Artificial Intelligence

Responding to Mark Lemley and Jacob Noti-Victor, Shishene Jing argues that licensing deals struck by incumbent artificial intelligence firms with content owners will not disadvantage smaller AI rivals. Even if such deals establish a legal precedent requiring licenses, content owners have little incentive to actually sue small, cash-poor AI startups, making the precedent toothless in practice.

In a new working paper, Benjamin Verschuere and Angus Cameron argue that the wide dispersion in economists' forecasts for the impact of artificial intelligence on the economy stems from two gaps. The first is that estimates for growth, jobs, and prices are each built in isolation, with no single framework to reconcile them. The second is that models fixate on AI’s current capabilities, rather than on how fast it spreads and how much of a given job it can eventually reach. The authors build a unified framework that predicts roughly $2 trillion in long-run output gains, the loss of about 20 million American jobs, and falling prices.

Investors have poured billions into using artificial intelligence to discover new drugs, and 2026 is the first real test of whether AI-designed medicines actually helps patients. The boom has genuinely transformed the search for molecules — but that was never the costly, failure-prone part of making a medicine, and there AI has so far had little to add. Capital, and the public subsidies have not yet priced the difference, writes Michael A. Santoro.

Microsoft CEO Satya Nadella’s argument that businesses need to be able to easily switch between artificial intelligence models is correct but elides the fact,...

The competitiveness of the artificial intelligence market at first glance masks how investment arrangements and partnerships between the largest players risks undermining their incentives to compete. Regulators must continue to monitor these arrangements for anticompetitive effects, writes Shishene Jing.

In new research, Christos Makridis and Andrew Johnston find that industries exposed to generative AI are seeing an increase in production, employment, and wages. However, the majority of AI-driven revenue growth is channelled back to capital as profits, rather than to workers.

An accounting rule introduced by the Financial Accounting Standards Board in 2016 was designed to address a flaw in the previous regime that contributed to the 2008 Financial Crisis. However, this same rule is enabling the circuit of investments that flows from Big Tech companies to artificial intelligence startups, whose increased valuation from these investments increases the value of the Big Tech companies, which they can then reinvest in the AI startups. The risk is an AI bubble that, if it pops, will also blow up Americans’ savings, writes Hera Hyeonseo Lee.

Artificial intelligence coding agents provide enormous value to consumers for very low fees. But the market is quickly shrinking with Anthropic in the lead. Only competition, and requiring Big Tech to build agents rather than buy them, will continue to let AI’s value flow to consumers. As such, the courts should ban SpaceX’s recently proposed acquisition of Cursor, writes Ketan Ahuja.

Artificial intelligence will change the market for economic consultants, likely reducing overall demand and shifting workers to current clients’ in-house units. However, both consulting firms and clients are still studying how to deploy AI, and there may yet be new opportunities for consultants as AI changes the broader economy, write Mona Birjandi and Mery Zadeh.

Anthropic has formed an exclusive artificial intelligence consortium to use its general purpose artificial intelligence model, Claude Mythos, to identify and fix vulnerabilities in critical internet and digital infrastructure. Madhavi Singh warns this consortium, called Project Glasswing, could contravene antitrust law and argues for regulatory oversight to ensure that it does not become a front for an illegal cartel.