Controlling bad-actor-artificial intelligence activity at scale across online battlefields.

We consider the looming threat of bad actors using artificial intelligence (AI)/Generative Pretrained Transformer to generate harms across social media globally. Guided by our detailed mapping of the online multiplatform battlefield, we offer answers to the key questions of what bad-actor-AI activity will likely dominate, where, when-and what might be done to control it at scale. Applying a dynamical Red Queen analysis from prior studies of cyber and automated algorithm attacks, predicts an escalation to daily bad-actor-AI activity by mid-2024-just ahead of United States and other global elections.

Rise of post-pandemic resilience across the distrust ecosystem.

Why does online distrust (e.g., of medical expertise) continue to grow despite numerous mitigation efforts? We analyzed changing discourse within a Facebook ecosystem of approximately 100 million users who were focused pre-pandemic on vaccine (dis)trust.

Shockwavelike Behavior across Social Media.

Online communities featuring "anti-X" hate and extremism, somehow thrive online despite moderator pressure. We present a first-principles theory of their dynamics, which accounts for the fact that the online population comprises diverse individuals and evolves in time. The resulting equation represents a novel generalization of nonlinear fluid physics and explains the observed behavior across scales.

Losing the battle over best-science guidance early in a crisis: COVID-19 and beyond.

Ensuring widespread public exposure to best-science guidance is crucial in any crisis, e.g., coronavirus disease 2019 (COVID-19), monkeypox, abortion misinformation, climate change, and beyond.