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Big Data and Employment Law: What Employers and Their Legal Counsel Need to Know
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Introduction
Technological innovation continues to change employer practices, creating new legal challenges for their legal counsel. One significant such development is employers' growing tendency to use big data to answer their most pressing questions.1 Once reliant on optimistic revenue predictions or sparse, anecdotal accounts of employee satisfaction, employers and legal counsel now may sift through enormous data sets to answer complex and sophisticated questions about applicants and employees.2
Harnessing the power of these massive data sets, or "big data,"3 allows attorneys to understand historical patterns of legal activity, improve existing employment practices, and even increase the efficiency and efficacy of their own law firms. Armed with these colossal resources, algorithms help employers uncover interactions behind the rise and fall of business revenue, employee productivity, hiring patterns, disciplinary pitfalls, financial risk, legal exposure, and myriad other factors that influence a business plan's success.4
However, using automated machine-based outputs to understand individual human beings' actions is fraught with risks. Potential exposure to serious legal action looms over every decision based on big data.5 Despite the risks, clear legal rules are largely absent. Lawyers' discussions of big data are rampant with misinformation, likely because few attorneys moonlight as data scientists.
We begin this discussion by defining some terms. Artificial intelligence is the idea that computers can "carry out tasks in a way that we would consider smart,"6 essentially meaning that a computer is capable of being taught to think and understand the world by classifying information as humans do.7 By contrast, "machine learning" is a "an application of [artificial intelligence]" based on the notion that programmers should be able to provide data to computers to allow them to learn on their own.8 Both concepts are important for understanding analysis of "big data."9
This Article provides an introduction to the fundamentals and breakthroughs of big...