Abstract
Locked and unlocked strategies are at the center of this article, as ways of shedding new light on the cognitive aspects of deep learning machines. The character and the role of these cognitive strategies, which are occurring both in humans and in computational machines, is indeed strictly related to the generation of cognitive outputs, which range from weak to strong level of knowledge creativity. I maintain that these differences lead to important consequences when we analyze computational AI programs, such as AlphaGo, which aim at performing various kinds of abductive hypothetical reasoning. In these cases, the programs are characterized by locked abductive strategies: they deal with weak (even if sometimes amazing) kinds of hypothetical creative reasoning, because they are limited in what I call eco-cognitive openness, which instead qualifies human cognizers who are performing higher kinds of abductive creative reasoning, where cognitive strategies are instead.
Funder
Università degli Studi di Pavia
Subject
History and Philosophy of Science,Philosophy
Reference74 articles.
1. Bounded Rationality. The Adaptive Toolbox;Gigerenzer,2002
2. Intelligence as smart heuristics;Raab,2005
3. Homo Heuristicus: Why Biased Minds Make Better Inferences
4. Abductive Cognition. The Epistemological and Eco-Cognitive Dimensions of Hypothetical Reasoning;Magnani,2009
5. Abduction, Reason, and Science. Processes of Discovery and Explanation;Magnani,2001
Cited by
15 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献