Battling Bias: AI's Fight for Fairness

As artificial intelligence (AI) continues to play a significant role in various industries and aspects of daily life, the issue of bias in AI algorithms has become increasingly prevalent. Biased AI systems can perpetuate existing social inequalities and lead to unfair treatment, creating a critical need for addressing and mitigating discrimination in machine learning applications. Bias in AI can originate from several sources, such as biased training data, lack of diversity in AI development teams, and biased algorithms themselves. Training data is the foundation of any AI system, and if the data used to train an algorithm contains biases, those biases will be passed on to the AI system. For example, biased facial recognition systems have been found to misidentify people of color at a higher rate than white individuals, leading to wrongful arrests and other consequences.