Social Construction of XAI: Do We Need One Definition to Rule Them All?
Not on the map. Why?
Abstract (arXiv)
There is a growing frustration amongst researchers and developers in Explainable AI (XAI) around the lack of consensus around what is meant by 'explainability'. Do we need one definition of explainability to rule them all? In this paper, we argue why a singular definition of XAI is neither feasible nor desirable at this stage of XAI's development. We view XAI through the lenses of Social Construction of Technology (SCOT) to explicate how diverse stakeholders (relevant social groups) have different interpretations (interpretative flexibility) that shape the meaning of XAI. Forcing a standardization (closure) on the pluralistic interpretations too early can stifle innovation and lead to premature conclusions. We share how we can leverage the pluralism to make progress in XAI without having to wait for a definitional consensus.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 9 of its 16 references that are in the map. First posted on arXiv 11 Nov 2022.
Builds on
9 of 16 references.
References · 9
- 2016Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localizationcited by 6,733
- 2017Explanation in Artificial Intelligence: Insights from the Social Sciencescited by 1,206
- 2018Sanity Checks for Saliency Mapscited by 1,156
- 2021Reframing Human-AI Collaboration for Generating Free-Text Explanationscited by 125
- 2021Expanding Explainability: Towards Social Transparency in AI systemscited by 124
- 2021Human-Centered Explainable AI (XAI): From Algorithms to User Experiencescited by 123
- 2020Human-centered Explainable AI: Towards a Reflective Sociotechnical Approachcited by 90
- 2019Automated Rationale Generation: A Technique for Explainable AI and its Effects on Human Perceptionscited by 81
- 2021The Who in XAI: How AI Background Shapes Perceptions of AI Explanationscited by 48
Built on by
Citing papers per year: 2023: 2; 2024: 2; 2025: 0; 2026: 2.
6 papers.
- 2023Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directionscited by 125
- 2023Charting the Sociotechnical Gap in Explainable AI: A Framework to Address the Gap in XAIcited by 33
- 2024Beyond principlism: Practical strategies for ethical AI use in research practicescited by 7
- 2024In Defence of Post-hoc Explainabilitycited by 1
- 2026Emergent, not Immanent: A Baradian Reading of Explainable AIcited by 0
- 2026Position: Explainable AI is Causality in Disguisecited by 0
- 2026Position: Explainable AI is Causality in Disguise30 Mar 2026
- 2026Emergent, not Immanent: A Baradian Reading of Explainable AI21 Jan 2026
- 2024In Defence of Post-hoc Explainability23 Dec 2024
- 2024Beyond principlism: Practical strategies for ethical AI use in research practices27 Jan 2024
- 2023Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions30 Oct 2023
- 2023Charting the Sociotechnical Gap in Explainable AI: A Framework to Address the Gap in XAI1 Feb 2023