Judgments of research co-created by generative AI: experimental evidence
Judgments of research co-created by generative AI: experimental evidence
The introduction of ChatGPT has fuelled a public debate on the use of generative AI (large language models; LLMs), including its use by researchers. In the current work, we test whether delegating parts of the research process to LLMs leads people to distrust and devalue researchers and scientific output. Participants (N=402) considered a researcher who delegates elements of the research process to a PhD student or LLM, and rated (1) moral acceptability, (2) trust in the scientist to oversee future projects, and (3) the accuracy and quality of the output. People judged delegating to an LLM as less acceptable than delegating to a human (d = -0.78). Delegation to an LLM also decreased trust to oversee future research projects (d = -0.80), and people thought the results would be less accurate and of lower quality (d = -0.85). We discuss how this devaluation might transfer into the underreporting of generative AI use.
cs.HC, cs.AI, cs.CL, cs.CY, econ.GN, q-fin.EC, K.4.2; I.2.7
Niszczota, Paweł
245606ca-f904-42f1-b6df-404d86f0f52a
Conway, Paul
765aaaf9-173f-44cf-be9a-c8ffbb51e286
Niszczota, Paweł
245606ca-f904-42f1-b6df-404d86f0f52a
Conway, Paul
765aaaf9-173f-44cf-be9a-c8ffbb51e286
[Unknown type: UNSPECIFIED]
Abstract
The introduction of ChatGPT has fuelled a public debate on the use of generative AI (large language models; LLMs), including its use by researchers. In the current work, we test whether delegating parts of the research process to LLMs leads people to distrust and devalue researchers and scientific output. Participants (N=402) considered a researcher who delegates elements of the research process to a PhD student or LLM, and rated (1) moral acceptability, (2) trust in the scientist to oversee future projects, and (3) the accuracy and quality of the output. People judged delegating to an LLM as less acceptable than delegating to a human (d = -0.78). Delegation to an LLM also decreased trust to oversee future research projects (d = -0.80), and people thought the results would be less accurate and of lower quality (d = -0.85). We discuss how this devaluation might transfer into the underreporting of generative AI use.
Text
2305.11873v1
- Author's Original
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Submitted date: 3 May 2023
Additional Information:
10 pages, 2 tables, 1 figure
Keywords:
cs.HC, cs.AI, cs.CL, cs.CY, econ.GN, q-fin.EC, K.4.2; I.2.7
Identifiers
Local EPrints ID: 479451
URI: http://eprints.soton.ac.uk/id/eprint/479451
PURE UUID: 017d3ce2-0556-40ce-a1fd-ad244ae3d6fc
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Date deposited: 24 Jul 2023 16:59
Last modified: 17 Mar 2024 04:17
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Author:
Paweł Niszczota
Author:
Paul Conway
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