Algorithmic Justice, Education, and the Lawyer of the Future

Author: Enrique Dans, Ph.D. Professor at IE University

The idea of algorithmic justice was, in fact, one of the topics often discussed in the Advisory Council for the Innovation of Justice, an advisory forum created by the Spanish Ministry of Justice under the previous legislature. The Council, unfortunately, does not seem to be finding continuity under today’s administration, despite its significantly independent character and composition.

Could algorithmic justice be a remedy for the apparent collapse of an administration of justice, which in many cases, already exceeds the limits referred to in the American maxim, “justice delayed is justice denied”? Or, going even further, could it offer interesting ways of reducing or eliminating arbitrariness in certain areas, without becoming crass automatism that diminishes the richness and complexity of such processes?

Throughout the history of information technology, computers have been seen as machines that automate repetitive tasks. For legal professionals, computers are typically used as basic office automation tools: machines capable of processing texts, calculating, creating presentations, or providing an interface for consulting databases. However, machine learning is refining this principle. Without any intention of using hyperbole and  elaborating this point with an image of the Terminator—which still happens frequently in mainstream media—the shift from the idea of seeing a computer as a typewriter or a glorified calculator to seeing it as something that can learn from data and perform complex tasks is something that will be essential to define as a concept within the education of all legal professionals.

To educate these new “bilingual” professionals, as MIT called them in the announcement of its new multidisciplinary center, the Stephen A. Schwarzman College of Computing, it will be essential for them to understand the workings of artificial intelligence algorithms and machine learning, which will be commonplace in their profession. And it is not only to prevent possible malfunction, as in the case of the algorithm used by Amazon, which decided to stop hiring women based on the company’s historical hiring data; but also to be able to understand what the machine is doing in each case. Algorithmic justice, as its use in US courts has already proven, requires a guaranteed amount of transparency that allows for the monitoring of all processes carried out by machines. The role of the legal professional as a hacker of the law with the ability to appeal a machine decision, for example, rests on their ability to understand the power of the new generation of tools at their disposal, which will sometimes be on their side, and sometimes work against them.

Adapting to these changes requires a multidisciplinary approach. It is not only necessary to understand what machine learning can contribute to the practice of law, but also to be able to understand what the law can contribute to the development of machine learning, which, without a doubt, is considerable. The law of the future will adapt, as it has throughout history, to the technological environment in which it exists. As a result of this change, legal professionals will learn to work within this environment in order to make up for and solve many of its shortcomings, problems, and limitations.

Adapting to these changes requires a multidisciplinary approach. It is not only necessary to understand what machine learning can contribute to the practice of law, but also to be able to understand what the law can contribute to the development of machine learning.

Understanding these changes and viewing them with an open mind is the task of innovative institutions at all levels. It is an attitude that will become a powerful generator of opportunities at all levels, and will affect a more rapid transition towards what justice and legal professionals will be or may become in the future—a future which is practically here already.

Enrique Dans is a professor of Information Systems at IE Business School and Senior Advisor for Innovation and Digital Transformation at IE University. He conducted postdoctoral studies at Harvard Business School and his research interests are related to the impact of disruptive technologies at three levels of analysis: individuals, organizations, and society as a whole. Professor Dans has been teaching and consulting in the technology field since 1990 and is a frequent contributor and columnist in business and economic newspapers and magazines.

Note: The views expressed by the author of this paper are completely personal and do not represent the position of any affiliated institution.