Future of Science by DeSci Foundation DeSci Foundation

In this episode, we talked to Professor James Zou, who brought us his perspective on how academia might collaborate with AI. He covered how AI could help us ask better questions instead of answering them, how they can translate information for different levels of expertise, and how we can use them to make our feedback more diverse and specific instead of general. After that, we explored how AI is already changing science by increasing the number of papers, creating more general GPT-generated reviews, and also making writing a more accessible task for incoming PhDs.

To top it off, we all agreed that we would absolutely go to an AI-generated concert (especially if there were robots).

James Zou is an Associate Professor of Biomedical Data Science and, by courtesy, of Computer Science and Electrical Engineering at Stanford University. He works on making machine learning more reliable, human-compatible and statistically rigorous, and is especially interested in applications in human disease and health. Several of his algorithms are widely used in tech and biotech industries.

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How does innovation work? Can we design systems that optimize for innovative ideas and solutions? James Evans has been researching rich digital twins of knowledge ecosystems like science and Wikipedia. A key finding of his work is that diversity is the prime driver of innovation. In the episode we discuss which dimensions of diversity matter, and whether there is an optimal amount of diversity. We also cover how AI might help diversify the scientific idea space, and debate whether it may eventually replace human scientists.



Professor James Evans is the Director of Knowledge Lab, Professor of Sociology, Faculty Director of the Computational Social Science program, and member of the Committee on Conceptual and Historical Studies of Science at the University of Chicago. He is also an External Professor at the Santa Fe Institute. His research focuses on the collective system of thinking and knowing, ranging from the distribution of attention and intuition, the origin of ideas and shared habits of reasoning to processes of agreement (and dispute), accumulation of certainty (and doubt), and the texture–novelty, ambiguity, topology–of human understanding. He is especially interested in innovation–how new ideas and technologies emerge–and the role that social and technical institutions (e.g., the Internet, markets, collaborations) play in collective cognition and discovery.

Taylor Oshan has been exploring how use and take advantage of decentralized infrastructure like IPFS and Filecoin for geospatial data. In this podcast we learn what geospatial data actually is - rumor has it it’s about 60% of all data! Then Taylor explains why decentralizing is an important effort and how it can increase the robustness as well as efficiency of data storage and access.

Taylor is a geographic information scientist at the University of Maryland and part of the Easier Data Initiative.

Allison Duettmann is the president and CEO of Foresight Insitute, a non-profit that’s focused on the beneficial development of high-impact technologies.

In this episode, Allison tells us about the history behind Foresight, and why it was started in the first place.

Then we talk about predicting progress: Is that even possible? Are we making enough progress? Too much? And what drives progress, anyways?

We also cover the opportunities of interdisciplinary collaboration to solve humanity’s biggest problems – and the difficulties that researchers encounter when attempting this.

Allison also tells us her personal opinion on what the biggest opportunities and risks that are facing humanity are.



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In this episode, we sat down with Daniel Hook CEO of Digital Science. Digital Science is a company that invests in software companies servicing researchers and research institutions. Daniel shared his personal journey from being a researcher in theoretical physics to starting his own software company to now leading innovation in the scientific tooling space with Digital Science. We also talked about the philosophy and ground revision behind this company, as well as what Daniel thinks the future of science should look like. 

In this episode we talked to Davide Grossi about peer review. Davide is a decision making and mechanism design researcher at University of Groningen and the University of Amsterdam. 

We first covered the state of peer review today: How it’s being done and how it’s going wrong – Davide likens the outcome of reviews to a lottery: Whether you get a positive or negative review seems to depend more on chance than on the quality of your work.

Then we dove into potential solutions and new designs for a fairer and more effective peer review system. Besides reducing the amount of reviews in general, Davide suggested some interesting new avenues for exploration when it comes to how we decide which proposals and publications get the limelight or funding.

There’s a lot more to be done before we find the “best” way to perform peer review. Davide is calling for a science of peer review to systematically engage with the design choices around this pillar of scientific integrity.



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