Title data
Jakesch, Maurice ; Bhat, Advait ; Buschek, Daniel ; Zalmanson, Lior ; Naaman, Mor:
Co-Writing with Opinionated Language Models Affects Users' Views.
2023
Event: CHI Conference on Human Factors in Computing Systems
, 23.04. - 28.04.2023
, Hamburg, Germany.
(Conference item: Conference
,
Paper
)
DOI: https://doi.org/10.1145/3544548.3581196
Project information
Project title: |
Project's official title Project's id AI Tools - Continuous Interaction with Computational Intelligence Tools No information |
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Abstract in another language
If large language models like GPT-3 preferably produce a particular point of view, they may influence people's opinions on an unknown scale. This study investigates whether a language-model-powered writing assistant that generates some opinions more often than others impacts what users write -- and what they think. In an online experiment, we asked participants (N=1,506) to write a post discussing whether social media is good for society. Treatment group participants used a language-model-powered writing assistant configured to argue that social media is good or bad for society. Participants then completed a social media attitude survey, and independent judges (N=500) evaluated the opinions expressed in their writing. Using the opinionated language model affected the opinions expressed in participants' writing and shifted their opinions in the subsequent attitude survey. We discuss the wider implications of our results and argue that the opinions built into AI language technologies need to be monitored and engineered more carefully.
Further data
Item Type: | Conference item (Paper) |
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Refereed: | Yes |
Keywords: | GPT-3; co-writing; social influence; opinion change; risks of large language models |
Institutions of the University: | Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science Faculties Faculties > Faculty of Mathematics, Physics und Computer Science |
Result of work at the UBT: | Yes |
DDC Subjects: | 000 Computer Science, information, general works > 004 Computer science |
Date Deposited: | 13 Feb 2023 06:43 |
Last Modified: | 13 Feb 2023 06:43 |
URI: | https://eref.uni-bayreuth.de/id/eprint/73653 |