Examining self-belief formation through artificial beliefs

Psychological research has addressed key questions about self-beliefs, such as when they are formed, how they are shaped, or what functions they might have. The fundamental question of how we arrive at these self-beliefs in the first place has mostly been neglected, and there is currently no mechanistic description of the underlying processes. While recent studies have provided insight into how external information is processed when updating discrete self-related information, they do not speak to the processes underlying the formation of a coherent self-belief when the input is connected. One reason, as we argue here, is that processes underlying self-belief formation are rooted in prior learning histories and are affected by motives and emotional states. As a novel approach to examining the processes underlying self-belief formation, we introduce the idea of artificial beliefs. We introduce a framework that shows how motives and emotional states influence feedback processing while forming novel (self-)beliefs. Conceptualizing (self-)belief formation within a feedback-learning framework, and as entangled with prior learning histories and affected by motives and emotional states, we aim to bridge fields between psychology, computational neuroscience, and sociology on the question of how we became what we think we are today.