I am a postdoctoral research fellow at the Centre for Philosophy & Artificial Intelligence Research (PAIR) at the University of Erlangen-Nuremberg in Germany. In Spring 2023, I completed my doctorate in philosophy with doctoral minors in neuroscience and cognitive science at the University of Arizona in the USA. I defended my dissertation Robust Normativity in Complexity Science with Sara Aronowitz (co-adviser), Mark Timmons (co-adviser), Jonathan Weinberg, and Allen Buchanan.
Philosophy pitch: I specialise in the philosophy of neuroscience and cognitive science, the philosophy of artificial intelligence, and the philosophy of biology. A common theme throughout my work is that normative standards (e.g., solutions, functions, reasons) are indispensable for telling us what about complex systems (which possible states, activities, parts, etc.) to explain. I argue that there are many types of norms and each plays distinct roles in functional explanation, mechanistic explanation, and radical interpretation across biology, neuroscience, psychology, and artificial intelligence. Moreover, I argue that normative standards can only play these roles if they are objectively and irreducibly normative. I hold my philosophical work accountable to advancing scientific practice, so I focus on using normative considerations to advance task design in several areas, especially in the sciences of (especially moral) judgment and decision-making (JDM).
Science pitch: I specialise in identifying and solving problems for task design and data interpretation in psychology, neuroscience, and artificial intelligence—especially for judgment and decision-making (JDM). For example, one problem is that tasks are often designed with ambiguous solutions, leaving room for subjects to interpret tasks in multiple ways, and confounding interpretation. A second problem is that most behaviour is explained by the demands of a well-designed task, leaving little room for cognitive theories to genuinely explain. A third problem is that tasks are usually designed with formal norms (e.g., expected utility maximization), biasing the kinds of cognition that we study and creating a need for task design that uses substantive norms (e.g., inventing an appropriate response to a challenging situation). I develop general strategies for addressing these problems using case studies and experiments on cognitive control, moral decision-making, reinforcement learning, self-representation, etc.