Artificial intelligence (AI) as an emerging technology continues to be deployed in many different areas and for many different applications. Brookings brought us this interesting information in their article, “Using AI and machine learning to reduce government fraud.”

Both public and private sector organizations are coming to rely on AI to manage financial resources and monitor fraud. Advanced algorithms can spot abnormalities and outliers. Human investigators then determine if fraud has actually taken place.

Most organizations have little knowledge regarding how AI systems make decisions, and as a result, they are unprepared to utilize any output. Explainable AI allows users to comprehend and trust the results and output created by machine learning algorithms. Explainable AI is used to describe an AI model, its expected impact and its potential biases. Explainability becomes critical when the results can have an impact on data security or safety.

Melody K. Smith

Data Harmony is an award-winning semantic suite that leverages explainable AI.

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