Epiq Q&A: Regulating Algorithms Could Stifle Innovation

Photographer: Chris Ratcliffe/Bloomberg

The revolutionary aspects of AI, big data, and predictive analytics pose thorny issues for investigative and legal processes. Cliff Dutton, who is chief innovation officer with Epiq, shared his views on how these change agents may affect different sectors of the economy.

Hear more from Dutton 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.

What are the probable scenarios data ownership poses with regard to investigations of self-driving car accidents?

Discovery issues that arise in the investigation of any matter that involves electronically stored information, ESI, will certainly arise in self-driving car accidents. Who has possession, custody, or control of the ESI? What are the boundaries of relevance? What is reasonably accessible, or likely to yield relevant evidence? For example, the cars involved will certainly have reasonably accessible ESI that is likely to be relevant.

What about other cars that can be known (by their GPS data) to have been in the vicinity (either self-driving or not)? What about GPS data from cell-phones of drivers or passengers in the cars? Traffic pattern data such as Waze or Google Maps data stored in their respective cloud infrastructures? Data ownership across such a span of providers and consumers will also raise issues of privilege and intellectual property protection.

More contextual data will probably help to understand the causes of self-driving car accidents, so broad boundaries in interpreting potential relevance will serve a public interest. Such broad boundaries will conflict with privacy interests, and it will probably be necessary for courts to weigh in.

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?

As we rely more and more on AI to deliver health care, liability issues will evolve. As theories of liability are stretched, they will need to be tested by sophisticated litigation support analytics.  The volume and types of non-traditional ESI that result from AI-driven health care will continue to expand and will have to be analyzed during the discovery phase of litigation. Discovery experts will require knowledge of both the discovery analytics and the underlying AI.

How will the regulatory framework in the U.S. respond to the impact of algorithmic decision-making, and which industries might feel the greatest impact?

There will be tension between the inclination to regulate algorithms and the desire to unleash innovation. We’ve started to see this tension emerge in recently heightened privacy concerns over the commercial use of personal data. The industries that will be most impacted are those that are already data-driven, such as the financial industry, e-commerce, and social media.

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For the 4th year, the Bloomberg Law Leadership Forum is the premier event for legal industry leaders to gain insights and discuss how global economic and regulatory changes impact their business. Epiq was a sponsor of the event.

The 2018 Forum featured an update on current regulatory priorities, a look at where corporate risk is rising, and an exploration of the technology and management tools legal counsel need to respond effectively.

Click here to learn more the 2018 Bloomberg Law Leadership Forum and here to register for the Bloomberg Law In-House Forum West on June 27.