ALGORITHMS AND EQUITY IN THE BRAZILIAN PUBLIC HEALTH SYSTEM (SUS): ETHICAL CHALLENGES OF ARTIFICIAL INTELLIGENCE IN PUBLIC HEALTH
DOI:
https://doi.org/10.56238/levv17n61-036Keywords:
Equity in Health, Ethics, Artificial Intelligence, Public Health, Digital HealthAbstract
OBJECTIVE: To analyze the ethical challenges related to the use of AI algorithms in public health, focusing on the impacts on equity in the Brazilian Unified Health System (SUS). METHODS: This is a narrative literature review, developed from searches in the PubMed/MEDLINE, Scientific Electronic Library Online (SciELO), and Virtual Health Library (BVS) databases. The DeCS/MeSH descriptors “Artificial Intelligence”, “Public Health”, “Health Equity”, “Ethics”, and “Digital Health” were used, combined with the Boolean operators AND and OR. Full articles published between 2021 and 2026, in Portuguese, English, and Spanish, related to artificial intelligence, algorithmic ethics, and public health were included. After applying the eligibility criteria, 7 studies comprised the final analysis. RESULTS: The results demonstrated that AI can contribute to epidemiological surveillance, healthcare organization, and data processing in public health. However, challenges related to algorithmic biases, digital inequalities, lack of interoperability, regulatory weaknesses, and the use of unrepresentative databases were identified, all of which could compromise equity in the Brazilian Unified Health System (SUS). Limitations related to data protection and the transparency of automated decisions were also observed. CONCLUSION: It is concluded that the incorporation of AI in the SUS requires digital governance, ethical regulation, and monitoring mechanisms capable of reducing inequalities and ensuring its use is compatible with the principles of universality, comprehensiveness, and equity in Brazilian public health.
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