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Bias in Machine Learning Panel

March 2 @ 6:00 pm - 7:30 pm

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Machine learning (ML) is a method of data analysis that automates analytical model building. ML not only encompasses algorithmic learning systems but also includes various types of artificial intelligence (AI) that rely on these algorithms. Advancements in the field of ML have been steadily increasing and have garnered the attention of a variety of industries and professions. In real-world applications, ML has been found to contain biases that affect various groups of people. Industry researchers and academics have been looking into this issue and have found that there are three overarching types of biases: bias in action perception systems, unfair bias, and discriminatory illegal bias. As ML continues to grow in popularity, this panel will present a diverse range of speakers who will discuss the origins of bias in ML, the ethics of using ML on a large scale, and the risks of ML bias specific to various fields.


Location TBA
UC Berkeley
Berkeley, CA United States
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