Est-ce que vous compute? Code-switching, cultural identity, and AI
This work addresses ethical and epistemic issues in AI for marginalized social groups, but it is incremental as it builds on existing analyses without proposing new methods or data.
The paper tackles the problem of AI systems lacking cultural code-switching capacities, arguing that this oversight risks widening opportunity gaps and entrenching social inequalities for marginalized groups. It introduces the concept of 'cultural smothering' as a form of epistemic oppression linked to AI technologies.
Cultural code-switching concerns how we adjust our overall behaviours, manners of speaking, and appearance in response to a perceived change in our social environment. We defend the need to investigate cultural code-switching capacities in artificial intelligence systems. We explore a series of ethical and epistemic issues that arise when bringing cultural code-switching to bear on artificial intelligence. Building upon Dotson's (2014) analysis of testimonial smothering, we discuss how emerging technologies in AI can give rise to epistemic oppression, and specifically, a form of self-silencing that we call 'cultural smothering'. By leaving the socio-dynamic features of cultural code-switching unaddressed, AI systems risk negatively impacting already-marginalised social groups by widening opportunity gaps and further entrenching social inequalities.