Explaining the ghosts: Feminist intersectional XAI and cartography as methods to account for invisible labour
This addresses the issue of underpaid and invisibilized labor in AI for stakeholders like workers and users, but it is incremental as it builds on existing feminist and XAI concepts.
The paper tackles the problem of invisible human labor in AI systems by proposing feminist intersectional XAI and cartography as methods to sensitize users to this labor, aiming to make it visible and accounted for in AI design.
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.