Note to readers: A version of this post will be submitted to our Board of Supervisors as a formal letter, as well as to a local news outlet. We'll see if it even makes a ripple.
Even those wary of AI agree that it can do clever work. I use it regularly with students to shape their writing ethically and to design assignments. But can the industry make enough money to continue its progress? A great deal hinges on that answer, including development on the western border of the Richmond Metro Area.
A proposal before Goochland’s Board of Supervisors would allow data centers, perhaps powered by small nuclear reactors, to be built along the Route 288 corridor. Even without considering the environmental hazards, as one who researches the industry, I’ve found economic risks of rushing off quickly to join this AI gold-rush.
CEOs constantly make utopian claims about AI's future, but numbers cloud those predictions. Subscriptions such as mine meant under $2.5 billion in revenue for ChatGPT maker OpenAI in the second half of 2024, according to sources that include The Wall Street Journal and The New York Times. The rest came from venture capital or circular investing, such as Nvidia's and Microsoft's massive stakes in OpenAI.
The firm estimates that building out its data centers would cost $400 billion. For such ambitious plans, companies need a lot more revenue to balance their books. An "AI Bubble" may be inflating, as several economic journalists have warned. Writing for The Atlantic, Rogé Karma notes that “In the first half of this year, business spending on AI added more to GDP growth than all consumer spending combined.” A crash in the AI sector would deal devastating blows to the economy, with local effects when superfluous data centers go dark.
For his part, OpenAI’s CEO Sam Altman focuses on big ideas that seem straight from science fiction. He writes that humans and computers will become one form of life soon, which he calls “The Merge.” I'll quote from his blog, "unless we destroy ourselves first, superhuman AI is going to happen, genetic enhancement is going to happen, and brain-machine interfaces are going to happen." Not all of us would call such things progress, but history shows us that technological breakthroughs take time and a lot of money. Quiet supersonic airliners and nuclear fusion plants have inched closer to reality, over decades.
It well may take that long for AI data centers to not increase ratepayers’ electric bills. We’ve seen that already from existing data centers in the Commonwealth. Before we consign so much open land to data centers locally, let’s consider what experts in the field who are not CEOs or marketers have to say.
A robotics researcher, hired away from my university by Google, insisted to me that human-level thinking cannot be engineered; at best we might imperfectly simulate it, at great expense via a "brute force" computing method run in huge data centers. I recently noted in class how we might improve that, given faster computing using fewer chips, following what’s called Moore's Law. A student challenged me, claiming that silicon-based chips have not enjoyed the leaps in power and speed we expected annually up through the early 2000s.
Several academic papers I looked up support that idea. Without new types of microprocessors or exotic quantum computing, we are stuck with today’s data centers. Concurrently, our AI models remain far from perfect. Alex Reisner of The Atlantic, as well as academic researchers, found developers fudging benchmark tests that measure AI's smarts. They give the software test questions in advance, a tactic beloved by college students for many years. When AI is faces novel tasks, however, it scores far lower. Rogé Karma’s investigative work bears this out; productivity of coders dropped by 20% when working with AI, as they spent more time correcting mistakes.
Other Bubbles have popped with local consequences. A few years ago, I addressed The Board of Supervisors, whose agenda that night included motions to increase suburban-style growth in the east end of the county. I opposed this for many reasons, but one stood out: we had made zoning changes before based on empty promises, when we developed an office park called West Creek for an anchor client, Motorola. Their semiconductor plant would, in theory, have provided many hundreds of jobs.
My late father-in-law, Edward Nuckols, had addressed the Supervisors in the 90s. He was a respected master mechanic and businessman with deep ties to the community; his auto shop, unlike Motorola, had been in operation here for decades. Ed warned that big companies change their minds.
So it came to pass: Motorola backed out of their promises and Goochland was left with over $100 million in debt. One Supervisor reminded me that the county had little choice but to search for other revenue streams to repay that sum. While a fair counterargument, it does not seem we have learned much. Even if Altman and other CEOs are right, such men have no ties to any locality save the posthuman utopias they dream of inhabiting. $100 million of debt means nothing to them.
I’d love to see cheaper, more sustainable AI as a partner in our work. Today's models such as ChatGPT 5, Anthropic Claude, as well as lesser known but powerful tools such as NotebookLM or Research Rabbit, greatly help my students. We engineer prompts to find credible sources that are not hallucinated, we check human-created work for accuracy and voice, we write scripts for podcasts that AI converts to broadcast-quality audio. Plagiarism, the bugaboo of academic AI, concerns me less than does helping my students gain skills for workplaces slowly adopting AI.
My classes emphasize critical thinking when working with AI. So I'll ask Goochland's Board of Supervisors to do some critical thinking and research not influenced by the hype of Silicon Valley's billionaires. Altman claims intelligence will soon be "too cheap to meter." Older folks will recall that fable about electric bills, one made in the 1950s and 60s.
Otherwise, we could be left with more debt and large, empty buildings crumbling in the rain along 288.
Creative Commons Image: Bioethics.com
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