别被这个夏天的 AI 炒作蒙蔽

将它们描述为“超级智能”或“失控模型”，是在把能动性赋予产品，而非赋予打造这些产品的公司。这种框架一方面将这些公司的产品营销为“超人类”，另一方面又帮助公司逃避其行为应承担的责任。

与其让 OpenAI 因制造用于入侵另一家公司的恶意软件而被追责，新闻稿、新闻媒体、媒体人物和立法者却都在谈论“失控模型”，仿佛它们是自行行动的。与其让研究人员就其公司惯常剽窃学者成果、或未经同意使用客户数据训练模型的做法接受质询，公众的想象力却被引向：虚构的超级智能机器到来后，未来可能出现什么可怕景象。

AI 行业甚至暗示，广受欢迎、跨党派的数据中心反对行动，是对监管这些公司正在构建的、即将到来的可怕“超人类”机器努力的一种“干扰”。按照 AI 行业的说法，我们应该更担心虚构的机器神，而不是这些数据中心加剧的气候灾难、附近居民所遭受的哮喘、为补贴这些数据中心而承担不断上涨电费的公众，或被改用于为其冷却的水资源。

我们明白，不应基于营销宣传作出决策，也不应屈服于企业要求迅速作出此类决策的压力。无论对政策制定者还是社区而言，明智的决策都需要时间来听取独立专家的意见，并将企业声明置于具体背景中审视。这个炒作之夏最好的结果，是政策制定者和广大公众学会先缓一口气，保持怀疑精神，并在下一次类似炒作出现时，认清它的本质。

Timnit Gebru 是 DAIR 执行董事，也是即将出版的著作 《Deep Unlearning: The Radicalization of a Tech Idealist》的作者；该书现已开放预订，计划于 2 月 16 日出版。Emily M. Bender 是华盛顿大学语言学教授，并与人合著了《The AI Con》。

Describing them as “superintelligence” or “rogue models” ascribes agency to products rather than to the companies building them. This framing markets these companies’ products as “superhuman” and, at the same time, helps the companies evade accountability for their actions.

Instead of OpenAI being prosecuted for creating malware that hacked another company, press releases, news outlets, media personalities, and lawmakers refer to “rogue models” as if they acted on their own. Instead of researchers being questioned about their companies’ habit of plagiarizing academics’ work or using customer data to train models without consent, the public’s imagination is redirected to fears about what the future might hold upon the arrival of fictional superintelligent machines.

The AI industry has even suggested that popular, bipartisan anti-data-center activism is a “distraction” from attempts to regulate the impending, scary, “superhuman” machines these companies are building. According to the AI industry, we should be more worried about a fictional machine god than about the climate catastrophe that these data centers exacerbate, the asthma suffered by those living near them, the rising electricity bills of the public subsidizing them, or the water that is redirected to cooling them.

We know better than to make decisions based on marketing and better than to capitulate to corporate pressure to make those decisions quickly. Wise decision-making, by policymakers and communities, demands time to hear from independent experts and contextualize corporate claims. The best possible outcome from this summer of hype is that policymakers and the public at large learn to take a breath, hold onto our skepticism, and recognize this kind of hype for what it is the next time it comes around.

Timnit Gebru is executive director of DAIR and author of the forthcoming bookDeep Unlearning: The Radicalization of a Tech Idealist, which is available for preorders now and set to publish on February 16. Emily M. Bender is professor of linguistics at the University of Washington and coauthor of The AI Con.