Description: Bias quantification refers to the process of measuring the extent of bias in algorithms or datasets, a crucial aspect of artificial intelligence (AI) ethics. This process involves identifying and assessing the disparities that may arise in the outcomes generated by AI systems, which often reflect inherent prejudices in the data used to train them. Bias quantification is essential to ensure that automated decisions do not perpetuate social inequalities or discriminate against specific groups. Through metrics and statistical analyses, researchers can determine the presence and degree of bias in a model, allowing for adjustments and improvements. This approach not only helps create fairer and more equitable systems but also promotes transparency and accountability in AI technology development. In a world where AI is used in various applications, bias quantification becomes a fundamental tool for addressing ethical and social issues, ensuring that technology benefits everyone equitably.
