What are the ethical considerations related to the use of AI and generative AI in insurance?
Read on to learn more about AI ethics:
Artificial intelligence first emerged decades ago, but recently there has been a rise in more sophisticated AI technologies in insurance, such as generative AI, which are systems capable of creating unique content based on data and patterns from which they learn.
As AI advances, its importance in property insurance will continue to grow. For what?
- AI can automate the claims processing workflow and detect fraudulent claims.
- AI-powered technology can perform virtual inspections and improve risk assessments for underwriters.
Applications of generative AI in insurance also continue to grow thanks to this technology’s ability to ingest massive amounts of data and help humans make better data-driven decisions.
However, insurers must be mindful of the regulatory environments in which they operate. There are compliance requirements – and therefore ethical considerations – that insurance companies must take into account when using AI.
Navigating a multitude of requirements can be difficult as vendors determine which AI technologies fit within a compliant legal framework. This is why it pays to have a trusted advisor when think about the right investment for your business.
Challenges of using AI in a highly regulated industry
In the United States, each state has its own set of regulations and compliance requirements that insurance companies must follow in order to operate legally.
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Each state’s insurance laws require carriers to submit their rate filing processes to confirm that they comply with a certain set of standards. These standards dictate not only how insurance companies should establish rating systems and pricing models, but also how they should handle sensitive data. In turn, certain state codes regulate the type of technology and models that insurers can use to make decisions about insurance policies and claims.
With different legal requirements from state to state, it can be complicated for insurers to determine how they can use AI. Additionally, although some states have established requirements for algorithms and risk models, others have not.
The National Association of Insurance Commissioners (NAIC) provides guidelines and recommendations for regulators regarding the use of AI. The NAIC guidelines could serve as the basis for future laws, but for now, most state governments have not set specific requirements for how insurance companies can take advantage of the AI technology.
There are no universal laws regulating AI technology in the property insurance industry.
As a result, much is left up to interpretation for insurance companies that operate in multiple states. Federal laws do not explicitly tell insurance companies:
- How and when can operators use AI
- The different types of AI carriers can exploit
- What data variables can AI take into account to make policy decisions
Although inconsistencies and legal uncertainties remain, there is too much to gain from using these solutions to avoid AI altogether. So, what is the best way for insurance companies to use AI in their daily operations?
Taking a Conservative Approach to AI: The Ethics of Artificial Intelligence
We can only expect more AI-specific laws to emerge as more insurance companies leverage this technology to conduct rating procedures and determine risk, and therefore insurability.
So, for insurance companies to ensure they are building compliant AI-based processes, even under possible future legislation, it is best to take the more conservative approach when they use AI to facilitate underwriting functions and claims processing.
“AI has the power to transform insurance functions. As such, the regulatory environment is evolving to keep up with advances in AI,” says Amy Gromowski, director of science and analytics at CoreLogic. “It’s important to manage your AI wisely. An agile and comprehensive governance program will ensure that you meet a varying degree of regulatory standards. When in doubt, be conservative in your governance programs; put processes and people in place to ensure responsible use of AI.
In the absence of universal AI-specific legislation, building an ethical and responsible data governance model that complies with regulations in the more conservative states in which your company provides coverage is a good start.
A data governance model should include standards for the collection, storage, processing and disposal of your data. These models will determine which AI technologies you can use (and how to use them), because it’s the data that trains the AI to make decisions and take action.
All technologies must manage data in accordance with your ethical and responsible data governance program.
Adhering to AI Ethics
Ethical AI is trained on a comprehensive set of accurate and unbiased data so that it does not lead to discriminatory decision-making against certain communities or classes of protected individuals. With ethical AI, there should be transparency about the type of data used. Sensitive data must also be kept private and secure.
To ensure that AI promotes unbiased decisions and actions, humans must always monitor the technology. Although some AI is capable of acting independently and making decisions without input from humans.ethical AI will still involve humans to ensure that insurance policies are fairly priced and that insurability is objectively determined.
Working with technology partners seeking responsible AI
It can seem impossible to keep tabs on all the updates to all the AI regulations in every state in which your organization operates. This is why it is important to work with technology partners who share a conservative and ethical view of AI and compliance and who have strict data governance models.
At CoreLogic, we provide AI solutions trained on robust sets of unbiased data. We also have two governance programs for AI solutions. Both programs were developed with input from legal experts to ensure that all of our software manages and processes comprehensive and objective (read: unbiased) data sets and aligns with all state compliance requirements .
For customers who are uncertain about how to implement AI so that it fits into their own data governance models, CoreLogic acts as a consultant to help them deploy our AI solutions. ethical manner.
Understanding AI Ethics
Since there are no explicit, uniform rules regarding AI in insurance, it is important to use ethics as a compass to guide your approach to AI.
As AI evolves, it will continue to push the boundaries of what can be done with data. Nonetheless, it is important to maintain human oversight and control over the data leveraged by your AI technology so you can ensure it is secure and unbiased. To remain compliant as AI grows in sophistication and influence, your entire digital ecosystem must be designed with ethics in mind.
It takes a village to pursue AI ethically and conservatively. Not only should you establish conservative data governance models to guide data processing, but you should also work with AI solution providers who have the same priorities.
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