How Explainable AI Could Transform the Insurance Industry
Artificial intelligence (AI) is growing and taking over more aspects of business. Many people are unsure of AI because of its lack of explanation when coming to a conclusion.
Explainable AI (XAI) is bridging the gap between those who already trust AI and those who want more explanation when it comes to receiving information from artificial intelligence. But what is explainable AI?
What is Explainable AI?
In simple terms, explainable AI is machine learning with the ability to describe how the machine arrived at the answer it came to. This is different than regular AI that outputs an answer. One way to think of XAI is “showing your work,” like you would have done in your middle school math class.
The goal of XAI is to explain how it came to the conclusion it came to in a way the average person can understand.
Some information included in explanations that XAI give includes
- program strengths and weaknesses.
- Criteria used to come to a conclusion.
- Why it made a particular decision.
- What level of trust is appropriate.
- Errors the system is prone to.
- How to correct errors.
Explainable AI is machine learning with the ability to describe how the machine arrived at the answer it came to.
Does the World Really Need XAI?
There are a lot of discussions when it comes to the reliability of AI. Explainable AI is contributing to solving this problem with the user’s ability to look at how the problem is solved and the ability to decide to what degree they want to trust the answer that is given.
According to Swathi Young, host at Women in AI, “most businesses believe that machine learning models are opaque, non-intuitive and no information is provided regarding their decision-making and predictions,” so with XAI human users can look at what information is used to come to the decision given.
What Does XAI Mean for the Insurance Industry?
It is important for insurance carriers and adjusters to have all the necessary information when making decisions. AI has become complex and people who benefit from using the technology want to see how the program comes to its decision.
For the insurance industry, this means a human can analyze the conclusion the machine comes to and decide whether to follow the decision.
Techopedia outlines three benefits of XAI for the insurance world:
- Those managing the model are held more accountable.
- When the results have an explanation, the user is more likely to act on them.
- Users can contribute their expertise to the final decision.
XAI is increasing user confidence, and the adoption of artificial intelligence in the insurance industry will continue to help businesses grow past their initial expectations and bring better outcomes to clients.
