What is Artificial Intelligence Bias and How to Remove it?

Artificial intelligence (AI) bias is a type of bias that can occur in AI systems. It can be caused by a number of factors, including the data that the AI system is trained on, the way that the AI system is designed, and the way that the AI system is used. There are two main types of AI bias: systematic bias and adversarial bias. Systematic bias is caused by the data that the AI system is trained on. If the data is biased, then the AI system will be biased as well. For example, if an AI system is trained on a dataset of resumes that only includes male applicants, then the AI system will be more likely to recommend male applicants for jobs. Adversarial bias is caused by people who try to manipulate the AI system to produce biased results. For example, someone might try to trick an AI system into thinking that a certain product is better than it actually is by giving the AI system biased reviews. There are a number of ways to remove AI bias. One way is to use bias mitigation techniques. These techniques are designed to identify and remove bias from AI systems. For example, one bias mitigation technique is to use data augmentation. Data augmentation involves artificially increasing the size of the training dataset by creating new data that is similar to the existing data. This can help to reduce the impact of bias in the training dataset. Another way to remove AI bias is to use fairness metrics. Fairness metrics are used to measure the fairness of AI systems. For example, one fairness metric is the equalized odds metric. The equalized odds metric measures the likelihood that two people with the same qualifications will receive the same outcome from an AI system. It is important to note that there is no single way to remove AI bias. The best way to remove AI bias will depend on the specific AI system and the type of bias that is present.