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Format: Layer, Start, End, Style, Name, MarginL, MarginR, MarginV, Effect, Text
Dialogue: 0,0:00:00.00,0:00:05.86,Default,,0000,0000,0000,,(intro music)
Dialogue: 0,0:00:05.86,0:00:07.37,Default,,0000,0000,0000,,My name is Laurie Santos.
Dialogue: 0,0:00:07.37,0:00:10.37,Default,,0000,0000,0000,,I teach psychology at Yale\NUniversity, and today
Dialogue: 0,0:00:10.37,0:00:12.55,Default,,0000,0000,0000,,I want to talk to you about anchoring.
Dialogue: 0,0:00:12.55,0:00:16.12,Default,,0000,0000,0000,,This lecture is part of a\Nseries on cognitive biases.
Dialogue: 0,0:00:16.12,0:00:19.43,Default,,0000,0000,0000,,Let's do a math problem.\Nreally quickly, and you've
Dialogue: 0,0:00:19.43,0:00:20.76,Default,,0000,0000,0000,,gotta do it in your head
Dialogue: 0,0:00:20.76,0:00:21.65,Default,,0000,0000,0000,,Ready?
Dialogue: 0,0:00:21.65,0:00:27.53,Default,,0000,0000,0000,,First, multiply the following numbers:\Neight times seven times six
Dialogue: 0,0:00:27.53,0:00:32.46,Default,,0000,0000,0000,,times five times four times three times\Ntwo times one.
Dialogue: 0,0:00:32.46,0:00:35.25,Default,,0000,0000,0000,,OK, that's it.
Dialogue: 0,0:00:35.25,0:00:36.84,Default,,0000,0000,0000,,What's your guess?
Dialogue: 0,0:00:36.84,0:00:37.84,Default,,0000,0000,0000,,A thousand?
Dialogue: 0,0:00:37.84,0:00:39.82,Default,,0000,0000,0000,,Two thousand?
Dialogue: 0,0:00:39.82,0:00:43.03,Default,,0000,0000,0000,,When the psychologists Danny Kahneman\Nand Amos Tversky tried this with
Dialogue: 0,0:00:43.03,0:00:45.39,Default,,0000,0000,0000,,human subjects, subjects on average
Dialogue: 0,0:00:45.39,0:00:47.99,Default,,0000,0000,0000,,guessed about two thousand\Ntwo hundred and fifty.
Dialogue: 0,0:00:47.99,0:00:49.38,Default,,0000,0000,0000,,Seems like an OK guess.
Dialogue: 0,0:00:49.38,0:00:53.11,Default,,0000,0000,0000,,But now, let's suppose I gave you\Na different math problem.
Dialogue: 0,0:00:53.11,0:00:54.65,Default,,0000,0000,0000,,What if I gave you this one?
Dialogue: 0,0:00:54.65,0:00:56.05,Default,,0000,0000,0000,,Ready?
Dialogue: 0,0:00:56.05,0:01:00.03,Default,,0000,0000,0000,,One times two times three times four
Dialogue: 0,0:01:00.03,0:01:04.77,Default,,0000,0000,0000,,times five times six times\Nseven times eight.
Dialogue: 0,0:01:04.77,0:01:06.31,Default,,0000,0000,0000,,What's your answer?
Dialogue: 0,0:01:06.31,0:01:08.15,Default,,0000,0000,0000,,If you're like Kahneman and Tversky's
Dialogue: 0,0:01:08.15,0:01:11.04,Default,,0000,0000,0000,,subjects, your answer might\Nbe a bit different here.
Dialogue: 0,0:01:11.04,0:01:13.88,Default,,0000,0000,0000,,For this question, their subjects\Nguessed a lot lower.
Dialogue: 0,0:01:13.88,0:01:17.45,Default,,0000,0000,0000,,On average they said the answer\Nwas about five hundred and twelve.
Dialogue: 0,0:01:17.45,0:01:19.51,Default,,0000,0000,0000,,The first amazing thing\Nabout these similar
Dialogue: 0,0:01:19.51,0:01:23.62,Default,,0000,0000,0000,,mathematical estimates is that people get\Nthe answers really, really wrong.
Dialogue: 0,0:01:23.62,0:01:25.22,Default,,0000,0000,0000,,In fact, the real answer?
Dialogue: 0,0:01:25.22,0:01:29.34,Default,,0000,0000,0000,,Well, for both, its forty thousand\Nthree hundred and twenty.
Dialogue: 0,0:01:29.34,0:01:31.94,Default,,0000,0000,0000,,People are off by an order of magnitude.
Dialogue: 0,0:01:31.94,0:01:35.26,Default,,0000,0000,0000,,But the second, even more amazing \Nthing is that people give
Dialogue: 0,0:01:35.26,0:01:39.60,Default,,0000,0000,0000,,different answers to the two problems,\Neven though they're just different ways
Dialogue: 0,0:01:39.60,0:01:42.02,Default,,0000,0000,0000,,of asking exactly the same question.
Dialogue: 0,0:01:42.02,0:01:44.06,Default,,0000,0000,0000,,Why do we give completely different answers,
Dialogue: 0,0:01:44.06,0:01:47.08,Default,,0000,0000,0000,,when the same math problem\Nis presented differently?
Dialogue: 0,0:01:47.08,0:01:49.50,Default,,0000,0000,0000,,The answer lies in how we make estimates.
Dialogue: 0,0:01:49.50,0:01:51.59,Default,,0000,0000,0000,,When you have lots of time to do a math
Dialogue: 0,0:01:51.59,0:01:55.81,Default,,0000,0000,0000,,problem, like eight times seven times six\Ntimes five times four times three times
Dialogue: 0,0:01:55.81,0:01:58.56,Default,,0000,0000,0000,,two times one, you can multiply all of
Dialogue: 0,0:01:58.56,0:02:01.14,Default,,0000,0000,0000,,the numbers together and get an exact product.
Dialogue: 0,0:02:01.14,0:02:02.72,Default,,0000,0000,0000,,But when you have to do the problem
Dialogue: 0,0:02:02.72,0:02:05.28,Default,,0000,0000,0000,,quickly, you don't really have time to finish.
Dialogue: 0,0:02:05.28,0:02:07.31,Default,,0000,0000,0000,,So you start with the first numbers.
Dialogue: 0,0:02:07.31,0:02:10.19,Default,,0000,0000,0000,,You multiply eight times\Nseven, and get fifty-six.
Dialogue: 0,0:02:10.19,0:02:12.70,Default,,0000,0000,0000,,And then you've gotta\Nmultiply that by six,
Dialogue: 0,0:02:12.70,0:02:16.67,Default,,0000,0000,0000,,and, well, you're guessing the final\Nnumber's gotta be pretty big, bigger than
Dialogue: 0,0:02:16.67,0:02:19.66,Default,,0000,0000,0000,,fifty-six, like maybe two thousand or so.
Dialogue: 0,0:02:19.66,0:02:22.45,Default,,0000,0000,0000,,But when you do the second problem, you start
Dialogue: 0,0:02:22.45,0:02:26.88,Default,,0000,0000,0000,,with one times two, and, well, that's only\Ntwo, and two times three's only six.
Dialogue: 0,0:02:26.88,0:02:28.53,Default,,0000,0000,0000,,Your answer's gonna be pretty small,
Dialogue: 0,0:02:28.53,0:02:31.31,Default,,0000,0000,0000,,maybe only like five hundred or so.
Dialogue: 0,0:02:31.31,0:02:33.78,Default,,0000,0000,0000,,This process of guessing based on the first
Dialogue: 0,0:02:33.78,0:02:36.11,Default,,0000,0000,0000,,number you see is what's\Nknown as "anchoring."
Dialogue: 0,0:02:36.11,0:02:37.68,Default,,0000,0000,0000,,The first number we think of
Dialogue: 0,0:02:37.68,0:02:39.73,Default,,0000,0000,0000,,when we do our estimate is the anchor.
Dialogue: 0,0:02:39.73,0:02:41.83,Default,,0000,0000,0000,,And once we have an anchor in our head,
Dialogue: 0,0:02:41.83,0:02:44.73,Default,,0000,0000,0000,,well, we sort of adjust\Nas needed from there.
Dialogue: 0,0:02:44.73,0:02:48.75,Default,,0000,0000,0000,,The problem is that our minds are biased\Nnot to adjust as much as we need to.
Dialogue: 0,0:02:48.75,0:02:51.58,Default,,0000,0000,0000,,The anchors are cognitively really strong.
Dialogue: 0,0:02:51.58,0:02:54.53,Default,,0000,0000,0000,,In the first, problem you probably\Nstarted with fifty-six, and
Dialogue: 0,0:02:54.53,0:02:57.72,Default,,0000,0000,0000,,then adjusted to an even\Nbigger number from there.
Dialogue: 0,0:02:57.72,0:03:00.100,Default,,0000,0000,0000,,And in the second problem, you started\Nwith six, and then adjusted from there.
Dialogue: 0,0:03:00.100,0:03:05.85,Default,,0000,0000,0000,,The problem is that starting at different\Npoints leads to different final guesses.
Dialogue: 0,0:03:05.85,0:03:10.97,Default,,0000,0000,0000,,Like real anchors, our estimated anchors\Nkinda get us stuck in one spot.
Dialogue: 0,0:03:10.97,0:03:14.71,Default,,0000,0000,0000,,We often fail to drag the anchor far\Nenough to get to a correct answer.
Dialogue: 0,0:03:14.71,0:03:17.71,Default,,0000,0000,0000,,Kahneman and Tversky discovered that this
Dialogue: 0,0:03:17.71,0:03:19.89,Default,,0000,0000,0000,,sort of anchoring bias happens all the time,
Dialogue: 0,0:03:19.89,0:03:22.48,Default,,0000,0000,0000,,even for anchors that are totally arbitrary.
Dialogue: 0,0:03:22.48,0:03:25.48,Default,,0000,0000,0000,,For example, they asked\Npeople to spin a wheel with
Dialogue: 0,0:03:25.48,0:03:28.32,Default,,0000,0000,0000,,numbers from one to a hundred,\Nand then asked them to estimate
Dialogue: 0,0:03:28.32,0:03:31.74,Default,,0000,0000,0000,,what percentage of countries in\Nthe United Nations are African.
Dialogue: 0,0:03:31.74,0:03:34.74,Default,,0000,0000,0000,,People who spun a ten on\Nthe wheel estimated that
Dialogue: 0,0:03:34.74,0:03:36.77,Default,,0000,0000,0000,,the number was about twenty-five percent.
Dialogue: 0,0:03:36.77,0:03:39.77,Default,,0000,0000,0000,,But people who spun a\Nsixty-five estimated that
Dialogue: 0,0:03:39.77,0:03:41.65,Default,,0000,0000,0000,,the number was forty-five percent.
Dialogue: 0,0:03:41.65,0:03:46.34,Default,,0000,0000,0000,,In another experiment, Dan Ariely\Nand his colleagues had people
Dialogue: 0,0:03:46.34,0:03:49.30,Default,,0000,0000,0000,,write down the last two digits\Nof their social security number.
Dialogue: 0,0:03:49.30,0:03:50.77,Default,,0000,0000,0000,,They were then asked whether they would
Dialogue: 0,0:03:50.77,0:03:54.12,Default,,0000,0000,0000,,pay that amount in dollars\Nfor a nice bottle of wine.
Dialogue: 0,0:03:54.12,0:03:58.25,Default,,0000,0000,0000,,Ariely and colleagues found that people\Nin the highest quintile of social security
Dialogue: 0,0:03:58.25,0:04:02.80,Default,,0000,0000,0000,,numbers would pay three to four times\Nas much for the exact same good.
Dialogue: 0,0:04:02.80,0:04:04.94,Default,,0000,0000,0000,,Just setting up a larger anchor can make a
Dialogue: 0,0:04:04.94,0:04:07.10,Default,,0000,0000,0000,,person who would pay eight\Ndollars for the bottle
Dialogue: 0,0:04:07.10,0:04:10.65,Default,,0000,0000,0000,,of wine be willing to spend\Ntwenty-seven dollars instead.
Dialogue: 0,0:04:10.65,0:04:14.62,Default,,0000,0000,0000,,Sadly for us, sales people use\Nanchors against us all the time.
Dialogue: 0,0:04:14.62,0:04:18.40,Default,,0000,0000,0000,,How many times have you noticed\Na salesperson or an advertisement
Dialogue: 0,0:04:18.40,0:04:21.10,Default,,0000,0000,0000,,anchoring you to a particular price, or
Dialogue: 0,0:04:21.10,0:04:23.89,Default,,0000,0000,0000,,even to how much of a particular\Nproduct you should buy?
Dialogue: 0,0:04:23.89,0:04:26.43,Default,,0000,0000,0000,,Whether it's buying a car, or a sweater,
Dialogue: 0,0:04:26.43,0:04:30.27,Default,,0000,0000,0000,,or even renting a hotel room, our\Nintuitions about what prices
Dialogue: 0,0:04:30.27,0:04:34.51,Default,,0000,0000,0000,,are reasonable to pay often come\Nfrom some arbitrary anchor.
Dialogue: 0,0:04:34.51,0:04:38.49,Default,,0000,0000,0000,,So, the next time you're given an\Nanchor, take a minute to think.
Dialogue: 0,0:04:38.49,0:04:40.14,Default,,0000,0000,0000,,Remember what happens when you
Dialogue: 0,0:04:40.14,0:04:42.30,Default,,0000,0000,0000,,drop your anger too high, and then
Dialogue: 0,0:04:42.30,0:04:45.33,Default,,0000,0000,0000,,consider thinking of a\Nvery different number.
Dialogue: 0,0:04:45.33,0:04:49.13,Default,,0000,0000,0000,,It might affect your final estimate\Nmore than you expect.