  Artificial Intelligence (AI) has demonstrated remarkable capabilities in
domains such as recruitment, finance, healthcare, and the judiciary. However,
biases in AI systems raise ethical and societal concerns, emphasizing the need
for effective fairness testing methods. This paper reviews current research on
fairness testing, particularly its application through search-based testing.
Our analysis highlights progress and identifies areas of improvement in
addressing AI systems biases. Future research should focus on leveraging
established search-based testing methodologies for fairness testing.
