Exploring Digital Exclusion in Emerging Economies Through AI Policy Research
The Problem: AI policy discussions often exclude SMEs in low-data, low-connectivity contexts leading to tools and systems that are unusable, unaffordable and irrelevant at the local level.
The Work
Ethics Research & Policy Exploration
Led a short-form research initiative examining how AI models exclude smaller data environments. Explored bias in data access, model assumptions, and systemic exclusion.
Relevance to Education: Informs how student data, especially from underrepresented groups or institutions, may be misrepresented or overlooked in AI-powered education tools.
The Insight
Most “responsible AI” conversations are built around enterprise assumptions bandwidth, budget, data access. This project surfaced five key intervention points for shifting toward more inclusive AI ecosystems.

Why It Matters
This work is the backbone of my long-term research into AI inclusion, ethical system design, and global policy adaptation — and fuels the writing I now publish through my Substack.

Tools Used
- Google scholar
- Notion
- Canva (for visual brief)
- Desk research sources
Skills Highlighted
- Policy analysis
- Research synthesis
- Stakeholder interviews
- Writing for policy audiences
- Equity-centered design
- Contextual system thinking
