Machine Learning Bias

Machine Learning Bias Machine learning bias, also sometimes called algorithm bias or AI bias, is a phenomenon that occurs when an algorithm produces results that are systemically prejudiced due to erroneous assumptions in the machine learning process. Machine Learning bias generally occurs when an individual design or train the machine learning systems. They maybe making the systems according to their understanding of what’s right but that might not be the case for other person which makes the machine learning systems bias. For example: The machine learning models were tested to see if they contain the bias and data were given in the following way:- Men->King Women-> ? The answer was very fascinating as the machine learning model predicted that if Men-> king, then Women->Housewife. Which might was very disturbing to people and the question arised why did the model predict that. This is because the data on which the model was trained was given certain examples that make women less valuable in terms of responsibility as men. These biases can be solved by involving people of various ideologies so that there may not be a system that might be fair to some people and unfair to other.

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