[00:25.960 --> 00:29.620] I think I can do this, but I might... [00:30.000 --> 00:31.040] I don't have the USB. [00:32.200 --> 00:32.860] No, that's fine. [00:34.080 --> 00:35.300] Not that I can ask you more. [00:35.340 --> 00:36.280] I can do it. [00:36.440 --> 00:37.440] This will work as well. [00:37.920 --> 00:39.280] Just let me know if you can see it. [00:39.980 --> 00:41.140] I mean, I can see it. [00:41.760 --> 00:43.400] Do you want me to put it there, right? [00:43.760 --> 00:45.680] Yeah, yeah, no, I just mean like... [00:45.680 --> 00:47.400] It's broken, I don't... I just don't know. [00:49.100 --> 00:50.040] Yeah, it should be. [00:51.860 --> 00:52.900] Are you getting signal? [00:54.520 --> 00:55.500] No, no, no. [00:55.860 --> 00:56.960] Not you, I'm sorry. [00:57.620 --> 00:58.340] AB, you got it. [00:58.400 --> 00:59.220] Yeah, yeah, yeah, yeah, perfect. [00:59.560 --> 01:00.320] Yeah, perfect. [01:00.700 --> 01:00.980] All right. [01:01.160 --> 01:01.580] That's great. [01:01.660 --> 01:01.860] Awesome. [01:02.080 --> 01:02.300] Awesome. [01:02.840 --> 01:03.060] Cool. [01:04.400 --> 01:05.500] We'll start in a few minutes. [02:09.350 --> 02:10.030] Hi, everyone. [02:10.710 --> 02:11.570] How's everyone doing? [02:11.990 --> 02:13.150] Are you having a good hope? [02:13.910 --> 02:14.170] Yeah. [02:14.630 --> 02:15.190] Come on. [02:15.410 --> 02:16.550] A little more enthusiasm. [02:16.830 --> 02:17.750] Are you having a good hope? [02:19.250 --> 02:19.650] Yeah. [02:20.210 --> 02:21.350] Do you have any hope? [02:23.050 --> 02:24.390] Good to see you all here. [02:24.390 --> 02:28.090] And we're going to start the next talk. [02:28.250 --> 02:30.390] But before we do that, I just want to do... [02:30.930 --> 02:32.630] Remember, everybody, please stay hydrated. [02:32.630 --> 02:34.470] It's very, very warm outside. [02:34.950 --> 02:36.190] And we don't want to... [02:36.190 --> 02:37.530] We don't want anyone overheating. [02:38.330 --> 02:38.890] So... [02:39.750 --> 02:51.710] The next talk we're going to have is Hacking the Anthropocene, Life, Biological Complexity, and Freedom, by Abhi Hassan and Isaac Overcast. [02:51.710 --> 02:54.850] So, please, a round of applause. [02:59.440 --> 03:00.180] All right. [03:00.280 --> 03:00.840] Hi, everybody. [03:01.980 --> 03:02.580] Welcome. [03:03.880 --> 03:07.340] So, I guess, quick, I'll just introduce myself. [03:07.540 --> 03:08.660] I'm Abhi Hassan. [03:08.660 --> 03:10.000] And I am... [03:10.660 --> 03:12.760] I guess not quite recovering. [03:12.760 --> 03:13.580] I'm a lawyer. [03:14.980 --> 03:15.940] By trade. [03:17.900 --> 03:26.220] And at least a hobbyist, political philosopher and organizer, activist type. [03:26.860 --> 03:31.960] And so, I've spent a lot of time kind of working with social movements and working with... [03:33.360 --> 03:35.540] Like, working with hacker communities also. [03:36.700 --> 03:37.300] And... [03:37.300 --> 03:39.680] But I also kind of... [03:39.680 --> 03:43.120] You know, Isaac and I actually went to college together and studied computer science. [03:43.360 --> 03:49.100] And so, I've always had a strong tilt towards computational way of thinking. [03:49.380 --> 03:54.020] And so, this is kind of a synthesis of a lot of things. [03:54.020 --> 04:00.320] But, like, primarily focused on this problem of the crisis that is our modern world. [04:00.680 --> 04:02.380] And so, I'll let Isaac introduce himself. [04:02.720 --> 04:03.600] My name is Isaac Overcast. [04:03.800 --> 04:05.020] I'm a biologist. [04:05.700 --> 04:07.140] I'm a computational biologist. [04:08.780 --> 04:18.180] You know, specifically, I focus on kind of trying to understand how biodiversity works from a, you know, complexity science or complex systems perspective. [04:20.040 --> 04:22.180] But, you know... [04:24.620 --> 04:27.460] So, my head is kind of in the more of the biology... [04:33.800 --> 04:36.560] My head's more in the biology and so... [04:36.560 --> 04:53.340] But, Abhi's always kind of drawing me back into applying the tools that I use to study, you know, nature or biodiversity to think more about how we can, you know, solve social problems or, you know, organizational problems or, you know... [04:53.340 --> 04:54.420] Political problems. [04:54.480 --> 04:55.640] Political problems, exactly. [04:59.560 --> 05:02.660] So, to start off, kind of, we're going to, you know... [05:03.040 --> 05:04.800] We're calling this hacking the Anthropocene. [05:04.880 --> 05:06.480] So, what do we mean by hacking, right? [05:07.340 --> 05:12.040] I think there's two kind of ideas of hacking expressed here. [05:12.040 --> 05:14.940] There's this kind of... [05:16.560 --> 05:18.400] This kind of old-school... [05:18.400 --> 05:22.180] If people are familiar with the book by Stephen Levy... [05:22.180 --> 05:23.340] This old... [05:23.340 --> 05:27.980] There's an old-school kind of, like, coming out of the MIT hacker scene. [05:28.080 --> 05:29.220] The origins of computing. [05:29.540 --> 05:30.920] This kind of... [05:30.920 --> 05:31.780] This... [05:31.780 --> 05:34.260] This kind of engineering-driven, but, you know... [05:34.760 --> 05:35.240] Just... [05:35.740 --> 05:37.980] The old-school notion of hacking, right? [05:38.680 --> 05:42.200] And I'm going to be working with these kind of two concepts from... [05:42.200 --> 05:43.800] From this Levy book and from... [05:43.800 --> 05:46.360] The Kinsey-Wark book... [05:46.360 --> 05:49.020] A Hacker Manifesto that is... [05:49.020 --> 05:49.980] Trying to abstract and... [05:50.760 --> 05:54.260] Think big about hacking and kind of... [05:54.260 --> 05:57.280] You know, this idea of bringing new things into the world, right? [05:57.280 --> 06:00.440] Kind of abstracting away from a purely computer... [06:00.440 --> 06:01.360] Computer... [06:01.360 --> 06:03.100] Computer geek world to, like... [06:03.100 --> 06:04.120] The world, right? [06:04.720 --> 06:05.320] But... [06:05.320 --> 06:07.740] Trying to also keep some of that essence of pure... [06:07.740 --> 06:08.640] Pure hacking. [06:09.740 --> 06:10.800] And so... [06:10.800 --> 06:13.340] What do we mean by the Anthropocene? [06:14.020 --> 06:15.120] I think... [06:15.120 --> 06:16.600] The Anthropocene is... [06:16.980 --> 06:18.340] A controversial term... [06:19.000 --> 06:19.860] In some sectors. [06:20.380 --> 06:20.480] I... [06:20.480 --> 06:20.820] I... [06:20.820 --> 06:22.380] Kind of used it because I think it's the most... [06:23.440 --> 06:23.900] Uh... [06:23.900 --> 06:25.060] Recognizable term. [06:25.580 --> 06:27.520] Yeah, it's the most accessible, the most recognizable. [06:27.720 --> 06:28.240] I think... [06:28.240 --> 06:29.680] All these other terms... [06:29.680 --> 06:29.860] Um... [06:29.860 --> 06:31.180] In parentheses... [06:31.180 --> 06:31.980] Are useful. [06:32.200 --> 06:34.780] It's kind of this idea of... [06:34.780 --> 06:35.480] Um... [06:35.480 --> 06:36.240] You know... [06:36.240 --> 06:36.600] It's... [06:36.600 --> 06:37.080] It's... [06:37.080 --> 06:39.340] It's recognizing human... [06:41.700 --> 06:42.340] Industrial... [06:42.340 --> 06:42.940] You know... [06:42.940 --> 06:44.920] Some might say capitalist... [06:46.220 --> 06:46.640] Technological... [06:47.200 --> 06:47.620] Um... [06:47.620 --> 06:47.900] You know... [06:47.900 --> 06:49.970] This idea of Plantationocene is kind of a... [06:50.500 --> 06:51.560] The idea of... [06:51.560 --> 06:52.940] Commercial agricultural... [06:54.020 --> 06:55.240] Post-colonial concept. [06:55.940 --> 06:58.300] Another one that I like that I'll probably use is this... [06:58.300 --> 06:59.340] The end of the world, right? [06:59.440 --> 07:00.920] This is coming from... [07:00.920 --> 07:01.130] Uh... [07:01.460 --> 07:01.940] Timothy Morton... [07:02.900 --> 07:03.400] And this... [07:03.400 --> 07:03.760] You know... [07:03.760 --> 07:05.220] And I think it's useful because it... [07:06.180 --> 07:06.600] It's... [07:07.180 --> 07:07.600] It... [07:07.600 --> 07:07.940] It... [07:07.940 --> 07:09.320] Kind of captures... [07:09.840 --> 07:10.260] Um... [07:10.260 --> 07:11.460] A lot of these ideas of... [07:11.460 --> 07:12.520] Of system change, right? [07:12.520 --> 07:13.620] That one world... [07:13.620 --> 07:14.480] Is ending... [07:14.480 --> 07:15.920] Or multiple worlds ending... [07:15.920 --> 07:16.340] Um... [07:16.340 --> 07:17.280] And the question of... [07:17.280 --> 07:17.960] What is beginning? [07:19.040 --> 07:19.640] Um... [07:19.640 --> 07:20.420] And so... [07:20.420 --> 07:22.460] When we're thinking about... [07:23.360 --> 07:23.960] Um... [07:23.960 --> 07:25.520] The crisis... [07:25.520 --> 07:26.640] Uh... [07:26.640 --> 07:27.920] It's kind of like we're in... [07:27.920 --> 07:29.740] We're in this age of collapse, right? [07:30.180 --> 07:31.040] That... [07:31.040 --> 07:32.800] And whether something is a crisis... [07:32.800 --> 07:34.560] Waiting for something else to be born... [07:34.560 --> 07:34.900] Or... [07:34.900 --> 07:36.520] A collapse into something... [07:37.500 --> 07:37.660] Uh... [07:38.320 --> 07:38.560] Simpler... [07:38.560 --> 07:39.200] Or... [07:39.200 --> 07:40.300] Less complex... [07:40.300 --> 07:41.820] Is kind of... [07:41.820 --> 07:43.280] An unknowable question, right? [07:43.640 --> 07:44.120] But... [07:44.340 --> 07:45.040] The... [07:45.040 --> 07:47.220] The perspective we're gonna take is kind of... [07:47.220 --> 07:49.340] How can we look at it from a computational perspective? [07:49.460 --> 07:51.880] How can we look at crisis and collapse... [07:51.880 --> 07:52.560] As... [07:52.560 --> 07:52.840] Uh... [07:52.840 --> 07:54.060] Computational thinkers... [07:54.060 --> 07:54.660] As hackers? [07:55.280 --> 07:55.760] Um... [07:55.760 --> 07:56.720] And so... [07:56.720 --> 07:57.160] If we... [07:57.160 --> 07:57.380] You know... [07:57.380 --> 07:58.500] These kind of... [07:58.500 --> 07:58.860] That... [07:58.860 --> 07:59.060] And... [07:59.060 --> 07:59.720] You know... [07:59.720 --> 08:04.420] I think it's important also to not think about it as purely just the idea of... [08:05.320 --> 08:05.800] Carbon... [08:05.800 --> 08:07.100] Or CO2 emissions. [08:07.340 --> 08:08.060] That it's also... [08:08.800 --> 08:10.060] What is being lost... [08:11.440 --> 08:11.920] Um... [08:11.920 --> 08:13.220] Can be looked at from a... [08:13.220 --> 08:14.240] Kind of... [08:14.240 --> 08:15.900] From a hacking perspective as well. [08:18.080 --> 08:18.560] Um... [08:18.560 --> 08:19.360] And so... [08:19.360 --> 08:20.260] I think it's also... [08:21.220 --> 08:22.160] Just to kind of... [08:22.160 --> 08:24.360] This is all just priming... [08:25.660 --> 08:26.140] Um... [08:27.160 --> 08:28.660] Kind of getting us thinking, right? [08:29.480 --> 08:30.000] Um... [08:30.000 --> 08:30.220] This... [08:30.220 --> 08:30.460] This... [08:30.460 --> 08:31.820] This quote is kind of... [08:32.460 --> 08:34.260] Looking at it from a post-colonial perspective. [08:34.680 --> 08:35.200] And... [08:35.780 --> 08:36.300] Um... [08:36.300 --> 08:39.220] And that's another place where this idea of the end of the world comes in, right? [08:39.300 --> 08:40.440] Because I think... [08:40.440 --> 08:40.940] The... [08:40.940 --> 08:42.560] The societies that we... [08:42.560 --> 08:43.660] In the kind of rich... [08:44.200 --> 08:44.580] Um... [08:44.580 --> 08:45.580] Global North... [08:45.580 --> 08:45.840] Uh... [08:46.440 --> 08:46.700] Western... [08:46.700 --> 08:48.220] Industrial world... [08:48.220 --> 08:48.640] Um... [08:48.640 --> 08:49.980] Is built on... [08:49.980 --> 08:51.720] The end of other worlds. [08:52.860 --> 08:53.380] Um... [08:53.380 --> 08:54.380] And... [08:55.500 --> 08:56.020] There's... [08:56.880 --> 08:57.400] Um... [08:57.400 --> 08:58.440] Even from a... [08:58.440 --> 09:00.200] Even from a computational perspective. [09:00.620 --> 09:01.220] Or... [09:01.220 --> 09:02.300] We can think of... [09:02.300 --> 09:03.300] Of loss there. [09:03.520 --> 09:06.360] And what problems were solved that... [09:06.360 --> 09:08.480] That we no longer have access to, right? [09:09.200 --> 09:09.800] Um... [09:09.800 --> 09:10.400] And so... [09:11.100 --> 09:11.740] You know... [09:11.740 --> 09:14.400] We're kind of looking at this idea of collapse... [09:15.100 --> 09:17.160] The creation of complexity as... [09:17.160 --> 09:17.660] As... [09:18.260 --> 09:19.060] Essential to life. [09:19.600 --> 09:20.120] And... [09:20.120 --> 09:23.280] The collapse or loss of complexity as a form of death. [09:23.280 --> 09:23.760] Right. [09:24.500 --> 09:25.040] Okay. [09:26.980 --> 09:27.780] Um... [09:27.780 --> 09:28.760] So... [09:28.760 --> 09:30.640] You know... [09:31.200 --> 09:32.380] We have... [09:32.380 --> 09:33.820] If we're looking at these... [09:33.820 --> 09:35.520] These kind of charts... [09:35.520 --> 09:36.620] Where we see... [09:36.620 --> 09:37.980] One of these... [09:37.980 --> 09:39.500] We have over here... [09:39.880 --> 09:40.780] This kind of... [09:40.780 --> 09:43.320] GDP growth or Moore's Law... [09:43.320 --> 09:43.620] Right? [09:44.000 --> 09:47.520] That we might think of Moore's Law as this kind of... [09:47.520 --> 09:48.700] Increasing complexity. [09:48.700 --> 09:49.400] And it is... [09:49.400 --> 09:49.900] In a sense... [09:49.900 --> 09:51.180] Of our society's... [09:51.450 --> 09:52.820] More transistors in... [09:52.820 --> 09:53.660] In less space. [09:54.540 --> 09:54.880] But... [09:54.880 --> 09:55.910] It's kind of being... [09:56.800 --> 09:58.720] Juxtaposed here with... [09:58.720 --> 09:59.020] Like... [09:59.020 --> 10:02.020] Those actual transistors are dug out of the actual earth. [10:02.380 --> 10:03.080] And... [10:03.080 --> 10:05.100] Are actually destroying... [10:05.100 --> 10:07.900] An entire realm of actual... [10:07.900 --> 10:08.680] Computation. [10:09.000 --> 10:09.280] Um... [10:09.280 --> 10:10.640] And actual... [10:10.640 --> 10:11.120] Um... [10:11.120 --> 10:12.180] Loss of... [10:12.570 --> 10:13.420] Of possibility. [10:13.900 --> 10:14.560] Um... [10:14.560 --> 10:15.900] And that's kind of what that... [10:15.900 --> 10:17.200] Top right chart is... [10:17.200 --> 10:18.020] It's kind of a... [10:18.620 --> 10:20.460] It's a living planet index. [10:20.700 --> 10:21.880] Which is kind of an index of... [10:21.880 --> 10:22.780] Many, many species. [10:23.140 --> 10:23.380] And... [10:23.380 --> 10:23.920] And... [10:23.920 --> 10:24.060] You know... [10:24.060 --> 10:25.740] These things are... [10:25.740 --> 10:26.380] At... [10:26.380 --> 10:28.260] Coming to a head... [10:28.260 --> 10:29.060] Rapidly. [10:29.180 --> 10:29.280] Right? [10:30.300 --> 10:30.740] So... [10:33.520 --> 10:33.960] So... [10:33.960 --> 10:35.200] The question is kind of... [10:36.460 --> 10:39.040] This is the big question that we're kind of playing with here. [10:40.020 --> 10:40.460] Um... [10:40.460 --> 10:41.740] Is the end of the world hackable? [10:43.860 --> 10:44.300] And... [10:44.960 --> 10:45.400] Um... [10:45.400 --> 10:47.180] The way we're gonna look at it is... [10:47.180 --> 10:50.220] Through looking at what living systems are. [10:51.420 --> 10:52.020] And... [10:52.020 --> 10:54.360] What it means to be alive, kind of. [10:54.880 --> 10:55.480] And... [10:55.480 --> 10:57.360] What are some of the... [10:58.440 --> 10:59.040] Conceptual... [10:59.040 --> 10:59.340] Tools... [10:59.880 --> 11:01.140] Or what we'll call hacks... [11:01.140 --> 11:02.300] That life has created. [11:03.200 --> 11:03.800] And... [11:03.800 --> 11:04.580] Um... [11:04.580 --> 11:05.080] So... [11:05.080 --> 11:05.360] We're gonna... [11:05.360 --> 11:05.700] So... [11:05.700 --> 11:07.260] So the idea is like... [11:07.260 --> 11:07.880] Uh... [11:07.880 --> 11:08.220] You know... [11:08.220 --> 11:09.140] We know that bio... [11:09.900 --> 11:13.560] Biological life is capable of developing complexity and solving problems. [11:14.900 --> 11:15.380] Uh... [11:15.380 --> 11:16.000] And so... [11:16.000 --> 11:16.960] What we want to do is... [11:16.960 --> 11:18.560] We want to think about... [11:18.560 --> 11:18.920] You know... [11:19.520 --> 11:20.000] How... [11:20.000 --> 11:20.860] How... [11:20.860 --> 11:21.300] Does... [11:21.300 --> 11:23.200] Biological life solve problems? [11:23.480 --> 11:24.920] What are some of the hacks that... [11:24.920 --> 11:27.260] That life uses in order to kind of like... [11:27.260 --> 11:29.180] Explore the space of possibility? [11:29.660 --> 11:31.100] And then we want to think about... [11:31.100 --> 11:31.820] How do we... [11:31.820 --> 11:33.400] How might we... [11:33.400 --> 11:36.380] Apply what we could learn from biology to... [11:36.380 --> 11:39.080] Social systems or political systems or organizations? [11:39.480 --> 11:39.540] Right? [11:40.480 --> 11:41.420] In order to kind of... [11:41.420 --> 11:41.740] Yeah... [11:41.740 --> 11:41.960] Like... [11:41.960 --> 11:43.640] Like Abi was saying in the beginning... [11:44.420 --> 11:44.900] Like... [11:45.480 --> 11:48.520] Approaching hacking is developing new things out of old. [11:48.660 --> 11:48.720] Right? [11:48.780 --> 11:51.000] So we have these ideas of... [11:51.000 --> 11:52.200] Kind of... [11:52.200 --> 11:54.840] Creating complexity and solving problems that are... [11:54.840 --> 11:55.460] As old... [11:55.460 --> 11:55.680] You know... [11:55.680 --> 11:56.860] More than three billion years old. [11:56.960 --> 11:58.620] What can we learn from... [11:58.620 --> 12:00.160] Three billion years of evolution? [12:06.360 --> 12:06.860] So... [12:09.720 --> 12:10.220] Yeah... [12:11.360 --> 12:11.860] So... [12:11.860 --> 12:13.120] We want to kind of start... [12:13.120 --> 12:14.090] In order to kind of... [12:15.660 --> 12:19.360] Frame this idea of thinking about how we might... [12:19.360 --> 12:20.020] Approach... [12:20.020 --> 12:20.580] You know... [12:20.580 --> 12:22.480] Hacking the Anthropocene... [12:22.950 --> 12:24.260] We'll start out by thinking about... [12:24.260 --> 12:24.840] What is life? [12:25.080 --> 12:25.840] And what is evolution? [12:26.140 --> 12:26.780] Like how... [12:26.780 --> 12:28.440] Why is there something instead of nothing? [12:28.760 --> 12:30.300] How does evolution solve problems? [12:30.400 --> 12:31.660] How can we think about this... [12:31.660 --> 12:33.800] In a computational perspective? [12:36.820 --> 12:37.340] So... [12:37.340 --> 12:37.960] So... [12:37.960 --> 12:39.440] In terms of what is life... [12:39.440 --> 12:40.040] We can... [12:40.040 --> 12:40.240] There... [12:40.240 --> 12:41.280] There's kind of... [12:42.400 --> 12:42.920] Two... [12:44.360 --> 12:45.400] Kind of... [12:45.400 --> 12:47.940] Lenses that we can use to think about... [12:47.940 --> 12:49.040] What is life? [12:49.180 --> 12:50.260] And one is a... [12:50.260 --> 12:51.900] Kind of information theory perspective... [12:52.540 --> 12:53.920] Where we can think of like... [12:53.920 --> 12:56.000] The complexity of molecules... [12:56.000 --> 12:56.400] As... [12:56.400 --> 12:56.960] You know... [12:56.960 --> 12:58.800] Things that are very, very... [12:58.800 --> 12:59.720] Simple... [12:59.720 --> 13:00.040] Like... [13:00.660 --> 13:01.500] Hydrogen atoms... [13:01.500 --> 13:02.100] Or water... [13:02.100 --> 13:02.840] You know... [13:02.840 --> 13:03.900] Molecules of water... [13:03.900 --> 13:04.720] Where there's just... [13:04.720 --> 13:05.160] An H... [13:06.540 --> 13:06.940] H... [13:06.940 --> 13:08.200] And two O's... [13:08.200 --> 13:08.340] Two... [13:08.340 --> 13:10.200] Two H's and an O... [13:10.200 --> 13:11.140] I'm not... [13:11.140 --> 13:11.860] I'm not a chemist... [13:11.860 --> 13:13.100] I'm a biologist... [13:14.400 --> 13:15.860] So we can think of it from an... [13:15.860 --> 13:18.380] Information theory perspective... [13:18.940 --> 13:20.840] Or we can also think of it from a... [13:20.840 --> 13:21.240] Process-based perspective... [13:22.080 --> 13:22.960] So then... [13:22.960 --> 13:24.040] Once we have an idea of... [13:24.040 --> 13:25.940] How we can conceptualize of life... [13:25.940 --> 13:27.640] Then we'll think about like... [13:27.640 --> 13:30.400] How life generates complexity... [13:30.400 --> 13:30.580] How... [13:30.580 --> 13:31.720] How life... [13:31.720 --> 13:32.640] Solves problems... [13:32.640 --> 13:34.860] What are some of the tools that life uses to solve problems? [13:36.740 --> 13:37.580] So... [13:37.580 --> 13:40.640] Can I just suggest you share that mic? [13:43.380 --> 13:44.080] Yours is... [13:44.080 --> 13:45.270] Oh... [13:45.270 --> 13:45.940] Yeah, sure... [13:45.940 --> 13:46.290] Just... [13:46.290 --> 13:46.920] Just... [13:46.920 --> 13:47.620] I'll switch... [13:47.620 --> 13:48.080] I'll switch... [13:48.080 --> 13:49.080] This one's better... [13:49.670 --> 13:50.080] Better? [13:53.500 --> 13:54.160] Thank you... [13:55.440 --> 13:56.290] Thanks... [13:59.720 --> 14:01.380] Assembly theory... [14:04.410 --> 14:04.930] So... [14:04.930 --> 14:05.110] Yeah... [14:05.110 --> 14:05.390] So... [14:05.390 --> 14:06.010] So... [14:06.010 --> 14:06.910] Like I was just saying... [14:06.910 --> 14:07.610] From... [14:07.610 --> 14:09.230] How do we identify life? [14:09.390 --> 14:09.490] Right? [14:09.570 --> 14:11.450] So one strategy for identifying life... [14:11.450 --> 14:13.090] Has been developed... [14:14.050 --> 14:14.570] By... [14:14.570 --> 14:16.490] Several people over the past... [14:16.490 --> 14:17.490] 10 or 15 years... [14:17.490 --> 14:18.930] When they call it... [14:19.510 --> 14:20.230] Assembly theory... [14:20.230 --> 14:22.410] The kind of root of this idea is... [14:22.410 --> 14:22.910] How do we... [14:22.910 --> 14:25.530] How might we identify... [14:26.690 --> 14:27.730] Extraterrestrial life... [14:27.730 --> 14:28.290] Out in the universe? [14:28.610 --> 14:28.750] Right? [14:29.490 --> 14:30.010] Because... [14:30.010 --> 14:30.250] You know... [14:30.250 --> 14:32.250] We can only really see... [14:33.710 --> 14:35.250] Signatures of chemical compositions... [14:35.770 --> 14:36.270] And very faintly... [14:36.790 --> 14:37.650] We can detect... [14:38.370 --> 14:40.010] The presence of planets... [14:40.010 --> 14:41.190] By the kind of... [14:41.190 --> 14:42.250] Twinkling of light... [14:43.250 --> 14:43.850] You know... [14:43.850 --> 14:45.030] Gravitational lensing... [14:45.030 --> 14:45.790] Kind of idea... [14:45.790 --> 14:46.110] We can... [14:46.110 --> 14:46.690] We can... [14:47.250 --> 14:49.050] See things very distantly... [14:49.050 --> 14:50.050] We can detect... [14:50.050 --> 14:50.890] Chemical signatures. [14:51.150 --> 14:52.390] So if we can understand... [14:52.390 --> 14:53.450] What are the... [14:53.450 --> 14:54.650] Kind of... [14:54.650 --> 14:56.730] Chemical signatures of life... [14:56.730 --> 14:57.970] Then we might be able to detect... [14:57.970 --> 14:58.690] Life in the universe... [14:58.690 --> 15:08.210] But the idea is, how can we kind of quantify the kinds of signatures, the chemical signatures of life? [15:08.370 --> 15:20.530] And so their idea is that you can formalize how complicated a particular molecule is by kind of how many steps that it would take to create. [15:20.850 --> 15:27.970] And then you can look in the universe at everything that is kind of created by passive physical processes. [15:28.850 --> 15:44.030] And everything that's created, at least here by life, and the idea is there should be some threshold beyond which kind of background processes that are happening in the universe would not be able to generate molecules of a complexity beyond this. [15:44.190 --> 15:53.910] And so then if you look through a telescope out and you can detect molecules of like sufficient complexity, then you could infer that life is generating these processes or generating these molecules. [15:54.730 --> 16:11.890] And then another kind of way to understand what life is, is the idea of autopoiesis, which is kind of the definition is up here, but you know, autopoiesis is, is the idea of what is a relational view of life, right? [16:11.890 --> 16:24.270] That, that a living system is a set of relationships whose function or whose kind of purpose is the reproduction of that network of relationships, right? [16:24.410 --> 16:32.650] So what, you know, what makes a living creature, like what makes Isaac, Isaac is not any particular, you know, is not any molecule. [16:33.450 --> 16:42.730] It's not any particular, you know, it's not any particular, you know, it's not any particular aspect of him, it is the, the network of relationships that has reproduced him through time. [16:44.050 --> 16:55.290] And so those are kind of two ways that we can think about what life is that, that are maybe fruitful for, for, for our thinking, so. [16:56.950 --> 17:05.570] Okay, so now, so now we're going to think about problem solving, how does, you know, how does biology solve problems? [17:05.970 --> 17:08.230] How does, how does life solve problems? [17:09.590 --> 17:18.130] And you can think of, of, you know, the process of solving problems is the process of kind of accumulating complexity through time. [17:18.130 --> 17:24.210] And so life solve problems solves problems with evolution, with, you know, we, evolution is descent with modification. [17:25.450 --> 17:28.230] And it solves problems by exploring possibility space. [17:28.370 --> 17:34.910] So we're going to go through some kind of examples of how, you know, how this works in a biological system. [17:35.050 --> 17:37.950] And what we're thinking, well, I'm talking specifically about biology. [17:38.470 --> 17:45.130] In the back of your mind, I want to think about, I want, I want you to be thinking about, okay, how can I kind of conceptual? [17:45.130 --> 17:53.450] How can I, how can I abstract this biological process to a realm of social systems or political systems or organizational systems? [17:55.690 --> 18:01.410] Uh, so, so we can start by just thinking about, uh, trait space. [18:01.690 --> 18:14.630] So the, the, the, the, the, the domain of possible bill shapes of Darwin's finches, for example, and I'm going to call this beak space, because you can imagine it's a two dimensional space. [18:15.290 --> 18:24.090] That's, that circumscribes all of the possible beaks that Darwin's finches might have from, uh, less pointy to very pointy beaks. [18:24.190 --> 18:26.990] And from less smaller beak size to larger beak size. [18:26.990 --> 18:34.870] And you can see, this is just four examples of these different Darwin's finches that do exist, that occupy different kind of areas of beak space. [18:34.870 --> 18:43.410] And so the question is, uh, you know, what, why do the, these finches, why, why aren't they all kind of the same? [18:43.510 --> 18:48.410] They haven't all, you know, there is there, shouldn't there be one kind of like optimal beak shape? [18:48.450 --> 18:50.190] And why isn't there one optimal beak shape? [18:50.830 --> 18:54.950] Or, you know, if there isn't one optimal beak shape, why are there different ones? [18:54.950 --> 19:02.670] And how do they become, you know, how do different species kind of evolve to have different beak shapes? [19:04.010 --> 19:08.910] And so this is right through a process of evolution. [19:08.910 --> 19:36.210] And how I want to frame evolution in this particular context is as accumulation of complexity or a computational process through time, whereby different lineages are solving problems, you know, and kind of like accumulating information within the lineage of how the problem was solved through time. [19:37.130 --> 19:40.250] And so we might start with this kind of ancestral finch. [19:40.350 --> 19:47.630] And then in a given environment, for example, let's say there's all of a sudden one year there's tons of insects. [19:50.890 --> 19:59.810] One offspring lineage might evolve kind of more pointy beak to increase its insect feeding abilities. [20:00.970 --> 20:25.090] And so the idea is that through time, as the environment changes, as the other organisms in its environment that's competing with change, there's pressures in beak space that cause things to kind of move, you can think about evolution in trait space as this kind of like walk through a two dimensional... [20:25.610 --> 20:44.010] If we just keep the two dimensional beak space idea for the moment, you can think of evolution through time as this kind of like walk through beak space, Which is constrained by the environment and available resources and competition with other things in its environment. [20:44.790 --> 20:50.510] So you can think of... I'm going to change from talking about beak space now to possibility space because then it's more general, right? [20:50.570 --> 21:01.890] We can stop thinking about, you know, birds and beaks and we can start thinking about kind of like any kind of possibilities for animal morphology or behavior. [21:01.890 --> 21:09.410] It's important just to know because beak space, the way we're characterizing this is limited by what we can actually measure. [21:09.670 --> 21:20.550] And the possibility spaces operating in the world are obviously like both the things we can measure, but many, many things that we don't even know that we can't measure at all, right? [21:21.210 --> 21:28.870] These are... we're all operating in, you know, kind of trillion dimensional hyperspace. [21:28.870 --> 21:34.230] Like what we can discern is the spaces that we could measure, right? [21:34.430 --> 21:39.730] And so it's important to try to... that's like the part that's... [21:39.730 --> 21:40.790] for me, at least. [21:40.970 --> 21:42.630] it's hard to break out of that. [21:42.730 --> 21:48.970] It's like... it's not just the things that we can measure are there and operating and we can make nice charts of them and this is, you know... [21:48.970 --> 21:54.470] but then we also have to have the humility to know that there's lots of things that we can't measure, right. [21:55.450 --> 21:56.370] Right, right. [21:58.790 --> 22:18.490] So you can think of each of these colored lines as a different lineage of something, a bird or an organization that you might be involved in that starts in some area of possibility space and because of through time and because of external and internal pressures, [22:18.510 --> 22:26.270] the structure of the organization, the structure of the species, it will change through time. [22:26.370 --> 22:28.970] It will kind of wander in this possibility space. [22:30.110 --> 22:34.070] And so, as Abhi was saying, possibility space isn't two-dimensional. [22:34.330 --> 22:36.250] It's highly, highly, highly multidimensional. [22:36.590 --> 22:58.370] If we look at the kind of possibility space of body plans for birds here, just kind of different characteristics of body size and beak size and kind of different proportions, we can look at, we can take measurements of all of the birds in the world and plot them into this just three-dimensional representation of body size possibilities. [22:59.890 --> 23:07.970] And there's a couple of, you know, there's a couple of things that you can notice from how birds are occupying possibility space here, right? [23:07.970 --> 23:08.830] There's clustering. [23:09.130 --> 23:14.050] So there's some, there's clumps, there's kind of clumping here and here. [23:14.190 --> 23:16.090] There's this very big, big central mass. [23:16.490 --> 23:18.490] I can't see a doodling because it's... [23:18.490 --> 23:19.010] Oh yeah, okay. [23:19.150 --> 23:21.850] So there's clustering and there's clumping. [23:21.850 --> 23:23.030] There's a big central mass. [23:25.230 --> 23:31.070] And the other important thing to notice is that there's kind of like vacancy in possibility space, right? [23:31.070 --> 23:36.250] So there's vacancy in the, in possible bird body morphologies. [23:36.430 --> 23:37.630] And so this could be for two reasons. [23:37.750 --> 23:46.790] It could be because these are bad body forms for birds to have, or it could be because no bird has tried this yet, right? [23:46.890 --> 23:47.990] No bird has gotten there. [23:48.250 --> 23:54.770] And that's a question of contingencies, multi-dimensional contingencies that are like almost unknowable. [23:54.770 --> 23:55.190] Right. [23:56.730 --> 23:57.790] Right, right. [24:00.510 --> 24:23.310] So now the critical thing to, to, to the critical consideration for, for thinking about possibility space and the exploration of possibility space is that it's, you know, it's, it's, it's possible for the exploration of possibility space to kind of like expand the dimensions of what's possible, [24:23.410 --> 24:23.610] right? [24:23.610 --> 24:31.730] If you're exploring what's possible, then you might open up a new domain of possibility that didn't previously exist. [24:32.730 --> 24:36.690] And so if you think about... a good example is with powered flight in birds. [24:36.910 --> 24:42.970] So you can think about the ancestors of birds were dinosaurs. [24:43.570 --> 24:47.130] They're terrestrial vertebrates. [24:47.130 --> 24:57.090] And you can see... you can think of this kind of like pink squiggle on the bottom here as like the ancestor of... [24:57.090 --> 25:04.590] the terrestrial ancestor of birds that is exploring possibility space kind of in two dimensions. [25:04.590 --> 25:14.470] It's only limited to what it can... you know, the possibilities that it can kind of obtain in its terrestrial habit. [25:15.550 --> 25:16.790] And then... [25:18.490 --> 25:30.750] over the course of, you know, instant... effectively instantaneously in evolutionary time, which is represented by this little lightning bolt here where... where the ancestor of birds evolved powered flight. [25:31.430 --> 25:39.830] This actually opens up an entirely new domain in possibility space that was not previously available to these organisms, right? [25:39.830 --> 25:44.730] So... so powered flight evolves and then this kind of constellation of new possibilities... [25:45.890 --> 25:48.330] has... has kind of been unlocked, right? [25:48.530 --> 25:49.870] By... by... by... [25:50.570 --> 25:53.390] this... this... this exploration and possibility space. [25:58.490 --> 25:59.090] Right? [25:59.330 --> 26:06.870] So... yeah, it's free... it's free... it's... you... you... you... develop a new... kind of... key innovation and then... there's free real estate everywhere, right? [26:06.870 --> 26:08.610] You... that's the joke. [26:11.270 --> 26:16.670] Okay, so now we have this kind of notion of possibility space and how descent with modification can... [26:17.130 --> 26:19.270] explore and expand possibility space. [26:19.410 --> 26:21.870] But what are some of the tools that evolution can use... [26:23.130 --> 26:24.470] in order to achieve this? [26:24.590 --> 26:28.290] And so... so again, like, let's think about, you know, thinking about... [26:28.290 --> 26:33.790] making abstractions and applying abstractions to different, you know, human systems. [26:34.970 --> 26:38.290] We're gonna just... I'm gonna talk to... talk to you about... [26:40.610 --> 26:46.790] you know, how... what... what we will say is that life is the accumulation of usefully complex hacks. [26:47.030 --> 26:47.610] And so... [26:47.610 --> 26:53.210] what are some of these hacks that biological life uses in order to solve problems and explore possibility space? [26:53.210 --> 26:57.130] You know, one... one hack is... multicellularity, right? [26:57.270 --> 26:59.210] So if you're a single-celled organism... [27:00.810 --> 27:02.010] you know... [27:02.010 --> 27:08.530] the hack of getting together with other single-celled organisms and aggregating and then specializing in... [27:08.530 --> 27:10.930] what you do, that's... that's... that's... [27:11.770 --> 27:12.650] that's a hack. [27:12.810 --> 27:18.210] That's a new... a new dimension of... opens up a new dimension of possibility space by kind of... [27:19.190 --> 27:20.390] obtaining multicellularity. [27:20.390 --> 27:21.270] So we're gonna talk about... [27:21.270 --> 27:25.790] modularity, extensibility, and reuse as things that... you know... [27:25.790 --> 27:28.590] as... as... as hacks... as biological hacks. [27:30.230 --> 27:32.650] So as an example of modularity... [27:32.650 --> 27:37.270] an example of modularity is the genetic code, which is the... [27:37.270 --> 27:39.250] the... the... [27:42.410 --> 27:43.050] the... [27:43.050 --> 27:49.170] code that translates your, you know, genetic sequence of A's and G's and C's and T's... [27:49.170 --> 27:50.930] into proteins... [27:52.170 --> 27:52.530] that... [27:52.890 --> 27:53.310] of... [27:53.310 --> 27:53.870] of... [27:53.870 --> 27:56.230] a whole host of different kinds that... [27:56.230 --> 27:57.390] your body is... you know... [27:57.390 --> 27:59.090] every cell in your body is composed of. [27:59.450 --> 28:02.170] And so the genetic code consists of... [28:03.270 --> 28:03.590] you know... [28:04.170 --> 28:06.050] in... in... in... [28:06.050 --> 28:06.750] in... the... [28:06.750 --> 28:09.010] the genome, each triplet of... [28:10.030 --> 28:12.570] base pairs encodes for one... [28:12.570 --> 28:13.830] amino acid. [28:14.570 --> 28:15.050] and... [28:25.350 --> 28:25.830] the... [28:31.410 --> 28:38.430] It allows for a form of memory through time that opens up, you know, just massive possibilities, right? [28:46.470 --> 28:49.970] So, another hack in biology is extensibility. [28:49.970 --> 28:57.070] So you can think of genome evolution, how genomes kind of evolve through time. [28:57.070 --> 29:17.110] You know, genomes can... plasticity represents a kind of mode of extensibility where you can see the different colored bars here represent kind of changes in genomic composition through time in mammalian groups. [29:17.110 --> 29:24.570] Where, you know, some genes are lost in humans that occur in all other mammals. [29:25.610 --> 29:30.770] And some genes are primate specific and some are carnivore specific, for example. [29:30.770 --> 29:45.390] So, genomic architecture of animals is this kind of, like, very fluid and dynamic and constantly changing, you know, suite of tools for developing body plans and solving problems. [29:48.330 --> 29:56.790] And the other kind of, you know, the other hack that biology uses... biology is constantly reusing everything. [29:57.350 --> 30:07.230] And one way that I think biology reuses information in a way that I think that a lot of hackers can understand is in whole genome duplications. [30:08.490 --> 30:19.420] So, throughout the radiation of vertebrates, there's been several instances of whole genome duplications, which results in, for example... [30:21.290 --> 30:26.790] You know, you can think of a whole genome duplication as like a fork in GitHub, right? [30:26.790 --> 30:34.230] So, if you have a project in GitHub and it's doing something, you fork it. [30:34.550 --> 30:38.730] The project that was there before can continue to carry the load that it was carrying. [30:39.050 --> 30:45.270] But the new project, which is the fork, it can change to do something slightly different. [30:45.630 --> 30:50.790] It can fill a space that was not filled by the original project. [30:51.350 --> 30:54.370] Or it can change to do something entirely different. [30:54.370 --> 31:08.110] So, whole genome duplications are a way of kind of like providing just like a dump of new raw material that an organism can use to... [31:08.110 --> 31:23.370] Often whole genome duplications are followed kind of quickly by adaptive radiations, where you have this massive amount of new potential that then gets exploited into like huge adaptive radiations. [31:25.650 --> 31:32.670] Okay, so those were some of the ideas of how complexity is generated through evolution. [31:32.990 --> 31:37.190] And so now we're going to kind of talk about some... [31:37.190 --> 31:41.990] Now is the downward slope of how things are lost. [31:42.250 --> 31:46.430] And we're going to talk about these three ideas of degeneration, extinction, and collapse. [31:47.410 --> 31:49.770] Again, from the computational perspective. [31:49.990 --> 31:52.570] And, you know, we're looking here at this timeline. [31:52.970 --> 32:00.590] And we're thinking about, you know, this is kind of a timeline of great extinctions. [32:00.590 --> 32:10.920] But then we're going to also look at, we're going to look at like strategies, like evolutionary strategies that lead to information loss. [32:11.290 --> 32:22.250] And then thinking about how collapse and extinction, how they function from an informational perspective. [32:22.250 --> 32:35.250] So, yeah, so in biology, one kind of way that you can kind of lose information is by giving up, essentially giving up the ability to explore possibility space. [32:35.250 --> 32:51.090] And so in, in some organisms, some, most organisms that we kind of commonly think of reproduce sexually, where they, you know, there's come, there's two genomes from two parents that fuse and there's recombination. [32:51.090 --> 33:01.630] So you get all of this kind of like mixing of genetic material, and you're bringing together two lineages that have solved problems differently through time, and you're taking the best of what each of these lineages have done. [33:01.990 --> 33:02.710] Over time. [33:02.710 --> 33:04.990] Over to over evolutionary time, right, exactly. [33:06.150 --> 33:16.710] But another strategy, some, some lineages, they say, forget this, I'm just going to, I'm going to take all of them, I'm going to put all of my eggs in my current genetic basket, and I'm going to reproduce asexually. [33:17.490 --> 33:19.050] And so this is called parthenogenesis. [33:19.470 --> 33:36.650] And so whereas kind of in the, in the organisms that replicate selflessly in order to explore possibility space, parthenogenesis, parthenogenetic species, replicate selfishly in order to maximize the propagation, propagation of their own genetic material through time. [33:37.090 --> 33:50.310] Essentially, they're abandoning the life giving process of being able to explore possibilities for the short term gain of being able to replicate their own, you know, being able to replicate their own, be able to replicate their own genetic material forward through time, [33:50.330 --> 33:51.230] most effectively. [33:57.520 --> 34:17.080] Another, another lens on information loss and biodiversity is extinction where, you know, we're, we're, I think, unfortunately, we're kind of attuned to, you know, hearing about biodiversity loss and extinction and our reaction is like, you know, the, [34:17.180 --> 34:20.620] the, we're never going to get the ivory to build woodpecker back. [34:21.860 --> 34:38.520] But I think another information theory and computational perspective on, which is true, and it's terrible, kind of computational perspective, even kind of exacerbates the loss. [34:38.520 --> 34:47.280] If you think about the, the branch that subtends the, a given extinct lineage. [34:47.280 --> 35:02.520] If you think of all of the time that that lineage existed as a record of the computation of all of the problems that evolution has solved along that branch, then when that branch goes extinct, all of that computation is gone forever. [35:06.880 --> 35:27.560] And then finally, if we think more from the perspective, rather than of individual lineages of ecosystems, there's the idea of collapse in bio, in, in ecosystem science, we think about tipping points whereby kind of complexity, you know, complexity of an ecosystem kind of sustains itself. [35:27.560 --> 35:32.460] And after a certain threshold of complexity is lost, and after a certain threshold of complexity is lost, then there's a, there, we call these tipping points. [35:32.600 --> 35:44.440] There's a collapse of the ecosystem and it collapses to a kind of either to inevitable doom or it collapses to a lower level of complexity. [35:44.440 --> 36:12.700] And so this is an example of how, in, in reef ecosystems, how fishing and kind of like abiotic conditions can, can, can drive a reef ecosystem from a higher state of complexity to kind of lower and lower states of complexity until eventually what's left is just a barren kind of rocky surface seafloor. [36:13.200 --> 36:18.080] And in a sense, in evolutionary time, that is maybe a brand new possibility space. [36:18.220 --> 36:22.040] But as people, we don't live in evolutionary time. [36:22.320 --> 36:22.540] Yeah, exactly. [36:23.040 --> 36:27.000] And so this is where we're coming to kind of collapse from a more human scale. [36:27.600 --> 36:34.480] These are, these are charts from, if people are familiar with Joseph Tainter's collapse of complex societies. [36:35.700 --> 36:52.600] You know, and, and his kind of main, his thesis is the idea of diminishing returns on complexity, that societies increase in complexity in terms of diversity of, of occupation and broadly in terms of any type of diversity of what people are doing within a society. [36:52.600 --> 37:00.000] But the energy returns on that, you know, that, that, that, that, that establishing and building that level of complexity in societies. [37:00.260 --> 37:01.600] And this guy's a archeologist. [37:01.740 --> 37:04.680] So he's looking through the history of like civilizations. [37:04.680 --> 37:05.160] Right. [37:05.860 --> 37:23.200] And so that, that, that it's increasing energy demands and depletion of resources leads to this, you know, the increase of complexity leads to like collapse, which is, is he's defining as a lowering or a lessening of, of complexity within society. [37:24.600 --> 37:35.040] And so here we have, so when we're thinking about these kinds of collapses and different types of collapses. [37:35.160 --> 37:43.360] and how to characterize them, we're looking at, uh, this is, this is an example of kind of endogenous versus exogenous, um, collapse, right? [37:43.480 --> 37:48.920] So we have this, you know, normally when we think of mass extinction, that the asteroid is kind of the big one. [37:49.100 --> 38:02.360] Um, the, the, the KT boundary event, um, the death of the dinosaurs, the, the, the, and, you know, the opening up of like, uh, you know, the, the mammal, the mammalian era. [38:02.360 --> 38:27.260] Um, and the, you know, that is, you know, a huge exploration of a, of a, of a space, but it's also like thinking about that as a bottleneck, um, event where, um, you know, uh, though, like the, the, the, the complex dinosaur ecosystems are, are destroyed through basically energy loss. [38:27.260 --> 38:27.520] Right? [38:27.760 --> 38:35.680] That, that, that, the, the, the, the climatological impact, it's not the, it's not the, it's not the asteroid itself that killed the dinosaurs. [38:35.900 --> 38:52.040] It's the resulting climate and loss of energy that destroys the, the, the more fragile ecosystems that they were dependent upon and allows for, um, you know, allows for the mammals to kind of take over all that space. [38:52.040 --> 38:55.780] It wasn't the, it wasn't the asteroid that caused the collapse, the, the extinction of the dinosaurs. [38:55.900 --> 38:58.220] It was the fact that they were over invested in a stable environment. [38:58.440 --> 38:58.560] Yeah. [38:58.840 --> 38:58.960] Right. [38:59.260 --> 39:13.140] And so, and so, but then thinking about that in contrast to a phase transition, um, this, this other, this other, um, over here is the idea of the great oxygen catastrophe. [39:13.140 --> 39:20.280] Um, which is like, I think from, from this perspective is like the, or hack of planet earth, right? [39:20.420 --> 39:31.860] Which is, um, like what 2.5 billion years ago, uh, some, some little molecule kind of developed the cut, the, the, the hack of photosynthesis, right? [39:32.100 --> 39:32.160] Right. [39:32.260 --> 39:36.660] Of, you know, there, there's two sources of energy on planet earth, right? [39:36.660 --> 39:40.040] There's geothermal and there's the sun, right? [39:40.540 --> 39:54.000] And, um, basically the oxygen catastrophe is the, the, the hack of figuring out how to stop using geothermal only and use the sun as a source of energy. [39:54.000 --> 40:01.060] And it's like what, it's like the biggest opening of possibility that life has developed on this planet, right? [40:01.060 --> 40:07.220] And so it, it, you know, it's, it's, it's the, the molecule in molecular form of, of chlorophyll, right? [40:07.840 --> 40:16.700] Um, but that's like, as, uh, extinction event, that is like also can be characterized more as like a phase transition, right? [40:17.080 --> 40:24.460] Because I mean, though there still are anaerobic bacteria that live on like, like, uh, On deep sea thermal vents. [40:24.460 --> 40:24.780] Yeah. [40:25.040 --> 40:32.360] Like deep thermal vents, like the vast majority of life, obviously in some sense or another is, is solar powered, right? [40:32.780 --> 40:42.060] Um, so, so that's how we're kind of going to move on to, uh, the second part. [40:42.320 --> 40:45.540] Um, and what time, what we got, what do we got? [40:45.660 --> 40:46.140] 15 minutes? [40:46.740 --> 40:47.000] Okay. [40:47.100 --> 40:48.120] Well, I mean, we have to be done. [40:48.340 --> 40:48.520] Yeah. [40:48.660 --> 40:48.860] All right. [40:48.860 --> 40:56.100] So, um, so now we're, we're, we're, we're, we're out of life. [40:56.300 --> 41:03.280] I hope those ideas have percolated something and we're into this kind of more, um, more into the idea of hacking. [41:03.500 --> 41:07.460] And, and, you know, this is the, think about the exclamation. [41:07.620 --> 41:09.260] The title of this involves the word freedom. [41:09.460 --> 41:14.540] I want to put instead of exclamation point, a question mark, because, you know, um, what is freedom? [41:14.540 --> 41:20.460] Um, how, you know, I think that here are three kind of concepts of freedom that come from hacking, right? [41:20.880 --> 41:24.680] Um, this idea of, you know, all information should be free. [41:24.820 --> 41:30.540] Access to computers is kind of the very, like the, the provenance of like computers as, as a new thing. [41:30.820 --> 41:35.340] And, and kind of the source of a tech utopian vision for computing, right? [41:35.880 --> 41:39.980] Um, and then we can see the evolution from the sixties to the seventies. [41:40.600 --> 41:47.080] The takeover of computing by, you know, by mega corporations and, and the closing of, of that space. [41:47.340 --> 41:54.160] Um, and, and then kind of, you know, the, in the middle here, we have the kind of four principles of, of free software, right? [41:54.340 --> 41:56.420] Where, where this is kind of a response. [41:56.860 --> 42:04.620] Um, and then I think we're kind of at a point now where we see like that, like, you know, the, the narrowness of that has achieved like wonders. [42:04.620 --> 42:16.380] But we're also at the point that like, you know, like one of the greatest, you know, one of the, the most significant products of free software being Linux is like, you know, basically a core tool of like the death machine at this point. [42:16.380 --> 42:16.600] Right? [42:16.660 --> 42:21.280] Like, it's like, so, um, it, it, it, it, it's not enough, right? [42:21.340 --> 42:22.300] Like how do we expand? [42:22.500 --> 42:28.340] How do we think, how do we, how do we, uh, reinterpret or, or think of, of hacking in this broader way? [42:28.340 --> 42:48.020] And I'm coming back to McKinsey work again, um, you know, to discover that, that in essence, this idea of discovery to freely invent, but that it has the, you know, the, the, the traditional kind of where that we, we're still, we were facing these kind of analogous to like some of these, [42:48.020 --> 42:50.100] um, systems of information loss. [42:50.120 --> 42:55.380] We have these, these systems, social systems that are, that are actually killing us, right? [42:55.380 --> 42:59.920] They're killing our ability to create, but they're also actually killing all of us, right? [43:00.460 --> 43:15.040] So, um, these, this idea of property, secrecy, monopoly, um, and, you know, that, that it is this kind, that, that, that, that, you know, that, that this relation of scarcity is being enforced upon us. [43:15.260 --> 43:24.740] Um, and, so, you know, it comes to this question of like, how do we think of, how do we create hacking as life? [43:24.740 --> 43:34.180] Um, you know, hopefully some of these ideas are percolating, of, of creating new complexity, um, the exploration of possibility space. [43:34.900 --> 43:41.220] And, you know, I think there's lots, like, I think a lot of people are thinking about moving beyond information space, right? [43:41.260 --> 43:49.760] A lot of it is, a lot of these battles, um, and the kind of, the, the hacker wars or the hacker ethos is a, is focused on information. [43:49.760 --> 43:54.760] And there is like a refocusing on users and a refocusing on kind of organization. [43:56.020 --> 44:06.720] Um, and, and this, this quote here is kind of telling us how do we, you know, in, in, in the most abstract sense, how do we, how are we bringing new things into relation? [44:06.720 --> 44:10.020] So that kind of thinking is, is, uh, is happening. [44:10.380 --> 44:20.380] And, but, you know, and, and so the last quote from, from the workbook is kind of, okay, this hacking property itself. [44:21.060 --> 44:30.180] And, and, and, and, you know, I don't want to get too, too narrowly focused on, on property itself, but it's like hacking in the world, engaging in the world. [44:30.180 --> 44:34.300] And like, you know, at, at the end of the day, like, this is the right idea. [44:34.500 --> 44:44.400] And, and unfortunately, like, I'm not going to have any answers, um, great answers for you, but this is, you know, the, the, the point is what, how do we bring our tools? [44:44.640 --> 44:45.820] How do we bring our ideas? [44:46.200 --> 44:48.720] How do we approach these problems? [44:48.720 --> 44:58.640] Because we don't have evolutionary time to do it, but we have the ability, you know, we do have the ability to accelerate our hacking. [44:58.640 --> 45:03.540] We can accelerate our exploration of possibility space if we are free ourselves up to do this, right? [45:03.680 --> 45:03.680] Yeah. [45:04.140 --> 45:11.520] And so I'm offering a couple, like the couple of tools that we're offering are kind of like, and this is, this is basically the last slide. [45:11.740 --> 45:18.460] Um, and hopefully people have some ideas or questions, you know, because what we have is tools and what we have is ideas and what we have is, is our ability to interact. [45:18.600 --> 45:35.900] And so I'm kind of like trying to maybe decide toward Gaia hacking or something like, um, you know, and I think there's a lot of, uh, uh, uh, so, I think that if we look at this kind of three part kind of thing, a lot of what we talked about in the hacker part is about information. [45:36.400 --> 45:47.300] Um, and so what I'm trying to, what I'm trying to bring in is, um, how we think of freedom in, in the other spaces, right? [45:47.300 --> 45:51.740] Like if we could think of something like occupy as like a space hack, right? [45:51.940 --> 45:57.080] Like that as, as, uh, as a space hack, that's opening up physical space and possibility space. [45:57.380 --> 46:08.440] Um, or like, if we think of time hack, you know, like that's kind of like labor organizing or taking, you know, like owning one's own time. [46:09.060 --> 46:09.440] Right. [46:09.800 --> 46:15.520] Or, um, you know, uh, and so, so these aspects of time. [46:15.540 --> 46:21.620] And so when we're thinking about freedom and I think that the word freedom could easily be, and I toyed with this. [46:21.720 --> 46:29.120] I'm not, you know, it could easily be the word capacity or it could be the word power because they all kind of, from this perspective, I think of the same thing. [46:29.120 --> 46:29.520] Right. [46:29.860 --> 46:46.180] And so this is kind of a tool that I'm using to like evaluate any particular, like a project or an idea or whatever, like that, that, uh, that, that, that how these all three are related to create a robust or more robust concept. [46:46.180 --> 46:52.220] I mean, uh, yeah, I mean, I think that yeah, what, what, you know, we're our company in our conversation earlier. [46:52.400 --> 47:07.800] I think it really made a lot of sense to me where I was talking about like, uh, you know, what is, you know, freedom is the ability to do something, it's, you know, the ability to have agency, to do something and that agency requires information and time and space. [47:07.800 --> 47:14.160] And as kind of like a hacker community, we're really good about generating our own agency in the kind of information domain. [47:14.800 --> 47:27.560] And we can, you know, we should be trying to develop our ability to, you know, form agency in the domains of time and space in order to kind of like accumulate more capacity. [47:28.500 --> 47:34.060] And so hopefully we can use this time and space to further discussion. [47:34.160 --> 47:36.420] If anybody has anything else, I'd love to hear. [47:47.520 --> 47:49.260] I think we have about five minutes left. [47:49.380 --> 47:49.680] Is that right? [47:50.680 --> 47:51.120] Seven. [47:51.280 --> 47:52.080] We have about seven minutes. [47:52.220 --> 47:52.240] Yeah. [47:52.400 --> 47:52.800] So, yeah. [47:57.330 --> 48:01.450] So I'm going to tell you what I abstracted from what you're saying. [48:01.590 --> 48:01.650] Great. [48:01.650 --> 48:04.070] And then I've got some questions that sort of build on that. [48:04.230 --> 48:04.290] Sure, sure. [48:04.510 --> 48:11.410] So what I took away is that you're in some way almost equating complexity and possibility. [48:11.810 --> 48:14.850] So more complexity gives you more possibility. [48:15.070 --> 48:17.230] Less complexity gives you less possibility. [48:17.970 --> 48:25.090] And that sense of possibility and complexity also is a source of freedom. [48:26.110 --> 48:36.310] And that when you lose that, you also lose the historical record of having solved problems or developed that complexity in the past. [48:36.310 --> 48:50.590] So if that's all true in what you said, the questions that I have that sort of were spurred in my mind have to do with both the immune system and neural development and plasticity. [48:50.590 --> 48:51.130] Sure. [48:51.130 --> 48:59.590] So the immune system is designed to meet new, unexpected, unforeseen, previously unknown things. [48:59.830 --> 49:10.370] And then it makes a shitload of different T cell receptors or antibodies, some of which are really good and some of which are not so useful. [49:10.370 --> 49:18.570] So there's this huge energetic investment in making a lot of different choices, read complexity. [49:19.030 --> 49:24.350] But because some of them are really not very effective, you get rid of those ones. [49:24.350 --> 49:28.670] And you end up pruning it down until you get a really good response. [49:28.890 --> 49:31.170] And then you remember that good response. [49:31.170 --> 49:42.630] So from an evolutionary standpoint, the solution that evolution has come up with is spend a lot of energy, figure out what works, and then condense. [49:43.430 --> 49:44.790] Which is kind of different... [49:44.790 --> 49:45.670] Yeah, that makes perfect sense, yeah. [49:45.870 --> 49:48.510] Which kind of is different than what you're talking about. [49:48.730 --> 49:53.330] If you look at neural development and neural plasticity, it's kind of the same thing. [49:53.350 --> 49:58.610] You make a whole lot of neuronal connections, and a lot of them are not very useful. [49:58.610 --> 50:05.090] And you prune those back so that the developing brain is making lots of connections. [50:05.270 --> 50:09.710] And if you look how many connections there are in adolescence or in adulthood, it's fewer. [50:10.370 --> 50:14.350] But you maintain the ability to make some degree of new connections. [50:14.710 --> 50:25.970] And so what I am inferring is that this is more of a cyclical process of sometimes you need to be expanded in a very high complexity state. [50:26.210 --> 50:32.230] And sometimes you need to reduce down into what's useful so that you don't waste a lot of energy. [50:32.470 --> 50:38.150] And then you can go into another sort of growth or increase phase. [50:39.130 --> 50:42.130] How does that fit with the way you're thinking about it? [50:42.170 --> 50:46.450] I mean, I think it's the kind of like next evolution of the thinking, right? [50:46.450 --> 50:48.390] Like, I don't disagree with anything that you just said. [50:48.470 --> 50:49.550] I think that that's really wonderful. [50:49.590 --> 50:53.470] And I think it's like an expansion of the ideas that we had. [50:53.490 --> 50:56.230] And I think that we didn't even get there because we... [50:57.830 --> 51:01.370] I definitely agree with you about the immune system and about neural generation. [51:01.690 --> 51:02.270] Those are great. [51:02.350 --> 51:02.930] That's a great insight. [51:02.950 --> 51:05.270] I think you've understood well what we're proposing. [51:05.790 --> 51:07.750] I mean, it sometimes worries me. [51:07.870 --> 51:10.770] I mean, I also like to think about complex adaptive systems. [51:10.770 --> 51:13.750] I'm an immunologist, so I think a lot about this kind of stuff. [51:14.110 --> 51:19.030] But complex adaptive systems, like everything, have an end game. [51:19.230 --> 51:20.790] It's maybe not a single end game. [51:20.810 --> 51:24.530] But, you know, sort of a set of things that the organism has to survive. [51:24.530 --> 51:27.670] Because if the organism doesn't survive, then it can't do anything else. [51:27.790 --> 51:27.950] Right. [51:27.990 --> 51:29.330] So survival is important. [51:29.610 --> 51:33.210] And then there's the question of what's the nature of that survival got to be. [51:33.670 --> 51:37.650] And complexity, per se, is a tool. [51:37.650 --> 51:39.750] I don't know that it's an end game. [51:39.750 --> 51:51.790] And, you know, even if you look at sort of geological history or cosmology, you do have this sort of cyclical, there's a lot of different choices. [51:52.050 --> 51:54.250] And then you lose a whole lot of species. [51:54.590 --> 51:57.990] And then you get a whole lot of evolution among the remaining species. [51:58.090 --> 52:00.170] Because there's space that they can fill. [52:00.290 --> 52:02.410] And there are functions they have to accomplish. [52:02.670 --> 52:04.730] And so it's sort of this give and take. [52:05.030 --> 52:06.210] I think that's a great observation. [52:06.390 --> 52:07.450] That makes perfect sense to me. [52:07.550 --> 52:07.950] Yeah, totally. [52:08.130 --> 52:08.570] A hundred percent. [52:08.570 --> 52:09.110] Okay. [52:09.350 --> 52:10.310] Then I really got what you said. [52:10.990 --> 52:11.830] No, thank you very much. [52:12.010 --> 52:12.170] Which I wasn't sure I did. [52:12.170 --> 52:15.830] I can tell you understood very well what we were talking about. [52:15.950 --> 52:16.590] Thank you very much. [52:20.700 --> 52:21.360] Last question. [52:21.520 --> 52:22.420] I think we have two minutes left. [52:22.780 --> 52:23.280] Thank you. [52:23.740 --> 52:24.960] Have you seen... [52:24.960 --> 52:34.820] From that triangle that you put up, are there examples of projects that you've seen that did a good job in more than one corner? [52:35.760 --> 52:36.320] Did a good job in more than one corner? [52:36.320 --> 52:36.520] That's... [52:36.520 --> 52:37.700] That's gonna put me on the spot. [52:38.320 --> 52:39.360] I mean, just... [52:39.360 --> 52:43.700] You gave the example of Occupy as a good hack of physical space. [52:43.800 --> 52:44.460] Yeah, yeah, yeah. [52:44.560 --> 52:47.700] And labor organizing as an example of time hacking. [52:48.980 --> 52:53.780] Have you seen anything that did well at more than one corner? [52:53.780 --> 52:57.640] Not that things have to do well at more than one corner, but... [52:57.640 --> 53:00.720] Well, I mean, that's a really good question. [53:00.900 --> 53:01.380] I mean... [53:03.200 --> 53:05.500] You know, I guess... [53:07.440 --> 53:09.960] I guess, you know... [53:09.960 --> 53:10.880] If I... [53:13.720 --> 53:14.780] That's a good question. [53:17.340 --> 53:18.880] I mean, I guess it's... [53:18.880 --> 53:19.620] I don't wanna... [53:19.620 --> 53:24.420] The point is maybe not to, like, say this is... [53:24.420 --> 53:25.460] It's not... [53:25.460 --> 53:25.940] It's... [53:25.940 --> 53:28.620] I don't wanna, like, use it as a way to rate. [53:29.460 --> 53:30.020] You know what I mean? [53:30.140 --> 53:30.300] Mm-hm. [53:30.300 --> 53:33.080] Like, it's much more of a way to, like... [53:33.080 --> 53:33.740] Like... [53:33.740 --> 53:34.740] Like... [53:34.740 --> 53:36.340] You know, because I think it needs... [53:36.340 --> 53:39.980] In an iterative model, like, it's about, like... [53:39.980 --> 53:41.620] Like, figuring out where... [53:42.200 --> 53:44.960] You know, so I think that, obviously, you know... [53:44.960 --> 53:49.380] Lots of organizations do these things well at times, right? [53:49.380 --> 53:52.590] And, like, you know, when they're growing or when... [53:53.240 --> 53:53.820] When, you know... [53:53.820 --> 53:55.400] Like, the Occupy example, right? [53:55.520 --> 53:56.400] Like, it... [53:57.320 --> 53:57.780] It... [53:57.780 --> 53:58.260] It did these... [53:58.260 --> 54:01.920] It probably did all of these things well for a period, right? [54:02.040 --> 54:02.380] And then... [54:03.960 --> 54:04.420] Then... [54:04.420 --> 54:05.100] Um... [54:05.580 --> 54:06.040] Was... [54:06.040 --> 54:08.740] Bulldozed by the NYPD or whatever, right? [54:09.060 --> 54:09.590] But, um... [54:11.040 --> 54:11.500] So... [54:11.500 --> 54:13.460] You know, I guess... [54:13.460 --> 54:15.480] I don't have a good answer for that. [54:15.480 --> 54:16.000] Um... [54:16.000 --> 54:17.360] But I think that it's... [54:17.360 --> 54:18.540] It's more about... [54:18.540 --> 54:21.460] Practices in particular moments, um... [54:21.460 --> 54:22.000] You know, that... [54:22.000 --> 54:23.400] That I can think of, you know, so... [54:23.400 --> 54:25.400] Yeah, I ask the question because I've... [54:26.280 --> 54:26.720] In... [54:26.720 --> 54:28.940] Other realms of work that I do, it's sort of... [54:28.940 --> 54:29.360] You... [54:29.360 --> 54:35.220] If you focus on just one, you can sometimes constrain possibilities in another space... [54:35.220 --> 54:35.980] In a way that... [54:35.980 --> 54:38.280] Isn't that harmful to the whole system? [54:38.620 --> 54:39.540] Yeah, I mean, I guess... [54:39.540 --> 54:40.040] That's interesting. [54:40.040 --> 54:40.760] Yeah, I... [54:40.760 --> 54:42.540] I think that the way to think of... [54:42.540 --> 54:43.060] I get... [54:43.060 --> 54:44.300] You know, the more you're talking about it... [54:44.300 --> 54:48.180] The way I was thinking about it would be during periods, right? [54:48.940 --> 54:49.400] Mm-hm. [54:49.400 --> 54:52.900] Like, how do we integrate all three, right? [54:52.960 --> 54:55.320] In periods of mobilization or... [54:55.320 --> 54:56.940] Or, um... [54:56.940 --> 54:58.100] Mass movement or... [54:58.100 --> 54:59.060] Or whatever, right? [54:59.220 --> 54:59.680] So... [54:59.680 --> 55:01.520] I think that we're out of time, so... [55:01.520 --> 55:02.740] Thank you very much, everybody. [55:03.060 --> 55:03.080] Thank you very much. [55:03.220 --> 55:03.520] Thanks for... [55:04.180 --> 55:05.120] Thanks for your attention.