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By Julia Haas
Julia Haas is an Assistant Professor in the Department of Philosophy at Rhodes College. Her research focuses on theories of valuation and choice.
Imagine a shopper named Barbara in the pasta aisle of her local market. Just as she reaches for her favorite brand of pasta, she remembers that one of the company’s senior executives made a homophobic statement. What should she do? She likes the brand’s affordability and flavor but prefers to buy from companies that support LGBTQ communities. Barbara then notices that a typically more expensive brand of pasta is on sale and buys a package of that instead. Notably, she doesn’t decide what brand of pasta she will buy in the future.
Barbara’s deliberation reflects a common form of human choice. It also raises a number of questions for moral psychological theories of normative cognition. How do human beings make choices involving normative dimensions? Why do normative principles affect individuals differently at different times? And where does the feeling that so often accompanies normative choices, namely that something is just right or just wrong, come from? In this post, I canvass two novel neuroethical approaches to these questions, and highlight their competing notions of value. I argue that one the most pressing questions theoretical neuroethicists will face in the coming decade concerns how to reconcile the reinforcement learning-based and neuroeconomics-based conceptions of value.
One popular approach to the problem of normative cognition has come from a growing interest in morally-oriented computational neuroscience. In particular, philosophers and cognitive neuroscientists have turned to an area of research known as reinforcement learning (RL), which studies how agents learn through interactions with their environments, to try and understand how moral agents interact in social situations and learn to respond to them accordingly.