tl;dr -Empire of AI is not the definitive chronicle of the genAI revolution or the sama drama at OpenAI. It is, instead, a cautionary example illustrating how ideological zeal ruins what could have otherwise been a significant journalistic venture.
Karen Hao’s Empire of AI aspires to be an expansive exposé of one of the most influential and enigmatic companies in the tech world. With its dramatic subtitle, the book promises a deep dive into the dreams and nightmares wrought by OpenAI under the leadership of Sam Altman. Yet, while Hao succeeds in marshaling an impressive quantity of interviews (300+ from 260 individuals) and experience (~7 years of reporting on the AI sector), the book ultimately suffers from a tendentious slant, an unwarranted contempt for the technology itself, namely the fervor for AGI, and a frustrating superficiality in its treatment of the internal dynamics and culture of OpenAI (One of the few reasons anyone would pick this book up would be to learn about why sama was briefly fired and re-hired as CEO).
The book's principal flaw lies in Hao’s persistent framing of OpenAI as an almost unambiguously self-serving, exploitative, and reckless empire masquerading as a public-spirited research lab. While directing skepticism at tech goliaths is reasonable, Hao’s argument relies on insinuation, which can often border on a sardonic or reproving tone, rather than rigorous and honest analysis. Whether a reader is persuaded by Hao will depend wholly on whether they share Hao's professed worldview (a popular understanding of academic post-colonialism) rather than the facts presented. In Hao's view, the three great sins of the AI industry are believing in scaling laws (a belief that justifies the high capital and energy costs associated with training LLMs), scraping copyrighted training data from the internet without paying royalties (to what extent this actually occurred is not well-researched in this book either; the evidence is anecdotal) and relying on cheap labor from the Third World to assist with data annotation and the fine-tuning of their models, a process referred to as reinforcement learning from human feedback (RLHF).
Hao's hostility to AI as a technology appears largely motivated by the idea that AI tech is the frontier of 21st century colonialism, where Western powers exploit and oppress the Global South to enrich themselves. Whether this idea makes any sense at all is never examined. Instead, it is simply something Hao assumes to be the case, and she doesn't let pesky facts get in the way of highlighting the supposed evils of our current tech companies in our current political economy. And she expects us to be enraged by the responses of OpenAI execs when they're confronted by her about her concerns about the ethical, environmental, or economic costs of developing AGI. She makes so much of the apparent paradox behind the impassioned pursuit of a technology that supposedly presents an existential risk to humanity. But is it really surprising that autists reared on science fiction believe AI has millenarian stakes? To anyone with a broader perspective on the history of technological innovation, the stakes of AI, while still very important, appear much more pedestrian.
This book also promises to provide some devastating insight into Sam Altman, but there is just no there there. Spending so much time on Ann Altman, for instance, was gauche. Hao's depiction of Sam Altman vacillates between that of a scheming Machiavellian and a hapless idealist overwhelmed by the demands of his many ventures and immense responsibility. This is at once a contradictory and thin portrait of Altman. The same takeaways wouldn't be that hard to gather by simply absorbing some of the ambient conversation about OpenAI on the internet (e.g. any AI-related podcast) and reading sama's tweets. The big failure here is that there are really no actual new insights into Altman's brief removal from his CEO position in November 2023, which still appears to be the result of incompetent bumbling from AI doomers, specifically Ilya Sutskever.
Hao's treatment of AI technology itself is disappointingly shallow. Despite covering one of the most technically complex and fast-evolving domains in contemporary science, Empire of AI rarely rises above the most surface-level exposition. Apart from some absolute basics about neural networks, there is scant effort to explain how transformer architectures work, what distinguishes frontier models from earlier iterations, or why scaling laws matter. Additionally, there is no real survey of the history of advancement in AI (Hinton, LeCunn, Minsky, McCarthy, Newell, etc - some get passing mentions at most). In fact, Hao dismisses much of the sophistication and complexity of the technology by saying once the pieces and parts of it are understood that it all seems quaint (fluency illusion). This leaves the reader without a coherent grasp of what exactly OpenAI has achieved or how it differs from competitors like DeepMind, Anthropic (she does describe why Anthropic exists!), Meta, or others. In place of analytical rigor, Hao often defaults to anecdote or second-hand metaphor, which may entertain but does little to enlighten.
Perhaps the most unforgivable aspect of the book is its failure to offer a substantive reconstruction of OpenAI’s internal debates about foundation genAI and business model questions. Hao just wants to tar OpenAI figures as weirdo techno-utopians or money-grubbing tech bros, whichever is most convenient for whatever point she wants to make at that moment. While the reporting frequently alludes to power struggles, ideological rifts, and a revolving door of talent, these conflicts are rendered in vague terms. Many of the figures are thinly sketched apart from, perhaps, Sutskever and Brockman. Hao doesn't give the reader a clear sense of the intellectual stakes in these disputes, nor does she convincingly differentiate between personality clashes and genuine philosophical disagreements. The result is a fatally slanted narrative of compiled grievances rather than a deep, thorough investigation of a central player in genAI.
Empire of AI is both overlong and flawed as a journalistic venture, while also tossing aside any pretense of journalistic objectivity in order to insert a bizarre polemical framing. Any reader looking for a nuanced, rigorous account of the latest in the AI sector or a history of OpenAI as a non-profit entity/company or its leader will come away disappointed. For those already inclined to view Silicon Valley with suspicion, Hao offers confirmation and comfort in the juvenile form of righteous indignation and smug superiority.