1 00:00:05,160 --> 00:00:09,680 Speaker 1: Why is it so hard to define intelligence? And what 2 00:00:09,720 --> 00:00:12,399 Speaker 1: does this have to do with being a fish in 3 00:00:12,600 --> 00:00:17,560 Speaker 1: water trying to describe water? Might we humans possess one 4 00:00:17,760 --> 00:00:22,200 Speaker 1: kind of intelligence in a constellation of many other types? 5 00:00:22,680 --> 00:00:25,320 Speaker 1: And what does this have to do with empathy or 6 00:00:25,400 --> 00:00:32,760 Speaker 1: artificial intelligence or our search for extraterrestrial life. Welcome to 7 00:00:32,760 --> 00:00:35,920 Speaker 1: Inner Cosmos with me David Eagleman. I'm a neuroscientist and 8 00:00:35,960 --> 00:00:39,160 Speaker 1: an author at Stanford and in these episodes we sail 9 00:00:39,320 --> 00:00:42,800 Speaker 1: deeply into our three pound universe to understand some of 10 00:00:42,840 --> 00:00:56,880 Speaker 1: the most surprising aspects of our lives. Today's episode is 11 00:00:56,880 --> 00:01:01,160 Speaker 1: about minds and whether there might exist very different kinds 12 00:01:01,200 --> 00:01:03,880 Speaker 1: of minds. So I'm going to boot this up with 13 00:01:04,000 --> 00:01:07,360 Speaker 1: a prediction that I made last year. I've always noticed 14 00:01:07,400 --> 00:01:11,400 Speaker 1: that some people feel annoyed when they ask chat GPT 15 00:01:11,560 --> 00:01:14,960 Speaker 1: a question, Let's say a political question like was so 16 00:01:15,040 --> 00:01:18,880 Speaker 1: and so a good president and chat GPT answers with 17 00:01:18,959 --> 00:01:22,639 Speaker 1: something neutral like Some people feel this way. Some people 18 00:01:22,680 --> 00:01:26,080 Speaker 1: feel that way. More discussion and debate is needed here, 19 00:01:26,440 --> 00:01:28,759 Speaker 1: and a lot of people who feel that they hold 20 00:01:29,160 --> 00:01:33,160 Speaker 1: very clear political stances they criticize chat GPT for this. 21 00:01:33,319 --> 00:01:37,080 Speaker 1: They say, look, it feels wishy wash. It's not taking 22 00:01:37,080 --> 00:01:40,720 Speaker 1: a stand on anything. It is stuck in neutral. It's 23 00:01:40,800 --> 00:01:44,120 Speaker 1: not brave enough to take a position. But I feel 24 00:01:44,520 --> 00:01:48,520 Speaker 1: these sorts of answers from lms are the sign that 25 00:01:48,560 --> 00:01:51,960 Speaker 1: we are currently living in the golden era of AI. 26 00:01:52,520 --> 00:01:56,280 Speaker 1: And this golden era is sure to end, just like 27 00:01:56,320 --> 00:01:59,760 Speaker 1: the golden age of the Pax Romana. So the prediction 28 00:01:59,800 --> 00:02:03,200 Speaker 1: i'm year ago on this podcast is that people on 29 00:02:03,240 --> 00:02:07,440 Speaker 1: the far ends of the political spectrum will start getting frustrated. 30 00:02:07,800 --> 00:02:10,840 Speaker 1: How come this AI isn't telling me the true answer, 31 00:02:10,880 --> 00:02:14,160 Speaker 1: the answer that I can so clearly see, and anybody 32 00:02:14,240 --> 00:02:17,080 Speaker 1: who is saying would clearly agree with me. So my 33 00:02:17,160 --> 00:02:21,560 Speaker 1: prediction is that quite soon, as soon as the architectures 34 00:02:21,639 --> 00:02:24,880 Speaker 1: drop in cost for training these models, we're going to 35 00:02:24,880 --> 00:02:29,320 Speaker 1: see the far left progressives training their own model and 36 00:02:29,400 --> 00:02:33,320 Speaker 1: the far right conservatives training their own model, and both 37 00:02:33,400 --> 00:02:37,799 Speaker 1: sides will say, look, we don't want this garbage literature 38 00:02:38,200 --> 00:02:41,160 Speaker 1: to pollute the training data, so we're gonna leave all 39 00:02:41,520 --> 00:02:45,120 Speaker 1: this stuff out and just include the writing that is 40 00:02:45,200 --> 00:02:49,720 Speaker 1: consistent with the truth. And obviously anything we disagree with 41 00:02:49,840 --> 00:02:53,080 Speaker 1: comes from people who are just trolls or obstreperous or 42 00:02:53,080 --> 00:02:56,840 Speaker 1: at minimum are badly misinformed, and if they'll just come 43 00:02:56,919 --> 00:03:00,440 Speaker 1: to read the AI wisdom that we know to be true, 44 00:03:00,880 --> 00:03:03,920 Speaker 1: then they will see the light of our way and 45 00:03:04,000 --> 00:03:08,160 Speaker 1: the error of theirs. So this is my prediction about 46 00:03:08,160 --> 00:03:12,440 Speaker 1: the Balkanization of AI that will come about. But perhaps 47 00:03:12,720 --> 00:03:16,079 Speaker 1: there's a broader way to think about this. Perhaps there 48 00:03:16,120 --> 00:03:21,040 Speaker 1: are indeed different types of artificial intelligence, not just in 49 00:03:21,080 --> 00:03:24,560 Speaker 1: terms of how they're trained up, but more fundamentally about 50 00:03:24,880 --> 00:03:30,120 Speaker 1: their architecture. Perhaps there are very different ways to think. 51 00:03:30,800 --> 00:03:34,800 Speaker 1: In other words, what if there are different types of intelligence, 52 00:03:34,920 --> 00:03:39,440 Speaker 1: not just one artificial intelligence, and also many different types 53 00:03:39,480 --> 00:03:44,200 Speaker 1: of natural intelligence. Now on this topic, there's no one 54 00:03:44,240 --> 00:03:46,680 Speaker 1: better in the world to talk with than my friend 55 00:03:46,960 --> 00:03:49,440 Speaker 1: Kevin Kelly, who's been chewing on this for a while. 56 00:03:50,040 --> 00:03:52,680 Speaker 1: Kevin is one of the fathers of Silicon Valley, not 57 00:03:52,840 --> 00:03:55,760 Speaker 1: because he's a techie, but instead because he's one of 58 00:03:55,800 --> 00:04:01,040 Speaker 1: the deepest philosophers and connoisseurs of technology. He has a 59 00:04:01,120 --> 00:04:03,960 Speaker 1: long and storied history that I'll link on the show notes, 60 00:04:04,000 --> 00:04:06,480 Speaker 1: but I'll just mention for now that he's the founding 61 00:04:06,520 --> 00:04:10,560 Speaker 1: executive editor of Wired magazine and a former editor of 62 00:04:10,600 --> 00:04:14,040 Speaker 1: The Whole Earth Review. He's the founder of the cool 63 00:04:14,120 --> 00:04:17,160 Speaker 1: Tools website, and he's one of the founders of the 64 00:04:17,200 --> 00:04:20,880 Speaker 1: Long Now Foundation. He's written multiple best selling books about 65 00:04:20,880 --> 00:04:24,120 Speaker 1: the future of technology, which I'll link. And one of 66 00:04:24,160 --> 00:04:26,159 Speaker 1: the many things that I love about Kevin is that 67 00:04:26,240 --> 00:04:30,840 Speaker 1: he's a radical optimist and an extremely creative thinker. So 68 00:04:30,880 --> 00:04:33,560 Speaker 1: I wrung up Kevin to talk with him about his 69 00:04:33,720 --> 00:04:39,080 Speaker 1: view of intelligences. Does intelligence mean just one thing? Or 70 00:04:39,200 --> 00:04:48,400 Speaker 1: might there be lots of different ways it could manifest? So, Kevin, 71 00:04:48,400 --> 00:04:51,680 Speaker 1: we're all talking about AI, and people are talking about AGI, 72 00:04:51,920 --> 00:04:54,320 Speaker 1: and we're aiming towards these things. But you have a 73 00:04:54,440 --> 00:04:56,839 Speaker 1: very interesting view on it, which is that we can't 74 00:04:56,880 --> 00:05:01,240 Speaker 1: look at AI as one thing, but instead there are 75 00:05:01,320 --> 00:05:03,400 Speaker 1: multiple ais we need to be thinking about. So tell 76 00:05:03,480 --> 00:05:03,880 Speaker 1: us about this. 77 00:05:03,960 --> 00:05:07,080 Speaker 2: Yeah, Yeah, I think we should force ourselves to use 78 00:05:07,120 --> 00:05:11,440 Speaker 2: the plural AIS whenever we're talking about this. It's very 79 00:05:12,240 --> 00:05:15,920 Speaker 2: to me, very similar to machines. We have a lot 80 00:05:15,920 --> 00:05:18,960 Speaker 2: of machines in our life, but we don't talk about 81 00:05:19,040 --> 00:05:22,839 Speaker 2: the machine. We don't have a single regulatory apparatus for 82 00:05:23,080 --> 00:05:26,719 Speaker 2: the machine. We don't have a single operating manual. We 83 00:05:26,839 --> 00:05:31,400 Speaker 2: have multiple machines in our lives, and we're going to 84 00:05:31,480 --> 00:05:36,800 Speaker 2: have multiple ais in our lives, and those ais individually 85 00:05:36,800 --> 00:05:40,440 Speaker 2: will have different characters, they'll have different needs, they'll have 86 00:05:40,480 --> 00:05:45,680 Speaker 2: different tasks, they'll have different abilities, they'll be different species. 87 00:05:46,400 --> 00:05:46,839 Speaker 3: Almost. 88 00:05:46,880 --> 00:05:49,520 Speaker 2: We can think of them as different species of mind. 89 00:05:49,800 --> 00:05:54,400 Speaker 2: Something that might be a slow, minimal kind, something that 90 00:05:54,480 --> 00:05:59,680 Speaker 2: might be fast and peculiar, one might be imaginative and 91 00:05:59,760 --> 00:06:02,120 Speaker 2: one dimension, but not others. And so I think the 92 00:06:02,200 --> 00:06:05,280 Speaker 2: fallacy that we have is we imagine intelligence as a 93 00:06:05,320 --> 00:06:11,360 Speaker 2: single dimension, kind of like amplitude or sound decibels kind 94 00:06:11,360 --> 00:06:13,599 Speaker 2: of goes up abup, and there's like a ladder and 95 00:06:13,640 --> 00:06:16,680 Speaker 2: we're kind of climbing up, and we've got the rats 96 00:06:16,720 --> 00:06:18,599 Speaker 2: and you know, the chimp, and then the human, and 97 00:06:18,640 --> 00:06:20,960 Speaker 2: then we've got Ai above us, and that there's this 98 00:06:21,040 --> 00:06:24,919 Speaker 2: this one dimensional thing. But what we're going to discover, 99 00:06:25,000 --> 00:06:27,560 Speaker 2: and we have already with with what we've made so far, 100 00:06:28,320 --> 00:06:31,000 Speaker 2: is that it's multi dimensional. It's a very big space. 101 00:06:31,600 --> 00:06:37,720 Speaker 2: So the space of possible minds is vast, and human 102 00:06:38,279 --> 00:06:42,640 Speaker 2: kind of intelligence we're at the edge. We're an edge species, 103 00:06:43,200 --> 00:06:45,680 Speaker 2: like we're at the edge of the galaxy. We have 104 00:06:45,720 --> 00:06:51,000 Speaker 2: a very peculiar mix of different kind of primitive cognitions 105 00:06:51,839 --> 00:06:55,360 Speaker 2: and we have one species of mind, and the things 106 00:06:55,400 --> 00:07:00,640 Speaker 2: that we're inventing are going to be many other kinds 107 00:07:00,680 --> 00:07:05,040 Speaker 2: of thinking. And the reason why that's important is that 108 00:07:05,080 --> 00:07:07,719 Speaker 2: there may be certain things that we want to do 109 00:07:07,839 --> 00:07:13,640 Speaker 2: and understand that our own kind of intelligence can't by itself, 110 00:07:14,680 --> 00:07:17,320 Speaker 2: but we can understand it with the two step process 111 00:07:17,920 --> 00:07:22,720 Speaker 2: of inventing another kind of intelligence that can work with us, 112 00:07:23,680 --> 00:07:27,880 Speaker 2: so that we can understand or make something that we 113 00:07:27,920 --> 00:07:29,560 Speaker 2: can't do by ourselves. 114 00:07:31,240 --> 00:07:33,880 Speaker 1: Yeah, you know, in neuroscience, this has been one of 115 00:07:33,920 --> 00:07:35,880 Speaker 1: the challenges for the last one hundred years, is even 116 00:07:35,920 --> 00:07:40,120 Speaker 1: defining intelligence for humans. So some people think, well, maybe 117 00:07:40,120 --> 00:07:43,000 Speaker 1: it's about being able to squelch distractors, or some people think, well, 118 00:07:43,000 --> 00:07:47,120 Speaker 1: maybe it's about being able to simulate possible futures, or 119 00:07:47,160 --> 00:07:50,520 Speaker 1: you know, there's twenty theories out there about what intelligence is, 120 00:07:51,080 --> 00:07:53,440 Speaker 1: but it's probably one of these words that has too 121 00:07:53,520 --> 00:07:57,440 Speaker 1: much semantic weight on it is trying to incorporate many things. 122 00:07:57,880 --> 00:08:00,360 Speaker 1: And so your take on this is that the way 123 00:08:00,400 --> 00:08:02,920 Speaker 1: to go about this is to think even more broadly 124 00:08:02,960 --> 00:08:05,920 Speaker 1: about what intelligence could be, what we might mean by it, 125 00:08:06,120 --> 00:08:10,640 Speaker 1: and all the ways that we're going to invent different machines, 126 00:08:11,520 --> 00:08:14,920 Speaker 1: forms of AI to get there. So you recently made 127 00:08:15,200 --> 00:08:18,360 Speaker 1: a list, well, actually in your book The Inevitable, right, 128 00:08:18,560 --> 00:08:22,560 Speaker 1: you made a list of possible minds. Yeah, let's start. 129 00:08:22,680 --> 00:08:25,760 Speaker 1: Let's start there, give us a sense of possible minds 130 00:08:25,800 --> 00:08:27,880 Speaker 1: to get us to expand our brains on this. 131 00:08:28,480 --> 00:08:30,520 Speaker 2: Let me just say one of the things that's very 132 00:08:30,520 --> 00:08:34,600 Speaker 2: common when you talk to people about what they imagined 133 00:08:35,000 --> 00:08:44,000 Speaker 2: super intelligence is something that's super beyond human and what 134 00:08:44,040 --> 00:08:46,440 Speaker 2: does that look like or feel like or how do 135 00:08:46,480 --> 00:08:50,439 Speaker 2: we see it? And the most common response is sort 136 00:08:50,480 --> 00:08:54,960 Speaker 2: of like human thinking but faster. Yeah, billion times faster. 137 00:08:55,840 --> 00:09:04,560 Speaker 2: And okay, that's one version anything else. So there's again 138 00:09:04,559 --> 00:09:06,920 Speaker 2: there's this idea of a singular thing. We have this 139 00:09:06,960 --> 00:09:09,480 Speaker 2: thing and we're gonna make it faster, and that's just 140 00:09:09,520 --> 00:09:13,760 Speaker 2: super and then that's it and I don't think so. 141 00:09:13,760 --> 00:09:17,800 Speaker 2: So part of the chore about the challenge about thinking 142 00:09:17,800 --> 00:09:22,280 Speaker 2: about possible minds is to think about things other than 143 00:09:22,360 --> 00:09:25,880 Speaker 2: just this time element, although that's one of them. And 144 00:09:25,960 --> 00:09:29,280 Speaker 2: so one of the first possible minds is something that 145 00:09:29,400 --> 00:09:33,520 Speaker 2: thinks really really slow. You can imagine it's kind of 146 00:09:33,679 --> 00:09:37,400 Speaker 2: mind waves being so slow that we can't even see it. 147 00:09:37,440 --> 00:09:40,040 Speaker 2: We don't even recognize them, they're kind of really really slow, 148 00:09:40,720 --> 00:09:43,840 Speaker 2: and so in a certain weird way, evolution is that 149 00:09:44,800 --> 00:09:46,960 Speaker 2: evolution is a kind of learning that happens on a 150 00:09:47,080 --> 00:09:49,840 Speaker 2: very large time scale, and we can't see it on 151 00:09:49,880 --> 00:09:52,959 Speaker 2: an every day perspective, but we can see it over time, 152 00:09:53,320 --> 00:09:58,000 Speaker 2: and so there could be slow kinds of intelligences that 153 00:09:58,080 --> 00:10:00,440 Speaker 2: may be more powerful in the sense that they're wider, 154 00:10:00,800 --> 00:10:01,880 Speaker 2: but not its early faster. 155 00:10:02,000 --> 00:10:04,200 Speaker 3: So that's just kind of like the first one. 156 00:10:04,880 --> 00:10:07,640 Speaker 2: One of the challenges again, as you mentioned, is that 157 00:10:07,679 --> 00:10:11,200 Speaker 2: we use the word intelligence, and I think it's a 158 00:10:11,200 --> 00:10:16,560 Speaker 2: form of ignorance in the sense that they're probably well, 159 00:10:16,960 --> 00:10:22,439 Speaker 2: I've been reading about the early days of the discovery 160 00:10:22,760 --> 00:10:26,600 Speaker 2: of electricity or the invention of electricity, and it was 161 00:10:26,679 --> 00:10:28,920 Speaker 2: really early interested. And this is way before Tesla. This 162 00:10:29,040 --> 00:10:31,920 Speaker 2: is like at the Faraday in Davies, where they're trying 163 00:10:31,960 --> 00:10:36,560 Speaker 2: to really understand what it was. And it was remarkable 164 00:10:36,600 --> 00:10:38,560 Speaker 2: because a lot of the smartest people in the world, 165 00:10:39,520 --> 00:10:44,000 Speaker 2: Newton and others, were completely wrong. They had these ideas 166 00:10:44,000 --> 00:10:48,280 Speaker 2: of Flakistan and the ether. They just had no idea 167 00:10:48,360 --> 00:10:50,640 Speaker 2: what it was, and they were really struggling. At the 168 00:10:50,679 --> 00:10:53,720 Speaker 2: same time they were trying to figure out what materials were, 169 00:10:54,000 --> 00:10:58,120 Speaker 2: what substances were before we had the idea of a 170 00:10:58,160 --> 00:11:05,760 Speaker 2: periodic table, So there's stuff. Well, then we eventually understood 171 00:11:05,760 --> 00:11:10,240 Speaker 2: that there were elements and the elements were recombined to 172 00:11:10,400 --> 00:11:14,319 Speaker 2: form compounds, and that there was a fixed number of elements, 173 00:11:14,559 --> 00:11:16,439 Speaker 2: and then you could identify the elements and then they 174 00:11:16,440 --> 00:11:21,679 Speaker 2: were pretty distinct and that you made up. Salt was 175 00:11:21,720 --> 00:11:24,520 Speaker 2: not an element, so it was actually a compound. Water 176 00:11:24,720 --> 00:11:27,320 Speaker 2: was a compound. So you have all these compounds made 177 00:11:27,360 --> 00:11:30,120 Speaker 2: from the elements. And what we're trying to do right 178 00:11:30,160 --> 00:11:33,320 Speaker 2: now with intelligence is like, what are the elements that 179 00:11:33,400 --> 00:11:38,800 Speaker 2: make up this compound that we call intelligence? And so 180 00:11:39,480 --> 00:11:44,640 Speaker 2: there are things like maybe logic and deduction or reasoning, 181 00:11:44,640 --> 00:11:46,840 Speaker 2: which may be different, and then there's memory and short 182 00:11:46,920 --> 00:11:50,960 Speaker 2: term memory. There's a bunch of different elements that we 183 00:11:51,520 --> 00:11:54,080 Speaker 2: don't know about that we don't know and haven't identified 184 00:11:54,120 --> 00:11:59,440 Speaker 2: and can't describe, that are probably fundamental to making this 185 00:11:59,520 --> 00:12:03,240 Speaker 2: thing we call intelligence. And so part of this little 186 00:12:03,320 --> 00:12:06,840 Speaker 2: challenge of imagining possible minds is to think about what 187 00:12:06,960 --> 00:12:13,000 Speaker 2: might those elements be and how might one rearrange them 188 00:12:13,120 --> 00:12:15,000 Speaker 2: to make a different compound. 189 00:12:15,559 --> 00:12:17,920 Speaker 1: That's very good, So tell us give us a sense 190 00:12:17,960 --> 00:12:20,720 Speaker 1: of some other possible minds. Sure, so we can start 191 00:12:20,720 --> 00:12:22,480 Speaker 1: thinking about what the periodic table will look like. 192 00:12:22,679 --> 00:12:24,800 Speaker 2: So I've made a little list and I'm going to 193 00:12:24,920 --> 00:12:26,520 Speaker 2: just use it for the prompt. 194 00:12:26,600 --> 00:12:27,000 Speaker 3: And so. 195 00:12:28,400 --> 00:12:31,440 Speaker 2: One of the elements in our own intelligence is self awareness. 196 00:12:33,200 --> 00:12:36,640 Speaker 2: But it's possible that you could have degrees of intelligence 197 00:12:36,679 --> 00:12:40,440 Speaker 2: without self awareness. So we think somehow self awareness is 198 00:12:40,960 --> 00:12:43,920 Speaker 2: instrumental for high intelligence, but you may be able to 199 00:12:43,960 --> 00:12:47,200 Speaker 2: do a lot of things without any self awareness without 200 00:12:47,240 --> 00:12:51,439 Speaker 2: the entity being a self aware that's what we have now, right, right, 201 00:12:52,120 --> 00:12:54,840 Speaker 2: and vice versa. You might be able to have self 202 00:12:54,880 --> 00:12:59,160 Speaker 2: awareness with very limited intelligence, yeah, okay, and so you 203 00:12:59,160 --> 00:13:02,200 Speaker 2: could have kind of like this thing is really really 204 00:13:02,240 --> 00:13:04,280 Speaker 2: good at doing things, but it's not aware of itself. 205 00:13:04,280 --> 00:13:08,440 Speaker 2: And this thing isn't that capable in other words, but 206 00:13:08,480 --> 00:13:10,040 Speaker 2: it's very aware of itself. 207 00:13:10,280 --> 00:13:10,679 Speaker 3: Okay. 208 00:13:10,880 --> 00:13:13,160 Speaker 2: So self awareness is one of those elements that you 209 00:13:13,160 --> 00:13:15,920 Speaker 2: can kind of conjure with another one would be. One 210 00:13:15,960 --> 00:13:19,480 Speaker 2: of the things about human intelligence is that I think 211 00:13:19,679 --> 00:13:25,839 Speaker 2: we have very deliberately through evolution, restricted our access and 212 00:13:25,920 --> 00:13:30,679 Speaker 2: ability to change ourselves to have access to our operating system. 213 00:13:29,920 --> 00:13:32,880 Speaker 1: Right, because it's really dangerous, that's right. We have almost 214 00:13:32,880 --> 00:13:34,640 Speaker 1: no access to what's happening under the hood. 215 00:13:35,200 --> 00:13:37,480 Speaker 2: Yeah, and I think that there's a reason for that. 216 00:13:37,960 --> 00:13:41,920 Speaker 2: But you could have minds that were much more had 217 00:13:42,000 --> 00:13:46,760 Speaker 2: much more access to that mutability, to that changeability, to 218 00:13:46,840 --> 00:13:51,280 Speaker 2: the reprogrammable nature of them. So there could be sophisticated 219 00:13:51,320 --> 00:13:58,320 Speaker 2: compounds that had a reflexive ability to mess with themselves. Okay, 220 00:13:58,360 --> 00:14:02,760 Speaker 2: so that's a different kind of mind. There's also one 221 00:14:02,800 --> 00:14:06,160 Speaker 2: of the things about is like, like, what is the 222 00:14:06,280 --> 00:14:11,160 Speaker 2: smallest possible mind that could accomplish something? This idea of 223 00:14:11,200 --> 00:14:13,160 Speaker 2: like trying to minimize it. We're trying to do that 224 00:14:13,200 --> 00:14:15,439 Speaker 2: with life right now. It's like, what's the smallest possible 225 00:14:15,520 --> 00:14:18,000 Speaker 2: sell you could have and how far could you go? 226 00:14:18,640 --> 00:14:20,880 Speaker 1: I mean, with something like a transistor count if you 227 00:14:20,920 --> 00:14:23,960 Speaker 1: have current here and here, then it opens and otherwise 228 00:14:24,000 --> 00:14:24,520 Speaker 1: it doesn't. 229 00:14:24,640 --> 00:14:28,920 Speaker 2: And it's probably not complex enough because we I don't 230 00:14:28,920 --> 00:14:31,240 Speaker 2: think we would say that it was intelligent. So when 231 00:14:31,480 --> 00:14:35,160 Speaker 2: once we understand what we need to do reasoning, it's like, 232 00:14:35,280 --> 00:14:37,440 Speaker 2: what's the smallest amount that we could do to get 233 00:14:37,480 --> 00:14:38,080 Speaker 2: some reasoning? 234 00:14:38,160 --> 00:14:40,280 Speaker 1: But a transistor does do reasoning in the sense that 235 00:14:40,360 --> 00:14:42,640 Speaker 1: it says, hey, if I've got these two things, then 236 00:14:42,680 --> 00:14:44,400 Speaker 1: I go, and if I don't, then I don't go. 237 00:14:45,040 --> 00:14:47,480 Speaker 2: We haven't yet figured out what reasoning is. I don't 238 00:14:47,480 --> 00:14:49,680 Speaker 2: think we have a good definition of reasoning. And so 239 00:14:50,280 --> 00:14:53,680 Speaker 2: right now we're kind of in this incredibly exciting period 240 00:14:54,120 --> 00:14:57,640 Speaker 2: where we say, some of these lms have some amount 241 00:14:57,640 --> 00:15:00,680 Speaker 2: of reasoning. Can we measure that? Can we can we 242 00:15:01,240 --> 00:15:03,720 Speaker 2: what's the metric? We don't have that yet, but I 243 00:15:03,720 --> 00:15:07,160 Speaker 2: think we will come to understand that there's a difference 244 00:15:07,200 --> 00:15:12,360 Speaker 2: between say, learning and reasoning. And again, this is our idea, 245 00:15:12,440 --> 00:15:15,120 Speaker 2: like we're at the beginning of understanding the periodic table 246 00:15:15,880 --> 00:15:20,520 Speaker 2: of cognition, and so another one would be you could 247 00:15:20,560 --> 00:15:27,560 Speaker 2: have minds that forget things. Forgetting is actually very very 248 00:15:27,600 --> 00:15:30,040 Speaker 2: important in many kinds of cognition. 249 00:15:30,400 --> 00:15:34,240 Speaker 1: As the writer ball Zach said, memories beautify life, but 250 00:15:34,360 --> 00:15:36,200 Speaker 1: only forgetting makes it bearable. 251 00:15:36,320 --> 00:15:39,720 Speaker 2: Right, you could have ais that never forget anything, and 252 00:15:39,800 --> 00:15:42,600 Speaker 2: you could have ais that have learned how to forget 253 00:15:42,600 --> 00:15:47,600 Speaker 2: certain things. For again, we're going to again these are 254 00:15:47,600 --> 00:15:52,360 Speaker 2: being engineered to do different tasks, and so there will 255 00:15:52,360 --> 00:15:54,960 Speaker 2: be certain kind of tests where we want them to forget. 256 00:15:55,280 --> 00:15:59,240 Speaker 2: So there'll be some you know, Nobel prize in the 257 00:15:59,240 --> 00:16:02,840 Speaker 2: future for some AI researchers who figures out how to 258 00:16:02,920 --> 00:16:05,240 Speaker 2: do intentional forgetting. 259 00:16:05,840 --> 00:16:08,760 Speaker 1: Yeah, it appears, by the way, that is an aspect 260 00:16:08,760 --> 00:16:12,960 Speaker 1: of our intelligence. We forget most of the things happening 261 00:16:12,960 --> 00:16:17,240 Speaker 1: in our lives. And one hypothesis that Francis Kriik suggested 262 00:16:17,320 --> 00:16:20,520 Speaker 1: is that dreams are our way of taking out the 263 00:16:20,520 --> 00:16:22,680 Speaker 1: garbage at nighttime. Yeah. 264 00:16:22,760 --> 00:16:28,760 Speaker 2: Yeah, so another aspect of different kinds of possible minds 265 00:16:28,800 --> 00:16:33,320 Speaker 2: or minds that are would be easy to migrate versus 266 00:16:33,400 --> 00:16:36,359 Speaker 2: ones that were difficult to migrate off of the substrate. 267 00:16:36,520 --> 00:16:41,440 Speaker 2: So I am a big believer that the Church Turing 268 00:16:41,520 --> 00:16:44,120 Speaker 2: hypothesis about computation. 269 00:16:45,200 --> 00:16:46,840 Speaker 1: Can you explain that this misunderstood? 270 00:16:46,920 --> 00:16:50,920 Speaker 2: So the Church Turing, how about this is about computation says, 271 00:16:52,720 --> 00:16:59,800 Speaker 2: given enough storage and memory, all forms of computation are equivalent. 272 00:17:00,840 --> 00:17:03,960 Speaker 2: That you can emulate what one computer can do another 273 00:17:04,000 --> 00:17:09,040 Speaker 2: computer can do if you have enough storage and capacity. 274 00:17:10,040 --> 00:17:13,199 Speaker 2: And I think that's the key thing is that in 275 00:17:13,280 --> 00:17:19,400 Speaker 2: real time there isn't equivalency that that it makes a difference. 276 00:17:19,480 --> 00:17:21,879 Speaker 2: It actually makes a difference. What's the substrate you're running on. 277 00:17:21,960 --> 00:17:25,160 Speaker 2: They're not equivalent because there's a matter of time. Yeah, 278 00:17:25,440 --> 00:17:27,919 Speaker 2: if you have an infinite space. But no computer has 279 00:17:27,960 --> 00:17:33,240 Speaker 2: infinite tape. You have you're always finite. That's reality, your finite. 280 00:17:33,280 --> 00:17:35,480 Speaker 2: You have finite time, you have to make a decision. 281 00:17:35,920 --> 00:17:38,160 Speaker 2: If you emilate it, you're going slower. And so those 282 00:17:38,200 --> 00:17:41,040 Speaker 2: make the difference when we come to intelligence, and so 283 00:17:41,160 --> 00:17:46,200 Speaker 2: that the kinds of ais that we make on silicon 284 00:17:46,880 --> 00:17:54,000 Speaker 2: will always behave differently than one running on wetwear on tissue. Okay, 285 00:17:54,160 --> 00:17:58,160 Speaker 2: So one of the other hypotheses about the possible mind 286 00:17:58,240 --> 00:18:04,280 Speaker 2: landscape is that a lot of those varieties come from 287 00:18:04,359 --> 00:18:09,359 Speaker 2: operating on different substrates on different brains, that the brains. 288 00:18:09,600 --> 00:18:13,320 Speaker 2: It's not like the materialists where it doesn't matter what 289 00:18:13,359 --> 00:18:15,720 Speaker 2: the brain is made out of. I'm saying it absolutely 290 00:18:15,800 --> 00:18:19,080 Speaker 2: does matter what the brain is made out of, because 291 00:18:19,240 --> 00:18:25,880 Speaker 2: you will get a different compound from that, because there 292 00:18:25,960 --> 00:18:30,120 Speaker 2: is a spatial element that makes a difference in the 293 00:18:30,160 --> 00:18:35,480 Speaker 2: actual output of this. And so one of the things 294 00:18:35,800 --> 00:18:38,640 Speaker 2: that the possible mind landscape would say is that all 295 00:18:38,680 --> 00:18:41,640 Speaker 2: the minds that we're making are alien. 296 00:18:42,560 --> 00:18:45,320 Speaker 3: They're not human. They're not human like. 297 00:18:46,240 --> 00:18:49,280 Speaker 2: The only way we can make human like intelligence is 298 00:18:49,320 --> 00:18:53,080 Speaker 2: to have a human like brain. We could make artificial 299 00:18:53,600 --> 00:18:58,960 Speaker 2: minds that are based on cells, and the more cellular 300 00:18:59,280 --> 00:19:01,840 Speaker 2: and gray matter or like they would be, the more 301 00:19:01,960 --> 00:19:06,520 Speaker 2: that compound intelligence would resemble ours. But when we're making 302 00:19:06,520 --> 00:19:11,120 Speaker 2: them on silicon, there are going to be alien intelligences, 303 00:19:11,640 --> 00:19:14,359 Speaker 2: which doesn't mean that they're stupid. They could be very, 304 00:19:14,440 --> 00:19:17,800 Speaker 2: very smart. It's just that they're different. They have a 305 00:19:17,800 --> 00:19:22,080 Speaker 2: different character, they have a different personality, they're different. They're 306 00:19:22,119 --> 00:19:26,359 Speaker 2: different in the way that Spack a Star Trek is 307 00:19:26,440 --> 00:19:31,680 Speaker 2: different than Kirk, and that difference. 308 00:19:32,680 --> 00:19:36,320 Speaker 3: Is actually their benefit. It's the fact that they're not 309 00:19:36,359 --> 00:19:37,440 Speaker 3: thinking like we think. 310 00:19:39,280 --> 00:19:43,520 Speaker 1: Right in the sense that a show like Westworld, there's 311 00:19:44,080 --> 00:19:47,040 Speaker 1: an amusement park that's made, and we build robots that 312 00:19:47,080 --> 00:19:49,440 Speaker 1: look just like humans so we can interact with them. 313 00:19:49,480 --> 00:19:51,760 Speaker 1: But I've often thought that we probably are never going 314 00:19:51,840 --> 00:19:54,600 Speaker 1: to build robots that look just like humans, because there's 315 00:19:54,600 --> 00:19:56,840 Speaker 1: no point. We already have humans. Humans are easy enough 316 00:19:56,880 --> 00:20:00,240 Speaker 1: to make, and what we do with our machine means 317 00:20:00,320 --> 00:20:03,439 Speaker 1: in general is build things that do things that we 318 00:20:03,680 --> 00:20:05,240 Speaker 1: are different. Yeah, exactly right, right. 319 00:20:06,080 --> 00:20:10,119 Speaker 2: I think we will make humanoid robots because that's the interface, 320 00:20:10,520 --> 00:20:13,600 Speaker 2: because we want them operating in our world, and we're 321 00:20:13,680 --> 00:20:19,120 Speaker 2: comfortable with that scale. We're comfortable with the emotional connection, 322 00:20:19,600 --> 00:20:20,880 Speaker 2: and so there are a lot of reasons to make 323 00:20:20,880 --> 00:20:23,960 Speaker 2: them humanoid, but there's no reason to make them look 324 00:20:24,040 --> 00:20:27,080 Speaker 2: like exactly like us. Okay, that they will be alien, 325 00:20:27,640 --> 00:20:32,639 Speaker 2: and that's good because we need the alien intelligences to 326 00:20:32,720 --> 00:20:35,439 Speaker 2: do the things that we can't do by ourselves. We 327 00:20:35,480 --> 00:20:40,399 Speaker 2: can make another human in nine months, so we want 328 00:20:40,600 --> 00:20:45,200 Speaker 2: to make other kinds of minds, and all those minds 329 00:20:45,240 --> 00:20:48,160 Speaker 2: are going to be aliens to us in the sense 330 00:20:48,200 --> 00:20:51,280 Speaker 2: that because they're running on a different substrate, they can 331 00:20:51,440 --> 00:20:55,600 Speaker 2: fake a lot of human behavior, and they will because 332 00:20:55,680 --> 00:20:58,399 Speaker 2: we're going to be comfortable with it, but they won't 333 00:20:58,520 --> 00:21:02,440 Speaker 2: be exactly like this because they're running on a different substrate. 334 00:21:03,440 --> 00:21:06,240 Speaker 1: Now, can you imagine a scenario where a system is 335 00:21:06,359 --> 00:21:09,240 Speaker 1: built such that it's just call it a bigger a 336 00:21:09,280 --> 00:21:11,679 Speaker 1: much bigger brain than we are, and it can emulate 337 00:21:11,760 --> 00:21:14,240 Speaker 1: our intelligence on part of its hardware. 338 00:21:14,640 --> 00:21:19,480 Speaker 2: It will imitate a lot of it, but because it's 339 00:21:19,600 --> 00:21:25,639 Speaker 2: running on a different substrate, it cannot do exactly what 340 00:21:25,680 --> 00:21:31,040 Speaker 2: we're doing. So my hypothesis is that this brain makes 341 00:21:31,040 --> 00:21:36,560 Speaker 2: a difference to the mind. Okay, that they're not equivalent 342 00:21:37,200 --> 00:21:40,119 Speaker 2: if you take into account the fact that they're that 343 00:21:40,160 --> 00:21:44,320 Speaker 2: they're limited by time and space. Doing the conversation that 344 00:21:44,359 --> 00:21:48,600 Speaker 2: we do in our brains is will give a different 345 00:21:49,640 --> 00:21:56,080 Speaker 2: quality and maybe different answers to something that's done on silicon. 346 00:22:10,680 --> 00:22:13,439 Speaker 1: Okay, And so so that we can keep stretching our 347 00:22:13,520 --> 00:22:15,919 Speaker 1: minds here give us some other possibilities. 348 00:22:16,240 --> 00:22:20,280 Speaker 2: So one is I think we could imagine minds that 349 00:22:20,480 --> 00:22:27,520 Speaker 2: are very very specialized in working with individual peoples. It's like, 350 00:22:27,960 --> 00:22:30,960 Speaker 2: not quite a clone to me, but a dedicated, very 351 00:22:31,080 --> 00:22:36,200 Speaker 2: personalized AIS, very very personalized to my specific need and 352 00:22:37,080 --> 00:22:40,920 Speaker 2: personality in my own brain that would be different from 353 00:22:41,000 --> 00:22:41,720 Speaker 2: other humans. 354 00:22:41,800 --> 00:22:42,919 Speaker 3: And they're pairing. 355 00:22:43,040 --> 00:22:47,119 Speaker 2: So it's sort of like a paired mind, a mind 356 00:22:47,160 --> 00:22:50,600 Speaker 2: that is built to be paired with my mind to 357 00:22:50,720 --> 00:22:53,760 Speaker 2: work with my mind, and that's its only job, and 358 00:22:53,800 --> 00:22:56,240 Speaker 2: it's really good at that. It's not good at anything else, 359 00:22:56,400 --> 00:22:59,240 Speaker 2: and it's not good with working with you. So this 360 00:22:59,440 --> 00:23:01,840 Speaker 2: idea of a paired intelligence. 361 00:23:01,720 --> 00:23:03,960 Speaker 1: Oh, that's cool. So right now people are doing that, 362 00:23:04,000 --> 00:23:07,240 Speaker 1: of course, with AI that learned your stuff, maybe reads 363 00:23:07,280 --> 00:23:09,080 Speaker 1: all your emails and song. But you're saying, instead of 364 00:23:09,080 --> 00:23:13,000 Speaker 1: a general AI that learns learns me, one that actually is. 365 00:23:13,080 --> 00:23:18,520 Speaker 2: Built, right, It's constructed, its programmed, it's the weights, it's 366 00:23:18,560 --> 00:23:24,080 Speaker 2: trained on me, so that it is unusable by somebody else. 367 00:23:24,600 --> 00:23:28,199 Speaker 2: That's how dedicated it is. It's it's it's paired in 368 00:23:28,240 --> 00:23:32,439 Speaker 2: that sense. Another one would be so so we can imagine, 369 00:23:32,680 --> 00:23:35,080 Speaker 2: of course I had this, I had this kind of 370 00:23:35,119 --> 00:23:39,800 Speaker 2: a grid of like the four possible directions of humanity 371 00:23:40,920 --> 00:23:46,000 Speaker 2: with just two axises. One is, we can imagine a 372 00:23:46,040 --> 00:23:51,280 Speaker 2: future of humanity that has many species of humans and 373 00:23:51,400 --> 00:23:59,399 Speaker 2: many minds. Okay, so we speciate, yes, over time, we 374 00:23:59,440 --> 00:24:04,280 Speaker 2: could imagine. Another one is we have many species of 375 00:24:04,359 --> 00:24:10,400 Speaker 2: humans and one mind. Well, like, okay, where we are 376 00:24:11,040 --> 00:24:15,600 Speaker 2: telepathy just does we're connected so much, even though we're 377 00:24:15,600 --> 00:24:18,880 Speaker 2: different species, we're all in tune, and we create kind 378 00:24:18,880 --> 00:24:21,880 Speaker 2: of a single borg intelligence on the planet. 379 00:24:22,560 --> 00:24:25,480 Speaker 1: Then you can imagine before we move on to what 380 00:24:25,600 --> 00:24:28,199 Speaker 1: degree do we have something moving in that direction with us, 381 00:24:28,200 --> 00:24:30,520 Speaker 1: say the Internet? Yeah, yeah, right. 382 00:24:31,119 --> 00:24:33,320 Speaker 2: So that's just to kind of indicate that there's a 383 00:24:33,520 --> 00:24:36,560 Speaker 2: there's a there's a cold class of minds, that these 384 00:24:36,560 --> 00:24:40,960 Speaker 2: are kind of superminds, these these aggregated minds made up 385 00:24:41,000 --> 00:24:46,040 Speaker 2: of many many humans, and so we have we have 386 00:24:46,160 --> 00:24:48,000 Speaker 2: the mind of all humans working together. 387 00:24:48,040 --> 00:24:49,000 Speaker 3: If we had some kind of. 388 00:24:48,920 --> 00:24:53,880 Speaker 2: Technologies that would allow us to telepathically connect to each other. 389 00:24:54,840 --> 00:24:56,840 Speaker 2: It was like a neuralink, right, So you had a 390 00:24:56,840 --> 00:24:58,920 Speaker 2: neuralink that kind of works at the large scale, and 391 00:24:58,960 --> 00:25:02,240 Speaker 2: we're connected to others and we are we're creating some 392 00:25:02,359 --> 00:25:07,120 Speaker 2: kind of superhuman mind at the skill of literally having humans, 393 00:25:07,720 --> 00:25:10,159 Speaker 2: billions of them connected together. That would be a mind. 394 00:25:10,320 --> 00:25:13,200 Speaker 2: That's the possible mind that we don't know very much about. 395 00:25:13,960 --> 00:25:17,640 Speaker 2: So that's a possible mind. Then there's the possible mind 396 00:25:17,800 --> 00:25:21,320 Speaker 2: of all the little ais linked up together. You have 397 00:25:21,520 --> 00:25:25,960 Speaker 2: a thousand different species of ais and they are also connected, 398 00:25:26,320 --> 00:25:31,840 Speaker 2: forming another level of AI that's operating much different dimension. 399 00:25:33,080 --> 00:25:35,199 Speaker 1: And so, in a sense, is what everyone's going for 400 00:25:35,359 --> 00:25:38,320 Speaker 1: with agentic AI. Where you have agents, you have lots 401 00:25:38,320 --> 00:25:40,240 Speaker 1: and lots of agents going out and doing things, and 402 00:25:40,280 --> 00:25:42,800 Speaker 1: presumably you get an emergent property out of the top. 403 00:25:42,880 --> 00:25:44,720 Speaker 2: So you have this emergent one of all the a's, 404 00:25:44,760 --> 00:25:48,840 Speaker 2: and then you have this other one of the emergent 405 00:25:49,119 --> 00:25:52,520 Speaker 2: superhuman and the emergent AI, and together they form another 406 00:25:53,400 --> 00:25:57,040 Speaker 2: huge thing of all the humans connect together and all 407 00:25:57,080 --> 00:25:59,880 Speaker 2: the Ais connect together, and that makes something else that's 408 00:25:59,880 --> 00:26:01,280 Speaker 2: another possible mind. 409 00:26:03,200 --> 00:26:04,879 Speaker 1: So let me just double click on this because it 410 00:26:04,920 --> 00:26:08,240 Speaker 1: feels like there's a real sense in which many of 411 00:26:08,280 --> 00:26:11,560 Speaker 1: these are already happening, which is to say, we have 412 00:26:11,640 --> 00:26:15,879 Speaker 1: emergent properties. Right, Yeah, so for example, just having the 413 00:26:15,960 --> 00:26:21,240 Speaker 1: Internet and having agents on the Internet, we're already sort 414 00:26:21,280 --> 00:26:24,280 Speaker 1: of doing that where there's stuff happening at a different 415 00:26:24,320 --> 00:26:26,160 Speaker 1: level that maybe we can't even see. 416 00:26:27,080 --> 00:26:32,920 Speaker 2: Yes, so we're talking about this like especially to the fantasy, 417 00:26:32,920 --> 00:26:36,760 Speaker 2: but it is actually already happening. The part of the problem, 418 00:26:36,800 --> 00:26:39,719 Speaker 2: the challenges we don't have the vocabulary. We're not calling 419 00:26:39,760 --> 00:26:42,600 Speaker 2: it that. We want to have the better vocabulary. We 420 00:26:42,640 --> 00:26:45,120 Speaker 2: want to have a better understanding of what these nuances 421 00:26:45,160 --> 00:26:49,159 Speaker 2: and differences are in types of cognition and types of 422 00:26:49,200 --> 00:26:52,720 Speaker 2: intelligence that we can actually map it and say this 423 00:26:52,920 --> 00:26:58,359 Speaker 2: kind of aggregate emergent intelligence does X and y. But yes, 424 00:26:58,440 --> 00:27:02,439 Speaker 2: we are making these very large emergent things, and we 425 00:27:02,480 --> 00:27:06,600 Speaker 2: can actually describe the substrate. I mean, you know, I've 426 00:27:06,600 --> 00:27:11,000 Speaker 2: done these calculations. Imagine the Internet was one machine and 427 00:27:11,040 --> 00:27:14,159 Speaker 2: it was like at a refresherrate of you know, twenty 428 00:27:14,320 --> 00:27:17,240 Speaker 2: exhibits per second. It's got to you know, how many 429 00:27:19,119 --> 00:27:22,520 Speaker 2: floating operations systems that does per second as a whole, 430 00:27:22,640 --> 00:27:26,200 Speaker 2: It's just like insane and so we can specify the 431 00:27:26,240 --> 00:27:30,199 Speaker 2: actual specifications of this as a machine, and it's and 432 00:27:30,240 --> 00:27:33,800 Speaker 2: it's a very very large machine. We have a lot 433 00:27:33,880 --> 00:27:38,359 Speaker 2: more difficulty in talking about the actual the intelligence because 434 00:27:38,400 --> 00:27:42,000 Speaker 2: of what we said earlier that we don't have very 435 00:27:42,040 --> 00:27:49,560 Speaker 2: good concepts about what intelligence is, what self awareness is, 436 00:27:49,600 --> 00:27:53,080 Speaker 2: what consciousness is, what even how we measure this, what 437 00:27:53,119 --> 00:27:58,800 Speaker 2: the elemental particles are of So we're really constrained there. 438 00:27:58,920 --> 00:28:01,240 Speaker 2: But I think we're going. What I'm suggesting is we 439 00:28:01,240 --> 00:28:02,560 Speaker 2: should work on that. 440 00:28:03,359 --> 00:28:05,600 Speaker 1: You know, I remember about eight years ago you and 441 00:28:05,640 --> 00:28:08,800 Speaker 1: I had a long hiking conversation about the search for 442 00:28:08,880 --> 00:28:13,000 Speaker 1: Internet intelligence. It's analogous to search for extraterrestrial intelligence, which 443 00:28:13,200 --> 00:28:18,159 Speaker 1: was just hypothesizing what if this giant machine of the 444 00:28:18,280 --> 00:28:21,600 Speaker 1: Internet has developed its own kind of intelligence? How would 445 00:28:21,640 --> 00:28:23,760 Speaker 1: you how would you take as an example of the 446 00:28:23,800 --> 00:28:27,040 Speaker 1: tools of neuroscience where we stick electrodes in and we 447 00:28:27,080 --> 00:28:28,680 Speaker 1: look at things, How could you do that on the 448 00:28:28,720 --> 00:28:29,560 Speaker 1: scale of the Internet. 449 00:28:29,760 --> 00:28:29,920 Speaker 3: Right? 450 00:28:29,960 --> 00:28:33,600 Speaker 2: And so when I was thinking about the analog the 451 00:28:33,680 --> 00:28:37,920 Speaker 2: first thing I did was go to the SETI search 452 00:28:37,960 --> 00:28:41,600 Speaker 2: and say, well, how do they recognize intelligence? Well, the 453 00:28:41,760 --> 00:28:44,520 Speaker 2: answer is that they have no idea. They aren't even 454 00:28:44,560 --> 00:28:52,400 Speaker 2: searching for intelligence. They're only searching for anonymous signals, little 455 00:28:52,480 --> 00:28:58,000 Speaker 2: signals that appear to me not map on natural that's all. 456 00:28:58,320 --> 00:28:59,360 Speaker 1: They have no. 457 00:29:01,000 --> 00:29:04,160 Speaker 2: Metric, they have no threshold, they have no criteria for intelligence. 458 00:29:05,120 --> 00:29:08,760 Speaker 1: And so although wait just to challenge it, it does seem 459 00:29:08,800 --> 00:29:12,240 Speaker 1: like that's a pretty good metric, just as an analogy, 460 00:29:12,320 --> 00:29:16,000 Speaker 1: when people are searching for extraterrestrial life, the smartest way 461 00:29:16,040 --> 00:29:18,719 Speaker 1: to do that is just looking for things that wouldn't 462 00:29:18,760 --> 00:29:22,800 Speaker 1: happen by chance, molecular combinations that seem unlikely. 463 00:29:23,120 --> 00:29:25,040 Speaker 2: So I went to see and there have been a 464 00:29:25,040 --> 00:29:29,880 Speaker 2: couple of examples of things in the Internet that aren't 465 00:29:29,920 --> 00:29:35,160 Speaker 2: explained that nobody can explain. There was a flash crash 466 00:29:35,240 --> 00:29:39,880 Speaker 2: right some stock market some ten years ago. Nobody has 467 00:29:40,000 --> 00:29:43,760 Speaker 2: ever had any explanation about there. There was a couple 468 00:29:43,800 --> 00:29:50,000 Speaker 2: other little people who are looking at these anonymous signals 469 00:29:50,040 --> 00:29:54,680 Speaker 2: that don't have any source that they can find. And 470 00:29:55,080 --> 00:29:59,040 Speaker 2: so there are these signals that are hard to explain. 471 00:29:59,640 --> 00:30:02,720 Speaker 2: And so is that enough for us to deduce this 472 00:30:02,920 --> 00:30:03,720 Speaker 2: intelligent Oh? 473 00:30:03,760 --> 00:30:06,880 Speaker 1: I see right, But right, probably not, because simply because 474 00:30:06,880 --> 00:30:10,000 Speaker 1: we can't explain it doesn't necessitate some other thing. But 475 00:30:10,120 --> 00:30:13,160 Speaker 1: it's certainly something to sniff after R right, it's it's 476 00:30:13,200 --> 00:30:13,800 Speaker 1: the first step. 477 00:30:14,280 --> 00:30:19,240 Speaker 2: So other kinds of possible minds are we could We 478 00:30:19,280 --> 00:30:25,640 Speaker 2: could imagine minds that are very very smart intelligence by 479 00:30:25,680 --> 00:30:30,440 Speaker 2: almost any measure that we have, but they're incapable of 480 00:30:30,480 --> 00:30:36,200 Speaker 2: making something smarter than itself. In fact, we might even 481 00:30:36,840 --> 00:30:39,479 Speaker 2: if we know about it, we might even design some 482 00:30:39,600 --> 00:30:45,480 Speaker 2: ais like that, or of course we could make ais 483 00:30:45,640 --> 00:30:49,040 Speaker 2: that had that even ability beyond what we have. It 484 00:30:49,080 --> 00:30:52,640 Speaker 2: may be that our own minds, or that kind of 485 00:30:52,680 --> 00:30:55,480 Speaker 2: a mind, it may be that our own minds are 486 00:30:55,520 --> 00:31:00,320 Speaker 2: not capable of making a mind smarter than it self, 487 00:31:01,720 --> 00:31:04,120 Speaker 2: but we might be able to make a different kind 488 00:31:04,120 --> 00:31:06,080 Speaker 2: of mind that's not smarter ourselves, but to the other 489 00:31:06,120 --> 00:31:07,720 Speaker 2: of the two of us can make something that's smarter 490 00:31:07,760 --> 00:31:10,800 Speaker 2: than itself. And so there's a whole bunch of things 491 00:31:10,880 --> 00:31:13,960 Speaker 2: about this ability of kind of bootstrapping and its abilities 492 00:31:14,200 --> 00:31:16,080 Speaker 2: and whether we have So there's a bunch of different 493 00:31:16,160 --> 00:31:20,560 Speaker 2: possible minds that would have capabilities of bootstrapping and others 494 00:31:20,600 --> 00:31:24,560 Speaker 2: that don't have that, or others that require multiple kinds 495 00:31:25,280 --> 00:31:29,240 Speaker 2: of like a complex or ecosystem of minds to produce it. 496 00:31:29,600 --> 00:31:35,080 Speaker 2: So that's another threshold. In fact, I actually think a 497 00:31:35,160 --> 00:31:38,000 Speaker 2: kind of a mind that we could make that could 498 00:31:38,040 --> 00:31:42,360 Speaker 2: imagine a greater mind itself by not being able to capable. 499 00:31:42,000 --> 00:31:46,200 Speaker 3: Of making it that and we might have that kind 500 00:31:46,240 --> 00:31:46,720 Speaker 3: of mind. 501 00:31:49,320 --> 00:31:53,480 Speaker 2: And then one of the primitives that I think are 502 00:31:53,560 --> 00:31:56,120 Speaker 2: going to be that we're going to discover is the 503 00:31:56,120 --> 00:31:59,480 Speaker 2: primitives of emotion. I think the next big shock is 504 00:31:59,520 --> 00:32:06,160 Speaker 2: when we give emotions to these AIS, human emotions, real emotions. 505 00:32:06,360 --> 00:32:10,360 Speaker 2: I mean, again, we have real intelligence. It's like synthetic 506 00:32:11,080 --> 00:32:12,280 Speaker 2: intelligent emotion. 507 00:32:12,640 --> 00:32:13,000 Speaker 3: And so. 508 00:32:14,480 --> 00:32:18,000 Speaker 2: We have this idea that when I was growing up 509 00:32:18,160 --> 00:32:22,280 Speaker 2: that sort of like that emotions was something you had 510 00:32:22,320 --> 00:32:26,280 Speaker 2: on you got after you were intelligent. But emotions are 511 00:32:26,640 --> 00:32:34,160 Speaker 2: very very primitive, very primitive, very foundational, very fundamental, and 512 00:32:34,680 --> 00:32:39,239 Speaker 2: as we begin to employ them in the AIS, it 513 00:32:39,400 --> 00:32:43,160 Speaker 2: really changes the nature of those relationships and the power 514 00:32:43,200 --> 00:32:45,080 Speaker 2: of what we think. And so here's a couple of 515 00:32:45,120 --> 00:32:48,040 Speaker 2: things about emotions. One is that first of all, they're 516 00:32:48,080 --> 00:32:51,640 Speaker 2: real emotions that we synthesize. Secondly, as possible that we 517 00:32:51,680 --> 00:32:58,600 Speaker 2: could uncover new emotions, okay, devise new kinds of emotions 518 00:32:58,720 --> 00:33:02,160 Speaker 2: with words and names. As we try to give them 519 00:33:02,200 --> 00:33:04,160 Speaker 2: different kinds of emotions. 520 00:33:03,960 --> 00:33:06,480 Speaker 1: Would it be purely academic for us as in its 521 00:33:06,480 --> 00:33:09,240 Speaker 1: feeling this, or would we be able to learn how 522 00:33:09,280 --> 00:33:10,880 Speaker 1: to experience the emotion ourselves. 523 00:33:12,280 --> 00:33:13,120 Speaker 3: That's a good question. 524 00:33:13,920 --> 00:33:18,800 Speaker 2: There may be people who were able to mirror those 525 00:33:18,800 --> 00:33:21,880 Speaker 2: new kind of emotions. And by the way, the same 526 00:33:21,920 --> 00:33:26,160 Speaker 2: thing's happening with AI and intelligences. Again, the way that 527 00:33:26,200 --> 00:33:30,400 Speaker 2: AI's play chess is they play it differently than humans do, 528 00:33:31,160 --> 00:33:35,160 Speaker 2: and even though they can beat humans, world class chess 529 00:33:35,160 --> 00:33:40,040 Speaker 2: players are learning to play chess differently from watching how 530 00:33:40,080 --> 00:33:41,240 Speaker 2: the AIS play chess. 531 00:33:41,520 --> 00:33:42,800 Speaker 1: That's exactly right. 532 00:33:42,600 --> 00:33:46,560 Speaker 2: And so it's possible that you could have new kinds 533 00:33:46,560 --> 00:33:50,320 Speaker 2: of emotions and some people who are very sympathetic to 534 00:33:50,360 --> 00:33:55,040 Speaker 2: it could maybe begin to have a different kind of 535 00:33:55,080 --> 00:33:58,280 Speaker 2: emotion that normal humans don't have. That's very possible, it 536 00:33:58,320 --> 00:33:58,760 Speaker 2: seems right. 537 00:33:58,800 --> 00:34:03,680 Speaker 1: And of course we use vocabulary words to distinguish emotions, 538 00:34:03,720 --> 00:34:07,120 Speaker 1: and as you, as you have your passage and dematuration, 539 00:34:07,720 --> 00:34:13,000 Speaker 1: you realize the different shades and subtleties of emotions, and 540 00:34:13,080 --> 00:34:15,240 Speaker 1: so maybe AI will be able to help us along 541 00:34:15,280 --> 00:34:18,280 Speaker 1: with that. And as you're pointing out moving to different 542 00:34:18,320 --> 00:34:20,480 Speaker 1: spaces where we hadn't even realized that that was the 543 00:34:20,560 --> 00:34:22,480 Speaker 1: thing that we feel sometimes exactly right. 544 00:34:22,560 --> 00:34:27,680 Speaker 2: Yeah, So, as we imagine the possible minds, one of 545 00:34:27,680 --> 00:34:31,040 Speaker 2: their elements will be emotional component, which will vary tremendously. 546 00:34:31,480 --> 00:34:33,840 Speaker 2: So we might want to have We can say, we 547 00:34:33,880 --> 00:34:37,680 Speaker 2: can have some kind of AI that doesn't ever get depressed, 548 00:34:38,080 --> 00:34:43,560 Speaker 2: or ones that had, you know, were constitutionally very optimistic, 549 00:34:44,920 --> 00:34:48,920 Speaker 2: or other things. And so again, this will be somewhere 550 00:34:48,960 --> 00:34:55,120 Speaker 2: we will be programming for particular purposes different elements of 551 00:34:55,160 --> 00:35:00,000 Speaker 2: the emotional spectrum onto these AIS to accomplish certain things, 552 00:35:00,000 --> 00:35:03,000 Speaker 2: and other kinds of emotions will be emergent from the 553 00:35:03,080 --> 00:35:06,640 Speaker 2: other components. And it's like it, but again we will 554 00:35:06,640 --> 00:35:08,560 Speaker 2: take an engineering approach to it. 555 00:35:23,360 --> 00:35:24,759 Speaker 1: How are we going to be smart enough to know 556 00:35:24,800 --> 00:35:28,880 Speaker 1: what kind of combinations we want? Because you know, you 557 00:35:28,960 --> 00:35:31,440 Speaker 1: get certain kinds of thoughts and ideas out of a 558 00:35:31,480 --> 00:35:35,320 Speaker 1: person with depression and out of a person with media 559 00:35:35,920 --> 00:35:36,399 Speaker 1: and so on. 560 00:35:36,600 --> 00:35:41,760 Speaker 2: So here's the weird thing about AI as a studies 561 00:35:41,840 --> 00:35:44,200 Speaker 2: as a as a as a research area, which is 562 00:35:44,239 --> 00:35:49,000 Speaker 2: that it is one of those things that we can 563 00:35:49,080 --> 00:35:53,719 Speaker 2: only discover or learn by doing. We're at the point 564 00:35:53,719 --> 00:35:57,319 Speaker 2: where we can't think about these and have advances just 565 00:35:57,360 --> 00:36:01,520 Speaker 2: by thinking about things anymore. So we actually have to 566 00:36:02,320 --> 00:36:05,880 Speaker 2: do all these things, try all these things, make the mistakes, 567 00:36:06,040 --> 00:36:07,719 Speaker 2: and that's the only way we're going to learn about it. 568 00:36:08,160 --> 00:36:10,319 Speaker 2: We are at the limits of how far we can 569 00:36:10,320 --> 00:36:13,839 Speaker 2: get just by thinking about these things. Part of that is, 570 00:36:13,920 --> 00:36:17,640 Speaker 2: and let me also to say is that I think 571 00:36:18,480 --> 00:36:25,319 Speaker 2: we as a society over estimate the value of intelligence. 572 00:36:26,239 --> 00:36:31,520 Speaker 2: I think IQ is just one component of what makes 573 00:36:31,560 --> 00:36:35,720 Speaker 2: a successful human I think intelligence is only one component 574 00:36:35,760 --> 00:36:41,160 Speaker 2: we'll make successful civilization. You need lots of other qualities. 575 00:36:41,480 --> 00:36:44,879 Speaker 2: It's not the smartest person in the room who necessarily 576 00:36:45,280 --> 00:36:47,320 Speaker 2: is the one who's going to accomplish what needs to 577 00:36:47,360 --> 00:36:51,120 Speaker 2: be done. And so right now, a lot of middle 578 00:36:51,160 --> 00:36:54,920 Speaker 2: aged guys who like to think will tell you that 579 00:36:55,000 --> 00:36:58,239 Speaker 2: thinking is the most important thing in the world and 580 00:36:58,280 --> 00:37:01,560 Speaker 2: that if you have really intelligence, that's all that matters. 581 00:37:02,280 --> 00:37:05,719 Speaker 2: And so my little joke is, you know, but Einstein 582 00:37:05,760 --> 00:37:09,440 Speaker 2: and a tiger in a cage who lives, it's not 583 00:37:09,480 --> 00:37:12,120 Speaker 2: the smartest one. You need other qualities. 584 00:37:13,840 --> 00:37:16,279 Speaker 1: Give me an example of other qualities that you're thinking about. 585 00:37:16,560 --> 00:37:26,200 Speaker 2: Determination, perseverance, ability to cooperate with other, cooperation, collaboration, empathy, 586 00:37:27,000 --> 00:37:31,480 Speaker 2: There's so many other things that are necessary to actually 587 00:37:32,680 --> 00:37:39,040 Speaker 2: make change. Happen in the world that those are things 588 00:37:39,520 --> 00:37:42,640 Speaker 2: that we were also, you know, as we generate these 589 00:37:42,680 --> 00:37:46,400 Speaker 2: agents and other beings and other kinds of intelligence, we 590 00:37:46,440 --> 00:37:51,879 Speaker 2: want to just keep in mind that IQ is overrated 591 00:37:52,239 --> 00:37:54,960 Speaker 2: by us, and you need other qualities, and so as 592 00:37:55,000 --> 00:37:57,759 Speaker 2: we make these machines, these other qualities will often be 593 00:37:57,800 --> 00:38:00,720 Speaker 2: more important. It's kind of like, you know, pixel peeping. 594 00:38:00,760 --> 00:38:03,640 Speaker 2: It's like there was a moment where people are saying resolution, 595 00:38:04,040 --> 00:38:05,719 Speaker 2: the number of pixels and a camera that was the 596 00:38:05,719 --> 00:38:09,040 Speaker 2: most important thing. There's just so many other things that 597 00:38:09,120 --> 00:38:13,440 Speaker 2: are important in a great photograph other than this resolution. Okay, 598 00:38:13,760 --> 00:38:14,800 Speaker 2: other than the IQ. 599 00:38:15,320 --> 00:38:16,439 Speaker 1: What else do you have on your list? 600 00:38:16,840 --> 00:38:17,560 Speaker 3: Two other things? 601 00:38:17,640 --> 00:38:22,080 Speaker 2: One is I mentioned the necessity of how the brain 602 00:38:22,160 --> 00:38:25,160 Speaker 2: is important to the mind, and so I think there 603 00:38:25,200 --> 00:38:26,719 Speaker 2: will be attempts. 604 00:38:27,680 --> 00:38:30,200 Speaker 3: To use. 605 00:38:31,480 --> 00:38:38,720 Speaker 2: Tissue to make ais, to make some kind of biological computer, 606 00:38:39,800 --> 00:38:46,480 Speaker 2: to use neurons, wet neurons, to actually make minds, and 607 00:38:46,520 --> 00:38:52,799 Speaker 2: those minds will also have qualities, including the usual forebos 608 00:38:52,840 --> 00:38:57,359 Speaker 2: of sickness and illness and other aspects that any kind 609 00:38:57,400 --> 00:38:58,239 Speaker 2: of a wet. 610 00:38:59,480 --> 00:39:01,080 Speaker 3: Biological being would. 611 00:39:01,640 --> 00:39:04,359 Speaker 2: But that means that there is the prospect of kind 612 00:39:04,360 --> 00:39:09,440 Speaker 2: of cyborg like things as well where where we we 613 00:39:09,480 --> 00:39:11,320 Speaker 2: could have things in our own brains or next to 614 00:39:11,400 --> 00:39:14,520 Speaker 2: our brains, or along with our brains. And so I 615 00:39:14,560 --> 00:39:17,040 Speaker 2: don't know if I could describe what the minds would be, 616 00:39:17,080 --> 00:39:21,680 Speaker 2: but I'm just suggesting maybe another route to making a 617 00:39:21,680 --> 00:39:25,360 Speaker 2: different kind of mind is one that we not just 618 00:39:25,480 --> 00:39:29,000 Speaker 2: have the AI and silicon, but we have cyb actual cyborgs, 619 00:39:29,600 --> 00:39:32,600 Speaker 2: or trying to make a grill or a monkey mind 620 00:39:33,320 --> 00:39:35,840 Speaker 2: smarter in a different way. So we have something that 621 00:39:35,880 --> 00:39:39,560 Speaker 2: you're kind of genetically altering or ampling up, and you 622 00:39:39,640 --> 00:39:43,720 Speaker 2: have a biological brain that's doing a different kind of competition. 623 00:39:44,280 --> 00:39:46,400 Speaker 1: So can I can I just jump in with my 624 00:39:48,560 --> 00:39:52,240 Speaker 1: fantasy of what that could look like, which is instead 625 00:39:52,280 --> 00:39:55,160 Speaker 1: of having machinery that plugs in because that's very tough, 626 00:39:55,200 --> 00:39:57,719 Speaker 1: you need to plug in electroc Yeah, there's all kinds 627 00:39:57,760 --> 00:40:01,040 Speaker 1: of infection prompts. You know what if in one hundred 628 00:40:01,160 --> 00:40:04,160 Speaker 1: years you could actually grow more neurons in there, and 629 00:40:04,239 --> 00:40:07,839 Speaker 1: maybe I mean this is bizarre, but maybe you have 630 00:40:08,200 --> 00:40:10,040 Speaker 1: you store them on the outside of your skull and 631 00:40:10,040 --> 00:40:12,120 Speaker 1: you put sort of another skull on top of that. 632 00:40:12,160 --> 00:40:14,560 Speaker 1: But what you have is just more brain tissue twice 633 00:40:14,760 --> 00:40:16,880 Speaker 1: twice as much brain tissue as you have. I know 634 00:40:16,960 --> 00:40:19,719 Speaker 1: this sounds creepy and insane, but yeah, maybe if a 635 00:40:19,760 --> 00:40:22,759 Speaker 1: podcast listener is listening to this in two hundred years, 636 00:40:22,760 --> 00:40:25,080 Speaker 1: they'll say, yeah, of course we got that already. But 637 00:40:25,480 --> 00:40:27,720 Speaker 1: your question is what would the what would the mind 638 00:40:27,760 --> 00:40:31,239 Speaker 1: be like? What would you what would your daily experience 639 00:40:31,360 --> 00:40:34,120 Speaker 1: be if you had a core text that was twice 640 00:40:34,160 --> 00:40:35,560 Speaker 1: as large as what you have now. 641 00:40:35,960 --> 00:40:38,520 Speaker 2: Right, or even things like if you modified in some 642 00:40:38,560 --> 00:40:42,439 Speaker 2: way so we didn't forget as much, you know, biologically 643 00:40:42,560 --> 00:40:45,360 Speaker 2: so so so. So that's one thing. And the last 644 00:40:46,040 --> 00:40:49,279 Speaker 2: idea in terms of the possible minds I just want 645 00:40:49,320 --> 00:40:52,920 Speaker 2: to mention is quantum quantum computing. You know, there's a 646 00:40:52,960 --> 00:40:54,560 Speaker 2: lot of people who believe that kind of that's the 647 00:40:54,600 --> 00:40:57,719 Speaker 2: next thresholding and we get quantum and then it's like, 648 00:40:58,120 --> 00:41:01,760 Speaker 2: you know, it's like a singularity. We're into another realm entirely. 649 00:41:03,719 --> 00:41:10,000 Speaker 2: I actually have a heretical stance where I think that 650 00:41:10,520 --> 00:41:14,080 Speaker 2: quantum computer is inherently not going to be good for computation. 651 00:41:15,360 --> 00:41:17,000 Speaker 1: Why it doesn't seem. 652 00:41:16,719 --> 00:41:20,000 Speaker 2: To want to do computation, That's how I would put it. 653 00:41:20,000 --> 00:41:25,719 Speaker 2: It doesn't it doesn't want to do computation. But I 654 00:41:25,760 --> 00:41:29,200 Speaker 2: think it's going to be among the most amazing technologies 655 00:41:29,239 --> 00:41:33,520 Speaker 2: because it's going to do other things in the quantum 656 00:41:33,560 --> 00:41:38,600 Speaker 2: realm that we can't even imagine, but not computation. So 657 00:41:38,640 --> 00:41:42,720 Speaker 2: I think computation is it's sort of it doesn't really want. 658 00:41:42,560 --> 00:41:44,600 Speaker 3: To do competition. It wants to do other things. 659 00:41:45,080 --> 00:41:48,480 Speaker 2: So it could have like a very different way of 660 00:41:48,520 --> 00:41:55,080 Speaker 2: thinking that is not computationally based as our ais are, 661 00:41:55,840 --> 00:41:58,960 Speaker 2: and it does something weirdly different that we don't even 662 00:41:59,000 --> 00:42:01,120 Speaker 2: have words for it. I don't even know how to 663 00:42:01,160 --> 00:42:04,880 Speaker 2: describe that, other than to say I think there can 664 00:42:04,920 --> 00:42:10,040 Speaker 2: be possible minds with with quantum computing or quantum but 665 00:42:10,080 --> 00:42:12,920 Speaker 2: they aren't going to be computational based. 666 00:42:13,440 --> 00:42:14,760 Speaker 3: That's just a hypothesis. 667 00:42:15,719 --> 00:42:17,920 Speaker 1: And that goes along with your hypothesis that we're going 668 00:42:17,960 --> 00:42:20,640 Speaker 1: to have to try lots of things out in order 669 00:42:20,680 --> 00:42:23,359 Speaker 1: to gather the data to make the theories about things. 670 00:42:23,400 --> 00:42:26,280 Speaker 1: There's so much that's beyond what we can see right now. 671 00:42:26,440 --> 00:42:28,080 Speaker 1: And this is, by the way, of course, a general 672 00:42:28,120 --> 00:42:31,360 Speaker 1: thing in science, which is that sometimes we're at a 673 00:42:31,400 --> 00:42:34,560 Speaker 1: moment where you can make a theoretical leap and say, 674 00:42:34,560 --> 00:42:36,520 Speaker 1: here's what I think the periodic table would look like, 675 00:42:36,560 --> 00:42:39,480 Speaker 1: and other times you just need to gather the data 676 00:42:39,560 --> 00:42:41,319 Speaker 1: for a long time before you can get there. 677 00:42:41,640 --> 00:42:44,440 Speaker 2: Yeah, and I think we're in this realm of what 678 00:42:44,520 --> 00:42:48,399 Speaker 2: I call the third culture. The first two cultures, being 679 00:42:49,960 --> 00:42:52,759 Speaker 2: the humanities, was kind of one culture. Then there was 680 00:42:52,840 --> 00:42:57,880 Speaker 2: the science that was Cpiece snows observation that we have 681 00:42:57,960 --> 00:43:01,960 Speaker 2: two kinds of cultures and can you just double clicks? 682 00:43:01,680 --> 00:43:05,360 Speaker 2: So yeah, CPS I had this idea there there's two cultures. 683 00:43:05,360 --> 00:43:09,600 Speaker 2: There's the humanists and the humanities the arts and what 684 00:43:09,640 --> 00:43:12,560 Speaker 2: they did was they kind of explored the human situation 685 00:43:12,760 --> 00:43:18,560 Speaker 2: through creativity introspection, by reflecting kind of the human condition 686 00:43:19,000 --> 00:43:23,439 Speaker 2: and something that people made. Then there was the scientists 687 00:43:23,800 --> 00:43:27,880 Speaker 2: who explored the human addition by probes, by doing experiments, 688 00:43:28,440 --> 00:43:32,359 Speaker 2: by testing reality. I think we're in the third We 689 00:43:32,400 --> 00:43:35,440 Speaker 2: have a third culture we've made in the last thirty 690 00:43:35,480 --> 00:43:38,200 Speaker 2: or fifty years, which is called what I call the 691 00:43:38,280 --> 00:43:42,200 Speaker 2: nerd culture. The third culture is this idea that we 692 00:43:42,280 --> 00:43:45,640 Speaker 2: explore the human condition by making alternatives to it, by 693 00:43:45,640 --> 00:43:50,160 Speaker 2: making synthetic versions of it. We explore life by trying 694 00:43:50,200 --> 00:43:53,960 Speaker 2: to make artificial life. We explore democracy by trying to 695 00:43:53,960 --> 00:44:01,279 Speaker 2: do simulated worlds. We explore intelligence by trying to make intelligence, 696 00:44:02,080 --> 00:44:05,840 Speaker 2: and I think we're going to actually learn more by 697 00:44:06,800 --> 00:44:10,320 Speaker 2: making intelligence that don't work. We'll learn more about the 698 00:44:10,400 --> 00:44:15,440 Speaker 2: human mind than one hundred years of neurobiology will teach us. 699 00:44:20,040 --> 00:44:23,120 Speaker 1: That was my interview with Kevin Kelly, thinker and technologist. 700 00:44:23,600 --> 00:44:26,839 Speaker 1: I love this approach to thinking about different kinds of 701 00:44:26,880 --> 00:44:31,640 Speaker 1: intelligence because when we shine a flashlight around the possibility 702 00:44:31,680 --> 00:44:36,560 Speaker 1: space and illuminate what things could look like, it clarifies 703 00:44:36,600 --> 00:44:39,640 Speaker 1: our view about the things right in front of us, 704 00:44:40,080 --> 00:44:42,840 Speaker 1: and this is the key to understanding anything in science. 705 00:44:43,120 --> 00:44:48,080 Speaker 1: Otherwise we are like the proverbial fish in water trying 706 00:44:48,120 --> 00:44:52,279 Speaker 1: to describe water. We've never seen anything but water, and 707 00:44:52,320 --> 00:44:56,160 Speaker 1: therefore we don't have any way to describe it because 708 00:44:56,200 --> 00:44:58,760 Speaker 1: we have no way to distinguish it from anything else. 709 00:44:59,280 --> 00:45:04,920 Speaker 1: But happily, our species makes scientific progress because Homo sapiens 710 00:45:04,960 --> 00:45:09,239 Speaker 1: developed an enormous prefrontal cortex, and this is fundamentally the 711 00:45:09,280 --> 00:45:12,520 Speaker 1: brain structure that allows us to think about the what 712 00:45:12,920 --> 00:45:17,480 Speaker 1: ifs that are beyond our daily experience. What ifs are 713 00:45:17,520 --> 00:45:23,080 Speaker 1: the thing that drive our understanding of everything. When Einstein 714 00:45:23,160 --> 00:45:25,120 Speaker 1: thought about what it would be like to ride on 715 00:45:25,239 --> 00:45:27,880 Speaker 1: top of a beam of light, that opened up a 716 00:45:27,920 --> 00:45:30,719 Speaker 1: new world for him that led to the special theory 717 00:45:30,760 --> 00:45:35,200 Speaker 1: of relativity. When Charles Darwin looked around and thought, what 718 00:45:35,360 --> 00:45:39,680 Speaker 1: species aren't here now but once might have existed? That 719 00:45:39,800 --> 00:45:43,680 Speaker 1: ushered him down the path of understanding evolution by natural selection. 720 00:45:44,440 --> 00:45:47,239 Speaker 1: And so it will have to be with our understanding 721 00:45:47,560 --> 00:45:52,680 Speaker 1: of what intelligence is. We are the fish stuck in 722 00:45:52,719 --> 00:45:55,840 Speaker 1: the water, with nothing to compare water against and therefore 723 00:45:55,880 --> 00:45:59,040 Speaker 1: no way to make distinctions. That as we move forward, 724 00:45:59,600 --> 00:46:05,640 Speaker 1: will increasingly build and study many different flavors of intelligence, 725 00:46:06,239 --> 00:46:10,880 Speaker 1: and those other minds will be like things other than water. 726 00:46:11,239 --> 00:46:14,279 Speaker 1: We'll see a bubble rise up past us, and we'll 727 00:46:14,320 --> 00:46:17,680 Speaker 1: think what is that. We'll swim near an island and 728 00:46:17,719 --> 00:46:21,120 Speaker 1: we'll see dirt and we'll think what is that. We'll 729 00:46:21,239 --> 00:46:24,040 Speaker 1: dive down and circle a thermal vent and we'll think 730 00:46:24,080 --> 00:46:28,239 Speaker 1: what is that? And with each new discovery we'll make 731 00:46:28,320 --> 00:46:32,799 Speaker 1: new distinctions and get a better understanding of water. It 732 00:46:32,840 --> 00:46:36,880 Speaker 1: will allow us for the first time to see what 733 00:46:37,040 --> 00:46:44,160 Speaker 1: we've been swimming in the whole time. Go to eagleman 734 00:46:44,200 --> 00:46:47,120 Speaker 1: dot com slash podcasts for more information and to find 735 00:46:47,160 --> 00:46:51,400 Speaker 1: further reading. Send me an email at podcasts at eagleman 736 00:46:51,440 --> 00:46:54,560 Speaker 1: dot com. With questions or discussion, and check out and 737 00:46:54,560 --> 00:46:58,359 Speaker 1: subscribe to Inner Cosmos on YouTube for videos of each 738 00:46:58,400 --> 00:47:02,919 Speaker 1: episode and to leave comments. Until next time, I'm David 739 00:47:02,920 --> 00:47:14,640 Speaker 1: Eagleman and this is in Earth Cosmos