# How can we reduce bias in AI tools used for mental health in African settings?

URL: https://tymirahealth.com/resources/faqs/how-can-we-reduce-bias-in-ai-tools-used-for-mental-health-in-african-settings
For: Digital health teams | Digital health and technology | Reviewed by Independent clinical reviewer, Registered mental health clinician, Kenya | Last reviewed 8 November 2026

**Answer:** Models trained mostly on data from other regions and languages may perform worse for African users, misread local idioms of distress or under-detect risk. Ask vendors what data trained and validated the model, test it on representative local cases, including Kiswahili and code-switched text, and compare accuracy across groups such as gender, age and language. WHO recommends inclusive design involving clinicians and patients from the start. Keep a human in the loop and drop tools that cannot show acceptable local performance.

Sources: World Health Organization: https://iris.who.int/handle/10665/375579 - World Health Organization: https://www.who.int/news/item/20-03-2026-towards-responsible-ai-for-mental-health-and-well-being--experts-chart-a-way-forward - World Health Organization: https://icd.who.int/browse/2024-01/mms/en

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**About Tymira Health:** Tymira Health is a healthcare technology company based in Nairobi, Kenya. It builds Tymira360, a practice management and EHR platform for mental health, physiotherapy and dental providers, clinics, hospitals, NGOs and insurers across Africa.

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