Description: XAI techniques (Explainable Artificial Intelligence) are methods used to make AI systems more interpretable and transparent. These techniques aim to demystify the functioning of machine learning algorithms, allowing users to understand how and why certain decisions are made. The importance of XAI lies in the increasing adoption of AI in critical sectors such as healthcare, justice, and finance, where automated decisions can significantly impact people’s lives. XAI techniques include approaches such as data visualization, generating local and global explanations, and using simpler models that are inherently more understandable. By providing clarity on the decision-making process of AI, these techniques foster user trust and help identify biases and errors in models, which is essential for ensuring fairness and ethics in the application of artificial intelligence. In a world where AI is increasingly integrated into our lives, XAI techniques become a crucial component to ensure that these technologies are used responsibly and effectively.
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