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Many industries have centered on AI-based innovation in their business development. However, trust in AI output is crucial for the broad adoption of AI systems. A natural question arises on how to ensure this trustworthiness. All industrial practices have dedicated phases and personnel for testing in the software development lifecycle towards ensuring reliability for traditional non-AI applications. In this post, I discuss the importance, challenges, and some of IBM Research’s efforts on AI model testing towards ensuring AI trustworthiness.#GlobalAIandDataScience#GlobalDataScience#Hands-on-feature#Highlights-home#News-DS