Cases › biased or discriminatory › LR-2026-0546
Kenya Social Health Authority means testing algorithm overcharges poor households and undercharges the wealthy
Preliminary Why: Publisher not yet named · subject to change
Developing: a major or severe case captured in the last 72 hours. Later changes are logged on the corrections page.
Status: no action reported
No source states: loss or records, developer and model, agent tool, could do, deployer, industry.
Severity major: Test: many third parties (a stated count of two or more). Fact: the model has calculated the public healthcare premiums of millions of Kenyans.
Kenya's Social Health Authority deployed a machine-learning means testing model, a linear regression trained on the 2021 Kenyan Continuous Households Survey, to set health insurance contributions for informal-sector workers. Under the reforms, workers pay 2.75 percent of estimated income. Lighthouse Reports, with Africa Uncensored and The Guardian, reconstructed the model from released training data, variables and formula. Their analysis found it overcharged the poorest households and undercharged the wealthiest. Among the poorest households, 80 percent had consumption overpredicted. An IDinsight evaluation before the 2024 launch had found the model inequitable, particularly for low-income households. The Social Health Authority did not respond to the detailed findings. The investigators note that their reconstruction may not match the deployed model exactly.
What happened
No source tells the story step by step yet.
What was done
No source states an action or fix.
Risks
Read from the sources; not yet reviewed by a person.
Controls
Not yet read for controls. Controls that mitigate the primary risk:
ApplicationBias testing · Risk assessment per deployment · Output filtering and redaction
Evidence
No source states: a step-by-step account, when it happened, when it was found, how many records were exposed, the direct loss, a count of the other parties affected, any court case, the cause, what set it off, what was done.
Show the full account: 2 items from the primary sources
What happened, in order
- 2025-08 Africa Uncensored sends a public access request for the model formula, variables and weights.
- 2025-11 The Social Health Authority responds, confirming training on the 2021 KCHS and disclosing the formula and variables but not the coefficients.
Show every field, with its source and grade
The AI system
What happened
Impact
Notes on gaps
The sources are a single press investigation by Lighthouse Reports. The IDinsight recommendations were not confirmed as adopted; SHA's later FOI account differed, and no fix was reported, so remediations is empty. The reconstruction was made by the investigators and may not match the deployed model; the SHA did not respond to the findings. No other controls are stated as held, failed or missing, so none are listed.
LR-2026-0546 · version 1 · published 2026-11-01 after automatic checks; not yet checked field by field by a person · JSON