In the Industrial Revolution, machines took on the burden of physical labor; in the Big Data Revolution, machines are taking on the tasks of making decisions. Algorithms are the rules and processes that enable machines to make those decisions. Machines will make many decisions that affect general well-being. This article addresses a threat to the efficacy of those decisions: the intentional distortion or manipulation of the underlying algorithm so that machines make decisions that benefit self-interested third parties, rather than decisions that enhance public well-being. That threat has not been recognized or addressed by legal thinkers or policy makers. This article first examines the lifecycle of an algorithm, and then demonstrates the likelihood that self-interested third parties will attempt to corrupt the development and operation of algorithms. The article then argues that existing mechanisms cannot protect the integrity of algorithms. The article concludes with a discussion of policies that could protect the integrity of algorithms: transparency in both the development of and the content of algorithms that affect general well-being and holding persons who corrupt the integrity of such algorithms accountable. Just as the Industrial Revolution eventually improved the quality of life for many, so too does the Big Data Revolution offer enhancement of general well-being. That promise, however, will only be realized if policy makers take action to protect the integrity of underlying algorithms now, at the beginning of the revolution.
Nichols, P. M. (2019). Bribing the Machine: Protecting the Integrity of Algorithms as the Revolution Begins. American Business Law Journal, 56(4), 771–814. https://doi.org/10.1111/ablj.12151