Empire of AI: Exposing the Dark Side of AI's Ascent

Published Date : 13/07/2025 

Karen Hao's 'Empire of AI' delves into the hidden costs and power dynamics of the AI industry, challenging the optimistic narrative of technological progress. 

Most conversations we have around Artificial Intelligence (AI) today share a common theme: the technology’s potential to transform society, drive breakthroughs, and create a better world. The founding mission of OpenAI, the company that made AI a household name with ChatGPT in 2022, is “to ensure that artificial general intelligence — AI systems that are generally smarter than humans — benefits all of humanity.”

Behind this seemingly optimistic idea, tech reporter Karen Hao argues, lies the shadow of historical empires — a civilizing mission that promises modernity and progress while accumulating power and wealth through the exploitation of labor and resources. Hao, who has spent seven years covering AI at MIT Tech Review, The Wall Street Journal, and The Atlantic, was the first to profile OpenAI and extensively document the AI supply chain, taking the conversation beyond the promise of Silicon Valley’s innovation.

Her debut book, 'Empire of AI: Inside the Reckless Race for Total Domination,' provides an intimate picture of the rise of AI, the people, strategy, and money behind it. Unlike many business books, Hao's work stands out by providing a framework for understanding the dizzying AI boom and the conversations surrounding it. It joins the list of non-fiction on AI that brings nuance and much-needed skepticism to the subject while being acutely aware of its potential. In 2024, Arvind Narayanan and Sayash Kapoor from Princeton University wrote 'AI Snake Oil: What Artificial Intelligence Can Do, What It Can’t, and How to Tell the Difference,' which helps distinguish hype from reality. The same year, tech journalist Parmy Olson wrote 'Supremacy: AI, ChatGPT, and the Race That Will Change the World' about the unprecedented monopoly that OpenAI and Google’s AI research wing, DeepMind, currently have in the world.

Hao takes the conversation further by arguing that today's empires are not as violent as before due to 150 years of moral and social progress. However, she warns against the inherent empire-building nature of the AI industry. The bedrock of the AI industry — vast amounts of data from books, articles, and the internet — is a way of claiming people’s labor as fair use. One of the outcomes of AI development, automation, erodes workers' rights to demand fair treatment. The AI industry also relies heavily on outsourced labor, particularly in the global South.

For AI models to be consumer-friendly and profitable, they must not produce toxic content. AI companies rely on 'reinforcement learning from human feedback,' where workers chat with bots, upvoting or downvoting responses to guide them towards more helpful and engaging answers. They also employ content moderation filters to block toxic content before it reaches users. “This labor-intensive aspect of AI development is hidden because companies want consumers to perceive AI as a magical, cost-free technology,” Hao explains.

The monopoly extends to AI research paradigms. Currently, all major generative AI models use deep learning, mimicking the way neurons interact in the human brain to process vast amounts of data and predict responses. This approach requires significant computing capacity, leading to the construction of massive data centers that consume a lot of energy. OpenAI cracked this technique and doubled down on it: more data, more high-functioning and expensive GPUs, and more data centers to house them.

This more-is-more approach has 'choked' alternative forms of AI research, which have been explored since the 1950s. “There was research before that explored minimizing data for training models while achieving similar gains. Then Large Language Models and ChatGPT entered the picture. Research suddenly stopped. Two things happened: money flowed into transformers and generative AI, diverting funding from other explorations,” Hao says.

With the enormous externalities of environmental costs, data privacy issues, and labor exploitation, it is crucial to redirect some funds to explore new scientific frontiers that offer the same benefits of advanced AI without extraordinary costs. However, this might be harder than it seems. In her book, Hao traces how researchers, who were working outside major AI companies, are now financially affiliated with them. Funding primarily comes from tech companies or academic labs associated with them. “There’s a misconception among the public and policymakers that AI research remains guided by a pure scientific drive,” Hao says, adding that “the foundations of AI knowledge have been overtaken by profit motives.” 

Frequently Asked Questions (FAQS): 

Q: What is the main argument of Karen Hao's book 'Empire of AI'?

A: The main argument of Karen Hao's book is that the AI industry has a hidden, empire-building nature, where the promise of modernity and progress masks the exploitation of labor and resources, much like historical empires.

Q: How does the AI industry exploit labor, according to Hao?

A: The AI industry exploits labor by using vast amounts of data as fair use, automating processes that erode workers' rights, and relying on outsourced labor, particularly in the global South, for content moderation and model training.

Q: What is 'reinforcement learning from human feedback' in the context of AI models?

A: 'Reinforcement learning from human feedback' is a process where workers chat with AI bots, upvoting or downvoting responses to guide the AI towards more helpful and engaging answers, ensuring the models are consumer-friendly and profitable.

Q: What are the environmental and social costs of the AI industry that Hao highlights?

A: Hao highlights the environmental costs of massive data centers that consume a lot of energy and the social costs of data privacy issues and labor exploitation, particularly in the global South.

Q: What does Hao suggest should be done to address the issues in the AI industry?

A: Hao suggests redirecting some funds to explore new scientific frontiers that offer the same benefits of advanced AI without the extraordinary costs and externalities, and addressing the profit-driven motives that have overtaken AI research. 

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