This episode is a re-run of the Ideas Matter podcast episode “The Future of Science and the Replication Crisis” hosted by Dean Sandro Galea, Co-Director of the Building Better Ways of Knowing initiative, in conversation with Professor John Ioannidis. The original episode was released by Ideas Matter on May 19, 2026.

This episode begins with a discussion of Dr. Ioannidis’ paper about how most research findings cannot be replicated. Following the argument of this paper, Dean Galea and Dr. Ioannidis unpack the structural and statistical forces—incentives, funding, tenure, and conflicts of interest—that drive this replication challenge, and highlight the progress that has been made despite these challenges, using genetic epidemiology as an example. They also discuss the pandemic, and how it served as a stress-test for science, requiring disciplines to show their capacity to rapid response but also promoting low-quality research.

Forward-facing, Dean Galea and Dr. Ioannidis discuss the role of AI and LLMs in both improving and potentially deteriorating science, including the rise of fake papers and the privatization of knowledge, they formulate what success for science might look like in 20-30 years, debate how scientists should handle controversy and pushback, and highlight the of humility in science and remaining open to being wrong.

If you have ever questioned whether science is getting things right, this conversation will give you both an honest answer and reasons for cautious optimism.

About the guest:

John Ioannidis is the George E. and Lucy Becker Professor of Medicine at the Stanford Prevention Research Center and Professor of epidemiology and population health at Stanford University. His research focuses on improving research methods and practices to generate more reliable, trustworthy, and useful evidence. He is among the most cited scholars in Clinical Medicine, Social Sciences and Psychiatry/Psychology, and is the author of the most-accessed article in the history of Public Library of Science.

Notes:

Acronyms mentioned in this episode include:

AI = Artificial Intelligence

LLM = Large Language Models

Useful resources:

Ioannidis JPA. Why Most Published Research Findings Are False. PLoS Med. 2005;2(8):e124. doi:10.1371/journal.pmed.0020124

Host: Dr. Salma Abdalla

Editors: Ryan Rhea and Catalina Melendez Contreras

Marketing: Kinkini Bhaduri

Music: Eden Avery / Melting Glass from Epidemic Sound https://www.epidemicsound.com/track/2fqOXWpHab/

The views and opinions expressed by the guest in this episode do not necessarily reflect those of their institution, the funders, or the podcast team.