[Script Info]
Title: 
[Events]
Format: Layer, Start, End, Style, Name, MarginL, MarginR, MarginV, Effect, Text
Dialogue: 0,0:00:00.84,0:00:02.99,Default,,0000,0000,0000,,Mark Twain summed up\Nwhat I take to be
Dialogue: 0,0:00:02.99,0:00:06.11,Default,,0000,0000,0000,,one of the fundamental problems\Nof cognitive science
Dialogue: 0,0:00:06.11,0:00:07.82,Default,,0000,0000,0000,,with a single witticism.
Dialogue: 0,0:00:08.41,0:00:11.49,Default,,0000,0000,0000,,He said, "There's something\Nfascinating about science.
Dialogue: 0,0:00:11.49,0:00:14.72,Default,,0000,0000,0000,,One gets such wholesale\Nreturns of conjecture
Dialogue: 0,0:00:14.72,0:00:17.92,Default,,0000,0000,0000,,out of such a trifling\Ninvestment in fact."
Dialogue: 0,0:00:17.92,0:00:19.51,Default,,0000,0000,0000,,(Laughter)
Dialogue: 0,0:00:20.20,0:00:22.80,Default,,0000,0000,0000,,Twain meant it as a joke,\Nof course, but he's right:
Dialogue: 0,0:00:22.80,0:00:25.68,Default,,0000,0000,0000,,There's something\Nfascinating about science.
Dialogue: 0,0:00:25.68,0:00:29.94,Default,,0000,0000,0000,,From a few bones, we infer\Nthe existence of dinosuars.
Dialogue: 0,0:00:30.91,0:00:34.78,Default,,0000,0000,0000,,From spectral lines,\Nthe composition of nebulae.
Dialogue: 0,0:00:35.47,0:00:38.41,Default,,0000,0000,0000,,From fruit flies,
Dialogue: 0,0:00:38.41,0:00:41.35,Default,,0000,0000,0000,,the mechanisms of heredity,
Dialogue: 0,0:00:41.35,0:00:45.60,Default,,0000,0000,0000,,and from reconstructed images\Nof blood flowing through the brain,
Dialogue: 0,0:00:45.60,0:00:50.31,Default,,0000,0000,0000,,or in my case, from the behavior\Nof very young children,
Dialogue: 0,0:00:50.31,0:00:53.14,Default,,0000,0000,0000,,we try to say something about\Nthe fundamental mechanisms
Dialogue: 0,0:00:53.14,0:00:54.76,Default,,0000,0000,0000,,of human cognition.
Dialogue: 0,0:00:55.72,0:01:00.48,Default,,0000,0000,0000,,In particular, in my lab in the Department\Nof Brain and Cognitive Sciences at MIT,
Dialogue: 0,0:01:00.48,0:01:04.13,Default,,0000,0000,0000,,I have spent the past decade\Ntrying to understand the mystery
Dialogue: 0,0:01:04.13,0:01:08.11,Default,,0000,0000,0000,,of how children learn so much\Nfrom so little so quickly.
Dialogue: 0,0:01:08.67,0:01:11.64,Default,,0000,0000,0000,,Because, it turns out that\Nthe fascinating thing about science
Dialogue: 0,0:01:11.64,0:01:15.17,Default,,0000,0000,0000,,is also a fascinating\Nthing about children,
Dialogue: 0,0:01:15.17,0:01:17.75,Default,,0000,0000,0000,,which, to put a gentler\Nspin on Mark Twain,
Dialogue: 0,0:01:17.75,0:01:22.40,Default,,0000,0000,0000,,is precisely their ability\Nto draw rich, abstract inferences
Dialogue: 0,0:01:22.40,0:01:27.06,Default,,0000,0000,0000,,rapidly and accurately\Nfrom sparse, noisy data.
Dialogue: 0,0:01:28.36,0:01:30.75,Default,,0000,0000,0000,,I'm going to give you\Njust two examples today.
Dialogue: 0,0:01:30.75,0:01:33.04,Default,,0000,0000,0000,,One is about a problem of generalization,
Dialogue: 0,0:01:33.04,0:01:35.89,Default,,0000,0000,0000,,and the other is about a problem\Nof causal reasoning.
Dialogue: 0,0:01:35.89,0:01:38.42,Default,,0000,0000,0000,,And although I'm going to talk\Nabout work in my lab,
Dialogue: 0,0:01:38.42,0:01:41.88,Default,,0000,0000,0000,,this work is inspired by\Nand indebted to a field.
Dialogue: 0,0:01:41.88,0:01:46.16,Default,,0000,0000,0000,,I'm grateful to mentors, colleagues,\Nand collaborators around the world.
Dialogue: 0,0:01:47.31,0:01:50.28,Default,,0000,0000,0000,,Let me start with the problem\Nof generalization.
Dialogue: 0,0:01:50.65,0:01:54.78,Default,,0000,0000,0000,,Generalizing from small samples of data\Nis the bread and butter of science.
Dialogue: 0,0:01:54.78,0:01:57.34,Default,,0000,0000,0000,,We poll a tiny fraction of the electorate
Dialogue: 0,0:01:57.34,0:01:59.66,Default,,0000,0000,0000,,and we predict the outcome\Nof national elections.
Dialogue: 0,0:02:00.24,0:02:04.16,Default,,0000,0000,0000,,We see how a handful of patients\Nresponds to treatment in a clinical trial,
Dialogue: 0,0:02:04.16,0:02:07.23,Default,,0000,0000,0000,,and we bring drugs to a national market.
Dialogue: 0,0:02:07.23,0:02:11.60,Default,,0000,0000,0000,,But this only works if our sample\Nis randomly drawn from the population.
Dialogue: 0,0:02:11.60,0:02:14.33,Default,,0000,0000,0000,,If our sample is cherry-picked\Nin some way --
Dialogue: 0,0:02:14.33,0:02:16.40,Default,,0000,0000,0000,,say, we poll only urban voters,
Dialogue: 0,0:02:16.40,0:02:20.79,Default,,0000,0000,0000,,or say, in our clinical trials\Nfor treatments for heart disease,
Dialogue: 0,0:02:20.79,0:02:22.67,Default,,0000,0000,0000,,we include only men --
Dialogue: 0,0:02:22.67,0:02:25.83,Default,,0000,0000,0000,,the results may not generalize\Nto the broader population.
Dialogue: 0,0:02:26.48,0:02:30.06,Default,,0000,0000,0000,,So scientists care whether evidence\Nis randomly sampled or not,
Dialogue: 0,0:02:30.06,0:02:32.08,Default,,0000,0000,0000,,but what does that have to do with babies?
Dialogue: 0,0:02:32.58,0:02:37.21,Default,,0000,0000,0000,,Well, babies have to generalize\Nfrom small samples of data all the time.
Dialogue: 0,0:02:37.21,0:02:40.36,Default,,0000,0000,0000,,They see a few rubber ducks\Nand learn that they float,
Dialogue: 0,0:02:40.36,0:02:43.94,Default,,0000,0000,0000,,or a few balls and learn that they bounce.
Dialogue: 0,0:02:43.94,0:02:46.89,Default,,0000,0000,0000,,And they develop expectations\Nabout ducks and balls
Dialogue: 0,0:02:46.89,0:02:49.61,Default,,0000,0000,0000,,that they're going to extend\Nto rubber ducks and balls
Dialogue: 0,0:02:49.61,0:02:51.48,Default,,0000,0000,0000,,for the rest of their lives.
Dialogue: 0,0:02:51.48,0:02:55.22,Default,,0000,0000,0000,,And the kinds of generalizations\Nbabies have to make about ducks and balls
Dialogue: 0,0:02:55.22,0:02:57.31,Default,,0000,0000,0000,,they have to make about almost everything:
Dialogue: 0,0:02:57.31,0:03:01.23,Default,,0000,0000,0000,,shoes and ships and ceiling wax\Nand cabbages and kings.
Dialogue: 0,0:03:02.20,0:03:05.16,Default,,0000,0000,0000,,So do babies care whether\Nthe tiny bit of evidence they see
Dialogue: 0,0:03:05.16,0:03:08.85,Default,,0000,0000,0000,,is plausibly representative\Nof a larger population?
Dialogue: 0,0:03:09.76,0:03:11.66,Default,,0000,0000,0000,,Let's find out.
Dialogue: 0,0:03:11.66,0:03:13.39,Default,,0000,0000,0000,,I'm going to show you two movies,
Dialogue: 0,0:03:13.39,0:03:15.85,Default,,0000,0000,0000,,one from each of two conditions\Nof an experiment,
Dialogue: 0,0:03:15.85,0:03:18.29,Default,,0000,0000,0000,,and because you're going to see\Njust two movies,
Dialogue: 0,0:03:18.29,0:03:20.42,Default,,0000,0000,0000,,you're going to see just two babies,
Dialogue: 0,0:03:20.42,0:03:24.37,Default,,0000,0000,0000,,and any two babies differ from each other\Nin innumerable ways.
Dialogue: 0,0:03:24.37,0:03:27.42,Default,,0000,0000,0000,,But these babies, of course,\Nhere stand in for groups of babies,
Dialogue: 0,0:03:27.42,0:03:29.32,Default,,0000,0000,0000,,and the differences you're going to see
Dialogue: 0,0:03:29.32,0:03:34.51,Default,,0000,0000,0000,,represent average group differences\Nin babies' behavior across conditions.
Dialogue: 0,0:03:35.16,0:03:37.74,Default,,0000,0000,0000,,In each movie, you're going to see\Na baby doing maybe
Dialogue: 0,0:03:37.74,0:03:41.20,Default,,0000,0000,0000,,just exactly what you might\Nexpect a baby to do,
Dialogue: 0,0:03:41.20,0:03:45.22,Default,,0000,0000,0000,,and we can hardly make babies\Nmore magical than they already are.
Dialogue: 0,0:03:46.09,0:03:48.10,Default,,0000,0000,0000,,But to my mind the magical thing,
Dialogue: 0,0:03:48.10,0:03:50.19,Default,,0000,0000,0000,,and what I want you to pay attention to,
Dialogue: 0,0:03:50.19,0:03:53.30,Default,,0000,0000,0000,,is the contrast between\Nthese two conditions,
Dialogue: 0,0:03:53.30,0:03:56.83,Default,,0000,0000,0000,,because the only thing\Nthat differs between these two movies
Dialogue: 0,0:03:56.83,0:04:00.30,Default,,0000,0000,0000,,is the statistical evidence\Nthe babies are going to observe.
Dialogue: 0,0:04:01.42,0:04:04.61,Default,,0000,0000,0000,,We're going to show babies\Na box of blue and yellow balls,
Dialogue: 0,0:04:04.61,0:04:09.23,Default,,0000,0000,0000,,and my then-graduate student,\Nnow colleague at Stanford, Hyowon Gweon,
Dialogue: 0,0:04:09.23,0:04:12.30,Default,,0000,0000,0000,,is going to pull three blue balls\Nin a row out of this box,
Dialogue: 0,0:04:12.30,0:04:15.43,Default,,0000,0000,0000,,and when she pulls those balls out,\Nshe's going to squeeze them,
Dialogue: 0,0:04:15.43,0:04:17.54,Default,,0000,0000,0000,,and the balls are going to squeak.
Dialogue: 0,0:04:17.54,0:04:20.30,Default,,0000,0000,0000,,And if you're a baby,\Nthat's like a TED Talk.
Dialogue: 0,0:04:20.30,0:04:22.21,Default,,0000,0000,0000,,It doesn't get better than that.
Dialogue: 0,0:04:22.21,0:04:24.77,Default,,0000,0000,0000,,(Laughter)
Dialogue: 0,0:04:26.97,0:04:30.63,Default,,0000,0000,0000,,But the important point is it's really\Neasy to pull three blue balls in a row
Dialogue: 0,0:04:30.63,0:04:32.93,Default,,0000,0000,0000,,out of a box of mostly blue balls.
Dialogue: 0,0:04:32.93,0:04:34.99,Default,,0000,0000,0000,,You could do that with your eyes closed.
Dialogue: 0,0:04:34.99,0:04:37.99,Default,,0000,0000,0000,,It's plausibly a random sample\Nfrom this population.
Dialogue: 0,0:04:37.99,0:04:41.72,Default,,0000,0000,0000,,And if you can reach into a box at random\Nand pull out things that squeak,
Dialogue: 0,0:04:41.72,0:04:44.56,Default,,0000,0000,0000,,then maybe everything in the box squeaks.
Dialogue: 0,0:04:44.56,0:04:48.21,Default,,0000,0000,0000,,So maybe babies should expect\Nthose yellow balls to squeak as well.
Dialogue: 0,0:04:48.21,0:04:50.73,Default,,0000,0000,0000,,Now, those yellow balls\Nhave funny sticks on the end,
Dialogue: 0,0:04:50.73,0:04:53.58,Default,,0000,0000,0000,,so babies could do other things\Nwith them if they wanted to.
Dialogue: 0,0:04:53.58,0:04:55.42,Default,,0000,0000,0000,,They could pound them or whack them.
Dialogue: 0,0:04:55.42,0:04:58.00,Default,,0000,0000,0000,,But let's see what the baby does.
Dialogue: 0,0:05:00.55,0:05:03.89,Default,,0000,0000,0000,,(Video) Hyowon Gweon: See this?\N(Ball squeaks)
Dialogue: 0,0:05:04.53,0:05:07.58,Default,,0000,0000,0000,,Did you see that?\N(Ball squeaks)
Dialogue: 0,0:05:08.04,0:05:11.10,Default,,0000,0000,0000,,Cool.
Dialogue: 0,0:05:12.71,0:05:14.66,Default,,0000,0000,0000,,See this one?
Dialogue: 0,0:05:14.66,0:05:16.54,Default,,0000,0000,0000,,(Ball squeaks)
Dialogue: 0,0:05:16.54,0:05:19.19,Default,,0000,0000,0000,,Wow.
Dialogue: 0,0:05:21.85,0:05:23.97,Default,,0000,0000,0000,,Laura Schulz: Told you. (Laughs)
Dialogue: 0,0:05:23.97,0:05:27.100,Default,,0000,0000,0000,,(Video) HG: See this one?\N(Ball squeaks)
Dialogue: 0,0:05:27.100,0:05:32.62,Default,,0000,0000,0000,,Hey Clara, this one's for you.\NYou can go ahead and play.
Dialogue: 0,0:05:39.85,0:05:44.22,Default,,0000,0000,0000,,(Laughter)
Dialogue: 0,0:05:44.22,0:05:47.21,Default,,0000,0000,0000,,LS: I don't even have to talk, right?
Dialogue: 0,0:05:47.21,0:05:50.11,Default,,0000,0000,0000,,All right, it's nice that babies\Nwill generalize properties
Dialogue: 0,0:05:50.11,0:05:51.64,Default,,0000,0000,0000,,of blue balls to yellow balls,
Dialogue: 0,0:05:51.64,0:05:54.74,Default,,0000,0000,0000,,and it's impressive that babies\Ncan learn from imitating us,
Dialogue: 0,0:05:54.74,0:05:58.41,Default,,0000,0000,0000,,but we've known those things about babies\Nfor a very long time.
Dialogue: 0,0:05:58.41,0:06:00.22,Default,,0000,0000,0000,,The really interesting question
Dialogue: 0,0:06:00.22,0:06:03.07,Default,,0000,0000,0000,,is what happens when we show babies\Nexactly the same thing,
Dialogue: 0,0:06:03.07,0:06:06.68,Default,,0000,0000,0000,,and we can ensure it's exactly the same\Nbecause we have a secret compartment
Dialogue: 0,0:06:06.68,0:06:08.79,Default,,0000,0000,0000,,and we actually pull the balls from there,
Dialogue: 0,0:06:08.79,0:06:12.27,Default,,0000,0000,0000,,but this time, all we change\Nis the apparent population
Dialogue: 0,0:06:12.27,0:06:15.17,Default,,0000,0000,0000,,from which that evidence was drawn.
Dialogue: 0,0:06:15.17,0:06:18.72,Default,,0000,0000,0000,,This time, we're going to show babies\Nthree blue balls
Dialogue: 0,0:06:18.72,0:06:22.11,Default,,0000,0000,0000,,pulled out of a box\Nof mostly yellow balls,
Dialogue: 0,0:06:22.11,0:06:23.43,Default,,0000,0000,0000,,and guess what?
Dialogue: 0,0:06:23.43,0:06:26.27,Default,,0000,0000,0000,,You [probably won't] randomly draw\Nthree blue balls in a row
Dialogue: 0,0:06:26.27,0:06:28.75,Default,,0000,0000,0000,,out of a box of mostly yellow balls.
Dialogue: 0,0:06:28.75,0:06:32.50,Default,,0000,0000,0000,,That is not plausibly\Nrandomly sampled evidence.
Dialogue: 0,0:06:32.50,0:06:37.62,Default,,0000,0000,0000,,That evidence suggests that maybe Yowan\Nwas deliberately sampling the blue balls.
Dialogue: 0,0:06:37.62,0:06:40.21,Default,,0000,0000,0000,,Maybe there's something special\Nabout the blue balls.
Dialogue: 0,0:06:40.85,0:06:43.82,Default,,0000,0000,0000,,Maybe only the blue balls squeak.
Dialogue: 0,0:06:43.82,0:06:45.72,Default,,0000,0000,0000,,Let's see what the baby does.
Dialogue: 0,0:06:45.72,0:06:48.62,Default,,0000,0000,0000,,(Video) YG: See this?\N(Ball squeaks)
Dialogue: 0,0:06:50.85,0:06:53.50,Default,,0000,0000,0000,,See this toy?\N(Ball squeaks)
Dialogue: 0,0:06:53.50,0:06:58.98,Default,,0000,0000,0000,,Oh, that was cool. See?\N(Ball squeaks)
Dialogue: 0,0:06:58.98,0:07:03.37,Default,,0000,0000,0000,,Now this one's for you to play.\NYou can go ahead and play.
Dialogue: 0,0:07:11.26,0:07:13.91,Default,,0000,0000,0000,,(Baby cries)
Dialogue: 0,0:07:14.90,0:07:17.65,Default,,0000,0000,0000,,LS: So you just saw\Ntwo 15-month old babies
Dialogue: 0,0:07:17.65,0:07:19.59,Default,,0000,0000,0000,,do entirely different things
Dialogue: 0,0:07:19.59,0:07:23.19,Default,,0000,0000,0000,,based only on the probability\Nof the sample they observed.
Dialogue: 0,0:07:23.19,0:07:25.51,Default,,0000,0000,0000,,Let me show you the experimental results.
Dialogue: 0,0:07:25.51,0:07:28.28,Default,,0000,0000,0000,,On the vertical axis, you'll see\Nthe percentage of babies
Dialogue: 0,0:07:28.28,0:07:30.80,Default,,0000,0000,0000,,who squeezed the ball in each condition,
Dialogue: 0,0:07:30.80,0:07:34.52,Default,,0000,0000,0000,,and as you'll see, babies are much\Nmore likely to generalize the evidence
Dialogue: 0,0:07:34.52,0:07:37.66,Default,,0000,0000,0000,,when it's plausibly representative\Nof the population
Dialogue: 0,0:07:37.66,0:07:41.39,Default,,0000,0000,0000,,than when the evidence\Nis clearly cherry-picked.
Dialogue: 0,0:07:41.39,0:07:43.81,Default,,0000,0000,0000,,And this leads to a fun prediction:
Dialogue: 0,0:07:43.81,0:07:48.68,Default,,0000,0000,0000,,suppose you pulled just one blue ball\Nout of the mostly yellow box.
Dialogue: 0,0:07:48.90,0:07:52.76,Default,,0000,0000,0000,,Now, you just can't pull three blue balls\Nin a row at random out of a yellow box,
Dialogue: 0,0:07:52.76,0:07:55.22,Default,,0000,0000,0000,,but you could randomly sample\Njust one blue ball.
Dialogue: 0,0:07:55.22,0:07:57.19,Default,,0000,0000,0000,,That's not an improbable sample.
Dialogue: 0,0:07:57.19,0:07:59.41,Default,,0000,0000,0000,,And if you could reach into\Na box at random
Dialogue: 0,0:07:59.41,0:08:03.40,Default,,0000,0000,0000,,and pull out something that squeaks,\Nmaybe everything in the box squeaks.
Dialogue: 0,0:08:03.88,0:08:08.32,Default,,0000,0000,0000,,So even though babies are going to see\Nmuch less evidence for squeaking,
Dialogue: 0,0:08:08.32,0:08:10.56,Default,,0000,0000,0000,,and have many fewer actions to imitate
Dialogue: 0,0:08:10.56,0:08:13.90,Default,,0000,0000,0000,,in this one ball condition than in\Nthe condition you just saw,
Dialogue: 0,0:08:13.90,0:08:17.80,Default,,0000,0000,0000,,we predicted that babies themselves\Nwould squeeze more,
Dialogue: 0,0:08:17.80,0:08:20.69,Default,,0000,0000,0000,,and that's exactly what we found.
Dialogue: 0,0:08:20.69,0:08:25.10,Default,,0000,0000,0000,,So 15-month old babies,\Nin this respect, like scientists,
Dialogue: 0,0:08:25.10,0:08:28.19,Default,,0000,0000,0000,,care whether evidence\Nis randomly sampled or not,
Dialogue: 0,0:08:28.19,0:08:31.70,Default,,0000,0000,0000,,and they use this to develop\Nexpectations about the world:
Dialogue: 0,0:08:31.70,0:08:33.88,Default,,0000,0000,0000,,what squeaks and what doesn't,
Dialogue: 0,0:08:33.88,0:08:37.02,Default,,0000,0000,0000,,what to explore and what to ignore.
Dialogue: 0,0:08:38.38,0:08:40.45,Default,,0000,0000,0000,,Let me show you another example now,
Dialogue: 0,0:08:40.45,0:08:43.18,Default,,0000,0000,0000,,this time about a problem\Nof causal reasoning.
Dialogue: 0,0:08:43.18,0:08:45.62,Default,,0000,0000,0000,,And it starts with a problem\Nof confounded evidence
Dialogue: 0,0:08:45.62,0:08:47.29,Default,,0000,0000,0000,,that all of us have,
Dialogue: 0,0:08:47.29,0:08:49.31,Default,,0000,0000,0000,,which is that we are part of the world.
Dialogue: 0,0:08:49.31,0:08:52.75,Default,,0000,0000,0000,,And this may not seem like a problem\Nto you, but like most problems,
Dialogue: 0,0:08:52.75,0:08:55.08,Default,,0000,0000,0000,,it's only a problem when things go wrong.
Dialogue: 0,0:08:55.46,0:08:57.28,Default,,0000,0000,0000,,Take this baby, for instance.
Dialogue: 0,0:08:57.28,0:08:58.98,Default,,0000,0000,0000,,Things are going wrong for him.
Dialogue: 0,0:08:58.98,0:09:01.25,Default,,0000,0000,0000,,He would like to make\Nthis toy go, and he can't.
Dialogue: 0,0:09:01.25,0:09:03.78,Default,,0000,0000,0000,,I'll show you a few second clip.
Dialogue: 0,0:09:09.34,0:09:11.26,Default,,0000,0000,0000,,And there's two possibilities, broadly:
Dialogue: 0,0:09:11.26,0:09:13.89,Default,,0000,0000,0000,,maybe he's doing something wrong,
Dialogue: 0,0:09:13.89,0:09:18.11,Default,,0000,0000,0000,,or maybe there's something\Nwrong with the toy.
Dialogue: 0,0:09:18.11,0:09:20.22,Default,,0000,0000,0000,,So in this next experiment,
Dialogue: 0,0:09:20.22,0:09:23.52,Default,,0000,0000,0000,,we're going to give babies\Njust a tiny bit of statistical data
Dialogue: 0,0:09:23.52,0:09:26.10,Default,,0000,0000,0000,,supporting one hypothesis over the other,
Dialogue: 0,0:09:26.10,0:09:29.56,Default,,0000,0000,0000,,and we're going to see if babies\Ncan use that to make different decisions
Dialogue: 0,0:09:29.56,0:09:31.39,Default,,0000,0000,0000,,about what to do.
Dialogue: 0,0:09:31.39,0:09:33.41,Default,,0000,0000,0000,,Here's the setup.
Dialogue: 0,0:09:34.07,0:09:37.10,Default,,0000,0000,0000,,Yowan is going to try to make\Nthe toy go and succeed.
Dialogue: 0,0:09:37.10,0:09:40.42,Default,,0000,0000,0000,,I am then going to try twice\Nand fail both times,
Dialogue: 0,0:09:40.42,0:09:43.53,Default,,0000,0000,0000,,and then Yowan is going\Nto try again and succeed,
Dialogue: 0,0:09:43.53,0:09:46.70,Default,,0000,0000,0000,,and this roughly sums up my relationship\Nto my graduate students
Dialogue: 0,0:09:46.70,0:09:49.54,Default,,0000,0000,0000,,in technology across the board.
Dialogue: 0,0:09:50.03,0:09:53.32,Default,,0000,0000,0000,,But the important point here is\Nit provides a little bit of evidence
Dialogue: 0,0:09:53.32,0:09:57.01,Default,,0000,0000,0000,,that the problem isn't with the toy,\Nit's with the person.
Dialogue: 0,0:09:57.61,0:09:59.34,Default,,0000,0000,0000,,Some people can make this toy go,
Dialogue: 0,0:09:59.34,0:10:00.30,Default,,0000,0000,0000,,and some can't.
Dialogue: 0,0:10:00.80,0:10:04.21,Default,,0000,0000,0000,,Now, when the baby gets the toy,\Nhe's going to have a choice.
Dialogue: 0,0:10:04.21,0:10:06.40,Default,,0000,0000,0000,,His mom is right there,
Dialogue: 0,0:10:06.40,0:10:09.72,Default,,0000,0000,0000,,so he can go ahead and hand off the toy\Nand change the person,
Dialogue: 0,0:10:09.72,0:10:12.87,Default,,0000,0000,0000,,but there's also going to be\Nanother toy at the end of that cloth,
Dialogue: 0,0:10:12.87,0:10:16.42,Default,,0000,0000,0000,,and he can pull the cloth towards him\Nand change the toy.
Dialogue: 0,0:10:16.42,0:10:18.52,Default,,0000,0000,0000,,So let's see what the baby does.
Dialogue: 0,0:10:18.52,0:10:21.28,Default,,0000,0000,0000,,(Video) YG: Two, three. Go!
Dialogue: 0,0:10:21.28,0:10:25.83,Default,,0000,0000,0000,,(Video) LS: One, two, three, go!
Dialogue: 0,0:10:25.83,0:10:33.21,Default,,0000,0000,0000,,Arthur, I'm going to try again.\NOne, two, three, go!
Dialogue: 0,0:10:33.68,0:10:36.28,Default,,0000,0000,0000,,(Video) YG: Arthur,\Nlet me try again, okay?
Dialogue: 0,0:10:36.28,0:10:40.83,Default,,0000,0000,0000,,One, two, three, go!
Dialogue: 0,0:10:41.58,0:10:43.47,Default,,0000,0000,0000,,Look at that. Remember these toys?
Dialogue: 0,0:10:43.47,0:10:46.73,Default,,0000,0000,0000,,See these toys? Yeah, I'm going\Nto put this one over here,
Dialogue: 0,0:10:46.73,0:10:48.79,Default,,0000,0000,0000,,and I'm going to give this one to you.
Dialogue: 0,0:10:48.79,0:10:51.13,Default,,0000,0000,0000,,You can go ahead and play.
Dialogue: 0,0:11:11.21,0:11:15.95,Default,,0000,0000,0000,,LS: Okay, Laura, but of course,\Nbabies love their mommies.
Dialogue: 0,0:11:15.95,0:11:18.13,Default,,0000,0000,0000,,Of course babies give toys\Nto their mommies
Dialogue: 0,0:11:18.13,0:11:20.16,Default,,0000,0000,0000,,when they can't make them work.
Dialogue: 0,0:11:20.16,0:11:23.76,Default,,0000,0000,0000,,So again, the really important question\Nis what happens when we change
Dialogue: 0,0:11:23.76,0:11:26.91,Default,,0000,0000,0000,,the statistical data ever so slightly.
Dialogue: 0,0:11:26.91,0:11:30.100,Default,,0000,0000,0000,,This time, babies are going to see the toy\Nwork and fail in exactly the same order,
Dialogue: 0,0:11:30.100,0:11:33.41,Default,,0000,0000,0000,,but we're changing\Nthe distribution of evidence.
Dialogue: 0,0:11:33.41,0:11:37.82,Default,,0000,0000,0000,,This time, Yowan is going to succeed\Nonce and fail once, and so am I.
Dialogue: 0,0:11:37.82,0:11:43.46,Default,,0000,0000,0000,,And this suggests it doesn't matter\Nwho tries this toy, the toy is broken.
Dialogue: 0,0:11:43.46,0:11:45.34,Default,,0000,0000,0000,,It doesn't work all the time.
Dialogue: 0,0:11:45.34,0:11:47.31,Default,,0000,0000,0000,,Again, the baby's going to have a choice.
Dialogue: 0,0:11:47.31,0:11:50.71,Default,,0000,0000,0000,,Her mom is right next to her,\Nso she can change the person,
Dialogue: 0,0:11:50.71,0:11:53.91,Default,,0000,0000,0000,,and there's going to be another toy\Nat the end of the cloth.
Dialogue: 0,0:11:53.91,0:11:55.29,Default,,0000,0000,0000,,Let's watch what she does.
Dialogue: 0,0:11:55.29,0:11:59.64,Default,,0000,0000,0000,,(Video) YG: Two, three, go!
Dialogue: 0,0:11:59.64,0:12:04.62,Default,,0000,0000,0000,,Let me try one more time.\NOne, two, three, go!
Dialogue: 0,0:12:05.46,0:12:07.16,Default,,0000,0000,0000,,Hmm.
Dialogue: 0,0:12:08.87,0:12:10.64,Default,,0000,0000,0000,,(Video) LS: Let me try, Clara.
Dialogue: 0,0:12:10.64,0:12:14.59,Default,,0000,0000,0000,,One, two, three, go!
Dialogue: 0,0:12:15.94,0:12:17.77,Default,,0000,0000,0000,,Hmm, let me try again.
Dialogue: 0,0:12:17.77,0:12:22.87,Default,,0000,0000,0000,,One, two, three, go!
Dialogue: 0,0:12:23.01,0:12:25.24,Default,,0000,0000,0000,,(Video) YG: I'm going\Nto put this one over here,
Dialogue: 0,0:12:25.24,0:12:27.24,Default,,0000,0000,0000,,and I'm going to give this one to you.
Dialogue: 0,0:12:27.24,0:12:30.84,Default,,0000,0000,0000,,You can go ahead and play.
Dialogue: 0,0:12:46.38,0:12:51.27,Default,,0000,0000,0000,,(Applause)
Dialogue: 0,0:12:52.99,0:12:55.38,Default,,0000,0000,0000,,LS: Let me show you\Nthe experimental results.
Dialogue: 0,0:12:55.38,0:12:57.86,Default,,0000,0000,0000,,On the vertical axis,\Nyou'll see the distribution
Dialogue: 0,0:12:57.86,0:13:00.44,Default,,0000,0000,0000,,of children's choices in each condition,
Dialogue: 0,0:13:00.44,0:13:04.99,Default,,0000,0000,0000,,and you'll see that the distribution\Nof the choices children make
Dialogue: 0,0:13:04.99,0:13:07.78,Default,,0000,0000,0000,,depends on the evidence they observe.
Dialogue: 0,0:13:07.78,0:13:09.63,Default,,0000,0000,0000,,So in the second year of life,
Dialogue: 0,0:13:09.63,0:13:12.21,Default,,0000,0000,0000,,babies can use a tiny bit\Nof statistical data
Dialogue: 0,0:13:12.21,0:13:15.58,Default,,0000,0000,0000,,to decide between two\Nfundamentally different strategies
Dialogue: 0,0:13:15.58,0:13:17.46,Default,,0000,0000,0000,,for acting on the world:
Dialogue: 0,0:13:17.46,0:13:20.20,Default,,0000,0000,0000,,asking for help and exploring.
Dialogue: 0,0:13:21.70,0:13:25.13,Default,,0000,0000,0000,,I've just shown you\Ntwo laboratory experiments
Dialogue: 0,0:13:25.13,0:13:28.82,Default,,0000,0000,0000,,out of literally hundreds in the field\Nthat make similar points,
Dialogue: 0,0:13:28.82,0:13:31.22,Default,,0000,0000,0000,,because the really critical point
Dialogue: 0,0:13:31.22,0:13:36.32,Default,,0000,0000,0000,,is that children's ability\Nto make rich inferences from sparse data
Dialogue: 0,0:13:36.32,0:13:41.67,Default,,0000,0000,0000,,underlies all the species-specific\Ncultural learning that we do.
Dialogue: 0,0:13:41.67,0:13:46.26,Default,,0000,0000,0000,,Children learn about new tools\Nfrom just a few examples.
Dialogue: 0,0:13:46.26,0:13:50.98,Default,,0000,0000,0000,,They learn new causal relationships\Nfrom just a few examples.
Dialogue: 0,0:13:51.93,0:13:56.80,Default,,0000,0000,0000,,They even learn new words,\Nin this case in American sign language.
Dialogue: 0,0:13:56.80,0:13:59.11,Default,,0000,0000,0000,,I want to close with just two points.
Dialogue: 0,0:14:00.05,0:14:03.74,Default,,0000,0000,0000,,If you've been following my world,\Nthe field of brain and cognitive sciences,
Dialogue: 0,0:14:03.74,0:14:05.66,Default,,0000,0000,0000,,for the past few years,
Dialogue: 0,0:14:05.66,0:14:08.08,Default,,0000,0000,0000,,three big ideas will have come\Nto your attention.
Dialogue: 0,0:14:08.57,0:14:11.52,Default,,0000,0000,0000,,The first is that this is\Nthe era of the brain.
Dialogue: 0,0:14:11.52,0:14:15.18,Default,,0000,0000,0000,,And indeed, there have been\Nstaggering discoveries in neuroscience:
Dialogue: 0,0:14:15.18,0:14:18.62,Default,,0000,0000,0000,,localizing, functionally specialized\Nregions of cortex,
Dialogue: 0,0:14:18.62,0:14:21.22,Default,,0000,0000,0000,,turning mouse brains transparent,
Dialogue: 0,0:14:21.22,0:14:24.100,Default,,0000,0000,0000,,activating neurons with light.
Dialogue: 0,0:14:24.100,0:14:26.99,Default,,0000,0000,0000,,A second big idea
Dialogue: 0,0:14:26.99,0:14:31.10,Default,,0000,0000,0000,,is that this is the era of big data\Nand machine learning,
Dialogue: 0,0:14:31.10,0:14:34.24,Default,,0000,0000,0000,,and machine learning promises\Nto revolutionize our understanding
Dialogue: 0,0:14:34.24,0:14:38.91,Default,,0000,0000,0000,,of everything from social networks\Nto epidemiology.
Dialogue: 0,0:14:38.91,0:14:41.60,Default,,0000,0000,0000,,And maybe, as it tackles problems\Nof seen understanding
Dialogue: 0,0:14:41.60,0:14:43.59,Default,,0000,0000,0000,,and natural language processing
Dialogue: 0,0:14:43.59,0:14:46.92,Default,,0000,0000,0000,,to tell us something\Nabout human cognition.
Dialogue: 0,0:14:47.76,0:14:49.69,Default,,0000,0000,0000,,And the final big idea you'll have heard
Dialogue: 0,0:14:49.69,0:14:53.08,Default,,0000,0000,0000,,is that maybe it's a good idea we're going\Nto know so much about brains
Dialogue: 0,0:14:53.08,0:14:54.100,Default,,0000,0000,0000,,and have so much access to big data,
Dialogue: 0,0:14:54.100,0:14:57.50,Default,,0000,0000,0000,,because left to our own devices,
Dialogue: 0,0:14:57.50,0:15:01.34,Default,,0000,0000,0000,,humans are fallible, we take shortcuts,
Dialogue: 0,0:15:01.34,0:15:04.77,Default,,0000,0000,0000,,we err, we make mistakes,
Dialogue: 0,0:15:04.77,0:15:08.25,Default,,0000,0000,0000,,we're biased, and in innumerable ways,
Dialogue: 0,0:15:09.33,0:15:11.42,Default,,0000,0000,0000,,we get the world wrong.
Dialogue: 0,0:15:12.84,0:15:15.79,Default,,0000,0000,0000,,I think these are all important stories,
Dialogue: 0,0:15:15.79,0:15:19.58,Default,,0000,0000,0000,,and they have a lot to tell us\Nabout what it means to be human,
Dialogue: 0,0:15:19.58,0:15:23.11,Default,,0000,0000,0000,,but I want you to note that today\NI told you a very different story.
Dialogue: 0,0:15:23.97,0:15:27.77,Default,,0000,0000,0000,,It's a story about minds and not brains,
Dialogue: 0,0:15:27.77,0:15:30.78,Default,,0000,0000,0000,,and in particular, it's a story\Nabout the kinds of computations
Dialogue: 0,0:15:30.78,0:15:33.37,Default,,0000,0000,0000,,that uniquely human minds can perform,
Dialogue: 0,0:15:33.37,0:15:37.31,Default,,0000,0000,0000,,which involve rich, structured knowledge\Nand the ability to learn
Dialogue: 0,0:15:37.31,0:15:42.58,Default,,0000,0000,0000,,from small amounts of data,\Nthe evidence of just a few examples.
Dialogue: 0,0:15:44.30,0:15:48.60,Default,,0000,0000,0000,,And fundamentally, it's a story\Nabout how starting as very small children
Dialogue: 0,0:15:48.60,0:15:52.78,Default,,0000,0000,0000,,and continuing out all the way\Nto the greatest accomplishments
Dialogue: 0,0:15:52.78,0:15:55.22,Default,,0000,0000,0000,,of our culture,
Dialogue: 0,0:15:56.62,0:15:58.62,Default,,0000,0000,0000,,we get the world right.
Dialogue: 0,0:16:00.43,0:16:05.70,Default,,0000,0000,0000,,Folks, human minds do not only learn\Nfrom small amounts of data.
Dialogue: 0,0:16:06.28,0:16:08.39,Default,,0000,0000,0000,,Human minds think\Nof altogether new ideas.
Dialogue: 0,0:16:08.75,0:16:11.44,Default,,0000,0000,0000,,Human minds generate\Nresearch and discovery,
Dialogue: 0,0:16:11.79,0:16:16.32,Default,,0000,0000,0000,,and human minds generate\Nart and literature and poetry and theater,
Dialogue: 0,0:16:17.07,0:16:20.60,Default,,0000,0000,0000,,and human minds take care of other humans:
Dialogue: 0,0:16:21.33,0:16:24.26,Default,,0000,0000,0000,,our old, our young, our sick.
Dialogue: 0,0:16:24.52,0:16:26.88,Default,,0000,0000,0000,,We even heal them.
Dialogue: 0,0:16:27.62,0:16:30.67,Default,,0000,0000,0000,,In the years to come, we're going\Nto see technological innovation
Dialogue: 0,0:16:30.67,0:16:33.28,Default,,0000,0000,0000,,beyond anything I can even envision,
Dialogue: 0,0:16:34.59,0:16:36.61,Default,,0000,0000,0000,,but we are very unlikely
Dialogue: 0,0:16:36.61,0:16:42.32,Default,,0000,0000,0000,,to see anything even approximating\Nthe computational power of a human child
Dialogue: 0,0:16:42.32,0:16:46.62,Default,,0000,0000,0000,,in my lifetime or in yours.
Dialogue: 0,0:16:46.62,0:16:51.67,Default,,0000,0000,0000,,If we invest in these most powerful\Nlearners and their development,
Dialogue: 0,0:16:51.67,0:16:54.58,Default,,0000,0000,0000,,in babies and children
Dialogue: 0,0:16:54.58,0:16:56.41,Default,,0000,0000,0000,,and mothers and fathers
Dialogue: 0,0:16:56.41,0:16:59.11,Default,,0000,0000,0000,,and caregivers and teachers
Dialogue: 0,0:16:59.11,0:17:03.28,Default,,0000,0000,0000,,the ways we invest in our other\Nmost powerful and elegant forms
Dialogue: 0,0:17:03.28,0:17:05.85,Default,,0000,0000,0000,,of technology, engineering, and design,
Dialogue: 0,0:17:06.49,0:17:09.44,Default,,0000,0000,0000,,we will not just be dreaming\Nof a better future,
Dialogue: 0,0:17:09.44,0:17:11.56,Default,,0000,0000,0000,,we will be planning for one.
Dialogue: 0,0:17:11.56,0:17:13.91,Default,,0000,0000,0000,,Thank you very much.
Dialogue: 0,0:17:13.91,0:17:17.81,Default,,0000,0000,0000,,(Applause)
Dialogue: 0,0:17:17.81,0:17:22.24,Default,,0000,0000,0000,,Chris Anderson: Laura, thank you.\NI do actually have a question for you.
Dialogue: 0,0:17:22.24,0:17:24.60,Default,,0000,0000,0000,,First of all, the research is insane.
Dialogue: 0,0:17:24.60,0:17:28.32,Default,,0000,0000,0000,,I mean, who would design\Nan experiment like that? (Laughter)
Dialogue: 0,0:17:29.15,0:17:30.94,Default,,0000,0000,0000,,I've seen that a couple of times,
Dialogue: 0,0:17:30.94,0:17:34.16,Default,,0000,0000,0000,,and I still don't honestly believe\Nthat that can truly be happening,
Dialogue: 0,0:17:34.16,0:17:37.32,Default,,0000,0000,0000,,but other people have done\Nsimilar experiments. It checks out.
Dialogue: 0,0:17:37.32,0:17:38.95,Default,,0000,0000,0000,,They really are that genius.
Dialogue: 0,0:17:38.95,0:17:41.96,Default,,0000,0000,0000,,LS: You know, they look really impressive\Nin our experiments,
Dialogue: 0,0:17:41.96,0:17:44.59,Default,,0000,0000,0000,,but think about what they\Nlook like in real life, right?
Dialogue: 0,0:17:44.59,0:17:45.76,Default,,0000,0000,0000,,It starts out as a baby.
Dialogue: 0,0:17:45.76,0:17:47.77,Default,,0000,0000,0000,,Eighteen months later,\Nit's talking to you,
Dialogue: 0,0:17:47.77,0:17:50.81,Default,,0000,0000,0000,,and babies' first words aren't just\Nthings like balls and ducks,
Dialogue: 0,0:17:50.81,0:17:53.69,Default,,0000,0000,0000,,they're things like "all gone,"\Nwhich refer to disappearance,
Dialogue: 0,0:17:53.69,0:17:55.97,Default,,0000,0000,0000,,or "uh oh," which refer\Nto unintentional actions.
Dialogue: 0,0:17:55.97,0:17:57.54,Default,,0000,0000,0000,,It has to be that powerful.
Dialogue: 0,0:17:57.54,0:18:00.31,Default,,0000,0000,0000,,It has to be much more powerful\Nthan anything I showed you.
Dialogue: 0,0:18:00.31,0:18:02.28,Default,,0000,0000,0000,,They're figuring out the entire world.
Dialogue: 0,0:18:02.28,0:18:05.43,Default,,0000,0000,0000,,A four-year old can talk to you\Nabout almost anything.
Dialogue: 0,0:18:05.43,0:18:07.03,Default,,0000,0000,0000,,(Applause)
Dialogue: 0,0:18:07.03,0:18:10.44,Default,,0000,0000,0000,,CA: And if I understand you right,\Nthe other key point you're making is,
Dialogue: 0,0:18:10.44,0:18:13.20,Default,,0000,0000,0000,,we've been through these years\Nwhere there's all this talk
Dialogue: 0,0:18:13.20,0:18:15.13,Default,,0000,0000,0000,,of how quirky and buggy our minds are,
Dialogue: 0,0:18:15.13,0:18:17.100,Default,,0000,0000,0000,,that behavioral economics\Nand the whole theories behind that
Dialogue: 0,0:18:17.100,0:18:19.60,Default,,0000,0000,0000,,that we're not rational agents.
Dialogue: 0,0:18:19.60,0:18:23.82,Default,,0000,0000,0000,,You're really saying that the biggest\Nstory is how extraordinary,
Dialogue: 0,0:18:23.82,0:18:28.76,Default,,0000,0000,0000,,and there really is genius there\Nthat is underappreciated.
Dialogue: 0,0:18:28.76,0:18:30.83,Default,,0000,0000,0000,,LS: One of my favorite\Nquotes in psychology
Dialogue: 0,0:18:30.83,0:18:33.12,Default,,0000,0000,0000,,comes from the social\Npsychologist Solomon Asch,
Dialogue: 0,0:18:33.12,0:18:35.93,Default,,0000,0000,0000,,and he said the fundamental task\Nof psychology is to remove
Dialogue: 0,0:18:35.93,0:18:38.55,Default,,0000,0000,0000,,the veil of self-evidence from things.
Dialogue: 0,0:18:38.55,0:18:43.10,Default,,0000,0000,0000,,There are a million orders of magnitude\Nmore decisions you make every day
Dialogue: 0,0:18:43.10,0:18:44.45,Default,,0000,0000,0000,,that get the world right.
Dialogue: 0,0:18:44.45,0:18:46.58,Default,,0000,0000,0000,,You know about objects\Nand their properties.
Dialogue: 0,0:18:46.58,0:18:49.61,Default,,0000,0000,0000,,You know them when they're occluded.\NYou know them in the dark.
Dialogue: 0,0:18:49.61,0:18:50.92,Default,,0000,0000,0000,,You can walk through rooms.
Dialogue: 0,0:18:50.92,0:18:54.45,Default,,0000,0000,0000,,You can figure out what other people\Nare thinking. You can talk to them.
Dialogue: 0,0:18:54.45,0:18:56.68,Default,,0000,0000,0000,,You can navigate space.\NYou know about numbers.
Dialogue: 0,0:18:56.68,0:18:59.70,Default,,0000,0000,0000,,You know causal relationships.\NYou know about moral reasoning.
Dialogue: 0,0:18:59.70,0:19:02.06,Default,,0000,0000,0000,,You do this effortlessly,\Nso we don't see it,
Dialogue: 0,0:19:02.06,0:19:04.97,Default,,0000,0000,0000,,but that is how we get the world right,\Nand it's a remarkable
Dialogue: 0,0:19:04.97,0:19:07.29,Default,,0000,0000,0000,,and very difficult-to-understand\Naccomplishment.
Dialogue: 0,0:19:07.29,0:19:09.92,Default,,0000,0000,0000,,CA: I suspect there are people\Nin the audience who have
Dialogue: 0,0:19:09.92,0:19:12.16,Default,,0000,0000,0000,,this view of accelerating\Ntechnological power
Dialogue: 0,0:19:12.16,0:19:15.11,Default,,0000,0000,0000,,who might dispute your statement\Nthat never in our lifetimes
Dialogue: 0,0:19:15.11,0:19:17.73,Default,,0000,0000,0000,,will a computer do what\Na three-year old child can do,
Dialogue: 0,0:19:17.73,0:19:20.98,Default,,0000,0000,0000,,but what's clear is that in any scenario,
Dialogue: 0,0:19:20.98,0:19:24.75,Default,,0000,0000,0000,,our machines have so much to learn\Nfrom our toddlers.
Dialogue: 0,0:19:26.23,0:19:29.45,Default,,0000,0000,0000,,LS: I think so. You'll have some\Nmachine learning folks up here.
Dialogue: 0,0:19:29.45,0:19:33.65,Default,,0000,0000,0000,,I mean, you should never bet\Nagainst babies or chimpanzees
Dialogue: 0,0:19:33.65,0:19:37.29,Default,,0000,0000,0000,,or technology as a matter of practice,
Dialogue: 0,0:19:37.29,0:19:41.82,Default,,0000,0000,0000,,but it's not just\Na difference in quantity,
Dialogue: 0,0:19:41.82,0:19:43.59,Default,,0000,0000,0000,,it's a difference in kind. Right?
Dialogue: 0,0:19:43.59,0:19:45.75,Default,,0000,0000,0000,,We have incredibly powerful computers,
Dialogue: 0,0:19:45.75,0:19:48.14,Default,,0000,0000,0000,,and they do do amazingly\Nsophisticated things,
Dialogue: 0,0:19:48.14,0:19:51.34,Default,,0000,0000,0000,,often with very big amounts of data.
Dialogue: 0,0:19:51.34,0:19:53.95,Default,,0000,0000,0000,,Human minds do, I think,\Nsomething quite different,
Dialogue: 0,0:19:53.95,0:19:57.84,Default,,0000,0000,0000,,and I think it's the structured,\Nhierarchical nature of human knowledge
Dialogue: 0,0:19:57.84,0:19:59.88,Default,,0000,0000,0000,,that remains a real challenge.
Dialogue: 0,0:19:59.88,0:20:02.94,Default,,0000,0000,0000,,CA: Laura Schulz, wonderful\Nfood for thought. Thank you so much.
Dialogue: 0,0:20:02.94,0:20:05.86,Default,,0000,0000,0000,,LS: Thank you.\N(Applause)