As artificial intelligence (AI) transforms nearly every domain of human endeavor, one of its most consequential impacts may be on science itself. This analysis explores how AI technologies could disrupt the power structures that govern research funding—structures that privilege senior investigators while sidelining early-career scientists and genuinely novel ideas. By juxtaposing the youth-driven innovation behind AI with the increasingly gerontocratic funding patterns in biomedical sciences, we highlight how institutional mechanisms shape not only who gets to do science but also when . Evidence suggests that conventional grant peer review has become a self-reinforcing system—more effective at preserving consensus than fostering discovery. AI presents a compelling alternative: evaluation frameworks that could reduce bias, broaden participation, and open more meritocratic pathways to research independence. The implications extend far beyond individual careers. At stake is society's ability to mobilize scientific creativity against its most urgent challenges. By rethinking outdated practices—especially the gatekeeping role of study sections—and exploring algorithmic approaches to assessment, we may be able to reverse troubling trends and unleash a broader, more diverse wave of discovery. AI will not fix science on its own, but it could help build a system where innovation is no longer an accident of privilege and timing.
Madhur Mangalam (Fri,) studied this question.