Artificial Intelligence

Eli Orbach examines how the United States’s decentralized education system impedes the diffusion and adoption of generative artificial intelligence in K-12 schools. Slow and uneven diffusion will exacerbate current socioeconomic inequalities, harm students’ future work prospects, and impede macroeconomic growth and productivity.

Crypto assets and social media are changing how finance operates. Uncertainty around the future of AI is affecting financial markets. Claudia Biancotti argues that regulators must expand their range of expertise and pursue a multidisciplinary approach to protecting society against the potential negative spillovers from these developments.

In new research, Filippo Lancieri, Laura Edelson, and Stefan Bechtold explore how the political economy of artificial intelligence regulation is shaped by the strategic behavior of governments, technology companies, and other agents.

Recent government wins against Big Tech demonstrate the prudence of proactively stopping consolidation in the emerging AI startup ecosystem to prevent harm to innovation and consumers. OpenAI’s recent acquisition of Windsurf raises these competition concerns. The antitrust agencies should block it.

The Federal Trade Commission’s case against Meta for monopolizing personal social media through its acquisitions of Instagram and WhatsApp serves as a warning of allowing Big Tech companies to acquire nascent competitors in the artificial intelligence market through quasi-mergers that dodge government scrutiny. Based on new research, Alexandros Kazimirov argues that antitrust agencies can look at a combination of circumstantial evidence, including market product proximity, price premiums and product discontinuation, to help adjust their approach to keep AI markets contestable, rather than trying to restore contestability ten years from now.

Rose Chan Loui explains the current controversy surrounding OpenAI’s decision to abandon its nonprofit status. To learn more about OpenAI’s proposed restructuring, what it means for the race to develop artificial general intelligence, and how it highlights the tricky legal concept of a nonprofit’s “purpose,” listen to Chan Loui’s recent appearance on Capitalisn’t.

The United States power grid is increasingly strained by the surging electricity demand driven by the AI boom. Efforts to modernize the power infrastructure are unlikely to keep pace with the rising demand in the coming years. Barak and Eli Orbach explore why competition in AI markets may create an electricity demand shock, examine the associated social costs, and offer several policy recommendations.

Johannes Fritz and Tommaso Giardini examine the state of AI rulemaking around the world and find that, despite global alignment on principles, execution at the national level diverges on three important metrics. The risk is fragmentation in AI as firms choose to exclude entire markets rather than navigate the intricacies of compliance in different regions.

Matt Perault writes that there is little indication that Big Tech investments in artificial intelligence startups are harming competition. In fact, the opposite is likely true. Antitrust regulators should instead focus their attention on the real threat to AI competition: rules and regulations that will make it harder for startups that to compete with large tech companies.

Artificial Intelligence (AI) is poised to permeate across different industry sectors, offering unprecedented opportunities alongside significant risks. Effective governance necessitates coordinated cross-border efforts to build institutional expertise, dispel misconceptions, foster innovation, and align global safety priorities. Advocating structured dialogue and a bottom-up approach, Oscar Borgogno and Alessandra Perrazzelli present a proposal which aims to avoid institutional redundancy and legal unpredictability for individuals and firms.