Thinking Fast and Slow in AI

Grady Booch, Francesco Fabiano, Lior Horesh, Kiran Kate, Jonathan Lenchner, Nick Linck, Andrea Loreggia, Keerthiram Murugesan, Nicholas Mattei, Francesca Rossi, Biplav Srivastava

AAAI 2021 pp. 15042-15046

doi:10.1609/AAAI.V35I17.17765 /aaai/2021/booch2021aaai-thinking/

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.

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Cite

Text

Booch et al. "Thinking Fast and Slow in AI." AAAI Conference on Artificial Intelligence, 2021. doi:10.1609/AAAI.V35I17.17765

Markdown

[Booch et al. "Thinking Fast and Slow in AI." AAAI Conference on Artificial Intelligence, 2021.](https://mlanthology.org/aaai/2021/booch2021aaai-thinking/) doi:10.1609/AAAI.V35I17.17765

BibTeX

@inproceedings{booch2021aaai-thinking,
  title     = {{Thinking Fast and Slow in AI}},
  author    = {Booch, Grady and Fabiano, Francesco and Horesh, Lior and Kate, Kiran and Lenchner, Jonathan and Linck, Nick and Loreggia, Andrea and Murugesan, Keerthiram and Mattei, Nicholas and Rossi, Francesca and Srivastava, Biplav},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2021},
  pages     = {15042-15046},
  doi       = {10.1609/AAAI.V35I17.17765},
  url       = {https://mlanthology.org/aaai/2021/booch2021aaai-thinking/}
}