There’s no question about the great potential that AI systems bring to our society. We’ve heard about AI systems identifying cancer tumors, helping to reduce crime as well as predicting traffic accidents. However, we’ve also been made aware of the potential risks of AI: discrimination, bias and complexity. The question that arises is What can we do to obtain trustworthy AI? The focus of this session will be to discuss different types of biases and how to handle these different types of biases in practice to minimize the risk of developing unethical AI systems.
Therése Svensson, M.Sc. in Engineering, is a solution specialist within IBM Data & AI. She has experience from IBM Expert Labs where she was working as a consultant within the area of Data Science, Predictive Analytics and Ethical AI. As a consultant Therése has led projects and technical deliveries targeting a wide variety of industries, including Government, Telco, Oil & Gas, and Banking in local as well as global settings.
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