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Value attributed to text-based archives generated by artificial intelligence
Kohinoor Darda1,2,3, Marion Carre2, Emily Cross2,3,4
1Penn Center for Neuroaesthetics, University of Pennsylvania, Philadelphia, PA, USA.
People value human-written texts over AI-generated ones, even when they cannot tell the difference. Attitudes toward artificial intelligence (AI) influence perceptions of AI-created content.
Area of Science:
- Natural Language Generation (NLG)
- Human-Computer Interaction
- AI Ethics
Background:
- Openly available NLG algorithms generate human-like texts, raising ethical concerns like misinformation.
- Understanding audience reception and evaluation of AI-generated content is crucial.
Purpose of the Study:
- Investigate audience reactions to algorithmically generated texts.
- Determine if AI-generated texts are distinguishable from human-generated texts.
- Assess the value assigned to AI-generated versus human-generated texts.
Main Methods:
- A preregistered study with 228 participants.
- Comparison of original text archives with AI-generated text archives.
- Analysis of participant categorization and value judgments.
Main Results:
- Participants favored preserving original archives over AI-generated ones.
- Participants could not accurately distinguish between AI-generated and original archives.
- Lower value was assigned to texts categorized as AI-generated, influenced by AI attitudes.
Conclusions:
- Automated text creation impacts reader and writer practices.
- Audience attitudes toward AI affect the perceived value and use of AI applications.
- Further research is needed on the societal implications of AI-generated content.
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