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Publishing fast and slow: A path toward generalizability in psychology and AI

Published online by Cambridge University Press:  10 February 2022

Andrew K. Lampinen
Affiliation:
DeepMind, LondonN1C 4DN, UK. lampinen@google.com scychan@google.com adamsantoro@google.com felixhill@google.com
Stephanie C. Y. Chan
Affiliation:
DeepMind, LondonN1C 4DN, UK. lampinen@google.com scychan@google.com adamsantoro@google.com felixhill@google.com
Adam Santoro
Affiliation:
DeepMind, LondonN1C 4DN, UK. lampinen@google.com scychan@google.com adamsantoro@google.com felixhill@google.com
Felix Hill
Affiliation:
DeepMind, LondonN1C 4DN, UK. lampinen@google.com scychan@google.com adamsantoro@google.com felixhill@google.com

Abstract

Artificial intelligence (AI) shares many generalizability challenges with psychology. But the fields publish differently. AI publishes fast, through rapid preprint sharing and conference publications. Psychology publishes more slowly, but creates integrative reviews and meta-analyses. We discuss the complementary advantages of each strategy, and suggest that incorporating both types of strategies could lead to more generalizable research in both fields.

Type
Open Peer Commentary
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

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