Ethiopian-born Rediet Abebe is a computer scientist with a strong interest in the promotion of equality and justice. She co-founded and co-organizes Black in AI, an international network of individuals focused on increasing the presence and inclusion of Black and African researchers in artificial intelligence

By Rediet Abebe (Forbes Insight) |

While artificial intelligence (AI) has the potential to solve an incredible spectrum of problems and challenges in our lives, our work and our world, there is a widening disconnect between the people who are introducing and deploying AI-based solutions and those who set policies for when and how these solutions are used.

Much has been written about one consequence of this disconnect—algorithmic bias in AI systems, in which machine learning algorithms trained on data that reflects historical discrimination replicate and even magnify it. But there’s another pressing issue: There are many missed opportunities to use AI for the good of many.

Just as AI systems susceptible to bias are a problem, so too is inadequate focus on contributions that improve the lives of marginalized communities, such as Black and brown individuals, economically vulnerable populations and many other groups whose interests are underserved in society. If teams that set research directions, write algorithms or deploy them are made up of individuals with similar backgrounds and experiences, then we will end up with research that is to the benefit of a similarly narrow and already privileged subset of society.

I see this gap in action every day. I was born and raised in Ethiopia, a country with a beautiful culture and history, but also a country that continues to face challenges that are distinct from those in the United States. So I look out for AI research focused on helping the people of Ethiopia and the people of Africa more generally. More often than not, however, I find a conspicuous lack of such research.

At many of the AI conferences that I attend, few research papers focus on problems that specifically affect people in Africa. Research communities that do, such as Information Communication Technology for Development (ICT4D), are still not fully integrated with the AI community as a whole. None of this will change without adequate representation of diverse viewpoints on research teams; only then will we able to produce research that serves the diverse needs of communities throughout the world.

Continue reading this story at Forbes 
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