As Artificial Intelligence systems become increasingly complex, the need for transparency and trust has led to the emergence of Explainable AI (XAI). XAI focuses on making AI decisions understandable to humans, fostering trust and facilitating better decision-making.
Importance of XAI:
Transparency: Provides clear insights into how AI models arrive at specific conclusions.
Accountability: Enables identification and correction of biases within AI systems.
Regulatory Compliance: Assists organizations in meeting legal requirements related to AI deployments.
Implementing XAI involves developing models that balance performance with interpretability, ensuring that AI systems are both effective and trustworthy.