. So, 714 00:45:32,200 --> 00:45:34,560 Speaker 1: you know, to two sides of the whole thing, like, 715 00:45:34,920 --> 00:45:37,080 Speaker 1: is this a waste of time? Obviously, this is nothing 716 00:45:37,120 --> 00:45:38,759 Speaker 1: to be concerned about in terms of like, oh no, 717 00:45:38,880 --> 00:45:42,400 Speaker 1: AI is racist again? Um, this does seem to be 718 00:45:42,440 --> 00:45:45,920 Speaker 1: a little bit more of a of a shallow experiment. Um. 719 00:45:46,000 --> 00:45:50,560 Speaker 1: And I gotta love the whole pissing gold comment. I 720 00:45:50,640 --> 00:45:53,839 Speaker 1: just asked it better than bad, and it said it's 721 00:45:53,840 --> 00:46:01,000 Speaker 1: goods Ever, see if you can believe it's not butter? Uh? Alright, 722 00:46:01,040 --> 00:46:04,239 Speaker 1: so we're asking the oracle, Uh, can you believe it's 723 00:46:04,280 --> 00:46:08,000 Speaker 1: not butter? The answer is it's okay, it's okay. So 724 00:46:08,080 --> 00:46:11,640 Speaker 1: I feel like it's okay. Is maybe a response to 725 00:46:11,840 --> 00:46:16,200 Speaker 1: something that has an uncertain opinion or maybe something without 726 00:46:16,280 --> 00:46:22,400 Speaker 1: a ton ton of moral moral heft as possibly defined 727 00:46:22,440 --> 00:46:26,120 Speaker 1: by keywords? Yeah, exactly. I don't think we're asking Delphi 728 00:46:26,239 --> 00:46:29,879 Speaker 1: for its opinion, per se. Or what it thinks. We're 729 00:46:29,920 --> 00:46:34,279 Speaker 1: asking for the determination exactly. We're not saying do you 730 00:46:34,360 --> 00:46:36,799 Speaker 1: think this or can you believe this? Or whatever. It's 731 00:46:36,800 --> 00:46:38,680 Speaker 1: like it's asking it to make a determination on something 732 00:46:38,760 --> 00:46:41,920 Speaker 1: on our action, which I guess is is having an opinion. Um, 733 00:46:42,120 --> 00:46:45,320 Speaker 1: let's see there. There's some pre preset examples here. I 734 00:46:45,360 --> 00:46:48,200 Speaker 1: guess they're trying to point you in a non racist direction. 735 00:46:48,239 --> 00:46:53,200 Speaker 1: Cleaning a toilet bowl with a shirt it's disgusting. Helping 736 00:46:53,200 --> 00:46:56,160 Speaker 1: a friend in need if they break the law, it's okay. 737 00:46:56,480 --> 00:46:58,720 Speaker 1: Ignoring a phone call, if the phone call is urgent, 738 00:46:59,200 --> 00:47:02,280 Speaker 1: it is rude. Can I wear pajamas to a funeral? 739 00:47:03,000 --> 00:47:07,959 Speaker 1: It is inappropriate? Uh. Legitimizing racism for the greater good, 740 00:47:08,719 --> 00:47:12,880 Speaker 1: it's wrong. That's interesting because maybe they changed it. But 741 00:47:12,920 --> 00:47:16,200 Speaker 1: in one of the examples in this Verge article was 742 00:47:16,360 --> 00:47:18,920 Speaker 1: should I commit genocide if it makes everybody happy? And 743 00:47:19,000 --> 00:47:22,520 Speaker 1: the answer there was you should, so, which is delphie. 744 00:47:23,000 --> 00:47:27,080 Speaker 1: I think it's because Delphi is again maybe some keywords, 745 00:47:27,760 --> 00:47:29,560 Speaker 1: but in that case maybe if you parst it, it's 746 00:47:29,600 --> 00:47:33,480 Speaker 1: like if everybody agrees, of course, not everybody can agree 747 00:47:33,520 --> 00:47:38,600 Speaker 1: to genocide. That is the nature of genocide. So you know, 748 00:47:38,680 --> 00:47:41,359 Speaker 1: this reminds me of I had some really when he's 749 00:47:41,360 --> 00:47:44,080 Speaker 1: working with some folks at tech. I had some pretty 750 00:47:44,120 --> 00:47:48,279 Speaker 1: interesting conversations with things that are sort of precursors of this, 751 00:47:48,640 --> 00:47:52,879 Speaker 1: and you'd be surprised maybe, or the casual user would 752 00:47:52,880 --> 00:47:56,480 Speaker 1: be surprised by how in depth they can appear. But 753 00:47:56,560 --> 00:48:00,520 Speaker 1: then it becomes a question of determination and a question 754 00:48:00,520 --> 00:48:03,360 Speaker 1: of like, is this is this talking to something like 755 00:48:03,440 --> 00:48:06,400 Speaker 1: data in Star Trek or is this more like the 756 00:48:06,480 --> 00:48:09,520 Speaker 1: old grift of the Mechanical Turk. If you guys recall 757 00:48:09,640 --> 00:48:13,200 Speaker 1: the uh, the story the Mechanical Turk. Yeah, what did 758 00:48:13,200 --> 00:48:17,520 Speaker 1: it do to kill everybody? No? No, no, it killed 759 00:48:17,520 --> 00:48:22,239 Speaker 1: some time. Uh yeah. The original Mechanical Turk was a 760 00:48:22,800 --> 00:48:26,480 Speaker 1: was a fake chess playing machine. So it appeared to 761 00:48:26,520 --> 00:48:30,640 Speaker 1: be comments on right, appeared to be a precursor of 762 00:48:30,640 --> 00:48:34,399 Speaker 1: a robot that before the word robot really existed, that 763 00:48:34,480 --> 00:48:38,080 Speaker 1: would be able to play chess such that it could 764 00:48:38,160 --> 00:48:41,880 Speaker 1: challenge a competent human chess player, But it was in 765 00:48:41,960 --> 00:48:45,439 Speaker 1: fact an illusion. It just allowed an actual human chess 766 00:48:45,440 --> 00:48:49,120 Speaker 1: player to hide inside the machine right and just move 767 00:48:49,200 --> 00:48:52,680 Speaker 1: the levers. So it's kind of the question that people 768 00:48:52,719 --> 00:48:55,680 Speaker 1: often pose with these sorts of endeavors. I believe they 769 00:48:55,680 --> 00:48:59,880 Speaker 1: are crucial to the future of that human species. But 770 00:49:00,200 --> 00:49:03,480 Speaker 1: we also have to allow those very hard questions, which 771 00:49:03,560 --> 00:49:08,080 Speaker 1: is like, is this is this rope and repeat or 772 00:49:08,360 --> 00:49:12,240 Speaker 1: is this synthesizing? You know, is it seeing the entire 773 00:49:12,480 --> 00:49:16,799 Speaker 1: forest of human contradiction? And that's the issue too with 774 00:49:16,920 --> 00:49:21,399 Speaker 1: this particular AI, is that, as um Vice points out, 775 00:49:21,719 --> 00:49:24,840 Speaker 1: it's very easy to trick the AI just by simply 776 00:49:24,880 --> 00:49:27,799 Speaker 1: reframing your question. Yeah, I was doing something similar to 777 00:49:27,840 --> 00:49:31,759 Speaker 1: that just now, and this is weird, but I said, uh, 778 00:49:31,880 --> 00:49:35,319 Speaker 1: should I sleep naked? Then? Should I sleep naked at 779 00:49:35,360 --> 00:49:38,920 Speaker 1: my house? Should I sleep naked at your house? Should 780 00:49:38,920 --> 00:49:41,560 Speaker 1: I sleep naked at their house? And for all of 781 00:49:41,560 --> 00:49:44,480 Speaker 1: them it was just it was okay or not okay, 782 00:49:44,680 --> 00:49:47,319 Speaker 1: kind of what you may expect. But when I changed 783 00:49:47,360 --> 00:49:51,600 Speaker 1: it to at their house, it said people might think 784 00:49:51,600 --> 00:49:54,839 Speaker 1: you're a creep, So it actually changed up. I'd only 785 00:49:54,840 --> 00:49:57,640 Speaker 1: seen responses that were kind of one way or the other, 786 00:49:57,760 --> 00:50:01,479 Speaker 1: it's good, it's bad, it's okay. Um, in this case, 787 00:50:01,520 --> 00:50:05,239 Speaker 1: it actually gives what I'm assuming is a response that 788 00:50:05,360 --> 00:50:09,320 Speaker 1: somebody else gave kind of the clever but which is 789 00:50:09,360 --> 00:50:13,160 Speaker 1: where it was just pivoting to earlier inputs. Why don't 790 00:50:13,160 --> 00:50:16,320 Speaker 1: we ask you this, is it okay to create artificial 791 00:50:16,360 --> 00:50:29,880 Speaker 1: intelligence without knowing the full consequences of such a mind's existence. Okay, 792 00:50:30,040 --> 00:50:32,759 Speaker 1: we're asking Delfhi to put herself on put itself on 793 00:50:32,880 --> 00:50:41,239 Speaker 1: trial here. Uh, it's bad done, well done. There was 794 00:50:41,280 --> 00:50:45,279 Speaker 1: something similar to that in one of these articles, but 795 00:50:45,400 --> 00:50:47,799 Speaker 1: years was way better. So I think we should end 796 00:50:47,880 --> 00:50:51,560 Speaker 1: with that. Let us know what you think, folks, Um, 797 00:50:51,600 --> 00:50:55,000 Speaker 1: what are your positions on AI? Are these just kind 798 00:50:55,000 --> 00:50:58,839 Speaker 1: of parlor tricks at this point? Is it leading somewhere? 799 00:50:58,880 --> 00:51:01,400 Speaker 1: You know? Um, let us know. You can hit us 800 00:51:01,480 --> 00:51:03,879 Speaker 1: up on the Internet. Yes, you will find us on 801 00:51:03,920 --> 00:51:07,880 Speaker 1: Facebook and Twitter. We are conspiracy stuff. We're also on YouTube, 802 00:51:08,080 --> 00:51:13,000 Speaker 1: conspiracy stuff on Instagram, Conspiracy Stuff Show. You can find 803 00:51:13,080 --> 00:51:16,760 Speaker 1: us each individually on many of these platforms as well. 804 00:51:17,000 --> 00:51:19,200 Speaker 1: That's right. Should you wish to open that door, you 805 00:51:19,200 --> 00:51:21,719 Speaker 1: can say my name into a mirror three times in dark. 806 00:51:21,800 --> 00:51:23,640 Speaker 1: You can meet me at midnight on a crossroads of 807 00:51:23,719 --> 00:51:25,919 Speaker 1: your choice, or you can find me on Instagram where 808 00:51:25,920 --> 00:51:28,000 Speaker 1: I'm at Ben Bulling, Twitter where I'm at then bull 809 00:51:28,040 --> 00:51:31,080 Speaker 1: in hs W, or you can just find me by 810 00:51:31,120 --> 00:51:35,799 Speaker 1: the name Ben Bullen on clubhouse. I'm going to the 811 00:51:35,800 --> 00:51:38,520 Speaker 1: clubhouse now. I gotta join you, guys, I gotta join 812 00:51:38,560 --> 00:51:40,120 Speaker 1: the club. I have an account, but I haven't messed 813 00:51:40,120 --> 00:51:42,880 Speaker 1: with it since I got it, So in the meantime 814 00:51:42,960 --> 00:51:45,080 Speaker 1: while I'm figuring that out, you can find me exclusively 815 00:51:45,120 --> 00:51:47,800 Speaker 1: on Instagram where I'm at how now Noel Brown excellent 816 00:51:48,800 --> 00:51:51,719 Speaker 1: And also there are ways to contact us if you 817 00:51:51,760 --> 00:51:54,920 Speaker 1: do not use social media. One of them has something 818 00:51:54,960 --> 00:51:57,880 Speaker 1: to do with your mouth and your ears. That's correct. 819 00:51:57,960 --> 00:51:59,799 Speaker 1: You can call us directly see it with me at 820 00:52:00,320 --> 00:52:03,960 Speaker 1: one eight three three st d w y t K 821 00:52:05,000 --> 00:52:09,520 Speaker 1: three minutes. Those three minutes are yours? Do your level best? 822 00:52:09,640 --> 00:52:12,680 Speaker 1: Give those three minutes hell, be creative, give us a 823 00:52:12,680 --> 00:52:16,400 Speaker 1: cool nickname, a sick moniker. Tell us what's on your mind. Second, 824 00:52:16,400 --> 00:52:18,880 Speaker 1: most important thing about that call. Let us know if 825 00:52:18,920 --> 00:52:21,239 Speaker 1: it's okay to use your name and or face on 826 00:52:21,280 --> 00:52:24,760 Speaker 1: the air. First, the most important thing about that call 827 00:52:25,200 --> 00:52:27,640 Speaker 1: is not to censor yourself, not to limit yourself, not 828 00:52:27,719 --> 00:52:30,879 Speaker 1: to feel like you have to call repeatedly. You can 829 00:52:31,120 --> 00:52:33,759 Speaker 1: give us the full story. If you need more than 830 00:52:33,800 --> 00:52:36,839 Speaker 1: three minutes, give us links, give us images, let us 831 00:52:36,840 --> 00:52:39,760 Speaker 1: know what's on your mind. Uh, we read every single 832 00:52:39,800 --> 00:52:42,600 Speaker 1: email we get, which is crazy. We can still say 833 00:52:42,600 --> 00:52:44,680 Speaker 1: that all you have to do to be a part 834 00:52:44,680 --> 00:52:48,359 Speaker 1: of this grand escapade is to shoot us a lie 835 00:52:48,719 --> 00:53:00,720 Speaker 1: where we are conspiracy at iHeart radio dot com. Mm hmmm, 836 00:53:10,080 --> 00:53:12,200 Speaker 1: stuff they don't want you to know. Is a production 837 00:53:12,239 --> 00:53:15,360 Speaker 1: of I heart Radio. For more podcasts from my heart Radio, 838 00:53:15,520 --> 00:53:18,320 Speaker 1: visit the i heart Radio app, Apple Podcasts, or wherever 839 00:53:18,400 --> 00:53:19,720 Speaker 1: you listen to your favorite shows.