Explaining the ghosts: Feminist intersectional XAI and cartography as methods to account for invisible labour
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Abstract (arXiv)
Contemporary automation through AI entails a substantial amount of behind-the-scenes human labour, which is often both invisibilised and underpaid. Since invisible labour, including labelling and maintenance work, is an integral part of contemporary AI systems, it remains important to sensitise users to its role. We suggest that this could be done through explainable AI (XAI) design, particularly feminist intersectional XAI. We propose the method of cartography, which stems from feminist intersectional research, to draw out a systemic perspective of AI and include dimensions of AI that pertain to invisible labour.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 4 of its 38 references that are in the map. First posted on arXiv 5 May 2023.
Builds on
4 of 38 references.
References · 4
- 2019Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AIcited by 1,543
- 2020Human-centered Explainable AI: Towards a Reflective Sociotechnical Approachcited by 90
- 2018Stakeholders in Explainable AIcited by 48
- 2022Sensible AI: Re-imagining Interpretability and Explainability using Sensemaking Theorycited by 32
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Citing papers per year: 2026: 1.
1 paper.
- 2026Emergent, not Immanent: A Baradian Reading of Explainable AI21 Jan 2026