AI vs Cancer - How AI Can, and Can't, Cure Cancer (by Emilia Javorsky)
Emilia Javorsky explores how AI can realistically aid cancer research, where current hype exceeds evidence, and what changes researchers, policymakers, and funders must make to turn AI advances into real clinical impact.
Tech executives have promised that AI will cure cancer. The reality is more complicated — and more hopeful. This essay examines where AI genuinely accelerates cancer research, where the promises fall short, and what researchers, policymakers, and funders need to do next.
Li-Lian Ang from Blue Dot Impact discusses how to build a workforce to defend against AI-driven risks, including engineered pandemics, cyber attacks, job disempowerment, and concentrated power, using a defense-in-depth framework for uncertain AI progress.
Physician-scientist Emilia Javorsky argues that curing cancer is limited more by biology’s complexity, data quality, and incentives than by intelligence, and explores realistic uses of AI in drug development, trials, and reducing medical bureaucracy.
Researcher Zak Stein discusses how anthropomorphic AI can exploit human attachment systems, its psychological risks for children and adults, and ways to redesign education and cognitive security tools to protect relationships and human agency.
