Abstract

Ugar and Malele 1 critique the use of ‘generic’ technologies like artificial intelligence (AI) and machine learning (ML) for mental health diagnoses, particularly in sub-Saharan African countries. They highlight how these AI medical tools often overlook traditional perspectives and local contexts. The article has the merit of working on ethical issues regarding the particularities and risks of using AI and ML for health diagnosis in the Global South, an urgent and neglected topic. According to the authors, the use of these AI technologies leads to overgeneralisation in diagnosing mental disorders, which could be especially problematic in the mental health field because of value-laden judgements intrinsic to the definition of mental health disorders. This argument is theoretically grounded in the hybrid conceptualisation of mental disorders proposed by Wakefield. 2 This author’s perspective incorporates both factual and value components in defining mental disorders, framing them as context-dependent ‘harmful dysfunctions’...