The Foundation for American Innovation (FAI) today announces the addition of Dean Ball as Senior Fellow. He will focus on artificial intelligence policy, as well as developing novel governance models for emerging technologies.

Ball joins FAI after having served as Senior Policy Advisor for Artificial Intelligence and Emerging Technology in the White House Office of Science and Technology Policy (OSTP). He played a key role in drafting President Trump’s ambitious AI Action Plan, which drew widespread praise for its scope, rigor, and vision.

“We are thrilled to have Dean rejoin the team,” said Foundation for American Innovation Executive Director Zach Graves. “He’s a brilliant and singular talent, and we look forward to collaborating with him to advance FAI’s optimistic vision of the future, in which technology is aligned to serve human ends: promoting individual freedom, supporting strong institutions, advancing national security, and unleashing economic prosperity.”

Prior to his position with OSTP, Ball worked for the Hoover Institution, the Manhattan Institute, the Mercatus Center, and the Calvin Coolidge Presidential Foundation, among other positions.

“President Trump’s AI Action Plan represents the most ambitious U.S. technology policy agenda in decades,” said Ball. “After the professional honor of a lifetime serving in the administration, I’m looking forward to continuing my research and writing charting the frontier of AI policy at FAI.”

He serves on the Board of Directors of the Alexander Hamilton Institute and was selected as an Aspen Ideas Fellow. He previously served as Secretary, Treasurer, and trustee of the Scala Foundation in Princeton, New Jersey and on the Advisory Council of the Krach Institute for Tech Diplomacy at Purdue University. He is author of the prominent Substack Hyperdimensional.

The Foundation for American Innovation is a think tank that develops technology, talent, and ideas to support a better, freer, and more abundant future. Learn more at thefai.org.

The Coming of Agents
First thing’s first: eject the concept of a chatbot from your mind. Eject image generators, deepfakes, and the like. Eject social media algorithms. Eject the algorithm your insurance company uses to assess claims for fraud potential. I am not talking, especially, about any of those things.

Instead, I’m talking about agents. Simply put and in at least the near term, agents will be LLMs configured in such a way that they can plan, reason, and execute intellectual labor. They will be able to use, modify, and build software tools, obtain information from the internet, and communicate with both humans (using email, messaging apps, and chatbot interfaces) and with other agents. These abstract tasks do not constitute everything a knowledge worker does, but they constitute a very large fraction of what the average knowledge worker spends their day doing.

Agents are starting to work. They’re going to get much better. There are many reasons this is true, but the biggest one is the reinforcement learning-based approach OpenAI pioneered with their o1 models, and which every other player in the industry either has or is building. The most informative paper to read about how this broad approach works is DeepSeek’s r1 technical report.

During the SB 1047 debate, I noticed that there was a great deal of confusion—my own included—about liability. Why is it precisely that software seems, for the most part, to evade America’s famously capacious notions of liability? Why does America have such an expansive liability system in the first place? What is “reasonable care,” after all? Is AI, being software, free from liability exposure today unless an intrusive legislator decides to change the status quo (preview: the answer to this one is “no”)? How does liability for AI work today, and how should it work? It turned out that to answer those questions I had to trace the history of American liability from the late 19th century to the present day.

Answering the questions above has been a journey. This week and next, I’d like to tell you what I’ve found so far. This week’s essay will tell the story of how we got to where we are, a story that has fascinating parallels to current discussions about the need for liability in AI. Next week’s essay will deal with how the American liability system, unchecked, could subsume AI, and what I believe should be done.