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AI-Generated Summaries Affecting Decision Quality in Microcontent Interactions

Melander, Erik LU and Bjelvér, Jakob (2025) INFM10 20251
Department of Informatics
Abstract
The increasing integration of AI-generated microcontent summaries in everyday use lacks clear evidence of impact on user decision quality compared to simpler methods or original content, raising "AI-washing" concerns. This study empirically investigated the effects of AI-generated summaries of microcontent on user decision quality, considering content collection length, to assess if and when AI integration is advantageous. A controlled experiment (n=22) measured objective and subjective outcomes, constructed to operationalize decision quality as a measure. Results showed users subjectively preferred original microcontent, reporting higher subjective quality (satisfaction and confidence). Objectively, neither AI nor programmatic summaries... (More)
The increasing integration of AI-generated microcontent summaries in everyday use lacks clear evidence of impact on user decision quality compared to simpler methods or original content, raising "AI-washing" concerns. This study empirically investigated the effects of AI-generated summaries of microcontent on user decision quality, considering content collection length, to assess if and when AI integration is advantageous. A controlled experiment (n=22) measured objective and subjective outcomes, constructed to operationalize decision quality as a measure. Results showed users subjectively preferred original microcontent, reporting higher subjective quality (satisfaction and confidence). Objectively, neither AI nor programmatic summaries sig-nificantly improved or harmed accuracy or comprehension compared to original content. AI summaries offered no significant advantage over simpler programmatic techniques. Content length did not alter these comparative effects, though this result should be observed in an ex-plorative manner. Findings suggest AI summarization may offer no tangible benefit for micro-content within this scope, supporting AI-washing critiques. A cautious, user-centric approach, potentially offering original content options, is recommended. (Less)
Please use this url to cite or link to this publication:
author
Melander, Erik LU and Bjelvér, Jakob
supervisor
organization
course
INFM10 20251
year
type
H1 - Master's Degree (One Year)
subject
keywords
Decision Quality Information Systems Microcontent Digital Communication Human-Computer Interaction Digital Decision-Making AI-supported Decisions Information Design User Cognition Digital Information Processing Artificial Intelligence (AI) Generative AI Large Language Models (LLMs) AI Summarization Automatic Text Summarization Abstractive Summarization Extractive Summarization Programmatic Summarization Text Condensation Natural Language Processing (NLP) AI-Washing Information Filtering Cognitive Load Bounded Rationality Automation Bias Human-AI Interaction User Perception Algorithmic Trust Information Overload Technological Mediation
language
English
id
9202096
date added to LUP
2025-06-18 10:35:42
date last changed
2025-06-18 10:35:42
@misc{9202096,
  abstract     = {{The increasing integration of AI-generated microcontent summaries in everyday use lacks clear evidence of impact on user decision quality compared to simpler methods or original content, raising "AI-washing" concerns. This study empirically investigated the effects of AI-generated summaries of microcontent on user decision quality, considering content collection length, to assess if and when AI integration is advantageous. A controlled experiment (n=22) measured objective and subjective outcomes, constructed to operationalize decision quality as a measure. Results showed users subjectively preferred original microcontent, reporting higher subjective quality (satisfaction and confidence). Objectively, neither AI nor programmatic summaries sig-nificantly improved or harmed accuracy or comprehension compared to original content. AI summaries offered no significant advantage over simpler programmatic techniques. Content length did not alter these comparative effects, though this result should be observed in an ex-plorative manner. Findings suggest AI summarization may offer no tangible benefit for micro-content within this scope, supporting AI-washing critiques. A cautious, user-centric approach, potentially offering original content options, is recommended.}},
  author       = {{Melander, Erik and Bjelvér, Jakob}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{AI-Generated Summaries Affecting Decision Quality in Microcontent Interactions}},
  year         = {{2025}},
}