AI will fundamentally transform science. It will supercharge the research process, making it faster and more efficient and broader in scope. It will make scientists themselves vastly more productive, more objective, maybe more creative. It will make many human participants—and probably some human scientists—obsolete… Or at least these are some of the claims we are hearing these days. There is no question that various AI tools could radically reshape how science is done, and how much science is done. What we stand to gain in all this is pretty clear. What we stand to lose is less obvious, but no less important.
My guest today is Dr. Molly Crockett. Molly is a Professor in the Department of Psychology and the University Center for Human Values at Princeton University. In a recent widely-discussed article, Molly and the anthropologist Dr. Lisa Messeri presented a framework for thinking about the different roles that are being imagined for AI in science. And they argue that, when we adopt AI in these ways, we become vulnerable to certain illusions.
Here, Molly and I talk about four visions of AI in science that are currently circulating: AI as an Oracle, as a Surrogate, as a Quant, and as an Arbiter. We talk about the very real problems in the scientific process that AI promises to help us solve. We consider the ethics and challenges of using Large Language Models as experimental subjects. We talk about three illusions of understanding the crop up when we uncritically adopt AI into the research pipeline—an illusion that we understand more than we actually do; an illusion that we're covering a larger swath of a research space than we actually are; and the illusion that AI makes our work more objective. We also talk about how ideas from Science and Technology Studies (or STS) can help us make sense of this AI-driven transformation that, like it or not, is already upon us. Along the way Molly and I touch on: AI therapists and AI tutors, anthropomorphism, the culture and ideology of Silicon Valley, Amazon's Mechanical Turk, fMRI, objectivity, quantification, Molly's mid-career crisis, monocultures, and the squishy parts of human experience.
Without further ado, on to my conversation with Dr. Molly Crockett. Enjoy!
A transcript of this episode is available here.
Notes and links
5:00 – For more on LLMs—and the question of whether we understand how they work—see our earlier episode with Murray Shanahan.
9:00 – For the paper by Dr. Crockett and colleagues about the social/behavioral sciences and the COVID-19 pandemic, see here.
11:30 – For Dr. Crockett and colleagues’ work on outrage on social media, see this recent paper.
18:00 – For a recent exchange on the prospects of using LLMs in scientific peer review, see here.
20:30 – Donna Haraway’s essay, 'Situated Knowledges: The Science Question in Feminism and the Privilege of Partial Perspective’, is here. See also Dr. Haraway's book, Published on 2 months, 4 weeks ago
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