Bias in AI refers to systematic errors or prejudices that can occur within AI systems due to biased training data, faulty algorithms, or human biases. Addressing bias in AI is crucial for ensuring fairness, inclusiveness, and ethical practices in AI applications.
Explainable Artificial Intelligence focuses on developing AI systems that can provide understandable explanations for their decisions and behaviours. Transparent and interpretable AI models are…
