Bias problem in AI and ML. Now a days Artificial intelligence…

Now a days Artificial intelligence systems are critical for companies that wish to extract value from data by automating and optimizing processes or producing actionable insights but a concept named "Bias problem" comes into picture in situations where ML-based data analytics systems show bias against certain groups of people when predicting the output. The bias problem occurs when the training data which is being fed into a Machine learning model is more inclined towards a certain category of group in the input set. Due to this when the machine is trained with this data, the output generated by Machine learning model is more inclined towards the certain feature which leads to incorrect prediction of output. Bias can make way into algorithms in several ways. AI systems learn to make decisions based on training data, which can include biased human decisions or reflect historical inequities.