Explainable Artificial Intelligence

BEYOND THE BLACK BOX OF CONVENTIONAL AI

In high-risk, high-value industries such as energy, healthcare, and finance there is too much at stake to trust the decisions of a machine at face value, with no explainable understanding of its reasoning. Since machine learning is a component for many AI systems, it’s important for us to know precisely what the machine is learning. Machine learning is a great method for handling lots of data that can tell you the “what.” But for AI systems to become trusted advisors to human decision-makers they need to be able to explain the “why.”

Explainable AI
Artificial Intelligence you can trust

AI deployments are growing rapidly and machines are making decisions where millions of dollars — or even human health and safety — are on the line. In regulated, high-risk/high-value industries such as energy, finance, and healthcare, there’s too much at stake to trust the decisions of a machine at face value, with no understanding of its reasoning. Enterprises are increasingly demanding explainable AI (XAI).

The Problem

For many people, conventional AI techniques like machine learning, deep learning, or neural networks define AI. But the Achilles heel of such conventional AI approaches is that they are “black boxes” that cannot explain how they came up with an answer.

The Solution

In contrast, Beyond Limits' cognitive AI solutions are always “explainable.” Our cognitive engines deliver clear audit trails explaining the human-like reasoning behind their recommendations and showing the evidence, risks, certainties, and ambiguities. These audit trails are designed to be understood by people and interpreted by machines. Explainability is the key to building trust in AI.

How It Works

Explainable AI cannot be implemented as an afterthought or add-on to an existing system. It must be part of the original design. Beyond Limits systems cover the full spectrum of explainability, providing high-level system alerts, plus drill-down reasoning traces with detailed evidence, probability, and risk. Explainable AI helps take the mystery out of the technology and is the first step in enabling artificial intelligence to work with people in a trusting and mutually beneficial relationship.