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I want to start my talk today with two observations

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about the human species.

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The first observation is something that you might think is quite obvious,

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and that's that our species, Homo sapiens,

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is actually really, really smart --

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like, ridiculously smart --

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like you're all doing things

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that no other species on the planet does right now.

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And this is, of course,

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not the first time you've probably recognized this.

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Of course, in addition to being smart, we're also an extremely vain species.

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So we like pointing out the fact that we're smart.

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You know, so I could turn to pretty much any sage

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from Shakespeare to Stephen Colbert

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to point out things like the fact that

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we're noble in reason and infinite in faculties

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and just kind of awesome-er than anything else on the planet

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when it comes to all things cerebral.

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But of course, there's a second observation about the human species

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that I want to focus on a little bit more,

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and that's the fact that

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even though we're actually really smart, sometimes uniquely smart,

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we can also be incredibly, incredibly dumb

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when it comes to some aspects of our decision making.

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Now I'm seeing lots of smirks out there.

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Don't worry, I'm not going to call anyone in particular out

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on any aspects of your own mistakes.

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But of course, just in the last two years

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we see these unprecedented examples of human ineptitude.

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And we've watched as the tools we uniquely make

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to pull the resources out of our environment

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kind of just blow up in our face.

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We've watched the financial markets that we uniquely create --

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these markets that were supposed to be foolproof --

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we've watched them kind of collapse before our eyes.

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But both of these two embarrassing examples, I think,

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don't highlight what I think is most embarrassing

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about the mistakes that humans make,

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which is that we'd like to think that the mistakes we make

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are really just the result of a couple bad apples

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or a couple really sort of FAIL Blog-worthy decisions.

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But it turns out, what social scientists are actually learning

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is that most of us, when put in certain contexts,

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will actually make very specific mistakes.

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The errors we make are actually predictable.

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We make them again and again.

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And they're actually immune to lots of evidence.

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When we get negative feedback,

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we still, the next time we're face with a certain context,

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tend to make the same errors.

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And so this has been a real puzzle to me

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as a sort of scholar of human nature.

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What I'm most curious about is,

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how is a species that's as smart as we are

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capable of such bad

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and such consistent errors all the time?

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You know, we're the smartest thing out there, why can't we figure this out?

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In some sense, where do our mistakes really come from?

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And having thought about this a little bit, I see a couple different possibilities.

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One possibility is, in some sense, it's not really our fault.

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Because we're a smart species,

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we can actually create all kinds of environments

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that are super, super complicated,

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sometimes too complicated for us to even actually understand,

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even though we've actually created them.

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We create financial markets that are super complex.

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We create mortgage terms that we can't actually deal with.

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And of course, if we are put in environments where we can't deal with it,

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in some sense makes sense that we actually

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might mess certain things up.

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If this was the case, we'd have a really easy solution

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to the problem of human error.

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We'd actually just say, okay, let's figure out

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the kinds of technologies we can't deal with,

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the kinds of environments that are bad --

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get rid of those, design things better,

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and we should be the noble species

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that we expect ourselves to be.

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But there's another possibility that I find a little bit more worrying,

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which is, maybe it's not our environments that are messed up.

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Maybe it's actually us that's designed badly.

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This is a hint that I've gotten

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from watching the ways that social scientists have learned about human errors.

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And what we see is that people tend to keep making errors

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exactly the same way, over and over again.

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It feels like we might almost just be built

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to make errors in certain ways.

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This is a possibility that I worry a little bit more about,

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because, if it's us that's messed up,

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it's not actually clear how we go about dealing with it.

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We might just have to accept the fact that we're error prone

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and try to design things around it.

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So this is the question my students and I wanted to get at.

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How can we tell the difference between possibility one and possibility two?

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What we need is a population

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that's basically smart, can make lots of decisions,

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but doesn't have access to any of the systems we have,

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any of the things that might mess us up --

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no human technology, human culture,

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maybe even not human language.

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And so this is why we turned to these guys here.

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These are one of the guys I work with. This is a brown capuchin monkey.

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These guys are New World primates,

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which means they broke off from the human branch

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about 35 million years ago.

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This means that your great, great, great great, great, great --

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with about five million "greats" in there --

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grandmother was probably the same great, great, great, great

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grandmother with five million "greats" in there

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as Holly up here.

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You know, so you can take comfort in the fact that this guy up here is a really really distant,

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but albeit evolutionary, relative.

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The good news about Holly though is that

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she doesn't actually have the same kinds of technologies we do.

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You know, she's a smart, very cut creature, a primate as well,

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but she lacks all the stuff we think might be messing us up.

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So she's the perfect test case.

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What if we put Holly into the same context as humans?

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Does she make the same mistakes as us?

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Does she not learn from them? And so on.

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And so this is the kind of thing we decided to do.

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My students and I got very excited about this a few years ago.

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We said, all right, let's, you know, throw so problems at Holly,

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see if she messes these things up.

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First problem is just, well, where should we start?

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Because, you know, it's great for us, but bad for humans.

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We make a lot of mistakes in a lot of different contexts.

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You know, where are we actually going to start with this?

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And because we started this work around the time of the financial collapse,

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around the time when foreclosures were hitting the news,

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we said, hhmm, maybe we should

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actually start in the financial domain.

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Maybe we should look at monkey's economic decisions

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and try to see if they do the same kinds of dumb things that we do.

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Of course, that's when we hit a sort second problem --

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a little bit more methodological --

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which is that, maybe you guys don't know,

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but monkeys don't actually use money. I know, you haven't met them.

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But this is why, you know, they're not in the queue behind you

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at the grocery store or the ATM -- you know, they don't do this stuff.

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So now we faced, you know, a little bit of a problem here.

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How are we actually going to ask monkeys about money

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if they don't actually use it?

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So we said, well, maybe we should just, actually just suck it up

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and teach monkeys how to use money.

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So that's just what we did.

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What you're looking at over here is actually the first unit that I know of

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of non-human currency.

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We weren't very creative at the time we started these studies,

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so we just called it a token.

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But this is the unit of currency that we've taught our monkeys at Yale

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to actually use with humans,

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to actually buy different pieces of food.

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It doesn't look like much -- in fact, it isn't like much.

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Like most of our money, it's just a piece of metal.

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As those of you who've taken currencies home from your trip know,

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once you get home, it's actually pretty useless.

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It was useless to the monkeys at first

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before they realized what they could do with it.

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When we first gave it to them in their enclosures,

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they actually kind of picked them up, looked at them.

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They were these kind of weird things.

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But very quickly, the monkeys realized

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that they could actually hand these tokens over

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to different humans in the lab for some food.

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And so you see one of our monkeys, Mayday, up here doing this.

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This is A and B are kind of the points where she's sort of a little bit

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curious about these things -- doesn't know.

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There's this waiting hand from a human experimenter,

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and Mayday quickly figures out, apparently the human wants this.

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Hands it over, and then gets some food.

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It turns out not just Mayday, all of our monkeys get good

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at trading tokens with human salesman.

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So here's just a quick video of what this looks like.

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Here's Mayday. She's going to be trading a token for some food

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and waiting happily and getting her food.

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Here's Felix, I think. He's our alpha male; he's a kind of big guy.

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But he too waits patiently, gets his food and goes on.

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So the monkeys get really good at this.

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They're surprisingly good at this with very little training.

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We just allowed them to pick this up on their own.

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The question is: is this anything like human money?

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Is this a market at all,

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or did we just do a weird psychologist's trick

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by getting monkeys to do something,

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looking smart, but not really being smart.

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And so we said, well, what would the monkeys spontaneously do

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if this was really their currency, if they were really using it like money?

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Well, you might actually imagine them

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to do all the kinds of smart things

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that humans do when they start exchanging money with each other.

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You might have them start paying attention to price,

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paying attention to how much they buy --

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sort of keeping track of their monkey token, as it were.

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Do the monkeys do anything like this?

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And so our monkey marketplace was born.

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The way this works is that

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our monkeys normally live in a kind of big zoo social enclosure.

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When they get a hankering for some treats,

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we actually allowed them a way out

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into a little smaller enclosure where they could enter the market.

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Upon entering the market --

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it was actually a much more fun market for the monkeys than most human markets

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because, as the monkeys entered the door of the market,

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a human would give them a big wallet full of tokens

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so they could actually trade the tokens

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with one of these two guys here --

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two different possible human salesmen

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that they could actually buy stuff from.

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The salesmen were students from my lab.

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They dressed differently; they were different people.

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And over time, they did basically the same thing

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so the monkeys could learn, you know,

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who sold what at what price -- you know, who was reliable, who wasn't, and so on.

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And you can see that each of the experimenters

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is actually holding up a little, yellow food dish.

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and that's what the monkey can for a single token.

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So everything costs one token,

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but as you can see, sometimes tokens buy more than others,

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sometimes more grapes than others.

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So I'll show you a quick video of what this marketplace actually looks like.

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Here's a monkey-eye-view. Monkeys are shorter, so it's a little short.

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But here's Honey.

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She's waiting for the market to open a little impatiently.

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All of a sudden the market opens. Here's her choice: one grapes or two grapes.

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You can see Honey, very good market economist,

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goes with the guy who gives more.

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She could teach our financial advisers a few things or two.

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So not just Honey,

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most of the monkeys went with guys who had more.

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Most of the monkeys went with guys who had better food.

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When we introduced sales, we saw the monkeys paid attention to that.

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They really cared about their monkey token dollar.

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The more surprising thing was that when we collaborated with economists

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to actually look at the monkeys' data using economic tools,

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they basically matched, not just qualitatively,

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but quantitatively with what we saw

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humans doing in a real market.

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So much so that, if you saw the monkeys' numbers,

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you couldn't tell whether they came from a monkey or a human in the same market.

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And what we'd really thought we'd done

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is like we'd actually introduced something

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that, at least for the monkeys and us,

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works like a real financial currency.

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Question is: do the monkeys start messing up in the same ways we do?

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Well, we already saw anecdotally a couple of signs that they might.

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One thing we never saw in the monkey marketplace

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was any evidence of saving --

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you know, just like our own species.

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The monkeys entered the market, spent their entire budget

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and then went back to everyone else.

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The other thing we also spontaneously saw,

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embarrassingly enough,

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is spontaneous evidence of larceny.

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The monkeys would rip-off the tokens at every available opportunity --

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from each other, often from us --

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you know, things we didn't necessarily think we were introducing,

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but things we spontaneously saw.

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So we said, this looks bad.

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Can we actually see if the monkeys

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are doing exactly the same dumb things as humans do?

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One possibility is just kind of let

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the monkey financial system play out,

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you know, see if they start calling us for bailouts in a few years.

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We were a little impatient so we wanted

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to sort of speed things up a bit.

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So we said, let's actually give the monkeys

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the same kinds of problems

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that humans tend to get wrong

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in certain kinds of economic challenges,

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or certain kinds of economic experiments.

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And so, since the best way to see how people go wrong

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is to actually do it yourself,

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I'm going to give you guys a quick experiment

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to sort of watch your own financial intuitions in action.

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So imagine that right now

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I handed each and every one of you

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a thousand U.S. dollars -- so 10 crisp hundred dollar bills.

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Take these, put it in your wallet

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and spend a second thinking about what you're going to do with it.

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Because it's yours now; you can buy whatever you want.

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Donate it, take it, and so on.

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Sounds great, but you get one more choice to earn a little bit more money.

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And here's your choice: you can either be risky,

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in which case I'm going to flip one of these monkey tokens.

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If it comes up heads, you're going to get a thousand dollars more.

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If it comes up tails, you get nothing.

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So it's a chance to get more, but it's pretty risky.

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Your other option is a bit safe. Your just going to get some money for sure.

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I'm just going to give you 500 bucks.

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You can stick it in your wallet and use it immediately.

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So see what your intuition is here.

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Most people actually go with the play-it-safe option.

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Most people say, why should I be risky when I can get 1,500 dollars for sure?

295
00:11:24,000 --> 00:11:26,000
This seems like a good bet. I'm going to go with that.

296
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You might say, eh, that's not really irrational.

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People are a little risk-averse. So what?

298
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Well, the "so what?" comes when start thinking

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about the same problem

300
00:11:34,000 --> 00:11:36,000
set up just a little bit differently.

301
00:11:36,000 --> 00:11:38,000
So now imagine that I give each and every one of you

302
00:11:38,000 --> 00:11:41,000
2,000 dollars -- 20 crisp hundred dollar bills.

303
00:11:41,000 --> 00:11:43,000
Now you can buy double to stuff you were going to get before.

304
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Think about how you'd feel sticking it in your wallet.

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00:11:45,000 --> 00:11:47,000
And now imagine that I have you make another choice

306
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But this time, it's a little bit worse.

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Now, you're going to be deciding how you're going to lose money,

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but you're going to get the same choice.

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You can either take a risky loss --

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so I'll flip a coin. If it comes up heads, you're going to actually lose a lot.

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If it comes up tails, you lose nothing, you're fine, get to keep the whole thing --

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00:12:02,000 --> 00:12:05,000
or you could play it safe, which means you have to reach back into your wallet

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and give me five of those $100 bills, for certain.

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And I'm seeing a lot of furrowed brows out there.

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So maybe you're having the same intuitions

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as the subjects that were actually tested in this,

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which is when presented with these options,

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people don't choose to play it safe.

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They actually tend to go a little risky.

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The reason this is irrational is that we've given people in both situations

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the same choice.

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It's a 50/50 shot of a thousand or 2,000,

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or just 1,500 dollars with certainty.

324
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But people's intuitions about how much risk to take

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00:12:34,000 --> 00:12:36,000
varies depending on where they started with.

326
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So what's going on?

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Well, it turns out that this seems to be the result

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of at least two biases that we have at the psychological level.

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One is that we have a really hard time thinking in absolute terms.

330
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You really have to do work to figure out,

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well, one option's a thousand, 2,000;

332
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one is 1,500.

333
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Instead, we find it very easy to think in very relative terms

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00:12:55,000 --> 00:12:58,000
as options change from one time to another.

335
00:12:58,000 --> 00:13:01,000
So we think of things as, "Oh, I'm going to get more," or "Oh, I'm going to get less."

336
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This is all well and good, except that

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changes in different directions

338
00:13:05,000 --> 00:13:07,000
actually effect whether or not we think

339
00:13:07,000 --> 00:13:09,000
options are good or not.

340
00:13:09,000 --> 00:13:11,000
And this leads to the second bias,

341
00:13:11,000 --> 00:13:13,000
which economists have called loss aversion.

342
00:13:13,000 --> 00:13:16,000
The idea is that we really hate it when things go into the red.

343
00:13:16,000 --> 00:13:18,000
We really hate it when we have to lose out on some money.

344
00:13:18,000 --> 00:13:20,000
And this means that sometimes we'll actually

345
00:13:20,000 --> 00:13:22,000
switch our preferences to avoid this.

346
00:13:22,000 --> 00:13:24,000
What you saw in that last scenario is that

347
00:13:24,000 --> 00:13:26,000
subjects get risky

348
00:13:26,000 --> 00:13:29,000
because they want the small shot that there won't be any loss.

349
00:13:29,000 --> 00:13:31,000
That means when we're in a risk mindset --

350
00:13:31,000 --> 00:13:33,000
excuse me, when we're in a loss mindset,

351
00:13:33,000 --> 00:13:35,000
we actually become more risky,

352
00:13:35,000 --> 00:13:37,000
which can actually be really worrying.

353
00:13:37,000 --> 00:13:40,000
These kinds of things play out in lots of bad ways in humans.

354
00:13:40,000 --> 00:13:43,000
They're why stock investors hold onto losing stocks longer --

355
00:13:43,000 --> 00:13:45,000
because they're evaluating them in relative terms.

356
00:13:45,000 --> 00:13:47,000
They're why people in the housing market refused to sell their house --

357
00:13:47,000 --> 00:13:49,000
because they don't want to sell at a loss.

358
00:13:49,000 --> 00:13:51,000
The question we were interested in

359
00:13:51,000 --> 00:13:53,000
is whether the monkeys show the same biases.

360
00:13:53,000 --> 00:13:56,000
If we set up those same scenarios in our little monkey market,

361
00:13:56,000 --> 00:13:58,000
would they do the same thing as people?

362
00:13:58,000 --> 00:14:00,000
And so this is what we did, we gave the monkeys choices

363
00:14:00,000 --> 00:14:03,000
between guys who were safe -- they did the same thing every time --

364
00:14:03,000 --> 00:14:05,000
or guys who were risky --

365
00:14:05,000 --> 00:14:07,000
they did things differently half the time.

366
00:14:07,000 --> 00:14:09,000
And then we gave them options that were bonuses --

367
00:14:09,000 --> 00:14:11,000
like you guys did in the first scenario --

368
00:14:11,000 --> 00:14:13,000
so they actually have a chance more,

369
00:14:13,000 --> 00:14:16,000
or pieces where they were experiencing losses --

370
00:14:16,000 --> 00:14:18,000
they actually thought they were going to get more than they really got.

371
00:14:18,000 --> 00:14:20,000
And so this is what this looks like.

372
00:14:20,000 --> 00:14:22,000
We introduced the monkeys to two new monkey salesmen.

373
00:14:22,000 --> 00:14:24,000
The guy on the left and right both start with one piece of grape,

374
00:14:24,000 --> 00:14:26,000
so it looks pretty good.

375
00:14:26,000 --> 00:14:28,000
But they're going to give the monkeys bonuses.

376
00:14:28,000 --> 00:14:30,000
The guy on the left is a safe bonus.

377
00:14:30,000 --> 00:14:33,000
All the time, he adds one, to give the monkeys two.

378
00:14:33,000 --> 00:14:35,000
The guy on the right is actually a risky bonus.

379
00:14:35,000 --> 00:14:38,000
Sometimes the monkeys get no bonus -- so this is a bonus of zero.

380
00:14:38,000 --> 00:14:41,000
Sometimes the monkeys get two extra.

381
00:14:41,000 --> 00:14:43,000
For a big bonus, now they get three.

382
00:14:43,000 --> 00:14:45,000
But this is the same choice you guys just faced.

383
00:14:45,000 --> 00:14:48,000
Do the monkeys actually want to play it safe

384
00:14:48,000 --> 00:14:50,000
and then go with the guy who's going to do the same thing on every trial,

385
00:14:50,000 --> 00:14:52,000
or do they want to be risky

386
00:14:52,000 --> 00:14:54,000
and try to get a risky, but big, bonus,

387
00:14:54,000 --> 00:14:56,000
but risk the possibility of getting no bonus.

388
00:14:56,000 --> 00:14:58,000
People here played it safe.

389
00:14:58,000 --> 00:15:00,000
Turns out, the monkeys play it safe too.

390
00:15:00,000 --> 00:15:02,000
Qualitatively and quantitatively,

391
00:15:02,000 --> 00:15:04,000
they choose exactly the same way as people,

392
00:15:04,000 --> 00:15:06,000
when tested in the same thing.

393
00:15:06,000 --> 00:15:08,000
You might say, well, maybe the monkeys just don't like risk.

394
00:15:08,000 --> 00:15:10,000
Maybe we should see how they do with losses.

395
00:15:10,000 --> 00:15:12,000
And so we ran a second version of this.

396
00:15:12,000 --> 00:15:14,000
Now, the monkeys meet two guys

397
00:15:14,000 --> 00:15:16,000
who aren't giving them bonuses;

398
00:15:16,000 --> 00:15:18,000
they're actually giving them less than they expect.

399
00:15:18,000 --> 00:15:20,000
So they look like they're starting out with a big amount.

400
00:15:20,000 --> 00:15:22,000
These are three grapes; the monkey's really psyched for this.

401
00:15:22,000 --> 00:15:25,000
But now they learn these guys are going to give them less than they expect.

402
00:15:25,000 --> 00:15:27,000
They guy on the left is a safe loss.

403
00:15:27,000 --> 00:15:30,000
Every single time, he's going to take one of these away

404
00:15:30,000 --> 00:15:32,000
and give the monkeys just two.

405
00:15:32,000 --> 00:15:34,000
the guy on the right is the risky loss.

406
00:15:34,000 --> 00:15:37,000
Sometimes he gives no loss, so the monkeys are really psyched,

407
00:15:37,000 --> 00:15:39,000
but sometimes he actually gives a big loss,

408
00:15:39,000 --> 00:15:41,000
taking away two to give the monkeys only one.

409
00:15:41,000 --> 00:15:43,000
And so what do the monkeys do?

410
00:15:43,000 --> 00:15:45,000
Again, same choice; they can play it safe

411
00:15:45,000 --> 00:15:48,000
for always getting two grapes every single time,

412
00:15:48,000 --> 00:15:51,000
or they can take a risky bet and choose between one and three.

413
00:15:51,000 --> 00:15:54,000
The remarkable thing to us is that, when you give monkeys this choice,

414
00:15:54,000 --> 00:15:56,000
they do the same irrational thing that people do.

415
00:15:56,000 --> 00:15:58,000
They actually become more risky

416
00:15:58,000 --> 00:16:01,000
depending on how the experimenters started.

417
00:16:01,000 --> 00:16:03,000
This is crazy because it suggests that the monkeys too

418
00:16:03,000 --> 00:16:05,000
are evaluating things in relative terms

419
00:16:05,000 --> 00:16:08,000
and actually treating losses differently than they treat gains.

420
00:16:08,000 --> 00:16:10,000
So what does all of this mean?

421
00:16:10,000 --> 00:16:12,000
Well, what we've shown is that, first of all,

422
00:16:12,000 --> 00:16:14,000
we can actually give the monkeys a financial currency,

423
00:16:14,000 --> 00:16:16,000
and they do very similar things with it.

424
00:16:16,000 --> 00:16:18,000
They do some of the smart things we do,

425
00:16:18,000 --> 00:16:20,000
some of the kind of not so nice things we do,

426
00:16:20,000 --> 00:16:22,000
like steal it and so on.

427
00:16:22,000 --> 00:16:24,000
But they also do some of the irrational things we do.

428
00:16:24,000 --> 00:16:26,000
They systematically get things wrong

429
00:16:26,000 --> 00:16:28,000
and in the same ways that we do.

430
00:16:28,000 --> 00:16:30,000
This is the first take-home message of the Talk,

431
00:16:30,000 --> 00:16:32,000
which is that if you saw the beginning of this and you thought,

432
00:16:32,000 --> 00:16:34,000
oh, I'm totally going to go home and hire a capuchin monkey financial adviser.

433
00:16:34,000 --> 00:16:36,000
They're way cuter than the one at ... you know --

434
00:16:36,000 --> 00:16:38,000
Don't do that; they're probably going to be just as dumb

435
00:16:38,000 --> 00:16:41,000
as the human one you already have.

436
00:16:41,000 --> 00:16:43,000
So, you know, a little bad -- Sorry, sorry, sorry.

437
00:16:43,000 --> 00:16:45,000
A little bad for monkey investors.

438
00:16:45,000 --> 00:16:48,000
But of course, you know, the reason you're laughing is bad for humans too.

439
00:16:48,000 --> 00:16:51,000
Because we've answered the question we started out with.

440
00:16:51,000 --> 00:16:53,000
We wanted to know where these kinds of errors came from.

441
00:16:53,000 --> 00:16:55,000
And we started with the hope that maybe we can

442
00:16:55,000 --> 00:16:57,000
sort of tweak our financial institutions,

443
00:16:57,000 --> 00:17:00,000
tweak our technologies to make ourselves better.

444
00:17:00,000 --> 00:17:03,000
But what we've learn is that these biases might be a deeper part of us than that.

445
00:17:03,000 --> 00:17:05,000
In fact, they might be due to the very nature

446
00:17:05,000 --> 00:17:07,000
of our evolutionary history.

447
00:17:07,000 --> 00:17:09,000
You know, maybe it's not just humans

448
00:17:09,000 --> 00:17:11,000
at the right side of this chain that's duncey.

449
00:17:11,000 --> 00:17:13,000
Maybe it's sort of duncey all the way back.

450
00:17:13,000 --> 00:17:16,000
And this, if we believe the capuchin monkey results,

451
00:17:16,000 --> 00:17:18,000
means that these duncey strategies

452
00:17:18,000 --> 00:17:20,000
might be 35 million years old.

453
00:17:20,000 --> 00:17:22,000
That's a long time for a strategy

454
00:17:22,000 --> 00:17:25,000
to potentially get changed around -- really, really old.

455
00:17:25,000 --> 00:17:27,000
What do we know about other old strategies like this?

456
00:17:27,000 --> 00:17:30,000
Well, one thing we know is that they tend to be really hard to overcome.

457
00:17:30,000 --> 00:17:32,000
You know, think of our evolutionary predilection

458
00:17:32,000 --> 00:17:35,000
for eating sweet things, fatty things like cheesecake.

459
00:17:35,000 --> 00:17:37,000
You can't just shut that off.

460
00:17:37,000 --> 00:17:40,000
You can't just look at the dessert cart as say, "No, no, no. That looks disgusting to me."

461
00:17:40,000 --> 00:17:42,000
We're just built differently.

462
00:17:42,000 --> 00:17:44,000
We're going to perceive it as a good thing to go after.

463
00:17:44,000 --> 00:17:46,000
My guess is that the same thing is going to be true

464
00:17:46,000 --> 00:17:48,000
when humans are perceiving

465
00:17:48,000 --> 00:17:50,000
different financial decisions.

466
00:17:50,000 --> 00:17:52,000
When you're watching your stocks plummet into the red,

467
00:17:52,000 --> 00:17:54,000
when you're watching your house price go down,

468
00:17:54,000 --> 00:17:56,000
you're not going to be able to see that

469
00:17:56,000 --> 00:17:58,000
in anything but old evolutionary terms.

470
00:17:58,000 --> 00:18:00,000
This means that the biases

471
00:18:00,000 --> 00:18:02,000
that lead investors to do badly,

472
00:18:02,000 --> 00:18:04,000
that lead to the foreclosure crisis

473
00:18:04,000 --> 00:18:06,000
are going to be really hard to overcome.

474
00:18:06,000 --> 00:18:08,000
So that's the bad news. The question is: is there any good news?

475
00:18:08,000 --> 00:18:10,000
I'm supposed to be up here telling you the good news.

476
00:18:10,000 --> 00:18:12,000
Well, the good news, I think,

477
00:18:12,000 --> 00:18:14,000
is what I started with at the beginning of the Talk,

478
00:18:14,000 --> 00:18:16,000
which is that humans are not only smart;

479
00:18:16,000 --> 00:18:18,000
we're really inspirationally smart

480
00:18:18,000 --> 00:18:21,000
to the rest of the animals in the biological kingdom.

481
00:18:21,000 --> 00:18:24,000
We're so good at overcoming our biological limitations --

482
00:18:24,000 --> 00:18:26,000
you know, I flew over here in an airplane.

483
00:18:26,000 --> 00:18:28,000
I didn't have to try to flap my wings.

484
00:18:28,000 --> 00:18:31,000
I'm wearing contact lenses now so that I can see all of you.

485
00:18:31,000 --> 00:18:34,000
I don't have to rely on my own near-sightedness.

486
00:18:34,000 --> 00:18:36,000
We actually have all of these cases

487
00:18:36,000 --> 00:18:39,000
where we overcome our biological limitations

488
00:18:39,000 --> 00:18:42,000
through technology and other means, seemingly pretty easily.

489
00:18:42,000 --> 00:18:45,000
But we have to recognize that we have those limitations.

490
00:18:45,000 --> 00:18:47,000
And here's the rub.

491
00:18:47,000 --> 00:18:49,000
It was Camus who once said that, "Man is the only species

492
00:18:49,000 --> 00:18:52,000
who refuses to be what he really is."

493
00:18:52,000 --> 00:18:54,000
But the irony is that

494
00:18:54,000 --> 00:18:56,000
it might only be in recognizing our limitations

495
00:18:56,000 --> 00:18:58,000
that we can really actually overcome them.

496
00:18:58,000 --> 00:19:01,000
The hope is that you all will think about your limitations,

497
00:19:01,000 --> 00:19:04,000
not necessarily as unovercomable,

498
00:19:04,000 --> 00:19:06,000
but to recognize them, accept them

499
00:19:06,000 --> 00:19:09,000
and then use the world of design to actually figure them out.

500
00:19:09,000 --> 00:19:12,000
That might be the only way that we will really be able

501
00:19:12,000 --> 00:19:14,000
to achieve our own human potential

502
00:19:14,000 --> 00:19:17,000
and really be the noble species we hope to all be.

503
00:19:17,000 --> 00:19:19,000
Thank you.

504
00:19:19,000 --> 00:19:24,000
(Applause)