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Thinking Fast and Slow in AI

Grady Booch
•
Francesco Fabiano
•
Lior Horesh
altro
Biplav Srivastava
2020
  • other

Abstract
This paper proposes a research direction to advance AI which draws inspiration from cognitive theories of human decision making. The premise is that if we gain insights about the causes of some human capabilities that are still lacking in AI (for instance, adaptability, generalizability, common sense, and causal reasoning), we may obtain similar capabilities in an AI system by embedding these causal components. We hope that the high-level description of our vision included in this paper, as well as the several research questions that we propose to consider, can stimulate the AI research community to define, try and evaluate new methodologies, frameworks, and evaluation metrics, in the spirit of achieving a better understanding of both human and machine intelligence.
Archivio
http://hdl.handle.net/11390/1191583
https://arxiv.org/abs/2010.06002v1
Diritti
metadata only access
Visualizzazioni
1
Data di acquisizione
Apr 19, 2024
Vedi dettagli
google-scholar
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