Recent & Upcoming Talks

This paper examines ethical challenges that arise in the context of using deep learning models for nudging. In particular, I will show …

This paper examines the challenge to transparency that deep learning models used in recommender systems raise for ethical nudging. In …

This paper explores the implications of state-of-the-art large language models (LLMs) such as GPT-3.5-turbo for the concept of …

In the current debate on the relation between how-possibly explanations (HPEs) and understanding, two seemingly irreconcilable …

Some how-possibly explanations have epistemic value because they are epistemically possible; we cannot rule out their truth. One …

Some how-possibly explanations have epistemic value because they are epistemically possible; we cannot rule out their truth. One …

People are increasingly subject to algorithmic decisions, and it is generally agreed that end-users should be provided an explanation …

Discussions in the literature on economic methodology often do not explicitly concern explanation. The goal of this chapter is to show …

People are increasingly subject to algorithmic decisions, and it is generally agreed that end-users should be provided an explanation …

Two recent contributions have discussed, and disagreed, over whether so-called toy models that attempt to represent dispositions have …

Scientists seek to learn about targets of interest by representing them with models. This supposes that we have an account of how …

One strategy that scientists use to understand targets of interest is by representing them with models. Understanding the world by …

In this paper, I argue that two brands of inferentialism (Suárez 2004; Suárez 2015) and what I call the factive inferentialist account …

Naturalism is the view according to which philosophy should solve its problems using the empirical scientific methodology. It assumes a …