TEDxSydney
Tom Griffiths: 3 ways to make better decisions -- by thinking like a computer
湯姆葛里菲斯: 做出更好決策的三種方式——採用跟電腦一樣的思考方式
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如果你曾經為了做決策而掙扎，不妨看看這場演說。認知科學家湯姆葛里菲斯說明我們要如何應用電腦的邏輯來處理難搞的人類問題。他分享三種實際的策略，協助做出更好的決策，適用於各種問題，從找房子到選擇晚餐要去哪一家餐廳都可以用得上。
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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如果世界上有一個城市
00:15
where it's hard to find
a place to buy or rent,
a place to buy or rent,
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很難找到出售或是出租的地方，
00:17
it's Sydney.
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那就是雪梨。
00:19
And if you've tried
to find a home here recently,
to find a home here recently,
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如果你最近試著在這裡找個家，
00:21
you're familiar with the problem.
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你對這個問題就會很熟悉。
00:23
Every time you walk into an open house,
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每當你走進開放看屋的地點，
00:25
you get some information
about what's out there
about what's out there
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你就可以得到些資訊，
知道那裡有什麼，
知道那裡有什麼，
00:27
and what's on the market,
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以及市場上有什麼；
00:28
but every time you walk out,
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但每當你走出來時，
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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你就冒著錯過最佳選擇的風險。
00:33
So how do you know when
to switch from looking
to switch from looking
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所以，你怎麼知道
何時要從「看看」切換成
何時要從「看看」切換成
00:36
to being ready to make an offer?
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準備好提出交易條件？
00:39
This is such a cruel and familiar problem
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這是個殘酷又熟悉的問題，
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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讓人意外的是，
它的解決方案很簡單。
它的解決方案很簡單。
00:45
37 percent.
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37%。
00:46
(Laughter)
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（笑聲）
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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如果你想要把找到
最佳選擇的機率提升到最高，
最佳選擇的機率提升到最高，
00:52
you should look at 37 percent
of what's on the market,
of what's on the market,
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你得要看過市場上
37% 的所有選擇的，
37% 的所有選擇的，
00:55
and then make an offer
on the next place you see,
on the next place you see,
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接著到下一個地方時，
就提出交易條件，
就提出交易條件，
00:57
which is better than anything
that you've seen so far.
that you've seen so far.
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它會比你目前看過的
所有選擇都更好。
所有選擇都更好。
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，如果你要花一個月來尋找，
就取那段時間的 37% ——
就取那段時間的 37% ——
01:04
11 days, to set a standard --
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即 11 天，來設定標準——
接著你就可以準備行動了。
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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我們知道要這麼做，
是因為試圖找住房
是因為試圖找住房
01:12
is an example of an optimal
stopping problem.
stopping problem.
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就是「最佳停止問題」的例子。
01:14
A class of problems that has been
studied extensively
studied extensively
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這類問題一直被數學家
01:17
by mathematicians and computer scientists.
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和電腦科學家廣為研究。
01:21
I'm a computational cognitive scientist.
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我是一位計算認知科學家。
01:24
I spend my time trying to understand
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我把時間花在了解
01:26
how it is that human minds work,
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人類大腦如何運作，
01:27
from our amazing successes
to our dismal failures.
to our dismal failures.
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從達成了不起的成功
到遭遇令人沮喪的失敗。
到遭遇令人沮喪的失敗。
01:32
To do that, I think about
the computational structure
the computational structure
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要做到這一點，我得要思考
日常問題的計算結構，
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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並將那些問題的理想解決方案
與我們的真實行為做比較。
01:40
to the way that we actually behave.
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01:42
As a side effect,
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它有一個副作用，
01:43
I get to see how applying
a little bit of computer science
a little bit of computer science
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我可以看到應用一點點電腦科學
01:46
can make human decision-making easier.
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如何能讓人類決策變得更容易。
01:49
I have a personal motivation for this.
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我這麼做，背後有個私人的動機。
01:52
Growing up in Perth
as an overly cerebral kid ...
as an overly cerebral kid ...
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我在伯斯長大，以前
是個過度理智的小孩……
是個過度理智的小孩……
01:55
(Laughter)
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（笑聲）
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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我總是試著用我認為
合理的方式來做事，
合理的方式來做事，
02:03
reasoning through every decision,
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做每個決策都要依理推論，
02:04
trying to figure out
the very best action to take.
the very best action to take.
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試圖找出採取哪種做法最理想。
02:07
But this is an approach
that doesn't scale up
that doesn't scale up
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但這種方法無法做更廣的應用，
02:10
when you start to run into
the sorts of problems
the sorts of problems
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當你開始遇到成人
生活中的那些問題時，
生活中的那些問題時，
02:12
that arise in adult life.
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就派不上用場了。
02:13
At one point, I even tried
to break up with my girlfriend
to break up with my girlfriend
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我有一度甚至打算要和女友分手，
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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原因是我試著考量
她的偏好和我的偏好，
她的偏好和我的偏好，
02:20
and then find perfect solutions --
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以找出最完美的解決方案——
02:21
(Laughter)
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（笑聲）
02:24
was just leaving me exhausted.
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我真的被搞得疲憊不堪。
02:25
(Laughter)
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（笑聲）
02:28
She pointed out that I was taking
the wrong approach
the wrong approach
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她指出我在解決這個問題時
02:30
to solving this problem --
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用錯了方法——
02:32
and she later became my wife.
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後來她成了我的太太。
02:33
(Laughter)
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（笑聲）
02:36
(Applause)
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（掌聲）
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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不論是很基本的問題，
比如決定要去哪家餐廳吃飯，
比如決定要去哪家餐廳吃飯，
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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或是很重要的問題，
比如決定要和誰共渡餘生，
比如決定要和誰共渡餘生，
02:48
human lives are filled
with computational problems
with computational problems
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人生其實都充滿了計算問題，
02:50
that are just too hard to solve
by applying sheer effort.
by applying sheer effort.
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光靠努力是很難解決的。
02:55
For those problems,
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那些問題
02:56
it's worth consulting the experts:
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值得去諮詢專家：
02:58
computer scientists.
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電腦科學家。
03:00
(Laughter)
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（笑聲）
03:01
When you're looking for life advice,
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當你要尋求人生忠告時，
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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你最先想要問的人大概
不會是電腦科學家。
不會是電腦科學家。
03:07
Living life like a computer --
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把人生過得像電腦一樣——
03:09
stereotypically deterministic,
exhaustive and exact --
exhaustive and exact --
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刻板的決定論、
詳盡無遺，且精確——
詳盡無遺，且精確——
03:11
doesn't sound like a lot of fun.
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聽起來實在不好玩。
03:14
But thinking about the computer science
of human decisions
of human decisions
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但思考一下人類決策的電腦科學，
03:17
reveals that in fact,
we've got this backwards.
we've got this backwards.
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會發現，事實上，
我們把方向弄反了。
我們把方向弄反了。
03:19
When applied to the sorts
of difficult problems
of difficult problems
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當應用在人生中的
那些困難問題上時，
03:21
that arise in human lives,
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03:23
the way that computers
actually solve those problems
actually solve those problems
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電腦實際上用來解決
那些問題的方式
那些問題的方式
03:25
looks a lot more like the way
that people really act.
that people really act.
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看起來很像是人們真正使用的方式。
03:29
Take the example of trying to decide
what restaurant to go to.
what restaurant to go to.
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就用決定要去哪間餐廳
吃飯當作例子吧。
吃飯當作例子吧。
03:33
This is a problem that has
a particular computational structure.
a particular computational structure.
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這個問題有特定的計算結構。
03:36
You've got a set of options,
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你有一組選項，
03:37
you're going to choose
one of those options,
one of those options,
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你得要從那些選項中擇一，
03:39
and you're going to face
exactly the same decision tomorrow.
exactly the same decision tomorrow.
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且你明天還會面對
完全一樣的決策。
完全一樣的決策。
03:42
In that situation,
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在那樣的情況下，
03:43
you run up against
what computer scientists call
what computer scientists call
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你碰到的就是電腦科學家所謂的
03:46
the "explore-exploit trade-off."
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「探索／利用的權衡」。
03:49
You have to make a decision
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你得要做一個決策，
03:50
about whether you're going
to try something new --
to try something new --
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決定你是否要嘗試新選項——
03:52
exploring, gathering some information
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去「探索」，收集一些未來
03:55
that you might be able
to use in the future --
to use in the future --
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可能會用到的資訊——
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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或者你是否要選擇去
你已經知道不錯的地方——
你已經知道不錯的地方——
04:01
exploiting the information
that you've already gathered so far.
that you've already gathered so far.
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「利用」你目前已經
收集到的資訊。
收集到的資訊。
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／利用的權衡會出現在每次
04:08
between trying something new
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你必須要從新選項和已經知道
不錯的選項中擇一的情況下，
不錯的選項中擇一的情況下，
04:09
and going with something
that you already know is pretty good,
that you already know is pretty good,
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也許是聽音樂，
04:12
whether it's listening to music
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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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或者是試著決定
你要跟誰一起殺時間。
你要跟誰一起殺時間。
04:17
It's also the problem
that technology companies face
that technology companies face
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這也是科技公司會面臨的問題，
比如決定要在網頁上放什麼
廣告時，遇到的就是這種問題。
廣告時，遇到的就是這種問題。
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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它們應該要刊登新廣告，
從中得到一些資訊嗎？
從中得到一些資訊嗎？
04:23
Should they show a new ad
and learn something about it,
and learn something about it,
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或是它們應該要給你看
04:26
or should they show you an ad
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一則它們已經知道你很有可能
會點選的廣告？
會點選的廣告？
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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在過去六十年，
04:30
Over the last 60 years,
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電腦科學家在了解
探索／利用的權衡上，
探索／利用的權衡上，
04:31
computer scientists have made
a lot of progress understanding
a lot of progress understanding
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04:34
the explore/exploit trade-off,
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有相當多進展，
他們的結果帶來了
一些讓人吃驚的洞見。
一些讓人吃驚的洞見。
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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當你要試著決定該去哪一間餐廳時，
04:41
the first question you should ask yourself
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你應該先問你自己一個問題：
04:43
is how much longer
you're going to be in town.
you're going to be in town.
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你還會待在鎮上多久？
04:46
If you're just going to be there
for a short time,
for a short time,
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如果你只是短暫停留，
04:48
then you should exploit.
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那麼你應該要「利用」。
04:50
There's no point gathering information.
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收集資訊是沒有意義的。
04:52
Just go to a place
you already know is good.
you already know is good.
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直接去一個你已經
知道不錯的地方吧。
知道不錯的地方吧。
04:54
But if you're going to be there
for a longer time, explore.
for a longer time, explore.
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但如果你會待久一點，
就「探索」吧。
就「探索」吧。
04:57
Try something new,
because the information you get
because the information you get
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試試新選項，因為
你從中得到的資訊
你從中得到的資訊
04:59
is something that can improve
your choices in the future.
your choices in the future.
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可能協助你在未來做更好的選擇。
05:02
The value of information increases
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你越有可能用到一項資訊，
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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該資訊的價值就會增加。
05:08
This principle can give us insight
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這條原則也能協助我們
05:09
into the structure
of a human life as well.
of a human life as well.
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洞察人類的人生。
05:13
Babies don't have a reputation
for being particularly rational.
for being particularly rational.
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寶寶通常不會特別理性。
05:17
They're always trying new things,
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他們總是在嘗試新東西，
05:18
and you know, trying to stick them
in their mouths.
in their mouths.
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你們知道的，總把
新東西放到嘴巴裡。
新東西放到嘴巴裡。
05:22
But in fact, this is exactly
what they should be doing.
what they should be doing.
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但，事實上，他們
的確應該要這麼做。
的確應該要這麼做。
05:25
They're in the explore
phase of their lives,
phase of their lives,
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他們正處在人生的探索階段，
05:28
and some of those things
could turn out to be delicious.
could turn out to be delicious.
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他們嘗試的東西當中，
有些可能真的會很美味。
有些可能真的會很美味。
05:32
At the other end of the spectrum,
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在光譜的另一端，
05:33
the old guy who always goes
to the same restaurant
to the same restaurant
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是老人，他們總是去同樣的餐廳，
05:36
and always eats the same thing
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總是點同樣的食物，
05:37
isn't boring --
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並不是無趣，
05:39
he's optimal.
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而是最佳化的選擇。
05:40
(Laughter)
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（笑聲）
05:44
He's exploiting the knowledge
that he's earned
that he's earned
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他在利用他從一生的經驗中
05:46
through a lifetime's experience.
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已經得到的知識。
05:50
More generally,
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更普遍來說，知道有
「探索／利用的權衡」，
「探索／利用的權衡」，
05:51
knowing about
the explore/exploit trade-off
the explore/exploit trade-off
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就能讓你在做決策時能更輕鬆些，
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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不要對自己太嚴厲。
05:57
when you're trying to make a decision.
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你不需要每晚都去最好的餐廳。
05:59
You don't have to go
to the best restaurant every night.
to the best restaurant every night.
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06:01
Take a chance, try something new, explore.
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冒個險，嘗試新餐廳，去探索。
06:04
You might learn something.
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你可能會學到些什麼。
06:06
And the information that you gain
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而你所得到的資訊
06:08
is going to be worth more
than one pretty good dinner.
than one pretty good dinner.
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價值絕對勝過一頓好吃的晚餐。
06:12
Computer science can also help
to make it easier on us
to make it easier on us
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在家中或在辦公室裡的其他地方，
電腦科學也能夠讓我們更輕鬆些。
06:14
in other places at home and in the office.
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06:17
If you've ever had
to tidy up your wardrobe,
to tidy up your wardrobe,
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如果你得要整理你的衣櫥，
06:20
you've run into a particularly
agonizing decision:
agonizing decision:
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你會碰到一個特別煩惱的決定：
06:23
you have to decide what things
you're going to keep
you're going to keep
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你得要決定哪些東西該留下，
06:25
and what things you're going to give away.
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哪些東西該送人。
06:27
Martha Stewart turns out
to have thought very hard about this --
to have thought very hard about this --
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結果發現瑪莎史都華花了
很多功夫在想這件事——
很多功夫在想這件事——
06:30
(Laughter)
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（笑聲）
06:32
and she has some good advice.
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她有些不錯的忠告。
06:33
She says, "Ask yourself four questions:
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她說：「問你自己四個問題：
06:36
How long have I had it?
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我已經持有它多久了？
06:37
Does it still function?
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它還有功能嗎？
06:39
Is it a duplicate
of something that I already own?
of something that I already own?
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它是不是跟某樣
我已經擁有的東西一樣？
我已經擁有的東西一樣？
06:42
And when was the last time
I wore it or used it?"
I wore it or used it?"
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我上次穿它或用它是什麼時候？」
06:46
But there's another group of experts
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但還有另一群專家
06:48
who perhaps thought
even harder about this problem,
even harder about this problem,
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花了更多功夫在想這個問題，
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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他們會說，這些問題當中
有一個比其他的都還重要。
有一個比其他的都還重要。
06:55
Those experts?
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那些專家是誰？
06:57
The people who design
the memory systems of computers.
the memory systems of computers.
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設計出電腦記憶體系統的人。
07:00
Most computers have
two kinds of memory systems:
two kinds of memory systems:
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大部分的電腦有兩種記憶體系統：
07:02
a fast memory system,
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快速記憶體系統，
07:03
like a set of memory chips
that has limited capacity,
that has limited capacity,
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就像是一組記憶體晶片，容量有限，
07:07
because those chips are expensive,
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因為那些晶片很貴，
07:09
and a slow memory system,
which is much larger.
which is much larger.
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還有慢速記憶體系統，
它的容量大很多。
它的容量大很多。
07:13
In order for the computer to operate
as efficiently as possible,
as efficiently as possible,
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為了要讓電腦的
運作效能盡可能提高，
運作效能盡可能提高，
07:16
you want to make sure
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你會希望能確保你要存取的資訊
07:17
that the pieces of information
you want to access
you want to access
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位在快速記憶體系統中，
這樣你就能快速取得它。
這樣你就能快速取得它。
07:19
are in the fast memory system,
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07:21
so that you can get to them quickly.
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每當你存取一項資訊時，
07:23
Each time you access
a piece of information,
a piece of information,
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它就會被載入快速記憶體中，
07:25
it's loaded into the fast memory
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電腦得要決定要從
快速記憶體中移除哪個項目，
快速記憶體中移除哪個項目，
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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因為它的容量有限。
07:33
Over the years,
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數年來，電腦科學家
試過幾種不同的策略
試過幾種不同的策略
07:34
computer scientists have tried
a few different strategies
a few different strategies
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來判定該從快速記憶體中移除什麼。
07:37
for deciding what to remove
from the fast memory.
from the fast memory.
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他們有試過隨機選擇的方法，
07:40
They've tried things like choosing
something at random
something at random
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07:43
or applying what's called
the "first-in, first-out principle,"
the "first-in, first-out principle,"
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也試過採用「先進先出」的原則，
也就是說把在記憶體當中
最久的項目給移除。
最久的項目給移除。
07:46
which means removing the item
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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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不過，最有效的策略，
07:52
focuses on the items
which have been least recently used.
which have been least recently used.
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是把目標放在近期最少使用的項目。
07:56
This says if you're going to decide
to remove something from memory,
to remove something from memory,
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這種策略就是，如果你得
從記憶體中移除某樣東西，
從記憶體中移除某樣東西，
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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你應該選擇最後一次使用時間
是最久遠的那樣東西。
是最久遠的那樣東西。
08:05
And there's a certain
kind of logic to this.
kind of logic to this.
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這背後是有某種邏輯的。
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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如果你上次存取那項資訊
已經是很久以前的事了，
已經是很久以前的事了，
08:10
it's probably going to be a long time
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你下次需要存取它的時間
08:12
before you're going to need
to access it again.
to access it again.
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應該也會是很久以後。
08:15
Your wardrobe is just like
the computer's memory.
the computer's memory.
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你的衣櫥就像是電腦的記憶體。
08:18
You have limited capacity,
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你的容量有限，
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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你得要把你最有可能
用到的東西放進去，
用到的東西放進去，
08:25
so that you can get to them
as quickly as possible.
as quickly as possible.
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這樣你才能夠盡快取得它們。
認知到這一點後，
08:29
Recognizing that,
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08:30
maybe it's worth applying
the least recently used principle
the least recently used principle
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也許也值得嘗試應用
「近期最少使用」原則
「近期最少使用」原則
08:33
to organizing your wardrobe as well.
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來整理你的衣櫥。
08:35
So if we go back
to Martha's four questions,
to Martha's four questions,
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如果我們回到瑪莎的四個問題，
08:37
the computer scientists
would say that of these,
would say that of these,
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電腦科學家會說，在這些問題中，
08:39
the last one is the most important.
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最後一個問題是最重要。
08:43
This idea of organizing things
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在整理東西時，要讓你最可能
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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需要的東西最容易存取的這個想法，
08:48
can also be applied in your office.
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也可以應用到你的辦公室中。
08:51
The Japanese economist Yukio Noguchi
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日本經濟學家野口悠紀雄
08:53
actually invented a filing system
that has exactly this property.
that has exactly this property.
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真的發明了一個具有
這種特性的建檔系統。
這種特性的建檔系統。
08:57
He started with a cardboard box,
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他從一個紙箱子開始，
08:58
and he put his documents into the box
from the left-hand side.
from the left-hand side.
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他把他的文件
從左到右放進箱子中。
從左到右放進箱子中。
09:02
Each time he'd add a document,
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每當他放入一份文件時，
他就得要移動箱中的文件，
他就得要移動箱中的文件，
09:03
he'd move what was in there along
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才能把新放入的文件
放入箱子的左邊。
放入箱子的左邊。
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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每當他需要使用一份文件時，
他會把該文件取出，
他會把該文件取出，
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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使用完之後放回到最左邊。
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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這樣的結果是，
文件會從左到右排好，
文件會從左到右排好，
09:16
by how recently they had been used.
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最左邊的是最近期使用過的。
09:18
And he found he could quickly find
what he was looking for
what he was looking for
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他發現這樣排之後，
他只要從箱子的左邊開始
他只要從箱子的左邊開始
09:21
by starting at the left-hand
side of the box
side of the box
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一直向右找，就能快速
找到他想找的文件。
找到他想找的文件。
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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在你們衝回家導入
這個建檔系統之前——
這個建檔系統之前——
09:27
(Laughter)
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（笑聲）
09:29
it's worth recognizing
that you probably already have.
that you probably already have.
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值得先想想，你可能
已經有這個系統了。
已經有這個系統了。
09:32
(Laughter)
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（笑聲）
09:36
That pile of papers on your desk ...
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你書桌上的那疊紙……
09:39
typically maligned
as messy and disorganized,
as messy and disorganized,
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通常都被別人誹謗說是亂七八糟，
09:41
a pile of papers is, in fact,
perfectly organized --
perfectly organized --
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其實是有著完美
組織系統的一疊紙——
組織系統的一疊紙——
09:44
(Laughter)
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（笑聲）
09:45
as long as you, when you take a paper out,
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只要你每次把一張紙拿出來，
09:47
put it back on the top of the pile,
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用完之後會放回那疊紙的最上方，
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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那麼那疊紙從上到下
就排好了順序，
就排好了順序，
09:52
by how recently they were used,
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最上面的是最近期使用的，
09:54
and you can probably quickly find
what you're looking for
what you're looking for
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你從那疊紙的最上面開始找，
可能就能快速找到你要的。
09:56
by starting at the top of the pile.
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09:59
Organizing your wardrobe or your desk
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整理你的衣櫥或你的書桌
10:01
are probably not the most pressing
problems in your life.
problems in your life.
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可能不是你人生中最緊迫的問題。
10:05
Sometimes the problems we have to solve
are simply very, very hard.
are simply very, very hard.
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有時，我們需要解決的問題
就是非常非常難搞。
就是非常非常難搞。
但即使在那些情況下，
10:09
But even in those cases,
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10:10
computer science can offer some strategies
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電腦科學也能夠提供一些策略，
10:12
and perhaps some solace.
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也許還能提供一些安慰。
10:16
The best algorithms are about doing
what makes the most sense
what makes the most sense
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最好的演算法，
就是要在最短的時間內
就是要在最短的時間內
做出最合理的舉動。
10:19
in the least amount of time.
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10:22
When computers face hard problems,
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當電腦面臨困難的問題時，
10:24
they deal with them by making them
into simpler problems --
into simpler problems --
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它們的處理方式是把那些問題
變成更簡單的問題——
變成更簡單的問題——
做法包括使用隨機性、
10:27
by making use of randomness,
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10:28
by removing constraints
or by allowing approximations.
or by allowing approximations.
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移除限制式，或是允許近似值。
10:32
Solving those simpler problems
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解決那些較簡單的問題，
10:34
can give you insight
into the harder problems,
into the harder problems,
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就能提供你關於
原本困難問題的洞見，
原本困難問題的洞見，
10:37
and sometimes produces
pretty good solutions in their own right.
pretty good solutions in their own right.
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有時，還能自己產生出
很好的解決方案。
很好的解決方案。
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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知道這一切，讓我在
必須要做決策時能夠放輕鬆。
必須要做決策時能夠放輕鬆。
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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可以用找房子時的
37% 規則來當例子。
37% 規則來當例子。
10:49
There's no way that you can
consider all of the options,
consider all of the options,
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你不可能把所有的
選項都納入考量，
選項都納入考量，
10:51
so you have to take a chance.
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所以你得要冒險。
10:53
And even if you follow
the optimal strategy,
the optimal strategy,
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即使你遵循最佳化策略，
10:56
you're not guaranteed a perfect outcome.
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也不能保證你會得到最完美的結果。
10:59
If you follow the 37 percent rule,
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如果你遵循 37% 規則，
11:01
the probability that you find
the very best place is --
the very best place is --
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你能找到最棒的地方的機率是——
11:04
funnily enough ...
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很有趣……
11:06
(Laughter)
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（笑聲）
11:07
37 percent.
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是 37%。
11:09
You fail most of the time.
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大部分的時候，你會失敗。
11:12
But that's the best that you can do.
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但你能做到最好的就是這樣了。
11:14
Ultimately, computer science
can help to make us more forgiving
can help to make us more forgiving
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最終，電腦科學會協助讓我們
更能原諒自己的限制。
11:17
of our own limitations.
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11:20
You can't control outcomes,
just processes.
just processes.
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你不能控制結果，只能控制過程。
11:22
And as long as you've used
the best process,
the best process,
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只要你已經用了最好的過程，
11:25
you've done the best that you can.
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你就已經盡了全力。
11:26
Sometimes those best processes
involve taking a chance --
involve taking a chance --
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有時，最好的過程會需要冒點險——
11:30
not considering all of your options,
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比如不去考量所有的選項，
11:32
or being willing to settle
for a pretty good solution.
for a pretty good solution.
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或是願意妥協，接受
算是不錯的解決方案。
算是不錯的解決方案。
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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這些並不是我們在無法
理性時所做的讓步——
理性時所做的讓步——
11:38
they're what being rational means.
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它們就是理性的真締。
11:40
Thank you.
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謝謝大家。
11:42
(Applause)
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（掌聲）
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