Most AI isn't Explainable

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Neural networks are fast becoming the standard for high accuracy in modern AI applications. The problem with neural networks is that the data rules they learn are not easily explainable. Even traditional data science approaches don't offer the explainability needed to mitigate risk, promote trust and ultimately support adoption. No AI model is perfect, and the risk of being held accountable for decisions that aren't adequately understood is the number one barrier to AI adoption in the enterprise.

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Humans Need to Understand AI to Support Decisions

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A recent survey puts this into context, with only 20% of companies taking full advantage of AI in their decision making. The key reason these companies are struggling with AI adoption? They don't trust the AI's answers because they don't understand how it made those conclusions. Businesses need to clearly understand how an AI application makes its decisions to trust the outputs and mitigate the risks. In today's digital world, AI is often the only solution for making sense of vast amounts of information. Still, humans must be kept in the loop to promote trust, enable adoption and subsequently derive value from AI applications, which is why explainability is a core component of Oscar Enterprise AI (Oscar), not just a concept but a set of product features. 

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We Provide Explainable AI as Product Features not just a Concept

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Our data scientists and engineers designed Oscar to give model feedback to users, allowing you to trace the machine's reasoning and see how it has reached its conclusions. Explainable AI (XAI) isn't an afterthought with Oscar; it was designed from the ground up to be a trustworthy platform for enterprise AI which means the inclusion of XAI at its core. Furthermore our patented Artificial Precognition technology uses proprietary decision tree algorithms that are innately explainable. Enabling us to explain our exceptionally accurate predictions in a way that makes sense to all users. For a complete list of features, check out our white paper on XAI in Oscar.