Welcome!
By now its banal to say that Artificial Intelligence (AI) is having something of a moment. In 2022, we saw a near constant stream of back-to-back AI innovation, and in many ways the long-prophesized possibilities of AI seemed to burst into (admittedly wonky) practical realities. With new, potentially transformative technology comes boundless questions. Inevitably, public policy must follow.
The purpose of this Substack is to match policy thought with AI’s innovative speed. Evidence suggests federal policymakers are (understandably) already overwhelmed and quickly falling behind. To ease this burden they will require timely, external thought to provide analysis and options. This tech and the questions that follow are changing in real time, and I hope this newsletter can help public policy keep pace.
“AI policy” is an emerging field without well-established, time-tested thought. The second purpose of this newsletter is to put novel out ideas to be critiqued, built on, and refined. Topics this complex can only benefit from crowdsourcing solutions.
What is the Goal?
Today, most AI policy frameworks are rooted in a heavy-handed, regulation-centric approach. Meanwhile classical liberalism offers only partially sketched-out ideas. Under existing thought, it is unclear how a classically liberal approach might handle AI’s biggest worries. This is a problem. Unless a pragmatic liberally-minded framework has a seat at the table, policy will naturally default to alternatives. I want to use this space to explore and define what classically liberal AI policy might look like. Inherent to this challenge will be confronting certain tensions and edge cases within liberalism. How do market-based democracies deal with authoritarian AI innovation? How do we handle the tensions between data privacy and innovation needs? Most questions will not have simple answers.
Emerging from this is a natural secondary goal: to explore the government’s current and historical relationship with AI. Who’s In charge? What laws exist? AI has been a field since the 50s – what is the government’s track record? While AI policy may be a work-in-progress it’s not non-existent. I’d like to investigate this messy structural policy reality.
Why Digital Spirits?
In 1936, the preeminent economist John Maynard Keynes used the term “animal spirits” to describe a supposed base irrationality at the heart of economics. Many view AI with similar uncertainty, worried these black boxes might hide an irrational, and potentially harmful digital spirit. Keynesian remedies for animal spirits called for a hard-edged regulatory approach; many believe we need the same to tame these frightening digital spirits.
AI poses challenges to be sure, but these issues are not likely to be solved by the easy answers regulators demand. I prefer an ever skeptical, yet optimistic view. Entering the AI age will be rocky, but if we set a proper institutional table, and trust in human capabilities, we can ensure AI progress brings innumerable benefits to people and society.
As AI matures my spirits remain ever high.