Four of the biggest ethical challenges when using AI in insurance

According to experts on a Reuters panel, there are four major ethical challenges faced by insurance professionals today, when it comes to using AI.

The four challenges insurance professionals face are: built-in bias, human talent, transparency, and regulation, according to the panel. They suggested these uncertainties can be addressed, but stressed the urgency of doing so in a landscape where AI in insurance may become “table stakes” in the next 12-24 months.

“I would say put your principles in place, set the guardrails, and then go build a thing. Get out there, build something, make sure you evaluate it deeply and understand exactly how it’s going to perform in the real world, but get out there and build something,” Patrick Miller, head of data & AI, Newfront, said.

“Look, you don’t want to wake up three years from now and not move the needle. That is absolutely the wrong answer. You have to keep that top of mind and keep pushing forward,” Richard Wiedenbeck, Chief AI Officer, Ameritas, added.

Challenge 1: Built-in bias

One of the most frequently discussed challenges with using artificial intelligence in insurance relates to existing biases being built into AI tools and the data or language models upon which that knowledge base is formed.

For instance, Suzanne Grover, VP, underwriting, Coastal Wealth, pointed to people of color being pulled over and cited more frequently and medical records or pharmacological studies being historically based on men.

In one case study, Wiedenbeck noted a financial services AI system that uses data from the last 70 years was found to be biased against women, who were only allowed to own credit cards beginning in 1974.

“There are so many responsible AI framework models. Everybody should go get one and look at one. They’re very comprehensive,” Wiedenbeck said. “You should have an overarching frame of how you are looking at your responsible use of AI. You should have that as your backdrop, and then…dig into which parts of that you really want to lean into.”

Challenge 2: Human talent

The extent to which humans are not replaced but rather trained to handle AI, or the right talent is recruited, is another major ethical consideration for the industry.

Panelists suggested the insurance industry has struggled with training underwriters, managers and other professionals to understand the background technology of AI. They emphasized, however, that insurers must begin preparing their workforce.

“We’ve been talking about looking for that talent and finding that talent, but I think it’s going to start with training the talent we already have. It’s going to be different skill sets within these same jobs. That’s a massive leap, and that training really needs to start now,” Grover said.

Challenge 3: Transparency and explainability

Transparency around when, why and how AI is being used, and the ability to communicate that clearly, will set companies apart as “the real winners” in technology, panelists also suggested.

“That’s going to be where we’re seeing the competitive advantages [and] early wins in this technology as it kind of continues to evolve,” Grover said.

“You have people who don’t understand the systems and there’s a lot of fear and uncertainty with AI. Explainability is one of our core AI principles [and] I think it is one of the clearest paths towards actually building trust with your users,” Miller added.

In his view, insurers must take explainability seriously as “that’s the only way to build AI products today.”

Challenge 4: Regulation and governance

With federal AI regulation still lacking, companies were encouraged to continue overseeing their own internal structures governing ethics and use.

“We govern it daily… We have to be ready because we don’t want to implement AI that is going to be either illegal at some point, prohibited or otherwise heavily changed,” Frank Neugebauer, VP, generative AI, the Cincinnati Insurance Companies, said.

Panelists noted there is no one-size-fits-all solution. However, they recommended companies start with a centralized solution then federate over time

“You’ve got to have the rules that you’re going to play by as a company. That’s step one, and that isn’t something that you decentralize and say everybody plays by a different set of rules,” Wiedenbeck said.

Once that foundation is formed, he said, companies may want to push it further out “where it needs to go,” such as to co-leadership, co-sponsorship or partnership with IT.

Getting it right

The panelists agreed there is an urgency to get AI right in the insurance industry, which typically lags behind technological advancement in favor of minimizing risks.

“I think that this type of disruptor really only comes along maybe generationally. So, the people who do this well are not only just going to have a significant competitive advantage, but the people that do not do this well, or choose not to do it at all, lose the game completely,” Grover said.

The Reuters “AI and Ethics: A Collision Course for Insurance?” panel was moderated by Jennifer Kyung, president, NextGen Underwriting, a consulting business.

Newfront is a global business insurance company founded in 2017 and based out of San Francisco, California. It has offices throughout the United States.

Ameritas Life Insurance Corporation is an insurance company founded in 1887 and based out of Lincoln, Nebraska. It offers financial services with a focus on life insurance and annuities.

Coastal Wealth is a financial services firm founded in 2016 and based out of Fort Lauderdale, Florida.

The Cincinnati Insurance Company specializes in P&C and life insurance, while offering other services. It was founded in 1950 and is based out of Fairfield, Ohio.

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