Empire of AI is an informative and a chilling read by the AI expert and investigative journalist Karen Hao. The book dives into the inside story of OpenAI and Sam Altman long before ChatGPT was a thing. OpenAI started as a nonprofit organization in the modern, contemporary theater that is Silicon Valley with Sam Altman and Elon Musk (who left not soon after) convinced that they were working towards building safe AI, as opposed to rogue AI, which was yet an imaginary threat at best and a collective hallucination at worst. They were convinced that it was just a matter of time before it happened and that they had to control the AI space and be the paragon of what good AI looks like.
A core theme of this book is belief. Belief in deep learning. Belief in AGI. Self belief. How belief mobilizes and incites. Who is and isn’t to be believed.
The author narrates the story of the company and the many characters involved in getting us to where we are today. With sharp observations and opinions, the author shares with us the conversations she’s had with OpenAI employees and others working in the industry. This book confirmed my suspicions that nobody knows what they are doing and yet I was gobsmacked by the sheer on va voir type of energy from the top brass. In one brief recounting, one of them is performing a fire ritual with a wooden effigy.
ChatGPT’s success was surprising to the OpenAI team since it was a basic version of what they were using internally. Their research was all about proper AI (not just glorified chat bots) and”AGI”, which mind you, nobody knows what that means, but the execs believed that it could be done. So the teams dabbled in robotics, video games, and probably other research. With ChatGPT blowing up, the company was forced to move compute resources from research to this rising star.
Now comes the classic supply and demand issue. They were forced to add more compute power to it and keep bettering it to meet requirements so this cash cow keeps generating revenue, to get funding from Microsoft for chips, to keep competitors (Google, Meta) at bay while wading through internal politics. The internal politics largely included the Safety team not having enough time and resources to conduct proper tests or follow proper procedures. Sam Altman, we learn, is famous for being charming and convincing, and telling people exactly what they want to hear, while keeping his motivations concealed. The Amodei siblings who were initially heading the Safety team were completely disillusioned and left OpenAI to form their own company, Anthropic.
OpenAI continued to struggle and succeed simultaneously. More importantly, the author shows us the degree of fanaticism and delusion of some of these execs at the highest levels, the ones who are responsible for making decisions that are affecting millions of people. The things they say and believe has me questioning the reality we live in. As if I don’t question it enough already. It seems to me as though they live in a bubble of their own making and a world so far removed from the ground.
Another point that the author raises is the lack of independent research. Graduate and research students often join the tech companies to make a living. Their focus is then only on what the companies want, on what will bring profits. This leads us to wonder whether there can be alternative solutions and methods of implementing AI that we are missing out on because of the capitalist monopoly games.
In stark contrast to the shiny Silicon Valley offices, the author walks us through small cities in Kenya and Chile, where people are forced to do data annotation for cents, often being exposed to harmful scenes, where people are forced to eke out a living mining raw materials with little benefits, where companies like Google and Microsoft want to build data centers so they can drink up the water resources that the residents struggle to get. In general, the companies target those countries with unstable economics so the people are willing to work for pennies. In addition to the exploitation, they increase pollution of all elements in these areas. That’s why it’s laughable when they talk about solving climate change with AI. These are just pretenses, they never cared about climate change. The pretenses will drop as soon as they have what they want.
All is not lost as activists continue to fight the giants with what they have. Some have seen success but the problem continues to exist. Their accounts are eye-opening and heart-warming, showing us a glimpse into their lives, their work, and their motivations, inspiring us readers to collectively become aware and take actions against the crimes of the tech companies.
The author ends with possible frameworks that can help build a better tech future that benefits all. This includes redistributing knowledge, resources, and influence.
Whether or not you work in the tech industry or use AI at all, I’d recommend reading this book. I’d especially recommend this book if you are working in the tech industry and are caught up in the AI race. Reading this book would be the equivalent of touching some grass. The issues highlighted in this book are not only specific to the current AI industry, these have been long-standing problems as the tech industry upholds and propagates exploitation and colonization. And those of us in the tech industry must decide just where we are directing our energy. In my opinion, the current narratives that companies like OpenAI push about AI taking all jobs and going rogue and being harmful to humanity are problems of their own making. They talk about an imaginary Universal Basic Income while people continue to suffer, yesterday, today, and tomorrow. Their vision of AI is unoriginal and unsustainable.
Bottom line, there’s no doubt that AI tech and the computational power is great and valid cases exist where this power can be hugely beneficial. But any benefit at the cost of human lives is no benefit at all. We cannot continue to exist the way we have been, and we have much more power and influence than we are led to believe.
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