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Machine learning algorithms' output can be understood and trusted by human users using a set of procedures and techniques known as Explainable Artificial Intelligence (XAI). <br><br>Explainable AI is used to describe an AI model and expected impact and potential biases. It contributes to defining model transparency, correctness, fairness, and outcomes in decision-making system supported by AI. <br><br>When putting AI models into production, a business must first establish trust and confidence. A company and the Open Source community can develop and adopt a responsible approach to AI development with the aid of Explainable AI.<br><br>This session is a brief overview of Open Source and Explainable AI.
