Don’t be fooled by this summer of AI hype
Don’t be fooled by this summer of AI hype
别被这个“AI炒作之夏”给骗了
It’s been a busy few months for AI hype. At the end of April, Anthropic claimed that its model Claude Mythos is better at finding software vulnerabilities than most security experts. Then we had the OpenAI–Hugging Face hacking incident, after which Anthropic (proudly) and Meta (reluctantly) disclosed similar incidents involving their models. This was followed by Anthropic’s claim that one of its models had made a mathematical breakthrough; soon OpenAI claimed a mathematical breakthrough of its own. Most recently, Anthropic engineer Jacob Coxon went viral announcing his departure from the company, claiming that it and OpenAI are “racing straight towards self-improving superintelligence and gambling with our lives.”
过去几个月，AI 炒作可谓甚嚣尘上。四月底，Anthropic 声称其模型 Claude Mythos 在发现软件漏洞方面比大多数安全专家更出色。随后发生了 OpenAI 与 Hugging Face 的黑客事件，此后 Anthropic（自豪地）和 Meta（勉强地）披露了涉及其模型的类似事件。紧接着，Anthropic 声称其模型取得了数学突破；不久后，OpenAI 也宣称自己取得了数学突破。最近，Anthropic 工程师 Jacob Coxon 在宣布离职时引发热议，他声称该公司和 OpenAI 正“直奔自我进化的超级智能而去，并拿我们的生命在赌博”。
Each of these events was mostly covered breathlessly by the press, often repeating the companies’ anthropomorphizing framings—which are designed to portray their software is not only powerful but incipient “artificial general intelligence.” So what is really going on? Are we witnessing a massive, civilization-changing set of technological breakthroughs, or is this marketing?
媒体对这些事件大多进行了不遗余力的报道，并经常重复这些公司拟人化的叙事框架——其目的在于将软件描绘成不仅功能强大，而且是初具雏形的“通用人工智能”（AGI）。那么，真相究竟如何？我们是在见证一系列改变文明的重大技术突破，还是仅仅在看一场营销秀？
In all these incidents, massive fanfare from the companies (presented as mea culpas in illicit hacking cases) is accompanied by intense press coverage. Once there is time for experts in the relevant fields to examine what happened, a very different story emerges, but one that gets less media attention. Regarding the “hacking” incidents, cybersecurity experts say the story is more about OpenAI’s negligence and failure to adopt basic, established security practices than about “models gone rogue” or “AI agents creating civilizations.”
在所有这些事件中，公司大张旗鼓的宣传（在非法黑客攻击案例中表现为“认错”）总是伴随着密集的媒体报道。一旦相关领域的专家有时间审视事件真相，就会出现截然不同的叙事，但这些真相往往得到的媒体关注度更少。关于“黑客”事件，网络安全专家指出，这更多是关于 OpenAI 的疏忽以及未能采取基本的、既定的安全实践，而不是所谓的“模型失控”或“AI 代理创造文明”。
As for the mathematical results, mathematicians who were initially “stunned” by OpenAI’s press release saying that its latest chatbot, Astra, solved problems that “have been open and seen no progress on the main result for at least a decade”—but they later realized that the results weren’t as “novel as first appeared.” Since then, mathematicians have accused the company of research misconduct and plagiarism, and they’ve reiterated that Astra didn’t make a “profound intellectual leap.” Just weeks later, OpenAI claimed its own mathematical breakthrough. Two days before, Tristan Buckmaster, a math professor at New York University’s Courant Institute, published a bombshell statement suggesting that OpenAI had stolen other people’s work and improperly attributed it.
至于数学成果，数学家们最初被 OpenAI 的新闻稿“震惊”了，该稿称其最新的聊天机器人 Astra 解决了“至少十年没有取得实质性进展的开放性问题”——但他们后来意识到，这些结果并不像“最初看起来那样新颖”。此后，数学家们指责该公司存在学术不端和剽窃行为，并重申 Astra 并没有实现“深刻的智力飞跃”。仅仅几周后，OpenAI 又声称取得了自己的数学突破。而在两天前，纽约大学柯朗数学科学研究所的数学教授 Tristan Buckmaster 发表了一份重磅声明，暗示 OpenAI 窃取了他人的工作成果并进行了不当署名。
Claims of incipient, dangerous superintelligence are not based in good scientific or engineering practice. Rather, they are narratives based in ideologies of transhumanism, eugenics, and wishful thinking about imagined future digital humans. It’s worth thinking about why there is so much attention on computer programming and math as fields in which to apply large language models and related technology. Not only are they often elevated as the pinnacle of human intellectual achievement, but they involve problems where answers, once suggested, can be verified. The former property helps AI hype mongers sell the idea that they are building everything machines. The latter makes math and coding problems easier to tune systems for, since system output (sequences of likely words or pieces of computer code) can be evaluated without having to pay data workers to look at and annotate each one.
关于“初具雏形且危险的超级智能”的说法，并非基于严谨的科学或工程实践。相反，这些叙事植根于超人类主义、优生学以及对未来虚构数字人类的一厢情愿。值得思考的是，为什么计算机编程和数学领域在应用大语言模型及相关技术时会受到如此多的关注。它们不仅常被推崇为人类智力成就的巅峰，而且涉及的问题一旦给出答案，便可进行验证。前者有助于 AI 炒作者兜售他们正在构建“万能机器”的理念；后者则使数学和编程问题更容易进行系统调优，因为系统输出（概率性的词汇序列或代码片段）无需支付数据标注员费用即可进行评估。
Mathematicians in particular have warned against corporations using their field in this way. A statement signed by hundreds of them says there is “currently a strong commercial incentive on the part of the technology industry to overstate the capabilities of their products” and asks policymakers to “consult with experts, including mathematicians, in forming policy decisions rather than relying on press releases or popular reporting of mathematical results.” We echo this call and note that the illusion of speed and urgency promulgated by the tech companies is also a ploy to misdirect both policymakers and the public.
数学家们特别警告企业不要以这种方式利用他们的领域。数百名数学家签署的一份声明指出，“目前科技行业存在强烈的商业动机去夸大其产品的能力”，并要求政策制定者“在制定政策决策时咨询包括数学家在内的专家，而不是依赖新闻稿或对数学成果的大众化报道”。我们响应这一呼吁，并指出科技公司所宣扬的“速度与紧迫感”的幻觉，也是误导政策制定者和公众的一种策略。
Unfortunately, it sometimes works, such as with Senator Bernie Sanders’s well-meaning but ultimately misguided proposed legislation to prevent the development of “artificial superintelligence.” Describing them as “superintelligence” or “rogue models” ascribes agency to products rather than to the companies building them. This framing helps 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.
遗憾的是，这种策略有时确实奏效，例如参议员伯尼·桑德斯（Bernie Sanders）出于好意但最终被误导的立法提案，旨在防止“人工智能超级智能”的发展。将它们描述为“超级智能”或“失控模型”，是将主体性赋予了产品，而不是构建这些产品的公司。这种框架将这些公司的产品包装为“超人类”，同时也帮助这些公司逃避其行为的责任。OpenAI 本应因制造黑客攻击另一家公司的恶意软件而受到起诉，但新闻稿、新闻媒体、媒体名人和立法者却在谈论“失控模型”，仿佛它们是自主行动的一样。
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.
研究人员本应被质询其公司剽窃学术成果或未经同意使用客户数据训练模型的习惯，但公众的想象力却被转移到了对未来虚构的超级智能机器到来的恐惧上。AI 行业甚至暗示，两党普遍支持的反对数据中心的行动是一种“干扰”，阻碍了对这些公司正在构建的、即将到来的、可怕的“超人类”机器进行监管的尝试。按照 AI 行业的说法，我们应该担心的是虚构的机器神，而不是这些数据中心加剧的气候灾难、居住在附近的人们所遭受的哮喘、补贴这些中心的大众不断上涨的电费，或是被挪用于冷却它们的水资源。
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.
我们深知，不应基于营销做出决策，更不应屈服于企业压力而仓促行事。政策制定者和社区的明智决策，需要时间去倾听独立专家的意见，并对企业的声明进行背景分析。这个“炒作之夏”能带来的最好结果，就是政策制定者和广大公众学会深呼吸，保持怀疑态度，并在下一次炒作来临时，认清其本质。
Timnit Gebru is executive director of DAIR and author of the forthcoming book.
Timnit Gebru 是 DAIR 的执行董事，也是即将出版的新书的作者。