Overview of Bias and Fairness in AI
Speaker(s): Somaieh Nikpoor
Host: Serena McDonnell
Find the recording, slides, and more info at https://ai.science/e/bias-and-fairness-in-ai-overview-of-bias-and-fairness-in-ai--5mYsxRyBkVwApJhhJhH4
Motivation / Abstract
Many companies are looking to deploy AI systems across their operations. AI can help identify and reduce the impact of human biases, but it can also make the problem worse by deploying biases at scale. The first part of this presentation covers the different types of bias and the definition of fairness in the algorithm. The second part reviews the paper “Model Cards for Model Reporting” by Margaret Mitchelle and Simone Wu, et al (2018).
About the speaker:
Somaieh Nikpoor is a Research Advsior in AI/ML for the Government of Canada. She received her PhD from the University of Ottawa in Economics.
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#AISC hosts 3-5 live sessions like this on various AI research, engineering, and product topics every week! Visit https://ai.science for more details
Speaker(s): Somaieh Nikpoor
Host: Serena McDonnell
Find the recording, slides, and more info at https://ai.science/e/bias-and-fairness-in-ai-overview-of-bias-and-fairness-in-ai–5mYsxRyBkVwApJhhJhH4
Motivation / Abstract
Many companies are looking to deploy AI systems across their operations. AI can help identify and reduce the impact of human biases, but it can also make the problem worse by deploying biases at scale. The first part of this presentation covers the different types of bias and the definition of fairness in the algorithm. The second part reviews the paper “Model Cards for Model Reporting” by Margaret Mitchelle and Simone Wu, et al (2018).
About the speaker:
Somaieh Nikpoor is a Research Advsior in AI/ML for the Government of Canada. She received her PhD from the University of Ottawa in Economics.
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#AISC hosts 3-5 live sessions like this on various AI research, engineering, and product topics every week! Visit https://ai.science for more details
