Axes for Sociotechnical Inquiry in AI Research

Abstract

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.

9 pages, 1 figure

References in corpus (6)

• Equality of Opportunity in Supervised Learning
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Cited by in corpus (4)

• Auditing large language models: a three-layered approach
• Ethics-Based Auditing of Automated Decision-Making Systems: Intervention Points and Policy Implications
• How to Assess Trustworthy AI in Practice
• Developing and Evaluating a Design Method for Positive Artificial Intelligence