Data Innovation

In China Daily, Daniel Castro argues that the U.S. and China face AI risks—like models enabling biological threats or cyberattacks—that are too great for either to manage alone, and can be mitigated through coordinated safety measures such as joint research, incident reporting, and red-team testing.

Fifty conflicting state AI laws create a fragmented, innovation-crushing patchwork, which federal preemption can solve by establishing a single, coherent national framework for AI regulation.

Watch now for a panel discussion on how data and technology can create safer, healthier, and more productive workplaces, and the policies needed to encourage adoption while protecting workers.

Hodan Omaar spoke about opportunities for US-Japan collaboration on AI governance and quantum technology at an event hosted by the National Bureau of Asian Research.

Senator Blackburn’s call to shut down Google’s AI over a false claim is misguided, as the error came from a small, open developer model not designed for factual accuracy, and the incident does not demonstrate political bias or systemic failure.

A productive approach to emerging workplace technologies would focus on two overarching goals: 1) accelerating development, testing, and adoption, and 2) supporting positive uses of the technology while mitigating negative ones.

The UK’s refusal to formally designate China as a national security threat has undermined its ability to prosecute espionage, leaving its technology and innovation sectors vulnerable to Chinese infiltration and economic coercion.

Watch now for an expert panel discussion on the role of Chinese e-commerce platforms in facilitating counterfeiting, what this means for U.S. competitiveness, consumer trust, and global trade, and the steps policymakers should take to safeguard American innovators and consumers.

The UK Online Safety Act aims to protect children online but its vague rules and strict enforcement have led to over-censorship, threatening legitimate communities, and Parliament should clarify content definitions, allow remediation periods, and require judicial review to fix these issues.

California’s new AI safety law includes some constructive measures like incident reporting and whistleblower protections, but by acting at the state level, it creates a fragmented regulatory patchwork that undermines innovation, complicates a national framework, and risks weakening U.S. leadership in AI governance.