Bias in datasets used to train AI is a significant challenge. AI and machine learning can produce potentially disastrous results if training data sets are not managed. Pradyot Prasoon, director of emerging technologies, American Heart Assoc. Hettie Tabor, director of masters of science in business analytics, SMU Dwayne Paschall, data scientist - machine learning and AI, IDEXX Kalyana Chakravarthy Bedhu, head of AI and data innovation, Ericsson Group

Bias in datasets used to train AI is a significant challenge. AI and machine learning can produce potentially disastrous results if training data sets are not managed. Pradyot Prasoon, director of emerging technologies, American Heart Assoc. Hettie Tabor, director of masters of science in business analytics, SMU Dwayne Paschall, data scientist - machine learning and AI, IDEXX Kalyana Chakravarthy Bedhu, head of AI and data innovation, Ericsson Group

Bias in datasets used to train AI is a significant challenge. AI and machine learning can produce potentially disastrous results if training data sets are not managed. Pradyot Prasoon, director of emerging technologies, American Heart Assoc. Hettie Tabor, director of masters of science in business analytics, SMU Dwayne Paschall, data scientist - machine learning and AI, IDEXX Kalyana Chakravarthy Bedhu, head of AI and data innovation, Ericsson Group

Managing bias in datasets

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Managing bias in datasets

Managing bias in datasets