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Computer Vision Leader Fei-Fei Li on Why AI Needs Diversity


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Stanford University professor Fei-Fei Li.

Stanford University computer science professor Fei-Fei Li makes the case for an emphasis on ethnic and gender diversity in artificial intelligence.

Credit: L.A. Cicero/Stanford University

As artificial intelligence (AI) technologies increasingly are deployed to meet industrial and personal needs, the field will need to address its lack of ethnic and gender diversity, according to Stanford University professor Fei-Fei Li.

Women and ethnic minorities in the U.S. are particularly underrepresented in the computer science field, and the problem is expected to be worse in AI. At the recent White House Frontier Conference in Pittsburgh, Li raised three reasons why diversity is an important issue for those researching and developing AI.

She says the current labor force is insufficient to accommodate the amount of work required in the fields of computing and AI. The gross domestic product from automation and machine learning is expected to rise globally, indicating a need for a larger and more diverse workforce.

Another case for diversity is its impact on innovation and creativity, as research shows people working in diverse groups come up with more ingenuous solutions to problems.

Finally, Li says diversity is needed to ensure AI systems operate in a fair manner. Computers learn how to complete tasks through massive datasets compiled by computer scientists. If there is little diversity in the workforce, machines may learn from biased data.

To address these issues, Li suggests applying a humanistic mission statement to the field.

From IEEE Spectrum
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