EA - A California Effect for Artificial Intelligence by henryj

Link to original articleWelcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: A California Effect for Artificial Intelligence, published by henryj on September 9, 2022 on The Effective Altruism Forum. I just finished writing a 50-page document exploring a few ways that the State of California could regulate AI with the goal of producing a de facto California Effect. You can read the whole thing as a Google doc here, as a pdf here, or as a webpage here, or you can read the summary and a few key takeaways below. I'm also including some thoughts on my theory of impact and on opportunities for future research. I built off work by Anu Bradford, as well as a recent GovAI paper by Charlotte Siegmann and Markus Anderljung. This project was mentored by Cullen O'Keefe. I did this research through an existential risk summer research fellowship at the University of Chicago — thank you Zack Rudolph and Isabella Duan for organizing it! Abstract The California Effect occurs when companies adhere to California regulations even outside California’s borders because of a combination of California’s large market, its capacity to successfully regulate, its preference for stringent standards, and the difficulty of dividing the regulatory target or moving beyond California’s jurisdiction. In this paper, I look into three ways in which California could regulate artificial intelligence and ask whether each would produce a de facto California Effect. I find it likely (~80%) that regulating training data through data privacy would produce a California Effect. I find it unlikely (~20%) that regulation based on the number of floating-point operations needed to train a model would produce a California Effect. Finally, I find it likely (~80%) that risk-based regulation like that proposed by the European Union would produce a California Effect. If this seems interesting, please give the full paper a look. There's a more-detailed 1.5-page executive summary, and then (of course) the document itself. Key Takeaways The California Effect is a powerful force-multiplier that lets you have federal-level impact for the low(er) price of state-level effort. There are ways to regulate AI which I argue would produce a California Effect. State government in general and California's government specifically are undervalued by EAs. I believe that EAs interested in politics, structural change, regulation, animal welfare, preventing pandemics, etc, could in some cases have bigger and/or more immediate impacts on a state level than on a federal level. There are still plenty of opportunity for further research. Theory of Impact My hope — and ultimate theory of impact — is that this paper will help policymakers make better-informed decisions about future AI regulations. I hope to encourage those who believe in regulating artificial intelligence to give more attention to the State of California. At the very least, I hope that people with a broader reach than I have in the AI Governance space will read and even build off this work. I hope I can raise their awareness of the California Effect and ensure that they recognize the disproportionate impact it can have in the race to keep artificial intelligence safe. Opportunities for further research Before I list my own thoughts, I will direct readers to the list of further research opportunities that Charlotte Siegmann and Markus Anderljung collected in an announcement for their report on the potential Brussels Effect of the EU AI Act. I’m personally choosing to highlight their fourth and sixth bullet points, which I think would be especially effective (the latter even more so): “Empirical work tracking the extent to which there is likely to be a Brussels Effect. Most of the research on regulatory diffusion focuses on cases where diffusion has already happened. It seems interesting to instead look for leading indicators of regulatory diffusion. For exam...