To highlight the contributions of women in the field of AI, TechCrunch has been conducting a series of interviews with influential women who have played a significant role in the AI revolution. One of these remarkable women is Chinasa T. Okolo, whose research focuses on the impact of AI on the Global South. These profiles are being published throughout the year to bring attention to important work that is often overlooked. Read more profiles here.
Chinasa T. Okolo is a fellow at the Brookings Institution in the Center for Technology Innovation’s Governance Studies program. She has been involved in shaping AI policy and ethics, including contributing to Nigeria’s National Artificial Intelligence Strategy. Chinasa recently completed her Ph.D in computer science at Cornell University, where she studied how AI affects the Global South.
How did you initially get involved in AI and what drew you to the field?
I was initially drawn to AI by its potential to advance biomedical research and improve healthcare accessibility for marginalized communities. During my undergraduate studies at Pomona College, I began researching human-computer interaction, which exposed me to the issue of bias in AI. This sparked my interest in understanding how AI bias impacts the Global South, where many populations are underrepresented in AI development.
What accomplishment in the field of AI are you most proud of?
I take great pride in my work with the African Union on developing the AU-AI Continental Strategy for Africa. This strategy aims to facilitate responsible adoption, development, and governance of AI by AU member states. After over a year of drafting, the strategy was released in late February 2024 and is currently in an open feedback period, with plans for formal adoption in early 2025.
As a first-generation Nigerian-American with a passion for working in Africa, this opportunity to contribute to impactful AI governance has energized me to pursue similar initiatives.
How do you navigate the challenges of working in the male-dominated tech and AI industries?
Building a community with like-minded individuals who share my values has been crucial in overcoming the obstacles presented by male-dominated industries. I have been fortunate to connect with prominent Black female scholars in AI, whose leadership and research have inspired me to continue pushing boundaries and making a difference in the field.
What advice do you have for women interested in entering the AI field?
Don't be discouraged by a lack of technical background. The field of AI requires diverse expertise from various domains, including sociology, anthropology, cognitive science, and philosophy. My research has been enriched by insights from these disciplines.
What are some of the most critical issues facing the evolution of AI?
One pressing issue is the need to improve the representation of non-Western cultures in AI models and datasets. The dominance of English language and Western contexts in AI training data excludes valuable perspectives from the majority of the world's population.
Furthermore, the pursuit of larger AI models poses environmental concerns, as their development contributes to resource depletion and climate change impacts, disproportionately affecting Global South countries.
What should AI users be aware of regarding the limitations of AI?
Many AI tools oversell their capabilities and may not deliver as promised. Simple algorithms or basic automation may be sufficient for tasks that people attempt to solve with AI. Additionally, generative AI has the potential to exacerbate biases and harmful decision-making, underscoring the importance of AI and data literacy in society.
How can AI be responsibly developed?
Building AI responsibly requires a critical examination of the intended and unintended uses of AI tools. Developers must reject applications of AI for harmful purposes in areas like warfare and policing, and seek external guidance on appropriate use cases. Ensuring that AI development is mindful of existing social inequalities is crucial in dataset curation and model building.
How can investors promote responsible AI development? Many argue that venture capitalists focusing on profiting from AI have contributed to the rise of misleading AI technologies. Investors, along with academic, civil society, and industry partners, must advocate for responsible AI. It is essential for investors to invest in AI expertise for vetting companies and requesting external audits of AI tools.
Is there anything else you would like to share?
The current surge in AI development has led to an influx of self-proclaimed “AI experts” who may obscure important conversations about AI risks and capabilities. I encourage those seeking knowledge about AI to critically evaluate sources and seek reliable information from reputable experts.
