More is better: English language statistics are biased toward addition

Winter, B., Fischer, M. H., Scheepers, C. and Myachykov, A. (2023) More is better: English language statistics are biased toward addition. Cognitive Science, 47(4), e13254. (doi: 10.1111/cogs.13254) (PMID:37017257)

[img] Text
290197.pdf - Published Version
Available under License Creative Commons Attribution.



We have evolved to become who we are, at least in part, due to our general drive to create new things and ideas. When seeking to improve our creations, ideas, or situations, we systematically overlook opportunities to perform subtractive changes. For example, when tasked with giving feedback on an academic paper, reviewers will tend to suggest additional explanations and analyses rather than delete existing ones. Here, we show that this addition bias is systematically reflected in English language statistics along several distinct dimensions. First, we show that words associated with an increase in quantity or number (e.g., add, addition, more, most) are more frequent than words associated with a decrease in quantity or number (e.g., subtract, subtraction, less, least). Second, we show that in binomial expressions, addition-related words are mentioned first, that is, add and subtract rather than subtract and add. Third, we show that the distributional semantics of verbs of change, such as to improve and to transform, overlap more with the distributional semantics of add/increase than subtract/decrease, which suggests that change verbs are implicitly biased toward addition. Fourth, addition-related words have more positive connotations than subtraction-related words. Fifth, we demonstrate that state-of-the-art large language models, such as the Generative Pre-trained Transformer (GPT-3), are also biased toward addition. We discuss the implications of our results for research on cognitive biases and decision-making.

Item Type:Articles
Additional Information:Bodo Winter was supported by the UKRI Future Leaders Fellowship MR/T040505/1. Andriy Myachykov was supported by the Basic Research Program at the National Research University Higher School of Economics. Martin Fischer was supported by grant DFG-FI-1915/8-1 “Competing heuristics and biases in mental arithmetic.”
Glasgow Author(s) Enlighten ID:Scheepers, Dr Christoph
Authors: Winter, B., Fischer, M. H., Scheepers, C., and Myachykov, A.
College/School:College of Medical Veterinary and Life Sciences > School of Psychology & Neuroscience
Journal Name:Cognitive Science
ISSN (Online):1551-6709
Published Online:05 April 2023
Copyright Holders:Copyright © 2023 The Authors
First Published:First published in Cognitive Science 47(4): e13254
Publisher Policy:Reproduced under a Creative Commons License
Related URLs:

University Staff: Request a correction | Enlighten Editors: Update this record