The emergence of bias in artificial intelligence (AI) presents a significant challenge in the realm of algorithmic decision-making. AI models often mirror the data on which they are trained. It can unintentionally include existing societal biases, leading to unfair outcomes. To overcome this issue, continuous monitoring and validation emerge as critical processes which are essential for ensuring that AI models function ethically and impartially over time.
Understanding Bias in AI
Bias in AI is dynamic and evolving with societal shifts, trends, and application domains. This dynamic nature of bias needs an approach that continuously assesses and adjusts for it.