Dennett Says Engineering Limits Force Return to Darwinian Selection

丹尼特：工程极限迫使人类重回达尔文式选择 自上而下的人类工程已触及分析极限，迫使设计者放弃深思熟虑的预先规划，利用自下而上的进化选择来解决超复杂难题。 丹尼特将生物自然选择自下而上、无意识的“研发”与人类智能设计有目的、自上而下的本质进行了对比。借助达尔文和图灵的“奇特倒置”，他阐明了在动物信号传递与人类神经架构中，强大的能力通常先于有意识的理解而存在。他认为，人类文化扮演了第二次内共生革命的角色，以信息迷因和语言等数字化认知工具侵入灵长类大脑。最后，丹尼特描绘了从盲目的达尔文适应到有意识的人类发明的转变过程，并最终指出一个“后智能设计”的新时代：人类工程师将利用进化算法和定向选择，去应对超出人类分析极限的挑战。 人类文明极大地改变了陆生脊椎动物的生物量，尽管人类基因在过去10万年间几乎没有变化，但该生物量占比已从1万年前农业萌芽时期的不足1%，飙升至如今估计的98%（主要由牲畜和宠物构成）。 (13:25) 丹尼尔·丹尼特将文化迷因构想为信息共生体，它们在大脑2000亿神经元的基质上安装虚拟机，实现了可与远古时期原核生物融合产生真核生物相提并论的第二次重大内共生转变。 (27:55) 人类工程正步入“后智能设计”时代，自上而下的深思熟虑式设计正让位于受控的达尔文算法、定向进化以及深度学习，以突破人类理解力的极限。 (58:04)

[2:43] Daniel Dennett: You can't do much carpentry with your bare hands, and you can't do much thinking with your bare brain. [51:04] Daniel Dennett: Meme evolution creates adaptations that enhance the fitness of memes independently of whether it enhances our fitness. [27:55] Daniel Dennett: Being alive is thus not a requirement for evolution by natural selection, because viruses aren't alive and they sure do evolve. [31:25] Daniel Dennett: One of the lessons of Darwinism is you want to be a Darwinian about Darwinism and recognize that it doesn't have an essence. [38:13] Daniel Dennett: We are now living in the age of intelligent design of culture.

[0:05] [Music] [0:12] [Music] [0:13] thank you John that's [0:15] [Music] [0:20] great what I'm going to talk about [0:22] tonight is R&D research and development [0:25] of two kinds research and development is [0:28] a design process exploiting information [0:32] in the environment to create maintain [0:34] and improve the design of [0:37] things and R&D always takes time and [0:40] energy and there are two main varieties [0:43] one is evolution by natural [0:45] selection and the other is human [0:47] intelligent design notice [0:53] lowercase there will not be a single [0:56] word Beyond this sentence about [0:58] uppercase intelligence design in this [1:01] talk [1:02] tonight the processes differ in two uh [1:06] in several fundamental ways first of all [1:08] evolution is purposeless it's [1:11] foresight it's extremely costly think of [1:14] the billions trillions of lives that are [1:18] wasted on bad trials and it's [1:23] slow intelligent design is purposeful [1:26] somewhat [1:28] foresighted governed by cost [1:30] considerations and usually relatively [1:33] fast but there's more differences than [1:35] that and I'm going to explore a few of [1:38] them Evolution may be slow and costly [1:40] but it's [1:42] brilliant the late Francis Crick once [1:45] had a joke about this what he called [1:48] orgel's second rule uh teasing his [1:51] colleague lesli orgal and that is [1:53] evolution is cleverer than you [1:55] are and anybody who's in evolutionary [1:58] biology knows that very often whether [2:00] you're working at the molecular level or [2:02] at the at the at the ecological level [2:04] you find some feature of some organism [2:07] that seems this is daff this is stupid [2:11] design and then later you can't come to [2:12] realize it's much much more clever than [2:14] you realized it's actually more clever [2:16] than you are so that's orgel's second [2:21] rule now intelligent design of the human [2:25] sort now exists we have lots of [2:28] intelligent designers around [2:31] and it's becoming ever more [2:33] intelligent with some some surprising [2:36] implications and that's what I'm going [2:37] to talk about [2:43] tonight on the left we [2:46] see a termite Castle an Australian [2:49] termite [2:50] Castle on the right we see G's famous [2:53] sagata Familia Church in [2:56] Barcelona they are remarkably similar in [2:59] shape and in construction even [3:04] inside and yet I propose they are built [3:09] and designed by profoundly different [3:12] processes the one on the left is built [3:16] by [3:18] termites who [3:19] are I hope I don't offend any termite [3:22] lovers here they're pretty [3:25] clueless they don't know what they're [3:27] doing they don't know why they're doing [3:29] it [3:30] there is no architect termite or boss [3:33] there's a queen termite but she's not [3:35] really the boss they're just mindlessly [3:38] cluelessly uncomprehendingly doing their [3:40] little thing and this amazing Castle [3:45] arises Gaudi on the other hand is almost [3:48] a comic caricature of the creative [3:52] genius the megal maniac Big Boss lording [3:56] it over everybody publishing manifestos [3:59] raising money with very grandiose [4:01] gestures and all the rest so you [4:03] couldn't have a better contrast between [4:06] GOI the topdown intelligent designer the [4:11] genius and the termites the clueless [4:15] bottomup [4:17] Builders so we have bottom up design [4:20] versus top down design and here's a [4:23] puzzle this is a real [4:26] puzzle a ter my Colony I looked this up [4:29] the other day might have as many as 70 [4:32] million clueless termites and Termite [4:35] colonies can do some very clever things [4:37] clever enough so that books have been [4:39] written that there's a book called The [4:41] Soul of the white ant which some of you [4:43] may have read which suggests that a [4:45] termite Colony has a soul well they do [4:48] they forage very intelligently they're [4:50] very efficient they're very they're very [4:52] clever as a as a colony in many ways but [4:55] of course you will have noticed they [4:56] don't write poetry or make spaceships or [4:58] things like that [5:00] 70 million clueless termites is not [5:02] enough to give [5:04] you a very great [5:07] intelligence a brain might be 200 [5:09] billion clueless neurons smaller but [5:12] even more [5:14] clueless and now here's the question how [5:17] do you get a gudy type mind out of a [5:20] termite Colony [5:22] brain if you think of your brain as a [5:25] termite [5:27] Colony several orders of magnitude [5:29] larger you wonder how can you get the [5:31] kind of top- down intelligence that GOI [5:35] exhibits out of a brain which is a very [5:39] large collection [5:41] of basically uncomprehending little [5:46] single cells [5:48] neurons now there's a short answer and [5:50] that's this a friend of mine once said [5:53] you can't do much carpentry with your [5:55] bare hands and you can't do much [5:56] thinking with your bare [5:58] brain think that's very much to the [6:01] point so if you don't use your bare [6:03] hands what do you use you use Thinking [6:05] Tools a termite colony is a bare brain [6:09] doesn't have any Thinking Tools Gaudi on [6:12] the other hand had a well equipped [6:14] mind equipped [6:17] by eons Millennia of [6:23] culture where'd he get his [6:26] tools well the wrong answer comes from [6:30] Freeman [6:32] Dyson lovely man great [6:34] scientist but he said this technology is [6:39] a gift of God after the gift of life it [6:43] is perhaps the greatest of God's gifts [6:45] it is the mother of civilizations of [6:47] arts and of Sciences I entirely approve [6:50] of his honoring of Technology but I [6:54] don't believe for a minute that he's got [6:56] the source right [6:59] so that's the wrong answer and here's [7:01] the long [7:02] answer cultural [7:05] Evolution cultural evolution in our [7:08] species and only in our species designed [7:11] Thinking Tools that now impose novel [7:13] structures on our [7:16] brains evolved virtual machines that [7:20] then run on the basic underlying wetwear [7:23] of our neurons and gal [7:26] cells and it's that long answer that I'm [7:29] not to try to articulate a little bit [7:33] more a wonderful Book You'll see as I go [7:35] along this is a sort of book report talk [7:38] I'm going to be mentioning a number of [7:39] books that I think very highly of one of [7:41] them is this book by John Maynard Smith [7:43] the late great one of my heroes John [7:45] Maynard Smith and Earth zachari from [7:49] Budapest the major transitions in [7:51] evolution published in '95 and in it [7:54] they describe how Evolution evolves how [7:58] over the three and a half billion years [8:01] of evolution there have been some [8:03] profound transitions which change it's [8:06] like shifting gears Evolution goes into [8:08] a higher gear that can then explore [8:10] design space more [8:12] fruitfully more efficiently here is [8:15] their list there's the eukaryotic [8:17] Revolution about which more a little bit [8:19] more in a moment sex you'll be happy to [8:21] know is one of the major transitions [8:24] multicellularity cell differentiation is [8:26] another and then language in human [8:28] culture [8:29] are the uh fourth and fifth and which [8:32] comes first is an open question which [8:34] I'm trying to close but it's not [8:37] easy [8:39] now I'm going to talk only about [8:41] eukaryotic Revolution and language and [8:43] human culture because I want to point to [8:45] a striking and surprising similarity [8:48] between these two major [8:50] transitions this is my favorite diagram [8:53] of the tree of life every living thing [8:56] that has ever lived is represented in [8:58] one way or another on this tree and [9:01] let's see I think probably this outer [9:03] edge here can you you can see the arrow [9:07] yeah that's the present so everything [9:09] that's alive today is along this Outer [9:12] Rim here the mammals you know here are [9:14] we way down here on say on this Branch [9:17] right here this is the origin of Life [9:19] three and a half billion years ago and [9:22] as you can see first there were the [9:24] bacteria or the archa of Len Eisenberg [9:27] whose tree of life this is [9:31] Hedges his bets about whether the archa [9:33] are as their name suggests the first but [9:36] they may be they may not be we don't [9:38] have to settle that but for about a [9:40] billion years what we had was just these [9:42] single celled [9:44] organisms the so-called [9:47] procaryotes and then something wonderful [9:50] happens and you can see it right there [9:52] it's where that great sudden turn [9:56] happens find my pointer again there it [10:00] is right about there we get the great [10:05] eukaryotic Revolution everything else [10:07] you see all the colored things those are [10:09] all UK [10:10] carots we're UK carots basically to a [10:14] first approximation every living thing [10:16] that's you can see with a naked eye is a [10:19] eukaryot multi-celled eukaryotic [10:22] organism so what is this great [10:25] Revolution it's this [10:29] on the left we see a simple Pro carot on [10:33] the right we see a complicated ukar you [10:36] as the as the suffix as a prefix [10:38] suggests means good or better they're [10:40] bigger they have more moving Parts [10:42] they're much fancier they're simply more [10:45] versatile they're bigger all right so [10:47] how do we get from the simple cells on [10:49] the left to the cell on the right by an [10:52] amazing thing that only had to happen [10:55] once one day after a billion years or so [10:59] of UK of procaryotes swimming not [11:02] swimming well drifting around in the [11:05] water to different procaryotes not [11:10] twins two different procariotas with [11:13] perhaps two billion years of independent [11:17] R&D to create their particular Powers [11:20] they bumped into each other it's no [11:22] doubt happened a [11:23] lot but on this occasion instead of [11:27] a e B engulfing B and using B for energy [11:32] in parts or [11:35] B taking a apart from the [11:39] inside they join [11:42] forces in an [11:44] endosymbiotic relationship they became a [11:47] new thing an AB and the ab thing was [11:52] fitter Than A or B by [11:56] themselves and so they proliferated and [11:58] they had a common fate and they began to [12:01] their genomes began to merge and that [12:03] was the birth of the uh UK carotic cell [12:08] and the great fossil trace of that as [12:11] everybody should [12:13] know is in the fact that eukaryotic [12:18] cells have two or actually more two [12:21] genomes there's your nuclear genome your [12:24] nuclear genome that's for instance your [12:26] human DNA and then there's your [12:27] mitochondrial DNA and the mitochondria [12:31] are The Descendants the direct [12:33] descendants of early procaryotes that [12:36] join forces with u with other [12:39] procaryotes to form the eukaryotic cells [12:41] you get all your mitochondrial DNA from [12:44] your mother uh none from your [12:47] father so this is uh a great moment this [12:52] coming together this chance Collision a [12:56] moment of endosymbiosis symbiosis living [12:59] together Endo because one's inside the [13:01] other and uh it was the late Lynn [13:05] margulis who first really drove that [13:08] point home she wasn't the one who [13:10] invented the idea or first thought of it [13:12] but she's the one who persisted in spite [13:15] of ridicule and and much dis [13:18] disagreement and disapproval and she [13:20] eventually won the case and it's in all [13:21] the textbooks now so uh we owe a lot to [13:25] Lynn for that uh uh wonderful campaign [13:29] she fought on behal half of [13:31] endosymbiosis so what we have here is a [13:33] great case of Technology transfer you've [13:36] got two [13:39] independent traditions of R&D they come [13:42] together and boom you get this sudden [13:44] explosion of competence that you didn't [13:46] have [13:48] before now I want to describe another [13:53] explosion the mccre [13:56] explosion this was 10 th years ago Paul [14:01] mccre the late Paul mccre was a a [14:04] Caltech engineer some of you probably [14:07] know of him he was the uh designer of [14:09] the gossamer Albatross the human powered [14:13] plane that flew across the English [14:15] Channel uh very much into green uh uh [14:19] environmental engineering and he [14:22] calculated that 10,000 years [14:25] ago that's just a twinkling ago in in [14:29] geological or biological time the human [14:32] population this is at the dawn of [14:35] Agriculture plus their livestock and [14:38] pets was less than 1% maybe a tenth of a [14:42] percent of the terrestrial vertebrate [14:45] biomass by weight that is to say of the [14:48] animals we're not including the insects [14:50] or the worms we're not including the [14:51] fish and the sea or any of the [14:53] unicellular organisms we're just [14:56] including animals basically a [14:58] terrestrial vertebrates [14:59] and 10,000 years [15:02] ago less than [15:04] 1% what do you suppose the percentage is [15:09] today rather more would anybody Hazard a [15:12] guess 10% [15:14] 10% anybody think it might be higher [15:16] than [15:20] 10 I heard 99 [15:23] no [15:26] 98 well where is it there it is 98% by [15:31] by his Maybe by now it's [15:33] 99 Paul mccre made this a few years ago [15:37] we and our most of that is cattle by the [15:40] way we have engulfed the planet in one [15:44] of the most remarkable transitions ever [15:48] and that's it's happened in the last [15:49] 10,000 years in a [15:52] twinkling faster than the Cambrian [15:54] explosion this is the fastest and most [15:57] dramatic change in life forms well maybe [16:01] maybe some of the great extinctions [16:03] would be would be viable uh candidates [16:06] for just as uh for similarly uh sudden [16:11] changes to the biosphere what is [16:14] responsible for well he has a wonderful [16:16] thing to say about it he says over [16:17] billions of years on a unique sphere [16:21] chance has painted a thin covering of [16:23] Life complex [16:25] improbable wonderful and fragile sudden [16:28] suddenly we humans have grown in [16:30] population technology and intelligence [16:33] to a position of terrible power we now [16:35] wield the [16:38] paintbrush and our genes are just the [16:40] same as the genes of people 100 thousand [16:42] years AG very a few important a few [16:45] important differences but not many [16:47] genetic differences between us and uh [16:50] and our ancestors going back even a few [16:53] hundred thousand years but look at [16:55] what's changed technology and [16:58] intelligence is the [16:59] key just as Freeman Dyson [17:03] said so this was another great [17:05] technology [17:06] transfer and I'm going to put it in sort [17:09] of deliberately dramatic [17:12] terms the invasion of human brains by [17:16] symbiotic Thinking [17:19] Tools [17:21] memes Richard doin's memes from the [17:24] selfish Gene now I know that a lot of [17:27] people have a visceral dislike of the [17:30] idea of [17:31] memes and I have been fending [17:35] off second rate and Third Rate [17:38] objections to memes now [17:40] for 20 years and more and there are even [17:45] a few almost first trade objections [17:48] which I will be dealing with sarily in [17:51] my next book um I'm here to tell you [17:55] memes are [17:56] okay and they really do some wonderful [17:59] work I'm going to give you a sketch of [18:02] some of the work that they do and show [18:04] you uh why you should if you if you [18:06] think memes are a bad idea you might [18:08] want to change your [18:11] mind these Thinking Tools we don't [18:14] inherit them via our genes they're not [18:17] instincts we're not born with them we [18:19] don't have to design them ourselves [18:21] nobody has nobody in this room had to [18:23] design calculus or long division or [18:26] alphabetization or language or the wheel [18:30] we acquire these in our culture in our [18:34] education in our in growing up and [18:37] learning we don't have to design them [18:39] ourselves and here's the really [18:41] important Point nobody has to design [18:45] them any more than anybody has to design [18:49] the Nightingale or the palm [18:51] tree they are products of an R&D process [18:55] of cultural Evolution not genetic [18:58] Evolution but cultural Evolution which [19:02] is very much like evolution by natural [19:05] selection of genes but in this case [19:08] we're talking about the evolution of [19:11] memes now the mccre explosion was an [19:15] explosive amplification of of human [19:19] competence that's just [19:21] obvious it was competen largely without [19:25] comprehension in the early days it's [19:27] only recently very recently in many [19:30] regards only in the last 100 years or [19:32] less that we've really come to [19:33] understand what the heck happened and to [19:36] understand a lot of the tools that we're [19:38] using nevertheless it happened thanks to [19:41] those tools and this competence without [19:44] comprehension has evolved into [19:46] competence with [19:48] comprehension and this is what I like to [19:50] call the darwinian strange inversion [19:54] reined one of my favorite passages of [19:56] criticism of Darwin was was written by a [19:59] man named Robert Beverly McKenzie in [20:02] 1868 um I love this passage because the [20:05] passion of it the the the capital [20:07] letters are in the original and here's [20:10] what McKenzie had to say in the theory [20:13] with which we have to deal absolute [20:15] ignorance is the artificer so that we [20:18] may enunciate as the fundamental [20:19] principle of the whole system that in [20:21] order to make a perfectly beautiful [20:23] machine it is not requisite to know how [20:25] to make [20:26] it this proposition will be found on [20:29] careful examination to express in [20:31] condensed form the essential purport of [20:34] the theory and to express in a few words [20:37] all Mr Darwin's meaning who by a strange [20:41] inversion of reasoning seems to think [20:44] absolute ignorance fully qualified to [20:47] take the place of absolute wisdom in all [20:49] the achievements of creative [20:51] skill [20:53] exactly that's it that's just what [20:56] Darwin [20:57] showed and it's a strange inversion of [21:00] reasoning it's still strange to many [21:02] people they have a hard time getting [21:04] their head around this how could [21:05] absolute ignorance do all this brilliant [21:08] design [21:10] work so here's Darwin's strange [21:13] inversion of reasoning according to [21:15] McKenzie in order to make a perfect and [21:17] beautiful machine it's not requisite to [21:19] know how to make it now I'm going to [21:22] talk about touring and his strange [21:24] inversion you'll notice a [21:26] similarity in order to be a perfect and [21:29] beautiful Computing [21:31] machine it is not requisite to know what [21:33] arithmetic [21:37] is Darwin and touring before [21:41] touring computers were people [21:44] intelligent people they probably read [21:46] maths in University out of work they [21:49] work doing computation what are you I'm [21:50] a computer I work for such and such a [21:52] company doing computation what touring [21:55] realized was that wasn't necessary he [21:57] could boil all the comprehension out and [22:00] give you just basic minimalistic no no [22:04] comprehension at all and he could get [22:06] arithmetic and if you got arithmetic and [22:08] conditional branching it's Off to the [22:09] Races you can compute anything that's [22:11] what touring showed so what Darwin and [22:14] touring [22:15] showed and this is a strange inversion [22:17] is comp compet competence without [22:23] comprehension the process of natural [22:25] selection doesn't understand anything [22:28] and doesn't have [22:29] to similarly the CPU on your computer [22:34] doesn't have to understand [22:36] anything and yet they're both remarkably [22:40] competent processes that can build and [22:42] build and build and do more and more R&D [22:45] and this bottomup R&D is what we've seen [22:48] ever since in other words mind or [22:50] Consciousness or understanding is not [22:52] the cause the first cause it's an effect [22:55] and a very recent effect [22:58] now termites are not intelligent [23:01] designers beavers are not very [23:03] intelligent [23:06] designers we are the first intelligent [23:09] designers in the tree of life and [23:17] we're way over there that's about 6 [23:21] million years that little why that [23:22] little fork and so intelligent design [23:25] starts in one species about there [23:29] and that's the first intelligent [23:31] design since life started on the [23:36] planet a term of mine which I wish I [23:40] could recoin and do otherwise because a [23:42] lot of people don't like this term it [23:43] gives them the Willies or something heie [23:46] jibbies is free floating [23:49] rationals what's a free floating [23:50] rationale it's a reason why something is [23:53] the way it is but it's nobody's [23:55] reason trees do things for reasons as [23:58] any botanist can explain to you Bungie [24:01] do things for reasons the biotic world [24:04] is saturated with Reasons from the [24:06] molecular scale on up and we do things [24:09] for reasons we shiver we vomit we blink [24:13] they're not our reasons they are the [24:15] reasons why we do them we don't have to [24:16] know [24:17] them we do not have to comprehend these [24:20] reasons for these to be the reasons that [24:21] we're acting as we do and we even also [24:25] choose and decide and act for reason [24:28] that we don't need to [24:31] appreciate I'm going to give you an [24:33] animal example and suggest that although [24:35] it looks at first strikingly unlike what [24:37] we human beings do it's not that [24:39] different [24:41] starting um you've probably seen David [24:43] atenor film or some such nature [24:46] documentary where you see these [24:48] Preposterous wild High leaps that the [24:51] gazel do and they're being chased by say [24:53] lions in [24:55] Africa it's called starting [24:58] why do they do it it looks risky it [25:00] looks dangerous it looks show offy [25:02] what's going [25:03] on well we now have a very good idea [25:06] what the reason is why they do why they [25:09] do it this is the free floating [25:11] rationale of this particular [25:14] Behavior it's sending a signal don't [25:16] bother chasing me I can make these [25:18] energetically expensive leaps and still [25:21] outrun you go after my cousin who [25:25] can't it's a vivid case of what's known [25:28] know as costly signaling [25:31] Theory and it has to be costly otherwise [25:34] it wouldn't be credible if all the [25:35] animals could do it the lion would be [25:38] wise not to believe but the lion does [25:41] believe this communicative act and [25:43] doesn't chase the the gazel that can St [25:48] so it's serving a purpose it is [25:50] transferring information from the [25:53] gazelle to the lion they both [25:56] benefit it's a stable [25:58] system but here's the important thing [26:02] neither the gazelle nor the lion needs [26:03] to understand this this signal this [26:06] speech act as far as the gazelle is [26:09] concerned it doesn't know why it wants [26:11] to throw these ridiculous leaps it just [26:13] does it gets a great urge if it can to [26:16] throw those leaps and it does it's the [26:19] beneficiary of this clever strategy [26:22] without understanding it at all and [26:24] similarly the lion doesn't have to [26:26] figure out oh [26:28] the ones that can leap must be faster [26:31] and they're showing off to me no no [26:33] don't put soliloquies like that in the [26:36] in the lion's head if you want to put a [26:38] monologue in the lion's [26:40] head the lion is just [26:43] thinking oh I don't want to chase those [26:45] guys I don't know why but I they're just [26:47] not attractive somehow I'll go for the [26:49] ones that don't do those leaps they [26:52] don't have to understand the system [26:54] works [26:56] anyway hint [26:58] a lot more of human communication is [27:01] like [27:02] stotting than tradition would have it [27:05] and a lot of animal communication is [27:08] exactly like [27:10] starting this is competence without much [27:13] comprehension because you don't really [27:15] have to [27:17] comprehend and it's a good thing that we [27:19] can have examples of meaning and [27:21] communication without comprehension [27:23] because if we're going [27:26] Neuroscience we got a lot of signal [27:28] going on in the neurons between the eyes [27:30] and the lateral geniculate nucleus and [27:33] V1 and V2 and all of these different [27:35] areas of the brain all these signals are [27:38] being sent and the neurons don't have to [27:41] understand any of [27:42] it but there are reasons why they're [27:44] doing what they're doing and information [27:47] is being transmitted but it's just not [27:49] being comprehended by the receivers [27:52] doesn't have to [27:55] be so the problem that cultural [27:58] Evolution solves is how we get a gouty [28:00] mind out of a termite Colony brain how [28:03] do we get intelligent design with [28:04] representation of the reasons gouty's [28:06] type of intelligent design or touring's [28:10] type of intelligent design out of 200 [28:13] billion mindless [28:15] neurons it was the Second Great [28:18] endosymbiotic [28:20] Revolution we are it's human culture we [28:24] are Apes with infected [28:27] brains our brains from the day we're [28:30] born in fact even before we're born [28:34] already memes are entering our brains [28:37] through our [28:38] ears and through our eyes and taking up [28:41] resonance and building novel Virtual [28:45] machines thinking machines Thinking [28:47] Tools in our brains that change the [28:49] functional architecture of our [28:53] brains um viruses are not alive they [28:58] don't have a metabolism basically they [29:01] are just strings of nucleic acid with [29:04] attitude that is to say thanks to their [29:07] sequence they have a shape and thanks to [29:10] their shape they have a amazing [29:12] competence without any comprehension at [29:14] all to infiltrate into cells and trick [29:18] those cells into making copies of them [29:20] instead of of their own genetic [29:22] material that's how viruses [29:25] replicate and of course [29:28] evolution of viruses is classic [29:31] evolution by natural selection being [29:34] alive is thus not a requirement for [29:36] evolution by natural [29:38] selection because viruses aren't alive [29:41] and they sure do evolve the evolution of [29:44] HIV since it was first sequenced has [29:47] involved more change than the human [29:50] genome has changed since we parted [29:53] company from our common ancestor with [29:55] chimpanzee [29:58] well you might say but how about being a [30:00] material thing is that necessary is that [30:02] necessarily a requirement for evolution [30:04] maybe not being alive but certainly have [30:06] to be a material thing and the answer is [30:09] no you [30:11] don't viruses depend on living cells to [30:14] reproduce memes which are informational [30:17] things depend on living brains to [30:23] reproduce and they're not [30:25] made out of any anything except [30:31] information this is a hard point for [30:33] many people to accept and some people [30:36] are some very smart and clever [30:39] sophisticated people are not happy with [30:41] this line of mine but I'm going to [30:43] present it to you and try to defend it [30:46] first of all I want to point out this is [30:47] not dualism or if it is then the [30:50] hardware software distinction is dualism [30:53] but of course it's not in any bad sense [30:56] it's a perfectly respectable dualism how [30:58] many of you believe in the existence of [31:02] software yeah I mean what is Bill Gates [31:06] a fraud how did he make his money he [31:09] sold software was it valuable yes does [31:12] it exist of [31:14] course what is it made [31:16] of [31:18] bits that's what it's made [31:22] of here's another book I recommend [31:25] highly Peter Godfrey Smith philosopher [31:26] of biology was it Harvard now he's at um [31:29] NYU darwinian populations and natural [31:32] selection Oxford University press [31:35] 2009 in this book Peter introduces [31:38] something that he calls darwinian spaces [31:41] and I've come to think of this as one of [31:42] my favorite new Thinking Tools I didn't [31:44] put it in intuition pumps because I [31:46] would have had to do too much teaching [31:49] on the side about evolutionary biology [31:51] and I thought well I'll save that I'll [31:53] use these and introduce them in the next [31:55] book uh so let me see if I can [31:58] characterize this this is just a three [32:01] space of A Sort that you see in many [32:03] different scientific graphs um and the [32:06] thing is you can take any three [32:09] properties in which there's variation in [32:12] in In Living phenomena and put them on [32:14] the three axis X Y and Z Zed for you uh [32:19] uh and just consider all the other [32:21] dimensions fixed at some neutral vanilla [32:24] value or however you want we look at [32:26] three dimensions at a time and we can [32:27] pick and choose what dimensions we put [32:29] and then we can look at comparing [32:33] phenomena in this space to see how [32:36] darwinian they [32:38] are because one of the lessons of [32:40] Darwinism [32:41] is you want to be a darwinian about [32:44] Darwinism and recognize that it doesn't [32:47] have an Essence there isn't just one [32:50] sort of Darwinism there's all sorts of [32:52] sort of darwinian phenomena that are [32:56] almost darwinian rather wian it's rather [32:59] like the transition from therapsids to [33:01] mammals you got a lot of creatures that [33:04] are neither obviously mammals nor [33:06] obviously therapsids who are the [33:08] ancestors of mammals perfectly good [33:11] living creatures they just didn't fit [33:13] into those pigeon holes well they were [33:16] neither mammals nor thorpes or maybe [33:18] they were both don't even worry about it [33:20] you don't have to draw the line [33:22] similarly we should look for there to be [33:24] darwinian phenomena which are only sort [33:28] of [33:29] darwinian and you'll see in these [33:32] diagrams the Paradigm is up here at 111 [33:35] full doses of all three dimensions [33:39] that's the way he draws these diagrams [33:40] so we have the zero point and the [33:42] dimensions he put up here this is his [33:44] first one are sort of standard as as [33:48] everybody knows I hope you have to have [33:50] very high fidelity replication in the [33:53] genes to sustain Evolution if if the [33:56] replication makes [33:58] errors uh accumulate too fast then [34:01] Evolution stops that's known as the [34:02] error catastrophe but it can't be [34:04] perfect if if the Fidelity of of [34:08] replication of genetic material was [34:10] perfect then you'd have no mutations and [34:12] you an evolution would have come to a [34:14] stop so in the parade cases of evolution [34:17] you've got to have um [34:20] uh very you have to be very high on the [34:24] H scale the heredity Fidelity scale but [34:26] not all the way of perfection this is if [34:30] you want to have a naturalistic meaning [34:32] of original sin that should be [34:36] it the S Dimension dependency of [34:39] realized Fitness differences on [34:41] intrinsic [34:43] properties is best understood as a [34:45] contrast let's look at something that is [34:47] selected for a non-intrinsic [34:50] property right now in this room if we [34:52] held a like a tennis tournament an [34:55] elimination tournament a coin flipping [34:57] tournament somebody'd win the tournament [34:59] but it would not be as it were for an [35:01] intrinsic property they'd just be lucky [35:04] and that would mean there' be no reason [35:05] to think that on the very next coin flip [35:07] they'd be any more likely to win than [35:09] anybody else [35:12] right well there are many extrinsic [35:15] properties one of the most interesting [35:18] is the realtor's favorite location [35:20] location location and that's why Godfrey [35:24] Smith has put human cells up here [35:28] they are selected uh there's very high [35:30] fidelity of replication of the genetic [35:33] material in human cells basically all [35:35] the cells in your body have the same [35:37] genome there's some mutations that do [35:39] occur um and you have also uh a [35:42] smoothness of Fitness landscape I'll get [35:44] to that in just a moment but the main [35:46] thing is that for instance in in [35:48] embryonic development you have many more [35:50] neurons born then are going to [35:52] survive the ones that are in the right [35:54] place at the right time make the [35:56] connections they survive the other ones [35:57] get selected out and and uh their [36:00] materials are reused for the Next [36:02] Generation in in embryonic development [36:04] so it's a very darwinian process but it [36:07] isn't perfectly darwinian it isn't the [36:10] full-fledged parade case because you [36:12] don't have selection for cause you have [36:15] selection for an extrinsic property [36:17] location even though the the neurons [36:20] themselves may all be alike the one that [36:22] happens to be in just the right place is [36:24] the one that [36:25] survives I won't bother talking about [36:28] the other uh the other dimension there [36:30] it's smoothness of Fitness landscape if [36:32] you have a rug rugged uh uh Fitness [36:35] landscape then evolution is hard because [36:37] small steps in any direction May simply [36:40] throw you off a cliff instead of uh [36:42] slightly higher up the hill to the to [36:44] the to the summit of of Fitness space u [36:47] you if you understand what a fitness [36:50] landscape is so we'll move [36:52] on this is one of my applications of uh [36:57] pgs [36:58] Peter Godfrey Smith spaces and I want to [37:00] look at the origin of life just very [37:03] swiftly um before up in the upper right [37:07] hand corner we have the darwinian case [37:08] of bacteria they evolve by genuinely [37:12] darwinian means because they replicate [37:14] but before you have bacteria or whatever [37:17] the first living forms were you don't [37:19] have replication and a lot of people [37:22] Skeptics origin of Life Skeptics say [37:25] well there has to be a miracle no [37:27] because you have all these quasi [37:29] darwinian Pro processes which can make [37:32] the probability of getting to a [37:34] replicator much more likely you have [37:37] differential [37:38] persistence versus differential [37:41] reproduction some [37:43] processes [37:45] Prebiotic abiotic processes simply [37:48] Outlast others more stable and since [37:51] they're outlasting them they can [37:53] gather what are like mutations and hence [37:57] this can change that can change the [37:59] probability the odds of other things [38:01] happening when you have thousands of [38:04] asynchronous Cycles all working together [38:07] this keeps generating novelty generating [38:10] new combinations and in the fullness of [38:13] time you get back here and nobody knows [38:15] how to nobody knows how to fill this [38:18] space in time we start in an abiotic [38:22] world and some trajectory takes us up [38:25] there to the darwinian case [38:28] we don't know what it is but we sort of [38:29] know some of the dimensions that have to [38:31] be moved through whether a membrane [38:33] comes first or whether reproduction or [38:35] metabolism comes first you've got to [38:37] have all three by the time you get to [38:39] bacteria but the order in which they [38:41] come is very much up for grabs [38:44] now here we get to the one that [38:46] matters here's my main diagram of [38:50] cultural Evolution and you'll see that [38:55] I've put the termite Castle down here [38:57] here this is 0 0 0 but now I've inverted [39:00] Darwin's inversion and I put the pure [39:02] darwinian case down in this corner where [39:05] it's bottom up no comprehension and [39:09] where the search in the space is [39:11] essentially random it's not it's not [39:14] directed search at all there's no [39:15] information used it's it's just coin [39:17] flip search what you search so this is [39:20] our Pure darwinian case the termite [39:23] Castle culture and up here in this [39:26] corner is intelligent [39:29] design and what I'm suggesting is that [39:32] cultural Evolution over thousands of [39:35] years but not Millions only thousands of [39:38] years has moved from very [39:42] darwinian to very intelligent design we [39:44] are now living in the age of intelligent [39:46] design of culture so we want to look at [39:50] this D darwinizing of cultural [39:53] Evolution from the first beginnings of [39:56] for inst [39:59] language and that's why we see the [40:01] termite Castle down at the bottom and [40:03] why I've put up in the intelligent [40:05] design Corner you'll notice I've put [40:07] Picasso's name why did I put Picasso [40:11] there not because I think he's the [40:13] smartest most intelligent designer ever [40:16] but because he said he [40:24] wasu this is a brilliant lie [40:29] Baler Dash to use a polite [40:33] word he did a lot of [40:38] searching in order to [40:41] find I don't search I find notice what [40:45] he's saying is not for me random search [40:48] not for me grubby trial and error I just [40:50] leap to the highest peak in the design [40:53] space every time I comprehend perfectly [40:56] uh nothing hemsi about me I am at the [41:00] very Pinnacle I am an intelligent [41:01] designer well he this J appr is a [41:06] perfect motto for the intelligent [41:08] designer but as I say it's never [41:12] realized it certainly wasn't realized by [41:15] Picasso he was a very clever [41:18] dude I think a lot of his intelligence [41:20] was that although he did a lot of [41:22] searching made sometimes hundreds of [41:25] sketches his Brilliance was signing and [41:28] selling the sketches along with the [41:31] finished [41:34] product so Picasso couldn't meet that [41:37] but he can serve as emblematic of of [41:40] that extreme position on the [41:46] graph I want to thank Matt Ridley my [41:48] friend Matt Ridley for this wonderful [41:51] slide um two cultural artifacts on the [41:55] left you have an ash and hand a on the [41:58] right you have the mouse of course two [42:01] products of human [42:04] culture [42:05] nobody invented the Ashan hand ax nobody [42:11] Douglas engelbart invented the [42:14] mouse the hand ax was used with hardly [42:17] any changes at all for close to a [42:19] million [42:22] years there are different theories about [42:24] what it was exactly for my favorite is [42:27] that it was the human artificers version [42:30] of the peacock's [42:32] taale that basically you are saying this [42:35] is costly [42:37] signaling I am so good you say this to [42:41] the ladies that I can make all these [42:43] hand axes and still stay [42:46] alive either I'm very good at making [42:49] handaxes or I'm very good at stealing [42:51] handaxes I got a lot of you want to come [42:53] up and see my [42:55] handaxes this was this was uh actually [42:58] was Merck Cohen's idea that that the Ash [43:01] and hand ax was was a bit of costly [43:03] signaling and there's a one particularly [43:05] interesting data in its favor and that [43:07] is that troves of these have been found [43:10] you know dozens never used all together [43:13] in a in a pile A Little Treasure pile of [43:15] Ash and hand axes lovingly crafted never [43:18] used for [43:19] anything so maybe that was come up and [43:21] see my hand axes we don't know but in [43:24] any case that was an example of sort of [43:28] above the termite but [43:30] long way down low on the on the [43:34] scale Norbert weiner who is the youngest [43:38] and perhaps the most famous graduate of [43:39] my University tus University the founder [43:42] of cybernetics the coiner of the term [43:44] cybernetics uh once said information is [43:47] information not matter or energy no [43:50] materialism that does not admit this can [43:53] survive at the present day and I want to [43:54] underline that I think he's exactly [43:56] right as I say information is not matter [44:00] or energy it's information and we got to [44:02] take it seriously and I want to look at [44:04] some things made of [44:07] information [44:12] habits words poems songs jokes games [44:17] Sudoku crossword puzzles techniques dead [44:21] reckoning surveying long division basian [44:23] statistics [44:24] PCR and software [44:27] these are all things made of information [44:30] and I want to point out only the [44:32] software is made of bits I'm not talking [44:35] about bits when I'm talking about [44:36] information I'm talking about [44:37] information in a more fundamental [44:39] sense Shannon information measured in [44:42] bits is a recent and very important [44:45] refinement of a one concept of [44:47] information but it's not the concept I'm [44:49] talking about I'm talking about the [44:51] concept of information where when one [44:54] chimpanzee learns how to uh crack nuts [44:57] by watching this mother crack nuts [45:00] there's information passed from mother [45:03] to offspring and that is not in bits [45:06] that is that is an informational [45:08] transfer that is not accomplished in in [45:11] any Shannon channel that is worth [45:14] talking [45:16] about so habits I've just mentioned one [45:20] uh chimpanzees [45:22] learning I want I put this slide in [45:25] because I want to acknowledge that yes [45:27] we're not the only species with [45:30] culture arguably whales have two or [45:33] three or seven items of culture and [45:34] chimpan have maybe a dozen culturally [45:37] transmitted habits that are not in the [45:41] genome but nothing goes explosive [45:44] nothing goes Comm Comm minatori except [45:45] in our species we're the ones where [45:48] culture really takes off so now let's [45:51] look at [45:53] words in the [45:55] beginning we had what I want to call [45:57] synanthropic [45:59] words synanthropic species are species [46:02] that evolve by natural selection but are [46:05] not domesticated we don't own them but [46:07] they are sin anthropos they are with us [46:10] human beings so synanthropic species [46:13] would include mice and rats and pigeons [46:18] and bed [46:19] bugs and body lice they're s we don't [46:24] own them we don't domesticate them but [46:27] they are evolved to live and thrive in [46:29] our [46:31] company barn swallows chimney Swifts [46:35] Birds and the first words I argue were [46:39] synanthropic words the [46:42] people that were infested with these [46:44] didn't know what they were doing they [46:46] didn't know they were talking they [46:47] weren't even really paying attention to [46:50] what was happening but words were [46:51] beginning to take up residence in their [46:53] world and move from head to head via m [46:56] an ear and this was the birth of [46:59] language there's a long story to be told [47:02] about how that all works out I'm not [47:04] going into that tonight because I'm just [47:05] giving you the the bird's eye view um [47:09] then we move into a period where we have [47:10] domesticated [47:12] words these are not [47:15] just species of meme that thrive in [47:20] human company but we're beginning to pay [47:22] attention to controlling their [47:26] replication [47:27] which is usually the standard Mark of [47:29] domestication if you control the [47:31] reproduction of a species for your own [47:34] purposes then you've domesticated that [47:37] species so we have domesticated words [47:39] then we have coined [47:41] Words which is a little bit like [47:43] genetically [47:45] engineered organisms these are invented [47:48] by they have particular authors meme of [47:50] course is a good example of a coined [47:52] meme Dawkins is the coiner not one word [47:56] in 10,000 in our vocabulary is a coined [48:00] word most of the words have no authors [48:03] no creators at all they are products of [48:05] cultural [48:08] Evolution and then we get technical [48:11] terms which are takes it up even a notch [48:14] further and then we finally get to [48:17] internet [48:18] memes and when I put this up here I know [48:22] some of my students and others they [48:23] suddenly think aha now you're in the [48:26] trouble you're in the soup now denn it [48:29] why because they think this is just the [48:31] redu you OD absurdum of do Dawkins [48:34] concept of memes Dawkins introduced [48:36] memes to be evolvers to be things that [48:40] evolve by natural selection but internet [48:42] memes are the Creations the intelligent [48:45] the creations of presumably intelligent [48:47] designers there's competitions on the [48:49] internet who can design the meme that [48:52] goes viral best so this is would seem to [48:55] be the very [48:58] uh uh an intelligently designed meme [49:00] would seem to be a contradiction in [49:02] terms and I met for a while I thought so [49:05] too and I would I deplored the fact that [49:08] Dawkins wonderful word and concept was [49:11] being sullied was being was being [49:14] cheapened by being transformed in this [49:17] way into the word it is on on the [49:19] internet and then I suddenly realized no [49:25] no maybe this is a contradiction in [49:28] terms so [49:31] what after all a splitable atom is also [49:34] a contradiction in [49:35] terms the word atom initially meant [49:39] unsplittable thing a thing without Parts [49:43] a complete unit without any parts at all [49:46] now we have splitable atoms the very [49:48] idea of subatomic particles was a [49:50] contradiction in terms when it was first [49:52] introduced but we went along with we [49:54] kept the term and we understood that [49:58] it was in a certain sense misnamed where [49:59] we had we had a richer interpretation of [50:01] what Adams were same thing is true of [50:03] memes what we should realize is that the [50:06] original memes down in the bottom [50:09] layer when human cultural Evolution was [50:12] very darwinian they were pretty much [50:14] exactly what Dawkin said they were and [50:16] they've since become more and more [50:18] intelligently designed more and more [50:21] domesticated to where we now have memes [50:25] we'll still call them that even though [50:27] they're not products of darwinian [50:30] natural selection they're products of [50:32] intelligent design it reminds me of [50:34] course of an earlier contradiction and [50:36] that was Darwin's the very one that [50:38] McKenzie pointed out the very idea we've [50:41] reinert Darwin's strange [50:46] inversion KU Bono from the law who [50:49] benefits is a question that evolutionary [50:52] biologists should always ask themselves [50:55] and [50:57] we talk about three kinds of symbiant in [51:00] biology mutualists that do good for us [51:04] commensals and parasites only the [51:06] parasites are bad for our our our [51:08] fitness [51:09] reducing and as you probably know [51:13] there's actually trillions of symbient [51:17] in your body right now that you couldn't [51:20] that you couldn't live without they're [51:21] mutualists they're the floor and your [51:23] gut and so forth and there actually [51:25] trillions more of viruses which are not [51:28] doing you any harm all those Symbian [51:31] well the same is true of memes there are [51:34] mutualists commensals and [51:37] parasites and one of the key insights of [51:40] mimetics this is I think the key Insight [51:42] of memetics is that Meme Evolution [51:44] creates adaptations that enhance the [51:46] fitness of memes independently of [51:48] whether it enhances our [51:51] fitness human Fitness is not the end all [51:53] and be all that it is that species [51:57] fitnesses in other species how many of [51:59] you think that having more grandchildren [52:01] than anybody else is the most important [52:03] thing in [52:04] life I don't see any [52:07] hands in other words unlike every other [52:10] species on the planet you have things [52:12] that you think are more [52:14] important that's because your head is [52:16] full of [52:17] memes if it weren't you would be like [52:19] every other living thing on the planet [52:21] and all that you all of your energies [52:23] would be for having more offspring [52:28] what do you [52:29] see say [52:30] it but now look more closely and you'll [52:34] notice that the H and the a are exactly [52:37] the same shape you've corrected [52:39] unconsciously corrected those shapes in [52:42] your mind that's an example of simple [52:45] digitization you're correcting to the [52:48] norm and you're doing it because you [52:50] have a [52:51] system that of course is written [52:53] language I want to point out that the [52:55] same feature is in spoken language in [52:58] words spoken so we're going to have a [53:00] little [53:03] experiment so I want you to listen [53:06] carefully and repeat after [53:10] me mify the [53:15] epigastrium [53:17] again once [53:20] more perfect do you know what it means [53:24] no you don't care [53:29] second case again listen carefully [53:31] repeat after [53:37] me and and [53:40] again no now do it a third [53:43] time you can't do it there was just as [53:46] much energy the the rise and fall of the [53:49] graph was as striking in the third case [53:52] as in the first but you didn't have [53:56] the [53:57] evm the English virtual machine in your [54:01] brain which automatically corrected to [54:04] the norm by identifying the [54:07] phoning that is digitization it is [54:10] exactly the same trick that is used in [54:12] computers to give them High Fidelity [54:15] transmission it's exactly the same trip [54:17] that's used in [54:20] DNA phones are one of the great [54:22] Evolution one of Evolution's greatest [54:24] inventions right up there with DNA which [54:27] is a which is a for member alphabet a CG [54:29] and [54:30] T and phones are remarkably unreal if [54:34] you know about the physics of of [54:36] phonology they they they don't [54:37] correspond to any simple physical [54:39] properties they're like they're like [54:42] benign illusions that are that are [54:45] generated in your head by the Machinery [54:47] you have in your [54:48] brain uh Boyd and Richardson a wonderful [54:51] book another wonderful book uh not by [54:53] jeans alone is very good on the early [54:56] days the bottom level of my diagram of [54:59] cultural Evolution they concentrate on [55:02] how cultural Evolution starts with [55:04] minimally comprehending vectors they [55:07] have a very simple rule like copy the [55:09] successful and it generates interesting [55:11] results so they're very good on the [55:13] early days how to get cultural Evolution [55:15] up and running um against many uh [55:19] uh countervailing forces in evolution so [55:23] it's competence with minimal [55:24] comprehension leading to a little bit of [55:27] myopic [55:28] comprehension but now we want to move [55:30] beyond that in between we have every [55:32] degree and combination of semi- [55:34] insightful [55:36] tinkering one of my favorite examples is [55:38] the Polynesian canoe in a wonderful [55:41] article by Rogers and Erick about how [55:44] the Polynesian canoe evolved over time [55:48] they quote a Frenchman actually he was [55:50] writing not about Polynesian canoes I've [55:52] learned but about but about um uh [55:55] fishing uh Britany fishing [55:58] vessels every boat is copied from [56:00] another boat let's reason as follows in [56:03] the manner of Darin it's clear that a [56:05] very badly made boat will end up in the [56:07] bottom after one or two voyages thus [56:09] never be copied one could then say with [56:11] complete rigor that it is the sea [56:13] herself who fashion the boats choosing [56:16] those which function and destroying the [56:19] others if it comes back copy it that's [56:22] natural [56:23] selection doesn't require any particular [56:26] comprehension you don't have to be a [56:27] naval architect you follow that rule and [56:31] the boats are going to gradually get [56:32] better you may make some [56:34] mutations most of your mutations may [56:37] make worse boats doesn't matter any that [56:40] happen to make better boats that will be [56:42] copied and so [56:44] forth so we put the Polynesian canoes [56:47] sort of in the middle of the [56:49] diagram interesting to note that what [56:52] I'll call the economic model of culture [56:54] is up in the top layers our standard [56:57] traditional idea of human culture is [56:59] that it consists of treasures that are [57:01] made by the by the most creative genius [57:03] people we honor them we preserve them we [57:06] spend money protecting them we they're [57:08] the Legacy we pass on to the next [57:09] Generation this is sort of high culture [57:12] uh and it's an economic model these are [57:14] these are Goods but human culture has a [57:17] lot of other things in it which are not [57:19] necessarily Goods at all they're just [57:21] features they're not particularly prized [57:24] but they survive in mutate they travel [57:26] along anyway those are the uh uh [57:29] synanthropic cultural elements for [57:32] instance [57:33] okay in the middle We've Got What I Call [57:36] foible [57:38] exploiters competences with limited [57:40] comprehension provided by mechanisms [57:42] that are good enough for government work [57:44] as one [57:45] says that have characteristic foibles [57:47] and falling short that can then be [57:49] exploited in arms races and that's what [57:51] we see in the world of human [57:54] culture scams pyramid schemes are two [57:57] obvious examples it's a quasi darwinian [58:01] process so we're now in the age of [58:04] intelligent [58:05] design cultural Evolution has become [58:07] ever more top down ever more [58:09] comprehending and self-c [58:11] comprehending ever more refined in its [58:13] search methods so has genetic Evolution [58:17] thanks to gen genetically modified foods [58:20] and Craig Venter and genetic engineering [58:22] in general is very much a matter of [58:24] intelligent design of uh of [58:28] genes but I want to end by pointing to [58:30] the age that we're now entering the age [58:33] of post intelligent [58:35] design in many fields intelligent [58:37] designers are exploiting the truth of [58:39] orgo's second rule remember evolution is [58:42] cleverer than you are it turns out that [58:44] we can now harness Evolution to do a lot [58:46] of the design work for us genetic [58:49] algorithms were first area which that [58:52] happened you you probably use a computer [58:57] device which is optimized by genetic [59:01] algorithms uh deep learning the [59:05] current uh bandwagon and artificial [59:08] intelligence is a good example of this [59:10] evolutionary architecture I'm going to [59:11] show you an example and some [59:14] evolutionary approaches to [59:16] nanotechnology um the Ottawa House of [59:21] Commons has a roof this sort of sunroof [59:24] which was intelligently designed [59:26] by John Sullivan at MIT using [59:30] evolutionary architecture um this is [59:33] these are a few slides from one of his [59:35] presentations so we have a fitness [59:37] landscape there's one building and you [59:40] see it in the space and then he he tests [59:44] them in various ways for efficiency U [59:48] use of energy etc etc etc and there's [59:51] another one and there's another one and [59:53] out of this uh selection comes the best [59:56] design and it's better than he can do [59:59] without using Evolution I'm going to end [60:02] on this nice note Francis Arnold one of [60:05] one of my heroes one of my heroins won [60:08] the first Queen Elizabeth prize for [60:11] engineering in 2013 she's a Caltech [60:16] bioengineer and here's what she [60:19] does she evolves proteins that have [60:23] never existed before on the planet when [60:27] one of her supervisors when she was a [60:30] graduate student said but [60:33] Francis there's no protein in nature [60:37] that has the competences that you're [60:39] hoping to put into these proteins she [60:41] says that's because there's never been [60:43] selection for that so she's creating new [60:46] selection pressures in the lab and [60:49] evolving proteins by really quite [60:52] classic Evolution and as she says [60:54] consequently these enzymes may open up [60:56] whole new regions of chemical space that [60:59] could not be explored in previous [61:00] medical chemistry efforts we're [61:02] developing new tools for protein [61:04] engineering and using them to create new [61:06] and improved catalysts for carbon [61:07] fixation sugar release from renewable [61:09] polymers such as cellulose biosynthesis [61:12] of fuels and chemicals so the age of POS [61:16] intelligent design of evolutionary [61:19] design is now upon us thank you very [61:22] much for your attention [61:26] if you look back at the Daniel dennit of [61:28] one bont stre in 1964 and the evolution [61:31] of your thinking since then what are the [61:33] two or three ideas that have taken you [61:36] out of what would have been a smooth [61:38] evolution of thought