An Overview of Bias in Aritificial Intelligence

Bias in AI refers to the presence of unfair or unjustifiable assumptions or preferences in the decision-making processes of an AI system. These biases can arise from various sources, including the data used to train the AI, the algorithms used to process that data, or even the biases of the individuals who design and develop the AI system. One of the primary ways in which bias can arise in AI is through the data used to train the system. If the data used to train an AI system is biased towards one particular group of people, it may lead to the system making biased decisions that disadvantage or discriminate against other groups. For example, if an AI system is trained on data that predominantly represents one particular group of people, it may make biased decisions that disadvantage or discriminate against other groups.