Axes for Sociotechnical Inquiry in AI Research
Not on the map. Why?
Abstract (arXiv)
The development of artificial intelligence (AI) technologies has far exceeded the investigation of their relationship with society. Sociotechnical inquiry is needed to mitigate the harms of new technologies whose potential impacts remain poorly understood. To date, subfields of AI research develop primarily individual views on their relationship with sociotechnics, while tools for external investigation, comparison, and cross-pollination are lacking. In this paper, we propose four directions for inquiry into new and evolving areas of technological development: value--what progress and direction does a field promote, optimization--how the defined system within a problem formulation relates to broader dynamics, consensus--how agreement is achieved and who is included in building it, and failure--what methods are pursued when the problem specification is found wanting. The paper provides a lexicon for sociotechnical inquiry and illustrates it through the example of consumer drone technology.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 27 of its 89 references that are in the map. First posted on arXiv 26 Apr 2021.
Builds on
27 of 89 references.
References · 27
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15 more
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Built on by
Citing papers per year: 2022: 2; 2023: 1; 2024: 2.
5 papers.
- 2023Auditing large language models: a three-layered approachcited by 137
- 2022Reward Reports for Reinforcement Learningcited by 18
- 2024Search Engines in an AI Era: The False Promise of Factual and Verifiable Source-Cited Responsescited by 15
- 2024Roadmap on Incentive Compatibility for AI Alignment and Governance in Sociotechnical Systemscited by 6
- 2022Lost in Translation: Reimagining the Machine Learning Life Cycle in Educationcited by 1
- 2024Search Engines in an AI Era: The False Promise of Factual and Verifiable Source-Cited Responses15 Oct 2024
- 2024Roadmap on Incentive Compatibility for AI Alignment and Governance in Sociotechnical Systems20 Feb 2024
- 2023Auditing large language models: a three-layered approach16 Feb 2023
- 2022Lost in Translation: Reimagining the Machine Learning Life Cycle in Education8 Sep 2022
- 2022Reward Reports for Reinforcement Learning22 Apr 2022