  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.
