The ABA’s Legal Analytics Joint Working Group had a successful turn-out for the New Paradigms Panel discussion on September 9th. Our CEO, Michael Bommarito, sat on the panel to discuss a variety of topics including machine learning and data analytics. He also contributed to an interesting discussion about the development of probability theory. The legal profession has traditionally been resistant to the incorporation of numbers and theory into everyday practice. LexPredict is just one voice in a growing chorus of firms specializing in bringing law and mathematics closer together, and Michael argues that the reasons for this revolution not only have a practical basis, but a historical one as well.
The History of Probability
Probability theory has had a large impact on the legal profession, but what is often overlooked is that modern probability was fathered by lawyers. Probability as we know it today was formalized and embraced by lawyers as far back as the 17th century. Pierre de Fermat, most famous for his contributions to mathematics, began his career as a lawyer. At the beginning of the Modern Era, the necessity of quantifying proof and evidence in trials was a motivating force for Fermat to apply mathematical concepts to social problems. This is not unlike the current landscape of legal professionals, Michael points out. Lawyers working alongside philosophers and mathematicians and statisticians were key in the formalization of early probability theory.
The definition of the word “probability” itself underwent an evolution. Before modern redefinition, the word “probable” only meant that something was approved or favored, usually by some form of authority. New sciences like astronomy and physics sought observable facts about the world, but lawyers and mathematicians like Fermat and Blaise Pascal recognized the need for a concept based on facts, but not necessarily factual. Social systems were becoming more complex in the 17th century. Fields like medicine and alchemy were based on imprecise study and patterns in data. These new areas of study necessitated the creation of a form of mathematics that could quantify their findings. Leaders in these fields spearheaded an evolved definition of “probable”. This new word highlighted the evidence-based quality of probability, while also distancing the concept from something intrinsically tied to approbation or endorsement. For more details on this, look to our series on probability.
Probability is an important foundation of data analytics. As our steadily growing Intro series continues to point out, data analytics is a complex science requiring its own nomenclature. Understanding this nomenclature is critical to understanding the strong ties between law, social science, and mathematics.