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Articles by Yonathan Arbel
AI, China, AI race
AIThe AI Race Isn’t Real Published 25 May 2026 The notion of an AI race against China is at the center of the administration’s deregulatory turn. In Congress and the private sector, an AI race against China is also frequently invoked as a reason to favor light regulation of domestic AI companies, even in the presence of serious threat models. But the idea of an AI race that must be won at all costs is wrong. It is fundamentally flawed as a descriptive matter and normatively defective.
The AI Race Isn’t Real
As one of his first acts in office, President Trump rescinded President Biden’s executive order imposing basic safety reporting requirements on artificial intelligence (AI) companies. A few days later, Trump issued an executive order directing federal officials to change existing policies that might inhibit AI development.
Broadband Breakfast on July 23, 2025 - The Politics of Artificial Intelligence
Artificial Intelligence is now also becoming a subject of political division. The politics of AI is akin to the politics of information technology, 20 years ago: Everyone says they want the advances promised by AI. But there are clearly tensions, as demonstrated by a proposed 10-year moratorium on state laws, stripped at the last minute from the budget bill. This Broadband Live segment will consider questions about who speaks for AI: Will states charge forward?
The readability of contracts: Big data analysis
REFERENCES Agency for Healthcare Research & Quality. (2008). Saying it clearly. TalkingQuality Project. (2016). The dignity of commerce. University of Chicago Press. (1960). Let's not oversimplify legal language. Rocky Mountain Law Review, 32, 358–372. American News Pathways Project. (2020). Pew Research Center. https://www.pewresearch.org/pathways-2020/MAINSOPOL_GROUPS/race_ethnicity/us_adults , , , , , & (2020). Privacy policies over time: Curation and analysis of a million-document dataset.
Lawfare Daily: Chinny Sharma and Yonathan Arbel on the Promises and Perils of Open-Source AI
Yonathan Arbel is the Silver Associate Professor University of Alabama School of Law and Director of the AI Studies Initiative. Kevin Frazier is an Assistant Professor at St. Thomas University College of Law. He is writing for Lawfare as a Tarbell Fellow. Chinmayi Sharma is an Associate Professor at Fordham Law School. Her research and teaching focus on internet governance, platform accountability, cybersecurity, and computer crime/criminal procedure.
The False Choice in the Debate Over Artificial Intelligence Regulation
Since the release of ChatGPT3.5 roughly a year and a half ago, the promises and perils of artificial intelligence (AI) have captured the world’s attention. We are currently in the midst of a vigorous debate about which AI harms to focus on—those occurring now or more speculative harms that might happen in the future. This argument started on social media but has now reached major scientific journals and prominent news sources. It increasingly threatens to undermine calls for robust AI governance.
Open Questions in Law and AI Safety: An Emerging Research Agenda
Artificial intelligence (AI) is a transformative technology. Like previous technological advances, AI promises to improve socioeconomic conditions, while also presenting substantial risks to individuals, communities, and society at large. But compared with most technologies of the past, frontier AI systems may soon have substantially greater capabilities and thus present substantially larger risks.
Truth Bounties: A Market Solution to Fake News
North Carolina Law Review, Oct 2024 By Yonathan A. Arbel and Michael D. Gilbert, Published on 01/01/24 This is a preview of a remote PDF: https://scholarship.law.unc.edu/cgi/viewcontent.cgi?article=6960&context=nclr Yonathan A. Arbel, Michael D. Gilbert. , North Carolina Law Review, 2024, pp. 509, Volume 102, Issue 2,
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