Evidence map›Paper›PMID 38514688›Full record

ArticleScientific reports2024

A comparison of human and GPT-4 use of probabilistic phrases in a coordination game.

Laurence T Maloney, Maria F Dal Martello, Vivian Fei, Valerie Ma

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Laurence T MaloneyDepartment of Psychology, New York University, 6 Washington Place, Room 574, New York, NY, 10012, USA. ltm1@nyu.edu.
Maria F Dal MartelloDepartment of Psychology, New York University, 6 Washington Place, Room 574, New York, NY, 10012, USA.
Vivian FeiDepartment of Psychology, New York University, 6 Washington Place, Room 574, New York, NY, 10012, USA.
Valerie MaDepartment of Psychology, New York University, 6 Washington Place, Room 574, New York, NY, 10012, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

English speakers use probabilistic phrases such as likely to communicate information about the probability or likelihood of events. Communication is successful to the extent that the listener grasps what the speaker means to convey and, if communication is successful, individuals can potentially coordinate their actions based on shared knowledge about uncertainty. We first assessed human ability to estimate the probability and the ambiguity (imprecision) of twenty-three probabilistic phrases in a coordination game in two different contexts, investment advice and medical advice. We then had GPT-4 (OpenAI), a Large Language Model, complete the same tasks as the human participants. We found that GPT-4's estimates of probability both in the Investment and Medical Contexts were as close or closer to that of the human participants as the human participants' estimates were to one another. However, further analyses of residuals disclosed small but significant differences between human and GPT-4 performance. Human probability estimates were compressed relative to those of GPT-4. Estimates of probability for both the human participants and GPT-4 were little affected by context. We propose that evaluation methods based on coordination games provide a systematic way to assess what GPT-4 and similar programs can and cannot do.

Indexed as

CommunicationInvestmentsHumansKnowledgeLanguageProbabilityAmbiguityGPT-4LLMPragmaticsProbabilistic phrasesProbability

Identifiers

PMID38514688
PMCPMC10958015

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.