As we increasingly rely upon artificial intelligence (AI) systems to support human decision-making, insurance businesses are under pressure to produce interpretable data.

And while AI has tremendous benefits, it would be naïve to rely purely on the ‘black box’ as this could come at the cost of alienating customers.

However, one way insurance companies can ensure that the AI data and algorithms they use for critical decisions are not biased or otherwise untrustworthy, is taking a ‘glass box to AI.

Glass boxing, also known as white boxing, is a system of AI modelling that enables insurance companies to understand how AI programs come up with their predictions.

Ultimately, this enables clear communication and a proper explanation for end-user customers about how their data is being used.

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