So I’d like you to look at this image just for a moment. I’ll just let you watch it happen. 

A slow-motion clip of a lightning strike.

What it is, clear­ly, is light­ning. And what you see hap­pen is, you get a bang at the top left and then it starts fork­ing, and each fork forks again and forks again, until final­ly one hits the ground and all the oth­ers die away, and then you see the elec­trons trans­fer­ring back up to the cloud. So I’ll just let you watch it once more and then say why I’ve used this.

Funnily enough, this is very like a cer­tain style of pro­gram­ming called back­track­ing.” It’s an amaz­ing­ly pow­er­ful pro­gram­ming method. Imagine that you’ve got to get your­self through a for­est by fol­low­ing a path, and you don’t know all the dif­fer­ent turns which way to go. The way to solve it is by using back­track­ing. Whenever you come to a fork in the path, you take one of them, and if that does­n’t get you where you want to go then you back­track to that point and then you try the oth­er. If that does­n’t work, come back and try anoth­er. That works all the way down.

This is an exam­ple of the sort of tree that you get while you’re try­ing to do this with com­put­ers. At each deci­sion point you’ve got a state, and at each deci­sion you have to try one of the options, and you keep try­ing until it final­ly fails, like at point 5, and then you back­track one point and then you try that way, so then you go to 6 where you’ve got to make a deci­sion again. You go to 7, it fails, and then back. And you keep back­track­ing until you find a route through that succeeds.

There are sev­er­al dif­fer­ent ways of doing this when you pro­gram it. You can do it seri­al­ly, as I’ve just described, where at each point you just try one of them and then go back. Or you can do it in par­al­lel, where at each point you split off more pro­grams to do all the options simul­ta­ne­ous­ly. You can also just do it just to find one solu­tion, which might not be the best solu­tion but at least you’ve got a solu­tion. Or you can try it to find all the solu­tions and then decide which was the best.

And the last thought is heuris­tic, where there are so many options at each point that you could­n’t pos­si­bly do them all. So then you have to do some­thing smart at the deci­sion point to decide which sub-set of the deci­sions you’re going to take.

HOW TO RETURN (route, state) aim:
   IF state = aim:
      RETURN ("success", route with state)
   IF state in route OR deadend state:
      RETURN ("failure", {})
   PUT route with state IN new.route
   FOR option IN options state:
      PUT (new.route, state altered.for option) aim IN result, route
      IF result = "success":
         RETURN ("success", route)
   RETURN ("failure", {})

I’m not going to explain this pro­gram to you, but this is the pro­gram that just does all that. It’s a sur­pris­ing­ly small amount of code that solves an amaz­ing­ly large class of prob­lems. I wrote an arti­cle about this and I used it to solve a lot of prob­lems just to show that this one unchang­ing pro­gram could solve so many problems.

So for instance the Farmer and the Produce Problem. That’s where a farmer has got a bale of hay and a goat and a dog, and has to cross the riv­er in the boat but the boat will only hold two of those things. So he could only get two in the boat and then go to the oth­er side and then come back to get the oth­er. But he must nev­er leave the goat with the hay, or the dog with the goat. So that’s the prob­lem and you’ve got to solve it. This pro­gram will solve that.

The Two Jugs Problem. You’ve got two jugs of dif­fer­ent amounts, let’s say five liters and three liters, except the recipe says you’ve got to mea­sure out one liter. How do you do that? Well, one of the solu­tions is you fill the three-liter jug up, you pour it into the five-liter jug, you fill it up again, you pour it into the five-liter until it’s full, and then you’ve got a liter left. This pro­gram will solve that.

It will solve the Towers of Hanoi Problem where you’ve got a tow­er of discs, each of small­er size, and you have to move them from one peg to anoth­er. You’ve only got three pegs; you’ve got to move them from one to anoth­er. But you can only move them one disc at a time, and you must nev­er put a large disc on a small disc. This will solve that. In fact, when I tried it out just for two discs it found twelve solu­tions, and I had­n’t real­ized that that was possible.

But it will solve the Eight Queens Problem, where you’ve got to put eight queens onto a chess­board so that that they can’t take each oth­er. It’ll solve Sudoku, and many many others. 

By the way, this pro­gram is writ­ten in ABC, and ABC was the pro­gram­ming lan­guage that Python was based on. The rea­son was because Guido van Rossum and I used to work together. 

That’s me in those days. That’s Guido in the mid­dle. This was at a par­ty. They tell me it was a very good par­ty, but I don’t remem­ber any­thing about it.

The fun­ny thing is, evo­lu­tion works very sim­i­lar­ly to how back­track­ing works, and now that I’ve told you the words, it’s heuris­tic, and that is because each state of the pro­gram as it were is a per­son, you or me or a plant or an ani­mal. And you could pro­duce mil­lions of pos­si­ble chil­dren, but you don’t. You just pro­duce a small num­ber. So that’s why it’s heuris­tic. It’s par­al­lel because we’re all sur­viv­ing at the same time and we’re all doing this sim­i­lar­ly. It’s got a sim­i­lar def­i­n­i­tion of fail­ure, although it does have a dif­fer­ent def­i­n­i­tion of success.

There’s this great Dutch book called Cheese and the Theory of Evolution, unfor­tu­nate­ly not trans­lat­ed into English. I might do it one day if I get the urge to. It’s a great book. But any­way, it explains that you only need three things for evo­lu­tion to work. You need vari­a­tion, you need repli­ca­tion with inher­i­tance, and you need com­pe­ti­tion. Let me treat those one by one.

So, vari­a­tion. The crea­tures that are evolv­ing need to be dif­fer­ent from each oth­er in order to be dif­fer­ent so that they can com­pete. In the ear­ly days of evo­lu­tion, the only source of vari­a­tion was muta­tion. And muta­tion is actu­al­ly an extreme­ly bad way of gen­er­at­ing vari­a­tion because it’s almost always lead­ing to dele­te­ri­ous effects. It’s like tak­ing a recipe and let’s just take one ingre­di­ent at ran­dom and change it in some way. So, I know, let’s make this cake with, instead of sug­ar, salt, and try it out. Oh no, that’s dis­gust­ing. Okay, maybe we did­n’t put enough salt in. No, that does­n’t work either.”

So it’s a pret­ty bad way of doing it. But luck­i­ly, evo­lu­tion had a long long time to work over, and so occa­sion­al­ly an advan­ta­geous muta­tion occurred, and so things did slow­ly get better.

However, once sex evolved, which of course took a long time, all of a sud­den there was a huge source of vari­a­tion. Because now you’re com­bin­ing two lots of genes to cre­ate new crea­tures and that com­bi­na­tion cre­at­ed a whole new pool or vari­a­tion. And fur­ther­more, they were com­bi­na­tions of two things that had already been very suc­cess­ful. So this explains the suc­cess of sex, by which I mean why such a large num­ber of organ­isms use sex for pro­cre­ation, plants as well as animals.

Now, com­pe­ti­tion. You’ve got to have com­pe­ti­tion because if every­thing sur­vived then there’d be no selec­tion of advan­ta­geous genes. We’re guar­an­teed even­tu­al­ly there’s going to be com­pe­ti­tion because if every­thing sur­vived, they’d get big­ger and big­ger and more and more of them, and in the long run there won’t be enough resources to keep them alive. So we are ensured that there’s going to be competition. 

And death is evo­lu­tion’s back­track­ing. That is to say that’s the point of fail­ure. And as I’m going to explain more lat­er, death with­out off­spring is actu­al­ly the fail­ure. So if you’ve had off­spring and you die, that’s alright. You’ve suc­ceed­ed. But the def­i­n­i­tion of off­spring has changed for humans, as I’m going to be demon­strat­ing in this talk.

The envi­ron­ment affects the def­i­n­i­tion of suc­cess, actu­al­ly. And the envi­ron­ment changes and you have to adapt to the new envi­ron­ment, and there­fore it rede­fines suc­cess. This is how species hap­pen. A species, as we heard ear­li­er this week, is a group of ani­mals that can pro­cre­ate amongst them­selves but not with oth­ers. So the def­i­n­i­tion of species is whether things can pro­cre­ate with each other. 

It’s quite inter­est­ing to think that if you go back in evo­lu­tion, there was some time in the past where cats and dogs meet up. That is to say there’s a com­mon ances­tor of both cats and dogs, and that the chil­dren of that ances­tor of cats and dogs had the first cat and the first dog. And if you want to know what a dog-cat might look like, it’s inter­est­ing to know that a hye­na is actu­al­ly a cat and not a dog.

Camouflage is one of the results of the effects of the envi­ron­ment, because then that’s going to be advan­ta­geous for you because you’re not going to be so eas­i­ly caught and eat­en. But of course anti-camouflage is also advan­ta­geous for some ani­mals like wasps. The rea­son that king­fish­ers are so easy to see is because I’m told they’re dis­gust­ing to eat. I’ve nev­er tried it myself, but the rea­son that they’re so brightly-colored is to warn preda­tors off from eat­ing them because they are total­ly dis­gust­ing to eat.

Selection of advan­ta­geous genes [has] sur­pris­ing side-effects. Here’s a very nice exam­ple. Belyaev in Russia bred fox­es to try and breed tame fox­es. So he only select­ed fox­es for tame­ness. But it had the sur­pris­ing effect of chang­ing how they looked, so that his tame fox­es did­n’t look like fox­es any­more. They looked just like reg­u­lar dogs.

So the accre­tion of suc­cess­ful genes you can see as a form of mem­o­ry. That it’s a very slow-forming mem­o­ry, and it’s a read-only mem­o­ry. You can’t change it in any way. But it is a mem­o­ry of what’s been suc­cess­ful in the cur­rent envi­ron­ment in the past. In that pro­gram I showed you, there was a thing called the route, which saves the route that you’ve tak­en to get to the suc­cess­ful posi­tion so that you’ve got the answer to your prob­lem. And you can see the genes as the equiv­a­lent of the route in that program.

Just to give you some exam­ples of genet­ic learn­ing as it’s hap­pened in humans, why do we like sug­ar so much? Well, because one of the impor­tant things in the past for humans, before they could talk let’s say, so very very ear­ly humans before lan­guage evolved, and impor­tant thing was to eat enough. Starvation was one of the main forms of death. So how do you get the mes­sage to humans, how do the genes as it were, tell humans that some­thing has got a lot of calo­ries in it? Well, if it’s sweet, it’s got a lot of calo­ries in it, so there­fore some­body who evolves a gene to like sweet­ness is going to then eat more of those things and there­fore are less like­ly to die of star­va­tion. Similarly with fat, fat has lots of calo­ries and calo­ries were exact­ly the things that ear­ly humans need­ed. So the ones that devel­oped a lik­ing for fat were the ones that were more like­ly to sur­vive. Of course that’s bad luck for us now, because now that we’ve got enough food, it’s work­ing against us because we tend to eat too much sug­ar and too much fat. But that’s because it’s pro­grammed in us genet­i­cal­ly to eat these things.

Sex being fun is anoth­er exam­ple of some­thing that we’ve learned. That is to say, if you’ve got a pop­u­la­tion of peo­ple who are neu­tral to sex and then a gene comes up that makes you enjoy sex, then that gene is going to get a lot of pref­er­ence, of course, because the per­son who’s got that gene is going to be pro­duc­ing lots and lots more—well he’s going to be hav­ing more sex and there­fore is more like­ly to have chil­dren. So there­fore that gene is going to be advan­ta­geous for a sex­u­al crea­ture. So the rea­son why most of us find sex fun is because that gene has just spread right through the gene pool.

And age dif­fer­ences in cou­ples you can explain genet­i­cal­ly as well. It’s much more like­ly that you’ll see and old­er man with a younger woman than the oth­er way round, a younger man with an old­er woman. And that’s because, if it’s genetically-programmed, then this gene is going to get far more favor­ably treat­ed than the oth­er way around.

So after sex devel­op­ing in evo­lu­tion, true mem­o­ry was the next major devel­op­ment, because true mem­o­ry, where you remem­ber things your­self rather than just in your genes, allows you to learn behav­iors. It allows to adjust your behav­ior to what’s hap­pened to you in the past to recent out­comes to help you decide how to act. 

The Sphex wasp is a good exam­ple of some­thing that does­n’t have any mem­o­ry. What a Sphex wasp does is it makes a hole in the ground to make its nest, it lays its eggs, it goes off and it gets a prey, a cater­pil­lar or some­thing which it then stings to par­a­lyze it, drags it back to the nest, walks into the nest, checks that the nest is okay, drags the cater­pil­lar in, and then seals up the nest and goes away. And of course when the baby wasps come out, they eat up the prey.

What they’ve dis­cov­ered with the Sphex wasp is, at the moment when it drags [its prey] to the mouth of the nest and goes in to check, if you pull that prey away a few cen­time­ters, when it comes out it says, Hey, where’s my prey?” And then it finds it and pulls it back in again, and then it goes and checks again whether the inside of the nest is okay. And you can do this hun­dreds of times and it will con­tin­u­al­ly check whether the nest is okay before drag­ging it in. So it has no mem­o­ry what­so­ev­er. It’s entire­ly instinct-based. So when you’ve got mem­o­ry, all of a sud­den you can base your deci­sions whether you’re going to sur­vive or not on past expe­ri­ences rather than just pure instinct based in your genes.

I’m going to talk about why we like cer­tain things, and so I want to talk about aware­ness. Hypnosis is an exam­ple of where things hap­pen and we’re not aware of the real rea­sons. What hap­pens under hyp­no­sis, if you’re told to do some­thing, for instance if you hear the world London, open the win­dow,” when you come out of hyp­no­sis and you’re sit­ting there work­ing or what­ev­er and then you hear the word London” and you go and open the win­dow and some­body says, Why did you open the win­dow?” They’ll say, It was get­ting stuffy.” They won’t be aware of the real rea­son; they will ratio­nal­ize after the fact. 

There’s a great book, Surely You’re Joking, Mr. Feynman! by the Nobel prize-winning physi­cist, who under­went hyp­no­sis just to try it out. He was even aware that he’d been told to do some­thing, and he did it any­way. And he was say­ing, All the time, I was say­ing to myself I could do that,” in oth­er words do [a] dif­fer­ent thing than he’d been told, but I won’t.” And what he said is that’s just anoth­er way of say­ing you can’t. So in oth­er words, very often while under hyp­no­sis, you do things with­out know­ing the real rea­son for it, and you ratio­nal­ize a new rea­son. And there are some peo­ple who think in fact there’s no free will at all, that we always ratio­nal­ize after the action. And there’s some evi­dence for that. I don’t know if I believe it yet, but at least there are peo­ple who believe that free will does­n’t exist and it’s always post hoc rationalization.

So we are in a pro­fes­sion that’s pred­i­cat­ed on observ­ing peo­ple and doing things to make them hap­py. So it’s fun, then, to watch peo­ple and watch out for things that peo­ple appar­ent­ly love for some rea­son or anoth­er, because they clus­ter around it or some­thing, and try to pos­tu­late what would be the evo­lu­tion­ary advan­tage that this rep­re­sents. So let me give you some examples.

Water. Whenever there’s water, peo­ple love to clus­ter around it. I was dri­ving through England with my chil­dren, and every time we passed a riv­er or a lake or some­thing, they’d say, Stop! Stop! Stop!” and they’d be hap­py to play at the water’s edge for hours. Well, you could imag­ine evo­lu­tion­ary advan­tage for water. Water is an essen­tial resource, and so if you end­ed up by water, if you just liked being there then you would stay there and then you would have a source of water. But if you did­n’t like being there, then you might trav­el on fur­ther and then even­tu­al­ly die of thirst.

Heights is anoth­er thing that peo­ple clus­ter around. This is the Sacré-Cœur in Paris. Beautiful build­ing right at the top of a hill. And of course any tourist who goes there goes to see the Sacré-Cœur. They go in for twen­ty min­utes and look at the inside of the beau­ti­ful build­ing, and they come out­side and they sit on the steps out­side for hours, just look­ing at the view. So clear­ly, height is some­thing that peo­ple real­ly love to do. They’re just hap­py to sit and stare for no rea­son at all. It just makes them feel good.

Fire is a sim­i­lar sort of thing that peo­ple just like to sit around and just stare into the fire, and they’re will­ing to sit there for hours. And it’s inter­est­ing that humans are very dif­fer­ent from most ani­mals, because most ani­mals flee from fire as fast as they can. You can under­stand the rea­son for that, because if there was ever a gene for ani­mals in the for­est, Hey look, there’s a fire! Let’s go and watch it,” of course that gene would die out fair­ly quick­ly. So it’s sur­pris­ing, then, that humans have this gene for lik­ing fire. 

And I have to tell you a sto­ry which made me think dif­fer­ent­ly about why peo­ple like fire. Because there are obvi­ous advan­tages to lik­ing fire in the dis­tant past. For instance of course it keeps you warm. But also since most ani­mals are fright­ened of fire, then they won’t come near you at night, and it’ll keep you safe dur­ing the night while you’re asleep. So there are obvi­ous evo­lu­tion­ary advantages.

But the inter­est­ing sto­ry is that a col­league of mine was babysit­ting for anoth­er col­league of mine who hap­pens to be sit­ting in the audi­ence. And this baby was cry­ing and cry­ing and cry­ing. And he did not know what to do. In the end he strapped the child onto the baby car­ri­er and went for a walk with her to try and calm her down. At the end of the street there was a vend­ing machine, a cig­a­rette machine or some­thing, and on that vend­ing machine there was just one sin­gle red LED light. The child saw this and it stopped the child from cry­ing, and the child was just star­ing at this red light, com­plete­ly trans­fixed just by this red light. And was hap­py, hav­ing cried for so long. And it made me think maybe the rea­son we like fire is because it flick­ers. Because an LED flick­ers. It flick­ers very fast so that we don’t see it flick­ers, but it does flick­er. If you move your eyes quick­ly, then you can see that it’s flick­er­ing, because you see points rather than a con­tin­u­ous line. But an LED does flick­er, so maybe we have a gene that makes us like things that flick­er, and that there­fore the rea­son we like fire is because it flick­ers, and we don’t like fire because it’s fire, it’s just the flickering.

And that also got me think­ing, are there oth­er things that flick­er that peo­ple are will­ing to sit around in front of for hours regard­less of the rub­bish that’s on it? Yes, there are things. Maybe peo­ple stare at the tele­vi­sion for so long just because it tweaks the result of this flick­er gene that makes us hap­py. Which makes me won­der about the future of e‑ink because my sus­pi­cion then is that if some peo­ple are offered the same prod­uct, one with e‑ink which does­n’t flick­er and one with an LCD screen which does, they’ll look at it and say, I don’t know why, but I just pre­fer the LED ver­sion.” So I sus­pect that in the long run that e‑ink may—I mean e‑ink does have some advan­tages like long bat­tery life. But that peo­ple in the end do pre­fer to look at a flick­er­ing screen. Which might actu­al­ly also explain why peo­ple get their phones out so often. Because it just gives you a good feel­ing. We’re not aware of this, but just by look­ing at the phone, we get this fire/good feel­ing effect.

So the title of the talk has the word phe­no­type” in. The phe­no­type is the visu­al man­i­fes­ta­tion of your geno­type. Your geno­type is the col­lec­tion of genes that you hold, and the phe­no­type is what gets built with that. That could depend on the envi­ron­ment. For instance if you grow up in a place with lit­tle food, you’re going to be short­er and small­er than if you grow up in a place where there’s lots of food. So the phe­no­type includes your hair col­or, your size, your aggres­sion, your strength. And for some crea­tures… For instance bird nests, they’re built as a result of the genes, they’re not learned behav­ior. So it’s part of the phe­no­type. Beaver dams sim­i­lar­ly, spi­der webs; they’re build by the genes but they’re not actu­al­ly part of your body.

The next part of devel­op­ment for humans was the devel­op­ment of lan­guage. Because the advan­tage of lan­guage, the evo­lu­tion­ary advan­tage of lan­guage, is that it allows evo­lu­tion with plan­ning, because you’ve got these mem­o­ries that you can now pass on to your off­spring or your friends. So if you now have had an expe­ri­ence, you can say to some­body, Don’t do that. I tried it,” or, Don’t do that, you’ll hurt your­self.” And so this cre­ates with­in genet­ics what are called memes. We mis­use the word on the Internet to mean pic­tures of cats. But memes are actu­al­ly a spe­cif­ic piece of infor­ma­tion in anal­o­gy to genes, a car­ri­er of infor­ma­tion that gets passed around which may or may not help you in survival.

So things get built from memes, like hous­es or umbrel­las, or the idea of wash­ing your hands to keep you healthy. And some of them work and some of them don’t. So a bad meme… A cou­ple of hun­dred years ago there was this idea that if you were ill, some­body should drain off some of your blood to make you bet­ter. That was clear­ly a bad meme and I’m glad to say it’s clear­ly died.

What this means now is it’s not only impor­tant to pass on genes in evo­lu­tion, but it’s just as impor­tant to pass on ideas. In oth­er words, ideas are just as impor­tant as hav­ing babies. I don’t real­ly have time to go into Englebart, but Dough Englebart talked a lot about aug­ment­ing the col­lec­tive IQ, which is the same sort of idea. McLuhan also points out that all these things that we pro­duce with wheels are just exten­sions of our body. That it’s part of our extend­ed phe­no­type, in oth­er words.

And in fact, what’s the role of a con­fer­ence? To exchange ideas. In fact, it’s the memet­ic equiv­a­lent of hav­ing sex. Or, in fact, it’s more like an orgy. Because every­body is exchang­ing ideas all the time, as…well, I’ll just let you think that for yourself.

So the extend­ed human phe­no­type uses memes rather than genes to extend our abil­i­ties. So, pro­tec­tion hel­mets when we’re rid­ing on bicy­cles or motor­bicy­cles. Our clothes to keep us warm. Raincoats to keep us dry. Houses to live in. Memory, we can extend our mem­o­ry now with writ­ing, but [also] with pho­tog­ra­phy and video. We can repair things. I mean, glass­es… We don’t have to wait for evo­lu­tion to work out how to repair our bad eye­sight. We can repair it our­selves now. Medicine, hos­pi­tals. We can cure deaf­ness now, just by using memes. Our abil­i­ties are greater. We can trav­el much much faster. We can fly. We can trav­el over water and under water. In fact, there are not many things that we can’t do. And now we’re extend­ing our sens­es. Telescopes, of course. But now we’ve got weath­er radar; we can know what the weath­er’s going to be like in the next cou­ple of hours pret­ty accu­rate­ly. We can see whether it’s going to rain or not. And we’re the last gen­er­a­tion that will ever get lost because with sat-nav we now have this sort of sense in our body, and that’s our tele­phone, which when­ev­er we don’t know where we are we just look it up.

Now, the com­put­er is being used for so many of these things that I claim that we have to con­sid­er the com­put­er as part of our extend­ed phe­no­type. It’s just a part of a thing that has evolved with us using memes.

Moore’s Law has been going on for a long time, the pow­er of com­put­ers essen­tial­ly dou­bling every eigh­teen months. And a lot of peo­ple don’t real­ly under­stand its true con­se­quences, so let me just demon­strate what Moore’s Law has done for us. We take a piece of paper and we divide it in two and we write this year’s date on one side. That rep­re­sents the pow­er of your lap­top this year. Now we’re going to take the oth­er side and divide that in two and write the date eigh­teen months ago on the oth­er half. That’s the rela­tion ship of your com­put­er now with one that you could’ve bought eigh­teen months ago at the same price. We’re going to keep doing that. Divide the rest of the space in half, and that’s the pow­er of your lap­top three years ago, so you can see that it was a quar­ter of what it would be now at the same price. And then we do that all the way back as far as we can go until our pen­cil runs out or we get bored or whatever.

What this shows you is that your cur­rent com­put­er is more pow­er­ful than all the com­put­ers that you’ve ever owned, assum­ing you haven’t bought more com­put­ers than once every eigh­teen months, which I don’t know any­body who has. So in oth­er words your cur­rent com­put­er is more pow­er­ful than all the oth­er com­put­ers you’ve ever had, put together. 

What’s also inter­est­ing is that if you look at this as a soci­ety’s lev­el, com­put­ers last about four to five years, so if I know col­or red all the com­put­ers that are up to four or five years old, what you can see is that the amount of com­put­ing pow­er in the whole world now is more than 90% of the com­put­ing pow­er that has ever exist­ed in total. So we have an amaz­ing amount of com­put­ing pow­er avail­able to us.

Image via Wikipedia; graph originally by Ray Kurzweil

Image via Wikiepedia; graph orig­i­nal­ly by Ray Kurzweil

You may have heard of the Singularity. This is the idea of look­ing at how often par­a­digm changes hap­pen. So we’re look­ing back to 10 to the 11th years in the past here. A par­a­digm change is when some­thing essen­tial changes that means you do things in a com­plete­ly dif­fer­ent way. The print­ing press was a par­a­digm change, but also the Iron Age was a par­a­digm change from the Stone Age. Digital mon­ey was a par­a­digm change. Trains, the steam engine was a par­a­digm change.

What the per­son who drew this dia­gram did was ask amongst I think it’s fif­teen dif­fer­ent areas, when the par­a­digm changes hap­pened in that par­tic­u­lar area of soci­ety. What he found was that par­a­digm changes are get­ting faster and faster. And if you com­pare our life now to that of my grand­moth­er, when my grand­moth­er was born there were no inside toi­lets. There was no elec­tric­i­ty. My grand­fa­ther’s job in his house was to fill up the oil lights in the house, to make sure they were always full. The only what I would call mod­ern inven­tions that were avail­able when he was born were the steam engine train, and pho­tog­ra­phy. Those were the only mod­ern inven­tions that exist­ed. Since his time, which was only 120 years ago, we’ve had immense­ly many new par­a­digm changes. Television, radio, the car, the aero­plane. It’s incredible.

What this graph shows is that not only are par­a­digm shifts hap­pen­ing faster, but they’re hap­pen­ing steadi­ly fast at a faster rate. The inter­est­ing thing is that this line, you can see it’s a very clear line, cross­es the axis some­time in the next hun­dred years. That is the day, or that is the year, when par­a­digm changes hap­pen every day. So he’s called it the Singularity because the idea is that is the point when com­put­ers become smarter than us and sud­den­ly can start doing things that we can’t think of faster than the rate we could do it. I’m not sure if I will live to see it. Some of you here will live to see it. But it’s going to be a very inter­est­ing time.

So clos­ing the loop, it’s inter­est­ing the thread of this talk has been that DNA is a sort of mem­o­ry. True mem­o­ry evolved. And then lan­guage, which allowed you to pass mem­o­ries. And writ­ing, which records the mem­o­ries past your death.

Recently, last year, there was a DNA stor­age break­through, where peo­ple have dis­cov­ered how to store dig­i­tal infor­ma­tion in DNA. In fact, 700 ter­abytes of data in just one tiny gram of DNA. It’s a very slow stor­age, but it’s a huge stor­age. In oth­er words, one gram would store the same amount as 14,000 DVDs or a 150kg of hard disks.

So my con­clu­sion is that the rea­son that humans have suc­ceed­ed so well in com­par­i­son with many oth­er life­forms is because of the devel­op­ment of lan­guage, and there­fore the devel­op­ment of memes, which make us much more flex­i­ble in our abil­i­ty to sur­vive because we can do it faster and we can pass it on to more peo­ple. Particularly suc­cess­ful memes have caused par­a­digm shifts in human soci­ety, which has gen­er­at­ed the next gen­er­a­tion of memes. And what we’ve seen is that the rate of change is increas­ing­ly expo­nen­tial­ly over hun­dreds of thou­sands of years. So we’ll be con­front­ed with a very inter­est­ing time with­in the next cen­tu­ry, when we may have to con­tend with six new par­a­digms at breakfast.

This talk will appear as part of a book lat­er this year. The slides are online, and if you can’t find them you should be con­sid­er­ing a new career.

Thank you very much.

Further Reference

This pre­sen­ta­tion’s descrip­tion and bio for Steven, at the Interaction14 site.