Literature DB >> 33041198

Understanding Human Intelligence through Human Limitations.

Thomas L Griffiths1.   

Abstract

Recent progress in artificial intelligence provides the opportunity to ask the question of what is unique about human intelligence, but with a new comparison class. I argue that we can understand human intelligence, and the ways in which it may differ from artificial intelligence, by considering the characteristics of the kind of computational problems that human minds have to solve. I claim that these problems acquire their structure from three fundamental limitations that apply to human beings: limited time, limited computation, and limited communication. From these limitations we can derive many of the properties we associate with human intelligence, such as rapid learning, the ability to break down problems into parts, and the capacity for cumulative cultural evolution.
Copyright © 2020. Published by Elsevier Ltd.

Entities:  

Keywords:  artificial intelligence; cultural evolution; inductive bias; meta-learning; rational meta-reasoning

Mesh:

Year:  2020        PMID: 33041198     DOI: 10.1016/j.tics.2020.09.001

Source DB:  PubMed          Journal:  Trends Cogn Sci        ISSN: 1364-6613            Impact factor:   20.229


  3 in total

1.  Overcoming Individual Limitations Through Distributed Computation: Rational Information Accumulation in Multigenerational Populations.

Authors:  Mathew D Hardy; Peaks M Krafft; Bill Thompson; Thomas L Griffiths
Journal:  Top Cogn Sci       Date:  2022-01-15

2.  Biases and Variability from Costly Bayesian Inference.

Authors:  Arthur Prat-Carrabin; Florent Meyniel; Misha Tsodyks; Rava Azeredo da Silveira
Journal:  Entropy (Basel)       Date:  2021-05-13       Impact factor: 2.524

3.  Machine Teaching for Human Inverse Reinforcement Learning.

Authors:  Michael S Lee; Henny Admoni; Reid Simmons
Journal:  Front Robot AI       Date:  2021-06-30
  3 in total

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