Artificial Intelligence and Psychoanalysis: A New Concept of Research Methodology

Abstract

The recent high performance of ChatGPT on several standardized academic tests has thrust the topic of artificial intelligence (AI) into the mainstream conversation about the future of education. As deep learning is poised to shift the teaching paradigm, it is essential to have a clear understanding of its effects on the current education system to ensure sustainable development and deployment of AI-driven technologies at schools and universities. Hence, AI behavior cannot be fully understood without human and social sciences. After the imaginary and symbolic registers, AI is the third register of identification. Therefore, AI extends the movement that is at work in the Lacanian interpretation of the mirror stage and Oedipus complex and which Latour’s reading helps us to clarify. From this point of view, I describe an AI system as a set of three contrasting forces: the human desire for identification, logic, and machinery. In the “Miscomputation and information” section, I show how this interpretative model improves our understanding of AI. Systematic research on psychoanalytic treatments has been limited by several factors, including a belief that clinical experience can demonstrate the effectiveness of psychoanalysis, rendering systematic research unnecessary, the view that psychoanalytic research would be difficult or impossible to accomplish, and a concern that research would distort the treatment being delivered.