評論
打印
We invented the car, screwed up a bunch of times -- invented the traffic light, the seat belt and the airbag,
我們發明了汽車，又一不小心搞砸了很多次--發明了紅綠燈，安全帶和安全氣囊，
but with more powerful technology like nuclear weapons and AGI, learning from mistakes is a lousy strategy, don't you think?
但對于更強大的科技，像是核武器和AGI，要去從錯誤中學習，似乎是個比較糟糕的策略，你們怎么看？
It's much better to be proactive rather than reactive;
事前的準備比事后的補救要好得多；
plan ahead and get things right the first time because that might be the only time we'll get.
提早做計劃，爭取一次成功，因為有時我們或許沒有第二次機會。
But it is funny because sometimes people tell me, "Max, shhh, don't talk like that. That's Luddite scaremongering."
但有趣的是，有時候有人告訴我。“麥克斯，噓，別那樣說話。那是勒德分子在制造恐慌。”
But it's not scaremongering. It's what we at MIT call safety engineering.
但這并不是制造恐慌。在麻省理工學院，我們稱之為安全工程。
Think about it: before NASA launched the Apollo 11 mission,
想想看：在美國航天局（NASA）部署阿波羅11號任務之前，
they systematically thought through everything that could go wrong
他們全面地設想過所有可能出錯的狀況，
when you put people on top of explosive fuel tanks and launch them somewhere where no one could help them.
畢竟是要把人類放進易燃易爆的太空艙里，再將他們發射上一個無人能助的境遇。
And there was a lot that could go wrong. Was that scaremongering? No.
可能出錯的情況非常多，那是在制造恐慌嗎？不是。
That's was precisely the safety engineering that ensured the success of the mission,
那正是在做安全工程的工作，以確保任務順利進行，
and that is precisely the strategy I think we should take with AGI.
這正是我認為處理AGI時應該采取的策略。
Think through what can go wrong to make sure it goes right.
想清楚什么可能出錯，然后避免它的發生。
So in this spirit, we've organized conferences,
基于這樣的精神，我們組織了幾場大會，
bringing together leading AI researchers and other thinkers to discuss how to grow this wisdom we need to keep AI beneficial.
邀請了世界頂尖的人工智能研究者和其他有想法的專業人士，來探討如何發展這樣的智慧，從而確保人工智能對人類有益。
Our last conference was in Asilomar, California last year and produced this list of 23 principles
我們最近的一次大會去年在加州的阿西洛瑪舉行，我們得出了23條原則，
which have since been signed by over 1,000 AI researchers and key industry leaders,
自此已經有超過1000位人工智能研究者，以及核心企業的領導人參與簽署，
and I want to tell you about three of these principles.
我想要和各位分享其中的三項原則。
