将人工智能产品描述为“超级智能”或“失控模型”，是将主体性归咎于产品，而非制造这些产品的公司。这种叙事框架将这些公司的产品营销为“超人级”，同时帮助这些公司逃避对其行为的责任。

当OpenAI因创建黑客攻击另一家公司的恶意软件而面临起诉时，新闻稿、新闻媒体、媒体名人和立法者却将责任推给所谓的“失控模型”，仿佛它们拥有自主行动的能力。当研究人员被问及所在公司惯于抄袭学者成果或在未经同意的情况下使用客户数据训练模型时，公众的想象力却被引导至对虚构的超级智能机器到来后未来景象的恐惧上。

人工智能行业甚至暗示，广受两党支持的反对建设数据中心的民众运动是一种“干扰”，目的是让人们忽视对这些公司正在建造的、令人畏惧的“超人级”机器的监管尝试。根据人工智能行业的说法，我们更应该担心一个虚构的机器之神，而不是这些数据中心加剧的气候灾难、居住在它们附近的居民所患的哮喘病、由公众补贴而不断上涨的电费，以及被调去用于冷却的水资源。

我们深知不应基于营销宣传做出决策，也不应向企业施压要求快速决策的要求妥协。明智的决策——无论是政策制定者还是社区——都需要时间来听取独立专家的意见，并对企业的说法进行背景化分析。这个充满炒作的热夏可能带来的最佳结果，是政策制定者和广大公众学会深呼吸，保持怀疑态度，并在下次此类炒作出现时认清其本质。

蒂米尼特·格布鲁（Timnit Gebru）是DAIR的执行主任，也是即将出版的新书《深度遗忘：一个技术理想主义者的激进化》的作者，该书目前已开放预购，定于2月16日出版。艾米莉·M·本德（Emily M. Bender）是华盛顿大学的语言学教授，也是《AI骗局》的合著者。

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 book Deep 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 .