PreprintCited by 7Artificial Intelligence ApplicationsCreativity in Education and NeuroscienceEthics and Social Impacts of AI

The DOI matches its Crossref record.

Creative and Strategic Capabilities of Generative Ai: Evidence from Large-Scale Experiments

Open access
Bohren, Noah, Hakimov, Rustamdjan, Lalive, Rafael·2024·SSRN Electronic Journal

Abstract

Generative artificial intelligence (AI) has made substantial progress, but its full capabilities remain unclear, and we still lack a comprehensive understanding of how people augment productivity with AI and perceive AI-generated outputs. This study compares the ability of AI to a representative population of US adults in creative and strategic tasks. The creative ideas produced by AI chatbots are rated more creative than those created by humans. Moreover, ChatGPT is substantially more creative than humans, while Bard lags behind. Augmenting humans with AI improves human creativity, albeit not as much as ideas created by ChatGPT alone. Competition from AI does not significantly reduce the creativity of men, but it decreases the creativity of women. Humans who rate the text cannot discriminate well between ideas created by AI or other humans but assign lower scores to the responses they believe to be AI-generated. As for strategic capabilities, while ChatGPT shows a clear ability to adjust its moves in a strategic game to the play of the opponent, humans are, on average, more successful in this adaptation.

Overview

Integrity signals

Registry

Crossref · 10.2139/ssrn.4963992

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Much research on GenAI and its promise for creativity tends to be about singular, relatively short tasks that are mostly unconstrained.

    “Much research on GenAI and its promise for creativity tends to be about singular, relatively short tasks that are mostly unconstrained (e.g., write a poem on some topic and in a certain style, generate alternative uses, provide a list of ideas).”
  • Some studies show GenAI outperforming humans on creative tasks.

    “Other studies show GenAI outperforming humans. Consultants using GenAI [30] produced more than 40% higher quality solutions in a controlled study, where quality was an aggregate score comprising creativity, analytical thinking, writing proficiency, and persuasiveness.”

Citations

Cited by

Sorted by citations

Metadata

Authors
Bohren, N., Hakimov, R., & Lalive, R.
Affiliations
  • University of Lausanne (CH)
  • WZB Berlin Social Science Center (DE)
  • Ifo Institute for Economic Research (DE)
Corresponding author
Bohren, Noah
Venue
SSRN Electronic Journal
Publisher
Elsevier BV
Published
2024
ISSN
1556-5068 (ISSN-L)
OpenAlex
W4402728132
Cited by
7
References
0
Citations by year
2026: 3 · 2025: 3 · 2024: 1
Type
posted content
Language
en
Open access
Locations
  • SSRN Electronic Journal (acceptedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • Econstor (Econstor) (submittedVersion)
Funders
  • National Science Foundation
  • Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (207722, 100018)
  • Université de Lausanne
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Creativity in Education and Neuroscience
  • Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
Keywords
generative AI, ChatGPT, Google Bard, human-AI comparison, creativity, strategic thinking, human-AI collaboration, gender differences, strategic games, large language models

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review