The myth of scientific research is that it involves an exacting, methodical approach to uncovering the truth. But in reality, science is a lot messier and fraught with human error—and that messiness extends to scientific publishing.

When researchers submit their work to academic journals, it goes through a peer-review process, which is supposed to enhance and strengthen the work through critical feedback from experts in the field. But that process can be easily compromised by overworked researchers asked to volunteer their time, conflicts of interest from competing labs, and even fraudulent data that human reviewers might miss.
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But what if your reviewer were an intelligent machine? For several years now the world of academic publishing has been flirting with the idea of using artificial intelligence systems as part of the peer-review process. For example, A.I. would solve the problem of reviewer bias and could detect fraudulent data. But others argue that allowing an A.I. system to be the gatekeeper of new scientific knowledge is a dangerous step to take. Adam Marcus, co-founder of the blog Retraction Watch, joins us to discuss the role that A.I. could have in scientific publishing.
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Listen to this discussion piece