Join economist Matt Clancy, Stripe co-founder Patrick Collison, and OpenPhil CEO Alexander Berger as they explore whether scientific progress is really slowing down. They discuss the challenges in measuring scientific breakthroughs, revealing a paradox of increasing funding yet declining impact. The conversation dives into how historical evidence, evolving practices, and innovations like AI may influence future advancements. With insights on institutional reforms and diverse funding, they argue for a renewed focus on enhancing scientific productivity.
Despite increased funding and researcher numbers, the quality and significance of scientific breakthroughs are perceived to be declining.
Measuring scientific progress is challenging, as current metrics indicate a decrease in research quality and novel contributions over time.
Institutional dynamics and rigid funding structures may hinder innovation, highlighting the need for reform in research incentives and methodologies.
Deep dives
Science's Rate of Progress
Science is experiencing a slowdown in per capita breakthroughs despite a significant increase in funding and the number of researchers since the Second World War. The discussion highlights that although the total output of scientific research may be rising, the quality and significance of discoveries per individual scientist seem to be diminishing. Surveys of scientists across disciplines, such as physics, chemistry, and biology, indicate that recently achieved breakthroughs are perceived to be of constant or even declining significance. This suggests a troubling trend where more researchers and funding do not necessarily equate to more impactful scientific progress.
Difficulty in Measuring Scientific Impact
Measuring the true impact of scientific research poses considerable challenges, leading experts to utilize a patchwork of indicators to assess productivity. Metrics such as publication rates and citation analyses point to a decline in quality, with current work receiving fewer citations compared to older research. When looking at Nobel Prizes, citation trends, and even novel combinations of keywords in scientific papers, a consistent pattern emerges indicating that the novelty and significance of research outcomes are not keeping pace with the influx of new papers. These findings underscore the complexity of quantifying scientific progress and suggest an urgent need for better methodologies to evaluate research success.
The Role of Institutional Factors in Science
Institutional dynamics significantly influence scientific productivity and may be contributing factors to the observed slowdown. Institutionalization and professionalization of research funding, especially through sources like the National Institutes of Health (NIH), could restrict researchers' freedom and innovation. Many scientists express frustration over the limitations of grant applications, indicating a desire for greater flexibility in pursuing research topics that excite them. It emphasizes the need for reform in how scientific institutions operate to allow for more creative and impactful research endeavors.
Emerging Solutions in Scientific Research
Innovations like the ARC Institute aim to create new models for scientific research funding to enhance productivity and creativity among scientists. By providing internal funding and flexible project parameters over extended periods, ARC seeks to empower researchers to explore significant scientific inquiries. There is optimism that new models can revitalize the exploration of potentially groundbreaking scientific territory by reducing bureaucratic obstacles that currently stifle innovation. The discussion also highlights the potential of artificial intelligence to facilitate data analysis and increase efficiency in scientific research, suggesting a possible revolution in the productivity landscape.
Cultural and Policy Changes in Science
Cultural perceptions surrounding scientific endeavors and the overall incentives for scientists are shifting, reflecting an evolving landscape. Discussions bring forth the idea that diverse and innovative research environments, such as ARC, might inspire broader scientific enthusiasm and norm changes across the field. Engaging with social scientists to evaluate the effectiveness of different funding models is emphasized as vital for fostering a self-improving scientific ecosystem. Furthermore, changes to immigration policies could significantly influence the recruitment of talent in the scientific workforce, representing a straightforward policy avenue for improving scientific growth.
IN THIS EPISODE: OpenPhil CEO Alexander Berger interviews economist Matt Clancy and Stripe co-founder Patrick Collison to talk about whether science itself is slowing down, one of the key motivating concerns in metascience. They look at the challenges of measuring scientific progress, the reasons why progress might be slowing down, and what we might be able to do about it.
“Metascience 101” is a nine-episode set of interviews that doubles as a crash course in the debates, issues, and ideas driving the modern metascience movement. We investigate why building a genuine “science of science” matters, and how research in metascience is translating into real-world policy changes.
Chapters
(00:00:00) Introductions
(00:01:25) Per-capita slowing in science
(00:05:03) Measuring breakthroughs via inputs
(00:09:20) Measuring breakthroughs via outputs
(00:12:53) Books and sources
(00:14:57) Predictions from these models
(00:21:35) After the low hanging fruit era
(00:31:30) How much is institutional?
(00:45:17) Solutions to these problems
(01:01:03) Over- and underrated
(01:07:37) Other creative endeavors
(01:11:05) Audience comments
This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.macroscience.org
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