Colloquium Series

The Philosophy Department’s Colloquia Series takes place most Mondays of each academic quarter from 2-4pm in the Living and Learning Neighborhood in the Arts & Humanities Building 1, 0426. Snacks will be served.

To review past departmental colloquium please see our colloquium archive.

Schedule 2025-26

Fall 2025

October 20
Amanda Greene (UC Santa Barbara)

Democratic Legitimacy for Skeptics

 Today democracy is thought to be the most legitimate form of government the world has ever seen. But why does democracy matter at all for political legitimacy? As I understand this question, an adequate answer has not yet been given. Some accounts rely on standards of legitimacy that implicitly regard democracy as a necessary or even constitutive element. These defenses of the value of democracy tend to rely on idealized or romantic views about what democracy is and how it functions. This paper provides a challenge and an alternative to that family of approaches. It does so by showing how democracy makes a special contribution to political legitimacy, even though there is no legitimacy-based imperative to democratize. I argue that democracy contributes to legitimacy because it makes the exercise of power responsive to people’s views. I show that this realistic view has several advantages: it allows us to answer democratic skeptics with a legitimacy-based argument for democracy, it is more compatible with empirical research on political behavior, and it accepts the contingent relationship between democracy and other political values.

November 3
Kenny Easwaran (UC Irvine)

Neural Nets as a Model of "Knowing How"
Gilbert Ryle argued that there was an important distinction between "knowing how" and "knowing that". Stanley and Williamson, "Knowing How" (2001), argued that syntax and semantics require the meaning of "knowing how" to be a sub-type of "knowing that". I will not contest their claim about the formal semantics of English. However, I claim that in doing epistemology, it is useful to consider what concepts exist that are usefully like the concepts we apply to humans, that can be applied more broadly to subjects like animals, groups, and artificial intelligences. I will argue that neural nets are a class of systems that have been used for several decades, for which there is a useful concept of "knowing how" that can be applied. But until the rise of Large Language Models in the past few years, neural nets have not been the subject of a useful concept of "knowing that", and even now it is unclear. I claim that this conception of "knowing that" as a special and refined type of "knowing how" is also a useful way to think of humans, in line with the distinction that cognitive scientist Daniel Kahneman draws between "System 1" and "System 2" thinking.

Winter 2026

January 26
Adina Roskies (UC Santa Barbara)

February 23 
Anastasia Berg (UC Irvine)

Spring 2026

April 13
Sara Bernstein (UC Santa Cruz)

May 11
Arthur Ripstein (University of Toronto)