TEDxSydney
Tom Griffiths: 3 ways to make better decisions -- by thinking like a computer
汤姆 · 格里菲斯: 帮助你优化决策的3个方法——像电脑一样思考
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如果你曾在决定时十分纠结，这个演讲就是为你打造的。认知科学家汤姆 · 格里菲斯向我们展示了如何把电脑的逻辑应用在解决人类问题上，并分享了帮你做出更优决策的三个方法——从寻找居所，到决定去哪个餐厅吃晚餐。
Tom Griffiths - Psychologist, cognitive scientist
Tom Griffiths uses ideas from computer science to understand how human minds work. Full bio
Tom Griffiths uses ideas from computer science to understand how human minds work. Full bio
Double-click the English transcript below to play the video.
00:13
If there's one city in the world
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如果世界上有个城市
00:15
where it's hard to find
a place to buy or rent,
a place to buy or rent,
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很难买房或者租房，
它就是悉尼。
00:17
it's Sydney.
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00:19
And if you've tried
to find a home here recently,
to find a home here recently,
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如果你最近在找地方安家，
你一定对此深有感触。
00:21
you're familiar with the problem.
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每次你走进一个对公众开放的待售房，
00:23
Every time you walk into an open house,
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就会了解到市场上
00:25
you get some information
about what's out there
about what's out there
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相关的信息，
00:27
and what's on the market,
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00:28
but every time you walk out,
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但每次你从房子里走出去，
00:30
you're running the risk
of the very best place passing you by.
of the very best place passing you by.
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就冒着错过最好房子的风险。
那么你怎么知道何时从单纯的寻找，
00:33
So how do you know when
to switch from looking
to switch from looking
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00:36
to being ready to make an offer?
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转向准备出手呢？
00:39
This is such a cruel and familiar problem
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这个如此残酷和熟悉的问题
00:42
that it might come as a surprise
that it has a simple solution.
that it has a simple solution.
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却可能有个让人惊讶的简单解决方案。
00:45
37 percent.
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37%。
（笑声）
00:46
(Laughter)
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00:48
If you want to maximize the probability
that you find the very best place,
that you find the very best place,
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如果你想要最大化找到最佳居所的概率，
00:52
you should look at 37 percent
of what's on the market,
of what's on the market,
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就应该把市场上37%的房子看完，
然后在你看到的下一个地方出价，
00:55
and then make an offer
on the next place you see,
on the next place you see,
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这个地方要比你目前看过的都要更好。
00:57
which is better than anything
that you've seen so far.
that you've seen so far.
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01:00
Or if you're looking for a month,
take 37 percent of that time --
take 37 percent of that time --
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或者假如你要花一个月的时间
寻找，拿出37%的时间——
寻找，拿出37%的时间——
01:04
11 days, to set a standard --
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11天，来建立标准——
然后就可以准备行动了。
01:07
and then you're ready to act.
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01:09
We know this because
trying to find a place to live
trying to find a place to live
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我们知道这点是因为尝试找到好的居所
01:12
is an example of an optimal
stopping problem.
stopping problem.
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是“最优停止问题”的一个案例。
这是数学家和计算机科学家
01:14
A class of problems that has been
studied extensively
studied extensively
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广泛研究的一类问题。
01:17
by mathematicians and computer scientists.
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01:21
I'm a computational cognitive scientist.
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我是个计算认知科学家。
01:24
I spend my time trying to understand
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我把时间都花在理解
01:26
how it is that human minds work,
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人们的头脑如何工作上面，
从我们的惊人成就，到令人叹息的失败。
01:27
from our amazing successes
to our dismal failures.
to our dismal failures.
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01:32
To do that, I think about
the computational structure
the computational structure
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为此，我会考虑日常生活中
出现的问题的计算结构，
01:35
of the problems
that arise in everyday life,
that arise in everyday life,
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01:37
and compare the ideal
solutions to those problems
solutions to those problems
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并把这些问题的理想解决方案
与我们实际会做出的行为相比较。
01:40
to the way that we actually behave.
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01:42
As a side effect,
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作为副产品，
我还发现了如何利用一点计算科学知识
01:43
I get to see how applying
a little bit of computer science
a little bit of computer science
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让人类更轻松地做出决策。
01:46
can make human decision-making easier.
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01:49
I have a personal motivation for this.
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对此，我有一个私人动机。
01:52
Growing up in Perth
as an overly cerebral kid ...
as an overly cerebral kid ...
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作为在珀斯长大的一个过度理智的孩子…
01:55
(Laughter)
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（笑声）
我总试着用我觉得理性的方式行事，
02:00
I would always try and act in the way
that I thought was rational,
that I thought was rational,
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02:03
reasoning through every decision,
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对每一个决定进行推理，
02:04
trying to figure out
the very best action to take.
the very best action to take.
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想要算出要采取的最佳行动。
02:07
But this is an approach
that doesn't scale up
that doesn't scale up
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但这种方法无法扩展到
你开始在成人生活中
02:10
when you start to run into
the sorts of problems
the sorts of problems
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遇到的各种问题。
02:12
that arise in adult life.
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有一次，我甚至想和我女友分手，
02:13
At one point, I even tried
to break up with my girlfriend
to break up with my girlfriend
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只因为我在考虑如何在
她的喜好和我的喜好中
她的喜好和我的喜好中
02:16
because trying to take into account
her preferences as well as my own
her preferences as well as my own
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寻找最佳的折中方案——
02:20
and then find perfect solutions --
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（笑声）
02:21
(Laughter)
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02:24
was just leaving me exhausted.
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而最后却搞得我精疲力尽。
（笑声）
02:25
(Laughter)
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她指出我解决这个问题的方法
02:28
She pointed out that I was taking
the wrong approach
the wrong approach
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是错误的——
02:30
to solving this problem --
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后来她成为了我的妻子。
02:32
and she later became my wife.
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（笑声）
02:33
(Laughter)
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（鼓掌）
02:36
(Applause)
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02:40
Whether it's as basic as trying to decide
what restaurant to go to
what restaurant to go to
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不管是去哪家餐厅这样的小决策，
02:44
or as important as trying to decide
who to spend the rest of your life with,
who to spend the rest of your life with,
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还是重要到需要决定与谁度过余生，
人类的生活总是面临着各种
02:48
human lives are filled
with computational problems
with computational problems
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很难靠单纯的努力来解决的计算问题。
02:50
that are just too hard to solve
by applying sheer effort.
by applying sheer effort.
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02:55
For those problems,
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面对这些问题，
咨询专家是个不错的选择：
02:56
it's worth consulting the experts:
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02:58
computer scientists.
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我说的是计算机科学家。
03:00
(Laughter)
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（笑声）
03:01
When you're looking for life advice,
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当你寻找生活中的建议时，
03:03
computer scientists probably aren't
the first people you think to talk to.
the first people you think to talk to.
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计算机科学家可能不是你首选的谈话对象。
像电脑一样生活——
03:07
Living life like a computer --
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一成不变的确定性，详尽和准确——
03:09
stereotypically deterministic,
exhaustive and exact --
exhaustive and exact --
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03:11
doesn't sound like a lot of fun.
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听起来挺无趣的。
03:14
But thinking about the computer science
of human decisions
of human decisions
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但研究人类决策的计算机科学
03:17
reveals that in fact,
we've got this backwards.
we've got this backwards.
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揭示了这样一个事实，我们把它搞反了。
03:19
When applied to the sorts
of difficult problems
of difficult problems
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当处理人们生活中遇到的
03:21
that arise in human lives,
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各种难题时，
计算机解决这些问题的方式
03:23
the way that computers
actually solve those problems
actually solve those problems
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03:25
looks a lot more like the way
that people really act.
that people really act.
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跟人类真实行为非常相似。
03:29
Take the example of trying to decide
what restaurant to go to.
what restaurant to go to.
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拿试图决定去哪个餐厅为例。
03:33
This is a problem that has
a particular computational structure.
a particular computational structure.
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这个一个有着特定计算结构的问题。
你有一组选项，
03:36
You've got a set of options,
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需要在这些选项中选择一个，
03:37
you're going to choose
one of those options,
one of those options,
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并且明天你将会面对同样的决定。
03:39
and you're going to face
exactly the same decision tomorrow.
exactly the same decision tomorrow.
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在那种情况下，
03:42
In that situation,
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你遇到了计算机科学中所谓的
03:43
you run up against
what computer scientists call
what computer scientists call
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“探索与利用的权衡”。
03:46
the "explore-exploit trade-off."
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03:49
You have to make a decision
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你需要在
尝试新的——
03:50
about whether you're going
to try something new --
to try something new --
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即探索，收集
03:52
exploring, gathering some information
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你将来能够使用的信息——
03:55
that you might be able
to use in the future --
to use in the future --
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或者去那个已知的非常好的
地方之间做出选择——
地方之间做出选择——
03:57
or whether you're going to go to a place
that you already know is pretty good --
that you already know is pretty good --
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利用你目前已经收集到的信息。
04:01
exploiting the information
that you've already gathered so far.
that you've already gathered so far.
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04:05
The explore/exploit trade-off
shows up any time you have to choose
shows up any time you have to choose
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“探索与利用的权衡”出现在每一次
你需要在尝试新的
04:08
between trying something new
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和已知的优质体验之间作出选择，
04:09
and going with something
that you already know is pretty good,
that you already know is pretty good,
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不管是听音乐
04:12
whether it's listening to music
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还是决定要跟谁聚会。
04:14
or trying to decide
who you're going to spend time with.
who you're going to spend time with.
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科技公司也会面临同样的问题，
04:17
It's also the problem
that technology companies face
that technology companies face
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当他们需要决定比如应该在
网页上展示什么广告时。
网页上展示什么广告时。
04:19
when they're trying to do something
like decide what ad to show on a web page.
like decide what ad to show on a web page.
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他们是应该展现新广告，并从中学习呢，
04:23
Should they show a new ad
and learn something about it,
and learn something about it,
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还是给你展现那个
04:26
or should they show you an ad
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他们已经知道你很可能会点击的广告呢？
04:27
that they already know there's a good
chance you're going to click on?
chance you're going to click on?
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在过去60年中，
04:30
Over the last 60 years,
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计算机科学家在理解探索与利用的权衡
04:31
computer scientists have made
a lot of progress understanding
a lot of progress understanding
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上面取得了很大的进展，
04:34
the explore/exploit trade-off,
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而且他们的研究给出了
一些让人惊讶的洞察。
一些让人惊讶的洞察。
04:36
and their results offer
some surprising insights.
some surprising insights.
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04:39
When you're trying to decide
what restaurant to go to,
what restaurant to go to,
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当你在决定去哪家餐厅时，
你应该问自己的第一个问题是，
04:41
the first question you should ask yourself
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你还要在城里呆多久。
04:43
is how much longer
you're going to be in town.
you're going to be in town.
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04:46
If you're just going to be there
for a short time,
for a short time,
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如果你在那里只是短暂的停留，
那么你就应该享受（“利用”）。
04:48
then you should exploit.
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收集信息没有意义。
04:50
There's no point gathering information.
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只需要直接去那家你喜欢的餐厅。
04:52
Just go to a place
you already know is good.
you already know is good.
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但如果你会呆很长的时间，
那就花点时间“探索”。
那就花点时间“探索”。
04:54
But if you're going to be there
for a longer time, explore.
for a longer time, explore.
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试试新的餐厅，因为你收集的信息
04:57
Try something new,
because the information you get
because the information you get
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可以在未来优化你的选择。
04:59
is something that can improve
your choices in the future.
your choices in the future.
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有价值的信息增多了，
05:02
The value of information increases
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你将来使用它的机会也越多。
05:04
the more opportunities
you're going to have to use it.
you're going to have to use it.
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05:08
This principle can give us insight
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这个原则也可以帮助我们深入理解
05:09
into the structure
of a human life as well.
of a human life as well.
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人类生命的结构。
05:13
Babies don't have a reputation
for being particularly rational.
for being particularly rational.
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婴儿并不是理性的代名词。
05:17
They're always trying new things,
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他们总在尝试新东西，
比如，什么东西都想往嘴里塞。
05:18
and you know, trying to stick them
in their mouths.
in their mouths.
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05:22
But in fact, this is exactly
what they should be doing.
what they should be doing.
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事实上，这一行为非常合理。
他们正处于生命中的探索阶段，
05:25
They're in the explore
phase of their lives,
phase of their lives,
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这些东西可能正好是美味的。
05:28
and some of those things
could turn out to be delicious.
could turn out to be delicious.
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05:32
At the other end of the spectrum,
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相反，
老人总是去同样的餐厅，
05:33
the old guy who always goes
to the same restaurant
to the same restaurant
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吃同样的东西，
05:36
and always eats the same thing
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这跟单调的行为无关——
05:37
isn't boring --
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只是最优选择罢了。
05:39
he's optimal.
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05:40
(Laughter)
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（笑声）
他正在利用一生中
05:44
He's exploiting the knowledge
that he's earned
that he's earned
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05:46
through a lifetime's experience.
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所积累的知识。
05:50
More generally,
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更一般的情况下，
了解“探索与利用的权衡”这一原则，
05:51
knowing about
the explore/exploit trade-off
the explore/exploit trade-off
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可以让你在尝试做选择时
05:53
can make it a little easier for you
to sort of relax and go easier on yourself
to sort of relax and go easier on yourself
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感到更轻松。
05:57
when you're trying to make a decision.
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你不需要每晚都去最佳餐厅。
05:59
You don't have to go
to the best restaurant every night.
to the best restaurant every night.
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找个机会，试试新的，探索一番。
06:01
Take a chance, try something new, explore.
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你可能会有新的发现。
06:04
You might learn something.
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你获取的信息
06:06
And the information that you gain
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会比一顿美味的晚餐更有价值。
06:08
is going to be worth more
than one pretty good dinner.
than one pretty good dinner.
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06:12
Computer science can also help
to make it easier on us
to make it easier on us
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计算机科学也可以帮助我们
在家和工作场所的其他地方
在家和工作场所的其他地方
06:14
in other places at home and in the office.
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更轻松地做出决策。
06:17
If you've ever had
to tidy up your wardrobe,
to tidy up your wardrobe,
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如果你有需要整理衣橱的经历，
你就已经遇到了一个非常痛苦的决定：
06:20
you've run into a particularly
agonizing decision:
agonizing decision:
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你得决定哪些东西要留下来，
06:23
you have to decide what things
you're going to keep
you're going to keep
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哪些东西要丢掉。
06:25
and what things you're going to give away.
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06:27
Martha Stewart turns out
to have thought very hard about this --
to have thought very hard about this --
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玛莎 · 斯图尔特曾经
非常认真地思考过这个问题——
非常认真地思考过这个问题——
（笑声）
06:30
(Laughter)
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而且她有一些好建议。
06:32
and she has some good advice.
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她说，“问你自己4个问题：
06:33
She says, "Ask yourself four questions:
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我拥有这件东西多长时间了？
06:36
How long have I had it?
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它仍然完好吗？
06:37
Does it still function?
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我还有其他类似的东西吗？
06:39
Is it a duplicate
of something that I already own?
of something that I already own?
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我上次穿它或用它是什么时候？”
06:42
And when was the last time
I wore it or used it?"
I wore it or used it?"
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06:46
But there's another group of experts
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但还有另一群专家
对这个问题的思考更加深入，
06:48
who perhaps thought
even harder about this problem,
even harder about this problem,
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他们会说，其中一个问题
比其他问题更重要。
比其他问题更重要。
06:51
and they would say one of these questions
is more important than the others.
is more important than the others.
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06:55
Those experts?
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这些专家是谁呢？
06:57
The people who design
the memory systems of computers.
the memory systems of computers.
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就是设计计算机内存系统的人。
大部分电脑有两种类型的内存系统：
07:00
Most computers have
two kinds of memory systems:
two kinds of memory systems:
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07:02
a fast memory system,
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快速存储系统，
07:03
like a set of memory chips
that has limited capacity,
that has limited capacity,
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如一组容量有限的内存芯片，
07:07
because those chips are expensive,
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因为这些芯片非常昂贵，
07:09
and a slow memory system,
which is much larger.
which is much larger.
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还有慢速存储系统，但容量更大。
07:13
In order for the computer to operate
as efficiently as possible,
as efficiently as possible,
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为了让电脑工作效率尽可能高，
你想要确保
07:16
you want to make sure
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你需要获取的一段信息
07:17
that the pieces of information
you want to access
you want to access
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在快速存储系统中，
07:19
are in the fast memory system,
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这样就可以快速获取它们。
07:21
so that you can get to them quickly.
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每次你获取一段信息，
07:23
Each time you access
a piece of information,
a piece of information,
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该信息就会进入快速存储中，
07:25
it's loaded into the fast memory
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而电脑需要决定哪些信息
需要从那个存储中移除，
需要从那个存储中移除，
07:26
and the computer has to decide which item
it has to remove from that memory,
it has to remove from that memory,
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07:30
because it has limited capacity.
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因为它的容量有限。
07:33
Over the years,
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多年来，
计算机科学家试了几种不同的策略
07:34
computer scientists have tried
a few different strategies
a few different strategies
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来决定应该从快速存储中移除什么。
07:37
for deciding what to remove
from the fast memory.
from the fast memory.
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他们试过比如随机选择，
07:40
They've tried things like choosing
something at random
something at random
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或是应用“先进先出”原则，
07:43
or applying what's called
the "first-in, first-out principle,"
the "first-in, first-out principle,"
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意思是移除
07:46
which means removing the item
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被储存时间最长的信息。
07:47
which has been in the memory
for the longest.
for the longest.
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07:50
But the strategy that's most effective
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但最有效的策略是，
07:52
focuses on the items
which have been least recently used.
which have been least recently used.
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聚焦那些最近最少被使用的条目。
07:56
This says if you're going to decide
to remove something from memory,
to remove something from memory,
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也就是说，如果你打算从存储中删掉点什么，
就应该移除距离最近一次访问最久的内容。
08:00
you should take out the thing which was
last accessed the furthest in the past.
last accessed the furthest in the past.
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这显然是合乎逻辑的做法。
08:05
And there's a certain
kind of logic to this.
kind of logic to this.
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假如你上次访问那段信息
是在很久以前了，
是在很久以前了，
08:07
If it's been a long time since you last
accessed that piece of information,
accessed that piece of information,
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那么你也很可能在很久之后才会
08:10
it's probably going to be a long time
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再次需要访问这段信息。
08:12
before you're going to need
to access it again.
to access it again.
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08:15
Your wardrobe is just like
the computer's memory.
the computer's memory.
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你的衣柜就像计算机的内存。
衣橱的容量有限，
08:18
You have limited capacity,
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2030
你需要尽量把最常用的东西放进去，
08:20
and you need to try and get in there
the things that you're most likely to need
the things that you're most likely to need
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这样你就会尽可能快速地得到它。
08:25
so that you can get to them
as quickly as possible.
as quickly as possible.
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08:29
Recognizing that,
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认识到这点，
也许值得应用“最近最少使用”原则
08:30
maybe it's worth applying
the least recently used principle
the least recently used principle
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来管理你的衣柜。
08:33
to organizing your wardrobe as well.
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1949
如果我们回到玛莎的四个问题，
08:35
So if we go back
to Martha's four questions,
to Martha's four questions,
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计算机科学家会说，在这些问题中，
08:37
the computer scientists
would say that of these,
would say that of these,
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最后一个是最重要的。
08:39
the last one is the most important.
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08:43
This idea of organizing things
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这种管理东西的方法，
也就是让你最可能需要的东西最唾手可得，
08:45
so that the things you are most
likely to need are most accessible
likely to need are most accessible
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也可以应用在你的工作中。
08:48
can also be applied in your office.
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08:51
The Japanese economist Yukio Noguchi
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日本经济学家野口勇
08:53
actually invented a filing system
that has exactly this property.
that has exactly this property.
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就发明了一个拥有该属性的文件系统。
08:57
He started with a cardboard box,
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他从一个纸箱开始，
然后从左手边把文件放进盒子。
08:58
and he put his documents into the box
from the left-hand side.
from the left-hand side.
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09:02
Each time he'd add a document,
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1434
每次他增加一个文件，
09:03
he'd move what was in there along
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他会把里面的东西依次移动，
再把那个文件放在盒子的左手边。
09:05
and he'd add that document
to the left-hand side of the box.
to the left-hand side of the box.
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每次他需要看文件，就会把它取出来，
09:08
And each time he accessed
a document, he'd take it out,
a document, he'd take it out,
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用完之后放到左手边的位置。
09:10
consult it and put it back in
on the left-hand side.
on the left-hand side.
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09:13
As a result, the documents would be
ordered from left to right
ordered from left to right
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这样一来，文件就会根据最近使用的情况
从左到右排序。
09:16
by how recently they had been used.
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他发现只要沿着盒子的
09:18
And he found he could quickly find
what he was looking for
what he was looking for
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09:21
by starting at the left-hand
side of the box
side of the box
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左边到右边搜索，
就可以快速找到他要找的文件。
09:23
and working his way to the right.
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09:25
Before you dash home
and implement this filing system --
and implement this filing system --
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在你赶回家尝试搭建这个文件系统前——
（笑声）
09:27
(Laughter)
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值得注意的是，你可能已经拥有它了。
09:29
it's worth recognizing
that you probably already have.
that you probably already have.
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09:32
(Laughter)
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（笑声）
09:36
That pile of papers on your desk ...
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就是你桌上的那堆文件…
通常被认为是凌乱无序的
09:39
typically maligned
as messy and disorganized,
as messy and disorganized,
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这堆文件，实际上
已经经过了完美的整理——
已经经过了完美的整理——
09:41
a pile of papers is, in fact,
perfectly organized --
perfectly organized --
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（笑声）
09:44
(Laughter)
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只要你把一张纸抽出来，
09:45
as long as you, when you take a paper out,
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用完再放回到那堆文件上面，
09:47
put it back on the top of the pile,
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这些文件就会从上到下
09:49
then those papers are going
to be ordered from top to bottom
to be ordered from top to bottom
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根据最近使用的原则排序，
09:52
by how recently they were used,
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你就很可能在那堆文件中从上到下
09:54
and you can probably quickly find
what you're looking for
what you're looking for
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09:56
by starting at the top of the pile.
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快速找到你要找的东西。
09:59
Organizing your wardrobe or your desk
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整理你的衣柜或书桌
10:01
are probably not the most pressing
problems in your life.
problems in your life.
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可能不是你生活中最紧迫的问题。
10:05
Sometimes the problems we have to solve
are simply very, very hard.
are simply very, very hard.
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有时候我们需要解决的问题非常非常难。
10:09
But even in those cases,
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但即便在这些案例中，
计算机科学也可以提供一些策略
10:10
computer science can offer some strategies
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10:12
and perhaps some solace.
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和些许安慰。
10:16
The best algorithms are about doing
what makes the most sense
what makes the most sense
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最好的算法是在最短的时间内
10:19
in the least amount of time.
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做最合理的事情。
10:22
When computers face hard problems,
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1958
当电脑面对难题时，
会把它分解为简单问题——
10:24
they deal with them by making them
into simpler problems --
into simpler problems --
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通过利用随机性，
10:27
by making use of randomness,
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消除约束或允许近似。
10:28
by removing constraints
or by allowing approximations.
or by allowing approximations.
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解决这些简单问题
10:32
Solving those simpler problems
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10:34
can give you insight
into the harder problems,
into the harder problems,
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可以让你洞察更难的问题，
10:37
and sometimes produces
pretty good solutions in their own right.
pretty good solutions in their own right.
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而且有时会产生很好的解决方案。
10:41
Knowing all of this has helped me
to relax when I have to make decisions.
to relax when I have to make decisions.
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知道所有这些知识可以帮助
我们在做决定时倍感轻松。
我们在做决定时倍感轻松。
10:45
You could take the 37 percent rule
for finding a home as an example.
for finding a home as an example.
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拿37%的原则来找房子就是一个例子。
10:49
There's no way that you can
consider all of the options,
consider all of the options,
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你根本不可能考虑到所有的选项，
所以你必须碰碰运气。
10:51
so you have to take a chance.
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10:53
And even if you follow
the optimal strategy,
the optimal strategy,
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即便你遵循了最优策略，
也无法保证得到最佳结果。
10:56
you're not guaranteed a perfect outcome.
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10:59
If you follow the 37 percent rule,
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如果你遵循37%原则，
找到最佳居所的概率是——
11:01
the probability that you find
the very best place is --
the very best place is --
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11:04
funnily enough ...
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这就相当有趣了...
（笑声）
11:06
(Laughter)
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11:07
37 percent.
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37%。
11:09
You fail most of the time.
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你大部分时间都未能如愿。
11:12
But that's the best that you can do.
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但是你已经尽力了。
11:14
Ultimately, computer science
can help to make us more forgiving
can help to make us more forgiving
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最终，计算机科学可以帮我们更宽容地
11:17
of our own limitations.
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面对自己的局限性。
11:20
You can't control outcomes,
just processes.
just processes.
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你无法控制结果，只能调整方法。
11:22
And as long as you've used
the best process,
the best process,
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只要你使用了最好的方法，
11:25
you've done the best that you can.
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就已经尽了最大的努力。
11:26
Sometimes those best processes
involve taking a chance --
involve taking a chance --
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有时候，最好的方法就是抓住机会——
不去考虑你的所有选项，
11:30
not considering all of your options,
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2115
11:32
or being willing to settle
for a pretty good solution.
for a pretty good solution.
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或者愿意接受一个很好的解决方案。
11:35
These aren't the concessions
that we make when we can't be rational --
that we make when we can't be rational --
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这些不是我们在无法进行
理性思考时做的让步——
理性思考时做的让步——
它们就是理性的意义。
11:38
they're what being rational means.
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11:40
Thank you.
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谢谢。
（鼓掌）
11:42
(Applause)
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Translated by jacks jun
ABOUT THE SPEAKER
Tom Griffiths - Psychologist, cognitive scientistTom Griffiths uses ideas from computer science to understand how human minds work.
Why you should listen
Tom Griffiths's research explores connections between natural and artificial intelligence to discover how people solve the challenging computational problems they encounter in everyday life. Currently the Henry R. Luce Professor of Information Technology, Consciousness, and Culture at Princeton University, his work has received awards from organizations ranging from the American Psychological Association to the Sloan Foundation.
In 2016, Griffiths and his friend and collaborator Brian Christian published Algorithms to Live By, a book that illustrates how understanding the algorithms used by computers can inform human decision-making (and vice versa). The book was named one of the Amazon.com "Best Science Books of 2016" and appeared on Forbes's "Must-read brain books of 2016" list as well as the MIT Technology Review's "Best books of 2016" list.
Tom Griffiths | Speaker | TED.com