Essay by Henry Farrell and Hahrie Han: “Could existing democratic institutions and processes be improved by AI? A burgeoning body of scholarship asks how AI-driven machine learning can improve—or even replace— democratic institutions that aggregate opinions and beliefs (Ovadya 2023, Jungherr 2023).
This literature makes strong, but often unstated assumptions about how democracy works, and where it can go wrong, creating a tacit paradigm that guides scholars to focus on some questions, problems, and hypotheses at the expense of others. As one of us has argued together with co-authors in the past:
Paradigms guide action. Particularly in moments of crisis, those paradigms—or cohered sets of assumptions about ourselves, each other, and the world around us—shape the intentions we develop, the solutions we imagine, and, ultimately, the actions we choose. What happens when the paradigms we carry are limited or, worse, wrong? … [Paradigms] illuminate possibilities for change, they also constrain where we look. The wrong paradigm leads us to misread situations, overlook opportunities, and pursue the wrong solutions. (Vallone et al 2023)
In this paper, we argue that the existing paradigm of democracy driving scholarship about its relationship to AI highlights the wrong questions. The essay describes this broad paradigm—which emphasizes the benefits of deliberation and sortition—and explains why it is insufficient for understanding or acting in a healthy democracy. We argue that we should instead focus on enduring democratic publics and how they shape collective behavior. That would raise very different questions. How might AI reshape these publics and the feedback loops that they depend on? Will this contribute to democratic stability or undermine it? Such questions would underpin a broader and different research agenda on AI and democracy than the one we have today…(More)”.
