Abstract
<p>Science has been going through a sequence of public credibility tests which have made one gap visible: the difference between what science aspires to (transparency, reproducibility, self-correction) and what it can actually deliver and verify at scale. The reform movement of the last decade and a half gave the field shared norms and initial solutions, but change has been slow and its impact unclear. The recent rise in AI capability has, for the first time, the potential to narrow that gap. I discuss how AI is beginning to drive a change in the behavioral sciences and, by extension, science more broadly, by making feasible what was until recently very difficult or outright impossible, and to do so at scale: the ongoing systematic assessment, verification, updating, and improvement of evidence, relevance, and impact. The promise is that AI would empower researchers to ensure science credibility and maximize the value and impact of science for society.</p>