AI, Human Cognition and Knowledge Collapse
Daron Acemoglu, Dingwen Kong & Asuman Ozdaglar: “This paper is an attempt to contribute to a better theoretical understanding of how AI tools impact human cognition and knowledge. We build a dynamic model of learning and decision-making where AI inputs can be either complementary or substitutable to human effort. At the center of our approach is a distinction between two types of information: general and individual- (or context-) specific. To perform any task, individuals require general knowledge. For example, for investment decisions one needs a basic understanding of different financial instruments such as treasury bonds, corporate bonds, stocks, options, etc., as well as information on how world stock markets and economies have been performing, some relevant aspects of their institutional structure, an understanding of macroeconomic risks etc. But one also needs information related to an individual’s context: what is the risk tolerance and planning horizon of the individual in question? What correlation is there between their other income sources and different asset returns? Do they have information, hunches, preferences or beliefs affecting how they should invest and what types of risks they should take? And so on. Notably, human decision-makers often acquire both general and specific knowledge jointly. For example, most individuals will learn about general financial knowledge in a finance course or reading relevant financial literature, and they will come to recognize their own needs and form their preferences and beliefs relevant for investment during the same process. Put differently, often there [are] economies of scope in learning, with the same efforts generating both general and individual- or context-specific knowledge.”