Name: 【TED】Kriti Sharma：如何讓人類的偏見遠離AI（How to keep human bias out of AI | Kriti Sharma）。 (【TED】Kriti Sharma: How to keep human bias out of AI (How to keep human bias out of AI | Kriti Sharma))
Uploaded: 2021-01-14T08:14:09.000Z
Duration: 12 min 11 s

Translator: Ivana Korom Reviewer: Joanna Pietrulewicz

譯者: Lilian Chiu 審譯者: Bruce Sung

How many decisions have been made about you today,

今天，有多少與你有關的決策，

所以，不隱瞞大家，我是個怪胎。

about artificial intelligence stealing all our jobs,

內容有談到人工智慧 偷走我們所有的工作，

or robots getting citizenship of an actual country,

或是機器人取得 實際國家的公民權，

I'm the person my friends and followers message

我的朋友和追隨者 就會發訊息給我，

This media panic that our robot overlords are taking over.

這種認為機器人統治者 會接管世界的媒體恐慌。

But in reality, that's not the problem we should be focusing on.

但，在現實中，我們不該 把焦點放在那個問題上。

There is a more pressing danger, a bigger risk with AI,

還有更迫切的危機， 人工智慧有個更大的風險，

How many decisions have been made about you today by AI?

今天，人工智慧做了 多少關於你的決策？

were based on your gender, your race or your background?

是根據你的性別、你的種族， 或你的背景所做出來的？

to make decisions about who we are and what we want.

做出關於我們是什麼人、 我們想要什麼的相關決策。

Some of the women in this room will know what I'm talking about

這間房間中有一些女性 知道我在說什麼，

if you've been made to sit through those pregnancy test adverts on YouTube

如果你曾經坐在電腦前 看 YouTube 時，

被迫看完驗孕測試的廣告， 且發生過約一千次的話。

Or you've scrolled past adverts of fertility clinics

或者，你曾經在滑手機 看臉書動態時報時

或者，我的例子則是看到 印度婚姻介紹所的廣告。

But AI isn't just being used to make decisions

但，人工智慧不只是被用來判定

or which show we want to binge watch next.

或是我們接下來想要看追哪齣劇。

I wonder how you'd feel about someone who thought things like this:

我很好奇，對於這樣想的人， 你們有何感覺：

is less likely than a white person to pay off their loan on time.\"

準時還清貸款的可能性 沒有白人高。」

\"A person called John makes a better programmer

「名字叫做約翰的人， 和名叫瑪莉的人相比，

\"A black man is more likely to be a repeat offender than a white man.\"

「比起白人，黑人比較 有可能會再次犯罪。」

\"Wow, that sounds like a pretty sexist, racist person,\" right?

「哇，那聽起來是性別主義 和種族主義的人會說的話」對吧？

These are some real decisions that AI has made very recently,

上述這些是人工智慧 近期所做出的一些決策，

based on the biases it has learned from us,

決策依據是它向我們學來的偏見，

AI is being used to help decide whether or not you get that job interview;

人工智慧被用來協助判斷 你是否能參加工作面試；

and even what rating you get in your annual performance review.

甚至你在年度考績中 得到的評級是多少。

But these decisions are all being filtered through

its assumptions about our identity, our race, our gender, our age.

過濾依據就是關於我們的身分、 種族、性別、年齡等的假設。

Now, imagine an AI is helping a hiring manager

想像一下，人工智慧在協助 一位有人才需求的經理

find the next tech leader in the company.

尋找該公司的下一位技術主管。

So far, the manager has been hiring mostly men.

目前，這位經理僱用的人 大部分都是男性。

So the AI learns men are more likely to be programmers than women.

所以人工智慧學到的是，男性 比女性更有可能成為程式設計師。

And it's a very short leap from there to:

很容易就會從 這個現象直接下結論：

We have reinforced our own bias into the AI.

我們把我們自己的偏見 灌輸給人工智慧。

And now, it's screening out female candidates.

現在，它就會把 女性候選人給篩掉。

Hang on, if a human hiring manager did that,

等等，如果人類的經理這樣做，

我們會很火大， 我們不會容忍這種事。

This kind of gender discrimination is not OK.

And yet somehow, AI has become above the law,

但，人工智慧卻以 某種方式超越了法律，

因為那個決策是機器做出來的。

We are also reinforcing our bias in how we interact with AI.

我們和人工智慧的互動， 也加強了我們自己的偏見。

How often do you use a voice assistant like Siri, Alexa or even Cortana?

你們有多常使用語音助手，比如 Siri、Alexa，或甚至 Cortana？

第一，它們總是把我的名字弄錯，

They are designed to be our obedient servants,

它們被設計為順從我們的僕人，

turning your lights on and off, ordering your shopping.

幫你開燈、關燈，幫你下單購物。

You get male AIs too, but they tend to be more high-powered,

也會有男性的人工智慧， 但通常它們的功能比較強，

like IBM Watson, making business decisions,

比如 IBM 的 Watson， 做的是商業決策，

Salesforce Einstein or ROSS, the robot lawyer.

又如 Salesforce Einstein， 或是機器律師 ROSS 。

So poor robots, even they suffer from sexism in the workplace.

可憐的機器人，連它們也會 遇到工作場所的性別主義。

想想看，當這兩點結合起來時，

and affect a kid growing up in today's world around AI.

會如何影響現今世界中與人工智慧 一同生活的孩子成長。

So they're doing some research for a school project

所以，他們為了一項學校 專案計畫做了些研究，

他們用 Google 搜尋了 執行長的形象。

The algorithm shows them results of mostly men.

演算法呈現給他們看的搜尋結果， 大部分都是男性。

As you can guess, it shows them mostly females.

你們可以猜到，呈現出來的 搜尋結果大部分是女性。

And then they want to put on some music, and maybe order some food,

接著，他們想要播放音樂， 也許再點一些食物來吃，

and now, they are barking orders at an obedient female voice assistant.

Some of our brightest minds are creating this technology today.

Technology that they could have created in any way they wanted.

一些最聰明的天才們 創造出現今的這種技術。

And yet, they have chosen to create it in the style of 1950s \"Mad Man\" secretary.

他們可以依他們想要的 任何方式來創造這種技術。

但，他們選擇採用五〇年代 《廣告狂人》中的秘書風格。

this is not going to end with me telling you

that we are all heading towards sexist, racist machines running the world.

The good news about AI is that it is entirely within our control.

我們正在邁向一個由性別主義、 種族主義的機器所統治的世界。

We get to teach the right values, the right ethics to AI.

關於人工智慧的好消息是， 它完全在我們的掌控當中。

我們可以教導人工智慧 正確的價值觀、正確的倫理。

第一，我們可以意識到 我們自己有偏見存在，

Two, we can make sure that diverse teams are building this technology.

以及我們身邊的機器也有偏見。

【TED】Kriti Sharma：如何讓人類的偏見遠離AI（How to keep human bias out of AI | Kriti Sharma）。 (【TED】Kriti Sharma: How to keep human bias out of AI (How to keep human bias out of AI | Kriti Sharma))

字幕列表影片播放

【TED】Kriti Sharma：如何讓人類的偏見遠離AI（How to keep human bias out of AI | Kriti Sharma）。 (【TED】Kriti Sharma: How to keep human bias out of AI (How to keep human bias out of AI | Kriti Sharma))

assume

tend

bias

artificial