大约一年前，OpenAI首席财务官莎拉·弗里亚（Sarah Friar）表示，公司维持其当前财务“走钢丝”般状态的一种方式，可能是获得一种“后盾”或“担保”——即政府担保——“以使融资得以进行”。几乎在同一时间，公司首席执行官萨姆·阿尔特曼（Sam Altman）表示：“考虑到我预期人工智能的经济影响将呈现的巨大规模，”政府应充当“最后贷款人”的角色。他们对这些言论做了限定，但大意似乎是，《华尔街日报》称为“美国历史上最大经济赌注”的这个行业，对国家如此重要，以至于如果它需要更多资金，纳税人就应该买单。
It was about a year ago that Sarah Friar, the chief financial officer of OpenAI, said one way the company might sustain its current financial high-wire act was with a “backstop” or “guarantee” — as in, a government guarantee — “that allows the financing to happen.” Almost at the same time, Sam Altman, the company’s chief executive, said, “Given the magnitude of what I expect A.I.’s economic impact to look like,” the government should serve the role of “insurer of last resort.” They qualified those comments, but still, the gist seemed to be that the industry The Wall Street Journal calls “the biggest economic bet in U.S. history” is so important to the nation that if it needs more funding, taxpayers should be on the hook.
换一种说法就是，政府应该像对待2008年金融危机时的银行那样对待人工智能：大而不能倒。
Another way to put it is that the government should regard artificial intelligence the same way it regarded the banks in the 2008 financial crisis: too big to fail.
很难将这一建议与当今领先人工智能公司发出的另一种震耳欲聋的信息调和起来：正如前Anthropic研究员雅各布·考克森（Jacob Coxon）最近警告的那样，这项技术“可能在本十年末杀死我们所有人”，因此必须加以限制。人工智能重要到我们不能让它失败，却又风险大到我们不该让它继续前进？
It’s hard to reconcile that suggestion with the other message blaring out of leading A.I. companies these days: that the technology “could kill us all by the end of the decade,” as the former Anthropic researcher Jacob Coxon recently warned, and must therefore be restrained. A.I. is so important that we can’t let it fail, but so risky that we shouldn’t let it go forward?
现在再加上这种通念：美国必须不惜一切代价击败中国（正如特朗普总统所言，“谁赢了人工智能，谁就赢了！”），这些论点便开始相互强化。争夺主导权的竞赛越关乎生存，我们就越必须在上面投入更多；我们在该行业投入越多，它在经济和地缘政治上的后果就越重大；后果越重大，就越需要不顾安全顾虑加速前进；我们越是不顾一切地向前冲，风险就越大。总而言之，这提出了一个更可怕的可能性：如果人工智能不是“大而不能倒”，而是“大而不能停”，那该怎么办？
Now add the conventional wisdom that the United States has to beat China at all costs (or as President Trump put it, “Whoever wins A.I. wins!”), and the arguments can start to reinforce one another. The more the race to dominate becomes existential, the more we have to spend on it; the more we spend on the industry, the more economically and geopolitically consequential it becomes; the more consequential it becomes, the greater the need to speed ahead, safety concerns be damned; the more we race ahead heedless, the more risk there is. All in all, it raises an even scarier possibility: What if rather than being too big to fail, A.I. is too big to stop?
企业重要到政府有义务维持其运营这一观念，至少可追溯至1797年，当时一位英国金融家主张，当私人资金来源枯竭时，英格兰银行应当扶持陷入困境的公司。“大而不能倒”这一说法在1984年定型，缘于大陆伊利诺伊银行因承接过多不良能源贷款而濒临倒闭。时任众议员斯图尔特·麦金尼当时表示：“我们有了一种新型银行，它被称为‘大而不能倒’。”随后便是2008年危机，大型银行动用纳税人资金获救，理论依据是不这样做它们就会拖垮整个经济。
The idea that a business could be so important that the government is obligated to keep it afloat dates at least from 1797, when an English financier said the Bank of England should shore up ailing companies when private sources had been exhausted. The phrase crystallized in 1984, after Continental Illinois bank almost sank because it had taken on too many bad energy loans. “We have a new kind of bank,” Representative Stewart McKinney said at the time. “It is called too big to fail.” Then came the 2008 crisis, in which the big banks were bailed out using taxpayers’ money, on the theory that without it they would take down the whole economy.
这些“大而不能倒”的银行，是里根时代担忧的遗产：如果美国银行不迅速做大规模，就无法与欧洲和亚洲的金融机构竞争。今天，在特朗普总统断言对人工智能的恐惧是“骗局”、危及美国对中国的领先优势时，能听到类似的回响。另一个相似之处在于：在2008年金融危机酝酿期间，即使显而易见客户无法偿还银行像发糖果般发放的次级抵押贷款，这些银行的领导者依然拒绝改弦易辙。称之为理性的鲁莽吧：“只要音乐还在响，”时任花旗银行首席执行官查克·普林斯说道，“你就得站起来跳舞。”如今，数据中心背后的公司——如亚马逊、Alphabet和甲骨文，以及人工智能模型背后的公司——如OpenAI和Anthropic，也在跳舞，而且停不下来，否则就会输掉它们为击败竞争对手而投入的数千亿美元。
Those too-big-to-fail banks were the legacy of Reagan-era concerns that if U.S. banks didn’t bulk up, and fast, they’d be unable to compete with financial institutions in Europe and Asia. You can hear something similar today in President Trump’s assertion that fear about A.I. is a “hoax” that endangers America’s lead over China. Another similarity: In the buildup to the 2008 financial crisis, even as it was becoming clear that customers couldn’t pay back all the subprime mortgages the banks had been giving out like candy, the leaders of those banks refused to change course. Call it rational recklessness: “As long as the music is playing,” said Chuck Prince, then the chief executive of Citibank, “you’ve got to get up and dance.” Today, the companies behind the data centers, such as Amazon and Alphabet and Oracle, and the companies behind the A.I. models, such as OpenAI and Anthropic, are dancing too, and they can’t stop, lest they lose the hundreds of billions they’ve invested in beating the competition.