技术未来主义者的乌托邦幻觉

The delusions of techno-futurists who ask: crisis, what crisis?

技术未来主义者的乌托邦错觉

桑希尔：“AI+全民基本收入=乌托邦”把问题简单化了，技术专家应该设法寻找让AI帮助人类发挥创造力的方法。

The Covid-19 pandemic may have killed 2.7m people and resulted in the worst economic contraction in a generation. But the optimism of the West Coast tech elite remains undimmed. “The future can be almost unimaginably great,” as Sam Altman, who heads an artificial intelligence research company, wrote in a recent essay, Moore’s Law for Everything.

新型冠状病毒肺炎（COVID-19，即2019冠状病毒病）疫情可能已经导致270万人死亡，并造成了一个世代以来最严重的经济萎缩。但是美国西海岸科技精英的乐观情绪仍然不减。“未来可能会美好得难以想象。”一家人工智能(AI)研究公司的主管萨姆•奥尔特曼(Sam Altman)在最近的文章《万物皆适用摩尔定律》(Moore's Law for Everything)中如此写道。

Like many tech evangelists, Altman argues that we are on the brink of an AI-induced productivity explosion that will shower abundance on all. The entry of millions of Chinese workers into the global labour force over the past three decades will be seen as nothing compared with the arrival of tireless AI “workers” that will radically cut the cost of all tradable goods. When robots start inventing better robots, we will achieve “Moore’s Law for everything”, not just computing power.

像许多“科技布道者”(tech evangelist)一样，奥尔特曼认为，AI即将带来一场生产力大爆炸，这场爆炸将让所有物资极大丰富。过去三十年，数以百万计的中国工人进入全球劳动力市场，但这与不知疲倦的AI“工人”的到来相比简直微不足道，后者将会大幅削减所有可交易商品的成本。当机器人开始发明更好的机器人时，摩尔定律将适用于万物，而不仅仅是计算能力。

“Imagine a world where, for decades, everything — housing, education, food, clothing, etc — became half as expensive every two years,” he enthused.

他充满激情地写道：“想象这样一个世界：在几十年内，所有东西——住房、教育、食物、衣服等等——每两年价格就减一半。”

Altman admits that many readers may think his arguments utopian. Others will dismiss them as those of a techno-crank. But it is hard to deny that Altman has an interesting vantage point from which to peer into how the future may unfold.

奥尔特曼承认，许多读者也许认为他的观点很乌托邦。其他人可能认为这只不过是一个科学怪人的想法。但很难否认，奥尔特曼占据着一个有趣的位置，让他能更好地窥见未来可能的走向。

For many years, Altman helped run Y Combinator, the start-up accelerator that backed many of Silicon Valley’s smartest bus

多年来，奥尔特曼帮助经营Y Combinator——一家创业加速器，支持了许多硅谷最有想法的企业；现在，他是Open AI的首席执行官，这是一家研究公司，研发了GPT-3语言生成模型——这是个强大得令人毛骨悚然的模型，其生成的文本几可乱真。

More unusually among the Silicon Valley crowd, Altman has long expressed a deep concern about the flip side of technological creation: societal disruption. As he sees it, the AI revolution will further shift the balance of power from labour to capital, resulting in the concentration of phenomenal wealth among the machine owners. Good societal outcomes will only result if there is a radical change in public policy and a massive redistribution of wealth. He has himself sponsored an experiment with universal basic income in Oakland and proposes the creation of an American Equity Fund to give everyone a share of future technological riches.

奥尔特曼长期表现出对技术成果的负面影响——扰乱社会——的深切担忧，这种态度在硅谷人当中较为不寻常。他认为，AI变革将进一步让权力的天平从劳动者向资本倾斜，导致巨量财富集中到机器拥有者手中。只有在彻底变革公共政策、大规模重新分配财富的情况下，AI才会带来好的社会结果。在奥克兰，他自己资助了一项全民基本收入(UBI)实验；他还倡议建立美国平等基金(American Equity Fund)，让每个人都能享有一份未来技术创造的财富。

“A great future isn’t complicated: we need technology to create it and policy to fairly distribute it,” he wrote.

他写道：“美好的未来并不复杂：我们需要技术来创造它，需要政策来公平地分配它。”

There are three main criticisms of Altman’s equation of AI + UBI = utopia. The first is that he wildly overestimates the short-term impact of AI. The second is that he wildly underestimates the difficulties of policy change. The third is that by focusing on the fascinatingly improbable, we will crowd out more useful discussion about the worryingly probable.

奥尔特曼的“AI+全民基本收入=乌托邦”等式主要面临三类批评。第一类认为他严重高估了AI的短期影响。第二类认为他严重低估了政策改革的难度。第三类认为，如果我们专注于炫酷的不实际做法，就会挤占更有用的讨论的空间，即关于不完美但可行的做法的讨论。

Many of those who work in the field of AI themselves think that AI is overhyped. Erik Larson, author of a forthcoming book called The Myth of Artificial Intelligence, is one. He is critical of many of the “false narratives” around AI which suggest that machine superintelligence is somehow imminent. AI systems that can soar in one narrow domain still have a hard time jumping off the ground in others.

许多本身就在AI领域工作的人都认为，AI的作用被夸大了。埃里克•拉森(Erik Larson)就是其中之一，他的新书《人工智能迷思》(The Myth of Artificial Intelligence)即将出版。他批评了许多围绕AI的“错误说法”，这些说法认为超级机器智能很快就能出现。一些AI系统能在某一狭窄领域迅猛发展，但仍然很难在其他领域取得突破。

For example, IBM’s Watson may have won the quiz show Jeopardy! But it failed to cure cancer. A few years ago, autonomous cars seemed to be just round the corner. But they still have difficulty distinguishing between a turning bus and an overpass. “There is an odd cognitive dissonance between the reality of what we are doing and the science fiction debates you see about AI,” says Larson. What worries him more is the “spectre of a jobless future from mindless automation”.

例如，IBM的“沃森”(Watson)也许在智力竞赛节目《危险边缘》(Jeopardy!)上取得了胜利，但它无法治疗癌症。数年前，自动驾驶汽车似乎很快就能面世。但现在自动驾驶汽车仍难以区分一辆转弯的公交车和一座立交桥。拉森表示：“在技术发展的现状和现在有关AI的科幻辩论之间，有一种奇怪的认知失调。”更让他担心的是“盲目自动化可能造成未来无业可就”。

From the policy perspective, it is equally simplistic to believe that UBI is the remedy for all ills, although it may be a partial cure. Vi Hart, who also once worked at Y Combinator, acknowledges the danger of what she calls the “AI-pocalypse” but does not think that UBI is the answer.

从政策的角度看，如果你相信全民基本收入可以解决所有问题，那就同样把事情简单化了，尽管全民基本收入也许能解决部分问题。维•哈特(Vi Hart)——她也曾在Y Combinator工作——认为，确实存在她称之为“AI末日”(AI-pocalypse)的危险，但她不认为全民基本收入能够解决问题。

“I believe the apparent synergy of AI and UBI comes not from them being a radical brilliant solution, but from them being the easy way out, the status quo, the default choice that leads further down our current path of increasing inequality,” she wrote.

她写道：“我认为，AI和全民基本收入之间有明显的相似性，并非因为它们都是激进的绝妙解决方案，而是因为它们都是简单的出路，是维持现状，是引着我们继续走向日益扩大的不平等的默认选择。”

Altman frames the AI debate as one of techno-determinist inevitability: the technological revolution is unstoppable and so it will be the fault of politicians if we fail to adapt. But this is buck-passing of epic proportions that gives technologists a free pass to develop whatever they want.

奥尔特曼的总体看法是带有技术决定论色彩的，认为AI是不可逃避的未来：技术革命是不可阻挡的，因此如果我们无法适应，那就是政治人士的错。但这是严重的推卸责任，赋予技术专家随心所欲研发任何东西的权利。

Their efforts would be better spent figuring out how best to use AI to enhance human creativity and innovation in small, discrete and meaningful ways, rather than render it redundant.

对他们而言，更好的努力方向是，寻找最佳方法，以微小、分散而有意义的方式利用AI来提高人类的创造力和创新力，而不是荒废人类的能力。

编辑：古凤