"Where and should guardrails be placed?"

Please read this statement in full before responding to the survey questions.
Insurance fraud costs the United States $308.6 billion annually. Insurance companies and agents account for some of that fraud, for example when a company doesn’t pay claims that it should or an agent collects premiums but never sends them to the company. Consumers also commit insurance fraud – for example, when they stage accidents or use a stolen identity to make a claim.
We want your opinion about how insurers can identify and fight fraud. More and more insurers are using data science – artificial intelligence, machine learning, algorithms, big data – to fight fraud. For example, they might scan social media postings, use voice recognition to determine if a caller’s voice fits the demographic profile of the policyholder, or use cell phone data to determine if a caller is where she says she is.
While using data science to analyze consumers’ personal data can be helpful to fight fraud, there are concerns. Data science methods also can unfairly discriminate against some consumers, including racial and ethnic minorities. There also are privacy concerns about insurers’ use of personal data. Thus, legislators and regulators are debating whether to restrict insurers’ use of personal data, including to fight fraud. Your opinions will be helpful to those decisions.
All responses to this study are entirely confidential and will not be personally identified. You should base your answers on your personal experience and opinions. We are not asking you to respond on behalf of an employer or any other entity. Your responses will be combined with all other responses for analysis. Your responses will not be resold or used for any purpose other than to assist with this study. The survey will take about 10 to 15 minutes to complete.
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17% of survey complete.