My current research is concerned with understanding the way economic and financial decisions are made and the consequences for the economy and society, and understanding and specifying the core features of everyday psychoanalytic technique.
The first line of research has led to the development of Conviction Narrative Theory and Directed Algorithmic Text analysis. It differs from most work in economics and decision science in two main ways. First, it examines decision-making under uncertainty - that is, in a context in which the decision-maker is unsure about the nature of their own beliefs about what will happen or what will or will not work in the future. In this situation it is not that people make framing errors, or bias their decisions away from being "right"; they just can't know. Nonetheless, people develop enough confidence to act. They do this by more or less convincing themselves about what will happen, despite uncertainty. They draw on evolved human capacities to create emotionally meaningful narratives of the future, using their imagination. A consequence of this is that decisions are strongly influenced by the phantasies and states of mind that decision-makers develop. Directed Algorithmic Text analysis is a way of analysing expressed emotion in digital documents to track shifts through time in emotions and states of mind. These shifts turn out to predict important shifts in the economy.
The second line looks at the models of psychoanalytic practice that psychoanalysts or psychoanalytic therapists enact as they work. A group-discussion method, the comparative clinical method, has been designed to elicit this from descriptions of clinical working.