Science, Technology, and Public Policy

Belfer Center experts on security, intelligence, and cybersecurity issues were interviewed on the recent leak of classified military intelligence documents allegedly by Airman Jack Teixeira.

Thanks to large language models, a single scammer can run hundreds or thousands of cons in parallel, night and day, in every language under the sun.

This paper explores the unique conditions that made the Agreement to Prevent Unregulated High Seas Fisheries in the Central Arctic Ocean possible and examines how success was achieved by the interrelationships of science, policy, legal structures, politics, stakeholder collaboration, and diplomacy.

Joseph Nye argues hat the major threat to U.S. power comes from its internal divisions. These are serious liabilities but they were not created by the invasion of Ukraine.

The powerful effects of artificial intelligence are already being felt in business, politics, medicine, war, and almost every other domain of twenty-first century life. For all of its positive potential, the technology presents significant risks that are best addressed sooner rather than later.

Ethereum is the world’s most popular digital contract compiler, maintained by many but owned by none. Perhaps one of the most interesting factors behind its popularization is the future it paints — one that transforms current internet standards for ownership, value creation and, most importantly, privacy.

Kelly Sims Gallagher asserts that politicians' pledges of dramatic long-term reductions should not let them off the hook for their failure to achieve more modest progress in the short term.

Jonathan Zittrain differentiates between application and infrastructure moderation and analyzes the history of and the arguments for and against moderation of each.

Bruce Schneier and Nicholas Weaver recommend disrupting cryptocurrency markets, as opposed to banning cryptocurrencies outright,  to combat ransomware attacks.

Bruce Schneier warns that AIs are becoming hackers. They're able to find exploitable vulnerabilities in software code. They're still not very good at it, but they'll get better. It's the kind of problem that lends itself to modern machine learning techniques: an enormous amount of input data, pattern matching, and goals that permit reinforcement. We have every reason to believe that AIs will continue to get better at this task and will soon surpass humans. They'll even come up with hacks that we humans would judge creative.