李開復紐時專欄:人工智慧對人類社會的真正威脅

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本文獲創新工場同意轉載。

中文版

面對呼之欲出的人工智慧時代,您最擔心什麼?

通常,人們對於這個問題的回答很像各類科幻片中的驚悚情節。他們擔心人工智慧的發展會帶來所謂的「奇點」,即在人類發展的某一特定歷史時刻,人工智慧會完全超越人類智慧,繼而將人類社會帶入一場無法想象的變革當中。人們甚至開始懷疑,人工智慧是否最終會控制人類,使人類淪為所謂的「機械人」。

這些問題值得探討,但並非亟待解決。先不論這些問題是否會發生,即使哪天真的出現,也是數百年以後。而目前,人類還沒有任何已知的途徑和方法能夠將當前最卓越的人工智慧系統——比如剛剛戰勝了最出色的人類棋手柯潔的圍棋電腦程式 AlphaGo,轉化為通用的人工智慧,即具有自我意識、可進行常識性推理、能夠自覺地從多領域獲取知識、並具有感知、表達和理解等能力的電腦程式。

但這並不意味著我們就可以高枕無憂。恰恰相反,現有人工智慧技術和產品的發展速度之快大大超出我們的認識和預期,人工智慧技術注定會改變我們的世界,並不完全以我們的意願為轉移。人工智慧是工具,不是一種智慧形式。但它注定會重新定義工作的意義以及財富的創造方式;值得注意的是,它將帶來前所未有的經濟失衡現象,甚至改變全球的權力格局。

因此,當務之急,讓我們先對這些迫在眉睫的現實挑戰予以關注。

人工智慧到底是什麼?粗略來講,人工智慧技術指的是獲取某個領域(比如貸款償還記錄)的海量資訊,並利用這些資訊對具體案例(是否應給某人貸款)做出判斷,以達成某個特定目標(貸方利益最大化)的技術。這些技術在給定任務中所展現出的工作能力已經被證明可以完全超越人類的表現。

今天,這樣的人工智慧技術正在被廣泛應用於各個領域。隨著它的進一步發展,會不可避免地對就業造成衝擊。很多工作和職業會逐步消失,例如銀行出納員、客戶服務代表、電話銷售員、股票和債券交易員等;甚至律師助理和放射科醫生這樣的工作也會被這類軟體所取代。假以時日,人工智慧技術還會學會控制如無人駕駛汽車和機器人這類半自主或全自主硬體設施,逐步取代工廠工人、建築工人、司機、快遞及許多其他職業。

與工業革命及資訊革命不同,人工智慧技術所帶來的衝擊並非單純指向某些特定工作和職業,如傳統製造業中的手工藝者被流水線工人所取代;或只會使用紙張和打字機的秘書被精通電腦的個人助理所替代等;人工智慧所帶來的是對現有職業和工作版圖大規模地顛覆。毋庸諱言,其中大部分為低薪工作,但某些高薪工作也將面臨挑戰。

值得注意的是,這場變革將會為開發人工智慧技術及採用人工智慧技術的公司和企業帶來巨額利潤。試想,如果 Uber 能全面利用無人駕駛車進行營運;蘋果公司能夠省卻大量人力生產其產品;全年滿足超過三千萬筆貸款請求卻不需要任何人工干預的借貸公司;可以想見,這些企業將利用人工智慧技術創造何等驚人的利潤和收益!而這一切已經是現在進行時。創新工場最近就在中國投資支持了一家利用人工智慧技術進行借貸的的新創企業。

誠如你所看到的,人類正面臨著很難妥善共存的兩個發展前景:一方面我們面臨僅用少量人力就能創造巨大財富的發展時代,而另一方面,大量人員也將因此失業。各種權衡,何去何從?

答案之一當然是教育,即要對人工智慧所不擅長的領域進行有針對性的人員教育和再培訓。具體來說,人工智慧並不擅長需要創造力、規劃能力以及「跨領域」思考能力等類型的工作——比如辯護律師。這些能力也是目前很多高端職位所要求的,問題是通過短期培訓來傳授和獲取這些能力和技能的可能行較低。另一個方向則是彌補人工智慧系統所欠缺的「人際交往能力」,發展出更多類似社會工作者、酒保、按摩技師等需要人際間微妙互動的崗位。即便如此,另一個問題隨之出現:我們的社會對酒保或類似工作又有多大需求呢?

按照我的個人推測,要解決人工智慧變革所帶來的大規模失業問題,需要的是更多我所說的所謂「關愛服務」。 這是人工智慧無法完成,而社會又大量需要的服務;更不用講你我生而為人所賴以的使命感和榮譽感。此類服務職缺不勝枚舉,例如:陪伴老人就醫的志工、孤兒院的教導員、戒酒互助社的志願者,甚或未來可能出現的——幫助那些沈迷於電腦虛擬實境刺激中的「平行人」重返人生現實的熱心人。換言之,當下的很多所謂志願服務工作未來都可能成為真正的職業。

其中一些服務甚至會轉變為高薪職業並趨於專業化,例如可協助和配合「人工智慧癌症診斷程式」工作的、具有專業醫療知識、同時又富有同情心和極強溝通技巧的醫療服務提供者。總體而言,人們可以選擇比現在更短的工作時間。

那麼,誰會為這些工作買單呢?文章開始時我提到的那些集中於相對少數企業手中的巨額財富現在可以派上用場了。在我看來,人工智慧所創造財富中的相當一部分會不可避免的轉移到那些工作被取代了的人們那裡去。而這個過程似乎只能是通過凱因斯主義的財政政策——即提高政府相關領域的開銷,及增加高利潤公司的稅收來加以實現。

至於那樣狀況下的社會福利是何種形式,我認為可能是一種有條件的全民基本收入方案,即社會福利將面向有經濟需求並符合條件的人群。所謂「條件」,是指福利申請者必須努力參與就業或再就業培訓,或保證參與一定工時的「關愛服務」。

當然,為了給這類社會福利提供資金,提高稅率可能在所難免。政府不僅要補貼大部分人的生活和工作,還要設法對此前大量失業員工無法繳納的個人所得稅進行彌補。

這就帶來了關於人工智慧最終、也是最重要的挑戰。我所描繪的凱因斯主義的財政政策或許在美國和中國是可行的,因為這兩個國家可以通過其規模巨大且成功的人工智慧企業來獲取稅收,並以此支撐其高昂的社會福利方案。但是其它國家又該如何呢?

相較而言,其他國家會面臨兩個難以克服的問題。首先,大部分人工智慧所創造的財富會流入美國和中國。人工智慧是一個「強者更強」的產業:數據越多,產品越好;產品越好,所能獲得的數據就更多;數據更多,就更吸引人才;人才越多,產品就會更好。在這個良性循環裡,中美兩國目前已經匯聚了大量人才、市場份額以及能夠使用的數據。

舉例來說,中國的語音識別企業科大訊飛以及人臉識別公司如曠視科技、商湯科技等就市值來講,都已經成為產業翹楚。在 Google、Tesla 及 Uber 等企業的引領下,美國的無人駕駛技術也是首屈一指。而在消費互聯網領域,中美七家企業——Google、臉書、微軟、亞馬遜、百度、阿里巴巴、騰訊——都已在其現有產品和服務中大量使用人工智慧技術,並正快速將其營運版圖擴展到全球範圍內,盡可能佔據更大的人工智慧市場。從目前的情勢看,美國似乎佔據發達國家市場及部分發展中國家市場,而中國公司無疑贏得了多數發展中國家市場。

對於中國和美國以外的其他國家來講,另外一項挑戰則在於許多國家還在日益成長的人口,尤其是一些發展中國家。龐大的人口可以成為一種經濟資本,就如同其近幾十年來在中國和印度的經濟發展中所產生的積極作用。但是在人工智慧時代,這個資本卻可能成為經濟負擔,因為其中大部分人口將面臨失業。

所以,如果很多國家不能通過向高額盈利的人工智慧企業徵稅來補貼工人,他們還能有什麼其他選擇?依我個人推論,為避免本國人民陷入貧困,這些國家會與提供最多人工智慧軟體的國家——中國或者美國——進行磋商和談判,最後以特定人工智慧企業在本地用戶中的盈利來換取國家所需的社會福利補貼。從而最終成為中美兩國的經濟依附體,這樣的經濟發展態勢也將重塑當今的地緣政治版圖。

一言以蔽之,最大程度地縮小人工智慧可能造成的經濟失衡和貧富差距,已是當下必須要考慮的問題,此差距不僅體現在國家內部,也體現在國與國之間。從樂觀的角度看:人工智慧為我們展現了一個打破全球經濟失衡狀態的機會,而挑戰所帶來的巨大影響,將使任何國家都無法置身事外。

英文版

What worries you about the coming world of artificial intelligence?

Too often the answer to this question resembles the plot of a sci-fi thriller. People worry that developments in A.I. will bring about the “singularity” — that point in history when A.I. surpasses human intelligence, leading to an unimaginable revolution in human affairs. Or they wonder whether instead of our controlling artificial intelligence, it will control us, turning us, in effect, into cyborgs.

These are interesting issues to contemplate, but they are not pressing. They concern situations that may not arise for hundreds of years, if ever. At the moment, there is no known path from our best A.I. tools (like the Google computer program that recently beat the world’s best player of the game of Go) to “general” A.I. — self-aware computer programs that can engage in common-sense reasoning, attain knowledge in multiple domains, feel, express and understand emotions and so on.

This doesn’t mean we have nothing to worry about. On the contrary, the A.I. products that now exist are improving faster than most people realize and promise to radically transform our world, not always for the better. They are only tools, not a competing form of intelligence. But they will reshape what work means and how wealth is created, leading to unprecedented economic inequalities and even altering the global balance of power.

It is imperative that we turn our attention to these imminent challenges.

What is artificial intelligence today? Roughly speaking, it’s technology that takes in huge amounts of information from a specific domain (say, loan repayment histories) and uses it to make a decision in a specific case (whether to give an individual a loan) in the service of a specified goal (maximizing profits for the lender). Think of a spreadsheet on steroids, trained on big data. These tools can outperform human beings at a given task.

This kind of A.I. is spreading to thousands of domains (not just loans), and as it does, it will eliminate many jobs. Bank tellers, customer service representatives, telemarketers, stock and bond traders, even paralegals and radiologists will gradually be replaced by such software. Over time this technology will come to control semiautonomous and autonomous hardware like self-driving cars and robots, displacing factory workers, construction workers, drivers, delivery workers and many others.

Unlike the Industrial Revolution and the computer revolution, the A.I. revolution is not taking certain jobs (artisans, personal assistants who use paper and typewriters) and replacing them with other jobs (assembly-line workers, personal assistants conversant with computers). Instead, it is poised to bring about a wide-scale decimation of jobs — mostly lower-paying jobs, but some higher-paying ones, too.

This transformation will result in enormous profits for the companies that develop A.I., as well as for the companies that adopt it. Imagine how much money a company like Uber would make if it used only robot drivers. Imagine the profits if Apple could manufacture its products without human labor. Imagine the gains to a loan company that could issue 30 million loans a year with virtually no human involvement. (As it happens, my venture capital firm has invested in just such a loan company.)

We are thus facing two developments that do not sit easily together: enormous wealth concentrated in relatively few hands and enormous numbers of people out of work. What is to be done?

Part of the answer will involve educating or retraining people in tasks A.I. tools aren’t good at. Artificial intelligence is poorly suited for jobs involving creativity, planning and “cross-domain” thinking — for example, the work of a trial lawyer. But these skills are typically required by high-paying jobs that may be hard to retrain displaced workers to do. More promising are lower-paying jobs involving the “people skills” that A.I. lacks: social workers, bartenders, concierges — professions requiring nuanced human interaction. But here, too, there is a problem: How many bartenders does a society really need?

The solution to the problem of mass unemployment, I suspect, will involve “service jobs of love.” These are jobs that A.I. cannot do, that society needs and that give people a sense of purpose. Examples include accompanying an older person to visit a doctor, mentoring at an orphanage and serving as a sponsor at Alcoholics Anonymous — or, potentially soon, Virtual Reality Anonymous (for those addicted to their parallel lives in computer-generated simulations). The volunteer service jobs of today, in other words, may turn into the real jobs of the future.

Other volunteer jobs may be higher-paying and professional, such as compassionate medical service providers who serve as the “human interface” for A.I. programs that diagnose cancer. In all cases, people will be able to choose to work fewer hours than they do now.

Who will pay for these jobs? Here is where the enormous wealth concentrated in relatively few hands comes in. It strikes me as unavoidable that large chunks of the money created by A.I. will have to be transferred to those whose jobs have been displaced. This seems feasible only through Keynesian policies of increased government spending, presumably raised through taxation on wealthy companies.

As for what form that social welfare would take, I would argue for a conditional universal basic income: welfare offered to those who have a financial need, on the condition they either show an effort to receive training that would make them employable or commit to a certain number of hours of “service of love” voluntarism.

To fund this, tax rates will have to be high. The government will not only have to subsidize most people’s lives and work; it will also have to compensate for the loss of individual tax revenue previously collected from employed individuals.

This leads to the final and perhaps most consequential challenge of A.I. The Keynesian approach I have sketched out may be feasible in the United States and China, which will have enough successful A.I. businesses to fund welfare initiatives via taxes. But what about other countries?

They face two insurmountable problems. First, most of the money being made from artificial intelligence will go to the United States and China. A.I. is an industry in which strength begets strength: The more data you have, the better your product; the better your product, the more data you can collect; the more data you can collect, the more talent you can attract; the more talent you can attract, the better your product. It’s a virtuous circle, and the United States and China have already amassed the talent, market share and data to set it in motion.

For example, the Chinese speech-recognition company iFlytek and several Chinese face-recognition companies such as Megvii and SenseTime have become industry leaders, as measured by market capitalization. The United States is spearheading the development of autonomous vehicles, led by companies like Google, Tesla and Uber. As for the consumer internet market, seven American or Chinese companies — Google, Facebook, Microsoft, Amazon, Baidu, Alibaba and Tencent — are making extensive use of A.I. and expanding operations to other countries, essentially owning those A.I. markets. It seems American businesses will dominate in developed markets and some developing markets, while Chinese companies will win in most developing markets.

The other challenge for many countries that are not China or the United States is that their populations are increasing, especially in the developing world. While a large, growing population can be an economic asset (as in China and India in recent decades), in the age of A.I. it will be an economic liability because it will comprise mostly displaced workers, not productive ones.

So if most countries will not be able to tax ultra-profitable A.I. companies to subsidize their workers, what options will they have? I foresee only one: Unless they wish to plunge their people into poverty, they will be forced to negotiate with whichever country supplies most of their A.I. software — China or the United States — to essentially become that country’s economic dependent, taking in welfare subsidies in exchange for letting the “parent” nation’s A.I. companies continue to profit from the dependent country’s users. Such economic arrangements would reshape today’s geopolitical alliances.

One way or another, we are going to have to start thinking about how to minimize the looming A.I.-fueled gap between the haves and the have-nots, both within and between nations. Or to put the matter more optimistically: A.I. is presenting us with an opportunity to rethink economic inequality on a global scale. These challenges are too far-ranging in their effects for any nation to isolate itself from the rest of the world.


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