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Bias (ethics/fairness): Difference between revisions
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Machine learning is like teaching a robot how to do things like humans do. Sometimes, however, the robot may make mistakes due to being taught with poor examples--this is known as "bias". To address this issue, we can ensure the robot receives appropriate examples that mirror what it will be doing in the future, and ensure there are no biases based on skin color or gender. Furthermore, people should check up on the robot's work regularly to guarantee it does an adequate job. | Machine learning is like teaching a robot how to do things like humans do. Sometimes, however, the robot may make mistakes due to being taught with poor examples--this is known as "bias". To address this issue, we can ensure the robot receives appropriate examples that mirror what it will be doing in the future, and ensure there are no biases based on skin color or gender. Furthermore, people should check up on the robot's work regularly to guarantee it does an adequate job. | ||
[[Category:Machine learning terms]] [[Category:Terms]] | [[Category:Machine learning terms]] [[Category:not updated]] [[Category:Terms]] | ||