Responsible Artificial Intelligence Integration in Medical Student Education in Somalia and Low-Resource Settings: A Context-Sensitive Implementation Framework
Mohamed Mohamud Ali, Abdullahi Abdirahman Omar · 2026
Read Responsible Artificial Intelligence Integration in Medical Student Education in Somalia and Low-Resource Settings: A Context-Sensitive Implementation Framework by Mohamed Mohamud Ali, Abdullahi Abdirahman Omar (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13590255.txt.
Description
Ali and Omar propose a framework for artificial intelligence in Somali medical education, in work from twenty twenty-six. Students now use generative tools more and more for explanation, revision, simulation, and feedback. Institutional governance has not kept pace with that use. The gap is worst of all in low resource settings.
Somalia has more than a hundred health professions schools, many in urban areas. Access to faculty and to simulation is uneven across those schools. Their context sensitive framework aims for responsible integration that fits those limits. It deals with equity, oversight, and assessment integrity. A grounded framework can help similar countries adopt the tools without widening training gaps.
Catalog record
| CREATOR | Mohamed Mohamud Ali, Abdullahi Abdirahman Omar |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 32 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |