Artificial intelligence for Amazonian health: validation is the price of entry
At the AI as Catalyst meeting in Manaus (July 28–29, 2026; https://ia-como-catalisadora-manaus.netlify.app), participants ran a simple exercise. Working in teams, they wrote about ten clinical cases and put each one to widely used general-purpose chatbots twice: first in standard medical terminology, then in the terms and expressions a patient from the Amazon might use, with the same clinical facts, but carried by local language. The register of the answers changed with the framing, and so did their technical depth; more consequentially, the models inferred conditions from how the patient spoke rather than from what the case described.
Authors
- Leo Celi
- Luis Nakayama
- Michella Lasmar
- Gustavo Monnerat
- Matheus Serrao (ORCID: https://orcid.org/0009-0009-6836-121X)
Institutions
- Harvard University (US)
- Universidade de São Paulo (BR)
- Regional Health (US)
- Brazilian Society of Computational and Applied Mathematics (BR)
- Universidade do Estado do Amazonas (BR)
- Massachusetts Institute of Technology (US)
- Universidade Federal de São Paulo (BR)
Publication Details
- Journal
- The Lancet Regional Health - Americas
- Published
- 2026-09-05
- DOI
- https://doi.org/10.1016/j.lana.2026.101627
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Massachusetts Institute of Technology