Meta's newest AI fairness benchmark measures even more granular bias markers
Tomorrow’s chatbots and visual AIs will only serve to exacerbate this bias unless steps are taken today to ensure a benchmark standard of fairness and equitable behavior from these systems. To address that issue, Meta AI researchers developed and released the, designed to “help researchers evaluate their computer vision and audio models for accuracy across a diverse set of age, genders, apparent skin tones and ambient lighting conditions.
Since Casual Conversations first debuted two years ago, Meta has worked “in consultation with internal experts in fields such as civil rights,” according to Tuesday’s announcement, to expand and improve upon the dataset. Professor Pascale Fung, director of the Centre for AI Research, as well as other researchers from Hong Kong University of Science and Technology, participated in the literature review of government and industry data to establish the new annotation categories.
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