Published March 16, 2015
Who rules big data? That question, with special emphasis on how these information technologies are changing our understanding and application of the law, will be explored next week at the Mitchell Lecture, the UB Law School’s signature lecture series.
The lecture, “Who Rules Big Data? Law, Knowledge, and Power,” will take place at 2 p.m. March 27 in 106 O’Brian Hall, North Campus. A reception will follow. The event is free and open to the public.
“There’s a sea change here, a deeper question that is alarming,” says Martha McCluskey, professor of law and chair of the event’s organizing committee. “Some people are arguing that big data is not just another new thing for the law to address, but that it really cuts to the heart of what we think of as law. It’s usurping the decision-making of law to a large degree.”
One issue, McCluskey says, is that quantification “takes on the aura of law. It’s a method of decision-making that has the appearance of supreme rationality and objectivity, almost like a divine thing — we’re transcending the human flaws.”
Some scholars, she says, even have made the argument that computer code is law. But, she points out, human subjectivity finds its way into the analysis of big data and hides beyond the seeming objectivity of the numbers.
And the problem of mission creep in the use of data raises other issues of public policy. Credit scores, for example, not only help banks evaluate a potential borrower’s creditworthiness, McCluskey says, but are used by employers to screen out some job seekers, so that a person’s score determines qualifications in areas that “may have nothing to do with credit.”
Those uses of big data may be statistically valid because they identify patterns in the behavior of millions of people. But that raises important questions about how these generalizations should govern our lives. For instance, should the Fourth Amendment allow police to search individuals based on their statistical risk profiles? Or, when should law protect individuals from judgments by government or business based on inaccurate underlying data?
Further, if the algorithms used in business decisions are protected as trade secrets, might these hide prohibited discrimination or anticompetitive behavior? Without the ability to challenge or even understand the automated decisions that govern our lives, will public and private power become increasingly concentrated and unequal?
Leading the discussion at the Mitchell Lecture will be three scholars who come at the issues of big data in different ways. They are: