Exposing the Shortcuts: Improving Fairness of Artificial Intelligence in the Connected World
At the Warren B. Nelms Institute for the Connected World, located in the Herbert Wertheim College of Engineering on the University of Florida campus, My T. Thai, Ph.D., professor in the Department of Computer & Information Science & Engineering and associate director of the Institute, is developing software technologies that can explain how bias can creep into artificial intelligence (AI) algorithms. Her work is helping users who work with AI technology to extract analyses and predictions that are accurate and as close to reality as possible, as opposed to nominal, or worse, prejudiced and unfair.
Dr. Thai, funded by a grant from the National Science Foundation (NSF) and working with industry partner Amazon, is currently developing software technologies to help identify and explain where and how bias enters AI algorithms. “Using AI models as ‘black boxes’, without knowing why the model made a particular decision about the data, degrades the trustworthiness of the system,” Dr. Thai said. If the AI begins to use shortcuts, such as discounting any data that is not provided in a specific format designated by the machine learning tools used to train it, bias can begin to creep into the AI technology.
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