Dear Chair Beidle, Vice Chair Hayes, and Members of the Committee:

My name is Daniel Castro, and I am Vice President of the Information Technology and Innovation Foundation (ITIF) and Director of ITIF’s Center for Data Innovation, a nonprofit think tank that studies the intersection of data, technology, and public policy.

I write to express concerns regarding Senate Bill 889, which would prohibit what the bill terms “surveillance-based price setting” and “surveillance-based wage setting.”^[1] While policymakers are right to ensure that consumers and workers are treated fairly in the digital economy, the bill’s sweeping definitions would effectively prohibit many forms of dynamic, data-driven pricing and compensation that benefit both consumers and workers.

Dynamic pricing—using data to adjust prices or promotions based on real-time conditions—is a common and beneficial feature of modern markets. It allows companies to allocate resources efficiently, respond to shifts in supply and demand, and deliver lower prices or targeted discounts to consumers. By defining “surveillance-based price setting” as any practice that uses consumer or device data to determine prices, SB 889 risks banning many widely used and consumer-friendly practices.

For example, many services rely on location data to determine prices or availability. Ride-sharing and delivery platforms use location and demand data to match drivers with riders or customers efficiently. When demand increases in a particular area, prices may temporarily rise to encourage more drivers to come online, helping ensure that more people can get rides rather than facing long wait times or no service at all. This type of dynamic pricing improves market responsiveness and availability, and it increases earnings opportunities for drivers who choose to work during periods of high demand.

Similarly, businesses frequently use consumer data to offer discounts, loyalty rewards, and targeted promotions. Retailers may provide special offers to encourage a lapsed customer to return, or offer discounts to frequent shoppers through loyalty programs. Streaming services, restaurants, and online retailers regularly use customer engagement data to tailor promotions that lower costs for consumers. Under the bill’s broad definitions, these routine and beneficial practices could be prohibited because they rely on “consumer data” to determine individualized prices or offers.

Importantly, none of these practices involves discrimination based on protected characteristics. Such discrimination is already illegal under existing civil rights laws and should remain so. Protecting consumers from unlawful discrimination is essential. But banning broad categories of data-driven pricing tools is not necessary to achieve that goal and would instead eliminate many legitimate and beneficial uses of data.

The bill also raises similar concerns with respect to “surveillance-based wage setting.” Employers increasingly use data-driven tools to reward performance, improve safety, and design incentive programs.^[2] For example, transportation companies may offer bonuses to drivers who demonstrate safer driving behavior, such as avoiding sudden braking or maintaining safe speeds. Logistics companies may provide incentives to workers who verify their identity through biometric systems that help reduce cargo theft. In other industries, employers use performance data to create targeted bonuses or incentives that reward productivity and reliability.

The bill’s definition of “surveillance data”—which includes data obtained through observation or inference relating to behavior or biometrics—appears broad enough to capture many of these legitimate and beneficial practices. As a result, the bill could unintentionally limit employers’ ability to implement performance-based compensation systems that benefit both businesses and workers.

More broadly, SB 889 risks undermining innovation in Maryland’s digital economy. Data-driven decision-making—including algorithmic pricing and compensation systems—is increasingly central to modern commerce. If Maryland broadly prohibits these tools, businesses may face significant compliance uncertainty and may choose to limit services, reduce promotions, or avoid introducing innovative pricing models in the state.

Policymakers understandably want to ensure that data-driven technologies are used responsibly. Transparency requirements, strong privacy protections, and clear prohibitions on unlawful discrimination can all play constructive roles in protecting consumers and workers. However, SB 889 goes much further by effectively taking dynamic pricing and algorithmic compensation off the table altogether.

For these reasons, I respectfully urge the Committee to oppose Senate Bill 889.

Thank you for your consideration of these comments.

Sincerely,

Daniel Castro

Vice President, Information Technology and Innovation Foundation (ITIF)

Director, ITIF’s Center for Data Innovation

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