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Trust is key to gaining acceptance of AI technologies from customers, employees, and other stakeholders. As AI becomes increasingly pervasive, the ability to decode and communicate how AI-based systems reach conclusions will be fundamental to their widespread adoption. AI can't be seen as an impenetrable black box, to be accepted without question. Transparency and clear explanations about AI sourcing, machine learning, algorithms, language models, and evolving AI technologies support trustworthiness. From a technical perspective, interpretable models facilitate easier debugging, more effective model refinement, and smoother integration of AI into existing organizational workflows. How AI reaches its conclusions and drives its predictions should be explainable to be trusted.
Don't miss this live event on Wednesday, June 4th, 11:00 AM PT / 2:00 PM ET.
Register Now to attend the webinar Explainability and Interpretability: Building Trustworthy AI Models.
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