前幾天 MIT Technology Review 網站有文章談到深度學習大牛 Yann LeCun 認為機器可以利用機器視覺技術從大量影片中提取「常識」等級的知識,還有篇文章談如何利用機器學習技術,協助法官判案

光看這兩篇文章的標題,就讓我渾身冷颼颼,在人工智慧技術進展迅速的今日, John Markoff 的書Machines of Loving Grace 裡面所說 IA (intelligence augmentation) vs. AI (artificial intelligence) 的天平,似乎擺盪頻率愈發的高,擺盪幅度也愈發的大了。

看了上面這兩篇文章,我不禁懷疑,IA 和 AI 兩個取向,天平擺盪會有贏家輸家嗎?誰贏誰輸,最終對人類的影響究竟有什麼不同?

AlphaGo 初次露臉之後,李開復寫了一篇《人工智慧對人類真正的威脅是什麼?》,我覺得他對人工智慧議題的觀點是稍偏 IA 這一側的。但機器若能從大量影片裡面觀察到事物的特色與限制(真的邁向 common sense 了?),那可真的是「學習」路上一大步,不是 augmentation 或 amplification ,而是 intelligence 了。

One of the things we really want to do is get machines to acquire the very large number of facts that represent the constraints of the real world just by observing it through video or other channels. That’s what would allow them to acquire common sense, in the end. These are things that animals and babies learn in the first few months of life—you learn a ridiculously large amount about the world just by observation.

去年有人說臉書的廣告演算法和推薦演算法為什麼不一樣(唉,竟然忘記出處),因為他不需要 profiling 你是什麼樣的人,他根本就知道你是誰啊。Yann LeCun 現在可是臉書的人工智慧研究部門的老大,如果臉書的研究往前走了這麼一大步,怎麼不讓我感到冷颼颼。

說真格的,人工智慧對人類究竟是不是「威脅」,人言言殊,真的很難說。雖然現在不可能有答案,杞人憂天,畢竟也是談資啊Vox 讓旗下專欄作者 Sean Illing 找了十來個專家,問 How worried should we be about artificial intelligence?,答案可以說南轅北轍,也可以說所處的位置和行業決定了答案。人工智慧搶工作的議題是一定會一提再提的,技術演進的腳步快慢也一定有不同的看法。

當然,一定會有人要大家認真看待人工智慧的威脅,首先開槍的是來自牛津大學的哲學家 Nick Bostrom,人工智慧說不定那天就搞出大事了,怎麼能不小心謹慎呢。

The transition to machine superintelligence is a very grave matter, and we should take seriously the possibility that things could go radically wrong. This should motivate having some top talent in mathematics and computer science research the problems of AI safety and AI control.

最近幾年,只要談到資料挖掘、大數據、人工智慧,異常搶鏡的 Andrew Ng,則大剌剌的說,未來我們的後代也許需要擔心這個,但是現在擔心這問題,跟擔心火星上發生貪汙案一樣。中國味十足的答案,莫非因為他去了百度,常常閱讀中國材料,耳濡目染中國的反貪腐宣言,一不小心就帶進對話裡了。

Worrying about evil-killer AI today is like worrying about overpopulation on the planet Mars. Perhaps it’ll be a problem someday, but we haven’t even landed on the planet yet. This hype has been unnecessarily distracting everyone from the much bigger problem AI creates, which is job displacement.

我想,最好的答案,也是最雞湯的答案,應該是 MIT 的 Daniela Rus 的宣言吧!

It’s understandable that people have fears and anxieties about AI, and, as researchers, we have a duty to recognize those fears and provide different perspectives and solutions. I am optimistic about the future of AI in enabling people and machines to work together to make our lives better.

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