In order for Artificial Intelligence (AI) and Machine Learning (ML) to be useful, it must be trusted. And in order for it to be trusted, there needs to be a way to understand how decisions are being made by intelligence machines. The challenge is that some of the technologies being adopted for AI are not transparent and therefore not trustworthy. What do we need to make AI systems explainable and therefore reliable? This infographic, sponsored by simMachines, explains the details of what Explainable AI (XAI) is all about, what problems it addresses, and some use cases of XAI in practice.

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simMachines is the leader in explainable AI / machine learning technology. Founded in 2012, simMachines offers the most comprehensive explainable machine learning software in the world. simMachines enables data scientists, marketers, analysts and business leaders to achieve significant gains in efficiency, performance and innovation while providing inherently actionable insights delivered with transparency and trust behind every prediction. Find out more about simMachines at


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