The Limits of Antitrust Remedies in the Google Search Case | TechPolicy.Press The decision revealed the fundamental limitation of antitrust as a way to structure markets in the public interest, writes Mark MacCarthy.

My thoughts on the remedies decision in the Google search case.
www.techpolicy.press/the-limits-o...

AI Companies Should be Liable for the Illegal Conduct of AI Chatbots | TechPolicy.Press Companies providing services that mimic those provided by people have to be responsible for the services they provide, writes Mark MacCarthy.

Chatbots are not people and should not be treated as such. But the companies providing services that mimic the services provided by people have to be responsible for the services they provide, writes Mark MacCarthy.

AI Companies Should be Liable for the Illegal Conduct of AI Chatbots | TechPolicy.Press Companies providing services that mimic those provided by people have to be responsible for the services they provide, writes Mark MacCarthy.

www.techpolicy.press/ai-companies...

Why AI demand for energy will continue to increase | Brookings Mark MacCarthy and David Klaus explain the projections for AI's energy use and considerations for regulatory policy.

Why AI demand for energy will continue to increase www.brookings.edu/articles/why...

Setting the standard of liability for self-driving cars | Brookings Mark MacCarthy discusses maintaining the traditional negligence product liability standard for self-driving cars.

Setting the standard of liability for self-driving cars www.brookings.edu/articles/set...

Are AI existential risks real—and what should we do about them? | Brookings Mark MacCarthy highlights the existential risks posed by AI while emphasizing the need to prioritize addressing its more immediate harms.

My latest Brookings post on AI issues. Are AI existential risks real—and what should we do about them? www.brookings.edu/articles/are...

Privacy protections in the Google search case Mark MacCarthy discusses the privacy considerations of the Justice Department's proposed data access remedy in a Google antitrust case.

Here's my latest from Brookings on the need for strong privacy protections in the Google search case

www.brookings.edu/articles/pri...

Do AI systems have moral status? Mark MacCarthy explores differing views on AI moral status as some companies begin promoting the idea of "AI welfare."

My latest Brookings commentary on whether AI systems have moral status. While the issue is too speculative to absorb resources now, policymakers need a clear-eyed assessment.
www.brookings.edu/articles/do-...

The Privacy Challenges of Emerging Personalized AI Services | TechPolicy.Press Mark MacCarthy examines how policymakers can address the privacy challenges of a world with personalized AI.

My latest from Tech Policy Press www.techpolicy.press/the-privacy-...

Copyright alone cannot protect the future of creative work Mark MacCarthy discusses challenges with the future of creative work and the current guidelines around AI-generated content.

Here's my latest tech policy commentary from Brookings on AI and copyright. www.brookings.edu/articles/cop...

Trump’s Antitrust Agencies Stay the Course in the First 100 Days | TechPolicy.Press Continuity on antitrust and competition enforcement may be the most surprising tech policy news in Trump's first hundred days, writes Mark MacCarthy.

A new piece for Tech Policy Press on antitrust enforcement in Trump's first 100 days. www.techpolicy.press/trumps-antit...

A Win for European Regulators on Digital Privacy | PYMNTS.com Meta’s modification of its earlier offerings under regulatory pressure shows, among other things, the need for active and ongoing consultation among

My latest piece for CPI argues that Meta’s modification of its earlier offerings under regulatory pressure shows, among other things, the need for active and ongoing consultation among agencies with different regulatory missions that impact digital companies. www.pymnts.com/cpi-posts/a-...

Multiple sources are now reporting LLMs aren't scaling as hoped—larger datasets and more compute aren't improving AI systems as fast.

The companies, naturally, are pressing on, calling for billions more in investment. One way to read this: The hope is to make AI too big to fail.