"That's important, but...": How Computer Science Researchers Anticipate Unintended Consequences of Their Research Innovations
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Abstract (arXiv)
Computer science research has led to many breakthrough innovations but has also been scrutinized for enabling technology that has negative, unintended consequences for society. Given the increasing discussions of ethics in the news and among researchers, we interviewed 20 researchers in various CS sub-disciplines to identify whether and how they consider potential unintended consequences of their research innovations. We show that considering unintended consequences is generally seen as important but rarely practiced. Principal barriers are a lack of formal process and strategy as well as the academic practice that prioritizes fast progress and publications. Drawing on these findings, we discuss approaches to support researchers in routinely considering unintended consequences, from bringing diverse perspectives through community participation to increasing incentives to investigate potential consequences. We intend for our work to pave the way for routine explorations of the societal implications of technological innovations before, during, and after the research process.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). First posted on arXiv 27 Mar 2023.
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Citing papers per year: 2024: 4; 2025: 3; 2026: 1.
8 papers.
- 2024Farsight: Fostering Responsible AI Awareness During AI Application Prototypingcited by 28
- 2025Understanding the LLM-ification of CHI: Unpacking the Impact of LLMs at CHI through a Systematic Literature Reviewcited by 16
- 2024Particip-AI: A Democratic Surveying Framework for Anticipating Future AI Use Cases, Harms and Benefitscited by 9
- 2025Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigorcited by 7
- 2024BLIP: Facilitating the Exploration of Undesirable Consequences of Digital Technologiescited by 6
- 2024Data Ethics Emergency Drill: A Toolbox for Discussing Responsible AI for Industry Teamscited by 3
- 2025Societal AI Research Has Become Less Interdisciplinarycited by 0
- 2026Position: The Alignment Community is Unintentionally Building a Censor's Toolkitcited by 0
- 2026Position: The Alignment Community is Unintentionally Building a Censor's Toolkit5 Jun 2026
- 2025Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor17 Jun 2025
- 2025Societal AI Research Has Become Less Interdisciplinary10 Jun 2025
- 2025Understanding the LLM-ification of CHI: Unpacking the Impact of LLMs at CHI through a Systematic Literature Review22 Jan 2025
- 2024BLIP: Facilitating the Exploration of Undesirable Consequences of Digital Technologies10 May 2024
- 2024Particip-AI: A Democratic Surveying Framework for Anticipating Future AI Use Cases, Harms and Benefits21 Mar 2024
- 2024Data Ethics Emergency Drill: A Toolbox for Discussing Responsible AI for Industry Teams15 Mar 2024
- 2024Farsight: Fostering Responsible AI Awareness During AI Application Prototyping23 Feb 2024