As new technology rapidly permeates the economy, the regulatory function is having difficulty keeping abreast in areas such as data privacy and protection.Behnam Dayanimis a partner in thePaul HastingsWashington, D.C. office, where he specializes in privacy, cybersecurity, and compliance matters. He shared his insights on the evolving relationships driven by changing technology.
Hear more from Dayanim at the 2018 Bloomberg Law Leadership Forum on May 23 in New York, where corporate counsel from Fortune 500 businesses and leaders from top law firms will gather to discuss trends in trade, regulation, and technology.
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What probable scenarios might data ownership pose with regard to investigations of self-driving car accidents?
One key question will be who owns the data in connection with accidents (or other incidents). Candidates may include the car manufacturer, the software provider(s), the car insurer, or the owner or passenger(s) of the vehicle. Absent regulation, this issue likely will be settled contractually, with insurers eventually demanding that insureds agree to share the data with them.
We see these issues already arising in very early stages in the context of driving-related apps, where information is usually specified to belong to the driver but with exceptions—such as in response to subpoena—that in contested accident cases may result in its disclosure.
What impact—positive or negative—will technology changes such as AI, big data, and predictive analytics have on litigation in the U.S. health care system?
These developments hold enormous promise for improving the quality and efficiency of our health care system. At the same time, the byzantine regulatory environment and opaque economic structures surrounding the system make it difficult to implement dramatic change. Navigating the privacy requirements of HIPAA also will present challenges to technology providers—challenges that competitors in some less regulated markets will not face.
There is potential for negative impacts from these changes, most particularly from adverse treatment or coverage decisions made based on predictive analytics, without visibility to the patient or consideration for the patient’s idiosyncratic circumstances. It is in this respect where close regulatory—and potentially legislative—attention is warranted, to determine whether enforcement or legislative or regulatory changes are needed. At this point, any such determination would be premature.
How will the U.S. regulatory framework respond to the impact of algorithmic decision-making, and which industries might feel the greatest impact?
This is the billion-dollar question. Will we enact specific regulations responding to algorithmic decision-making and, if so, what will those rules require? Many industry advocates argue against regulation for fear it will stifle innovation, and those fears have merit. On the other hand, one might argue that, in the absence of the grant by Congress of immunity from liability for most user-posted content in Section 230 of the Communications Decency Act, our country’s then-burgeoning ISP and tech industries may have been hindered in their growth.
A key question for regulators to consider will be whether to require transparency in decision-making—disclosing clearly to individuals the bases on which automated decisions are made. The Federal Trade Commission likely possesses the authority to impose those requirements in most cases already, based on its ability to enjoin unfair or deceptive trade practices. Nonetheless, reasonable minds may differ on whether more specific legislative or regulatory authority is required.
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