Large companies like Google, Apple, OpenAI, for example, have not necessarily trained their models for tools that serve these markets. They don’t provide enough market value for them to..."
Dr. Chinasa T. Okolo is a fellow in the Center for Technology Innovation in the Governance Studies program at Brookings and a recent computer science Ph.D. graduate from Cornell University. Her research focuses on AI governance in emerging markets, AI literacy upskilling, human-centered approaches to AI explainability, the future of data work, and leveraging AI to advance global health.
At Cornell, Dr. Okolo’s dissertation research incorporated ethnographic methods to understand how frontline healthcare workers in rural India perceive and value AI. Her work also examined how explainability can be best leveraged in AI-enabled technologies deployed throughout the Global South, with a focus on healthcare. Outside of her dissertation focus, Dr. Okolo also conducted research examining the effective adoption and successful implementation of AI in Africa, COVID-19 misinformation spread on social networks within African communities, and the impact of generative AI within Africa.
Dr. Okolo’s research has been published at top-tier venues in HCI and sociotechnical computing (ACM CHI, CSCW, and COMPASS). Her work has been supported by funding from The National GEM Consortium, Oracle Corporation, the North American Network Operators’ Group (NANOG), the National Science Foundation (NSF), and Google and covered in venues like VICE, Bloomberg, Newsweek, The Washington Post, and VentureBeat, amongst others. She has been invited to share her work at industry research labs including Google Research India, Microsoft Research India, and the Microsoft Africa Research Institute (MARI). Dr. Okolo has also been recognized as a Trailblazer in Engineering, a Rising Star in Management Science & Engineering, and one of 100 Brilliant Women in AI Ethics™.
Dr. Okolo holds a B.A. in computer science from Pomona College, a M.S. in computer science from Cornell University, and a Ph.D. in computer science from Cornell University. She also serves as a Consulting Expert with the African Union, contributing to the development of the AU-AI Continental Strategy for Africa, and as an Ethics Advisor to the Equiano Institute, a research lab focused on steering safe and trustworthy AI in Africa. Additionally, Dr. Okolo participates in the IEEE Standards Association working group on algorithmic bias and is a member of the ACM US Technology Policy Committee.
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Areas of Expertise
- Human-centered AI
- Explainable AI
- Information & Communication Technologies for Development
- AI Literacy
- Data Economies
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Education
- Cornell University, Computer Science, Ph.D.
- Cornell University, Computer Science, M.S.
- Pomona College, Computer Science, BA
Media Coverage
Chinasa Okolo was named one of TIME’s top 100 most influential people in AI of 2024 for her efforts in ensuring those living in the Global South are not victims of biased systems and...
“Large companies like Google, Apple, OpenAI, for example, have not necessarily trained their models for tools that serve these markets”
We don’t necessarily know its full capacity, and so it’s kind of hard to predict…by the time regulators or policymakers have drafted up some sort of legal framework, it could already be..."
Nigeria has that human capacity to build out the model, and potentially sustain it. But I think that the infrastructure is really the biggest roadblock to that…
Thus, by investing in Africa, companies from AI superpowers like the U.S. and China stand to gain valuable data that they could use to build services and systems to be sold back to..."
We’re seeing a growth of AI in the continent; it’s really important there be set rules in place to govern these technologies…
“There is much more work needed to understand the harms of AI development and increase labor protections for data workers, who are often left out of conversations on the responsible..."
“Primary conversations at the summit revolve around the risks that ‘frontier models’ pose to society,” she says, “but leave out the harms that AI causes to data labelers, the workers..."