Analytics is changing our entire world — from drawing fairer voting districts to optimizing supply chains and even interpreting centuries of climate patterns. The accrual and study of data bring remarkable levels of insight. And help trim the fat from just about everything we do in our personal, professional and civic lives.
It should come as no surprise then, that artificial intelligence and advanced logistics are changing the face of legal studies and law school. Here’s how.
Reducing or eliminating administrative tedium
For example, what are the kinds of due diligence that are involved in determining a company’s exposure risk to lawsuits and liabilities?
There’s a lot that goes into the process, including the study of employee and customer grievances, personnel files, documents from court proceedings and regulatory documentation. Pouring over all these records and drawing meaningful conclusions is painstakingly tedious. Not to mention, since it required an entire team of legal analysts, it was expensive too.
AI and legal analytics are changing all this. When the project in question involves studying thousands of pages of records, it just makes good sense to use an algorithm to do it instead.
Legal teams can now digitize relevant records in bulk and have an AI platform find and extract words and phrases that are relevant to the case in question. It removes a huge amount of the human effort required and results in a far more manageable amount of case material.
Drawing more immediately relevant conclusions
Advancements in technology have a tendency to reveal blind spots buried in our workflows and records. Until quite recently, even though the human race is swimming in documentation and data, we just didn’t have the means to cut through the noise and clutter to find the conclusions that really matter.
The interpretation of the law seems an unlikely place to apply cold, hard algorithms since the outcomes of legal cases are anything but impersonal. Taken as a kind of mathematical formula, the outcome of a legal case — and a firm’s willingness to tackle it — nevertheless rest upon a set of variables. These include previous lawsuits and motions, the presiding judge involved, the part of the country in which the case is taken up and much more. It’s a lot to consider.
In the United Kingdom in 2017, 100 lawyers from noteworthy firms pitted themselves against a “recursive learning” AI. Their goal was to sift through several hundred pending financial disputes and find out whether flesh or silicon could more accurately predict which cases would be brought to court by the Financial Ombudsman and which would ultimately be thrown out as frivolous.
The legal AI achieved an accuracy rating of 86.6 percent in its predictions compared with the human legal team’s 66.3 percent. The parties involved admit that both the machine and the legal clerks could have performed better or worse, given different circumstances. However, the gauntlet has been thrown. The promise of AI in law and the immediate implications for seasoned as well as up-and-coming students are difficult to miss.
How law education is about to change — and how it won’t
There are some caveats concerning the upper limits of this technology’s usefulness. According to that U.K. study, smaller sets of data don’t deliver nearly the same results.
Moreover, some cases are simply too mired in idiosyncratic human behaviors or specific types of language for a more general-purpose law algorithm to know what to do with until it has more information. There are likely thousands of fringe cases or areas of specialized law that will require this technology to evolve even further before it delivers the same results.
There’s the question of bias, too. The history of human jurisprudence is littered with mistrials, misdirection, dishonesty, bribery, and a hundred other kinds of conscious and unconscious bias. The machines doing the data trawling here aren’t necessarily drawing their conclusions based on impartial cases or the fairest precedents.
Practicing law isn’t just about drawing fresh conclusions based on old cases — it’s often about reinterpreting and even rewriting the law to account for how society has changed over the years and decades.
Some of the harshest proof that algorithms are only as unbiased as their masters come from the controversial realm of cash bail. When algorithms were turned loose on the bail-setting process, they demonstrated a conspicuous racial bias.
A more recent example of this inherited machine bias comes from Amazon.com, which recently shuttered an AI program meant to screen job-seekers more effectively than a human hiring manager. The machine demonstrated a clear bias against female applicants.
What this tells us about the future of studying to be a lawyer is that some of the clerical work that requires a deep factual knowledge of legal precedent might well be outsourced to intelligent algorithms. AI might understand the nature of the case but won’t necessarily know how to draw the most pro-social conclusions from the data. Ian Dodd, representing a legal AI company called Premonition, said it like this: “The knowledge jobs will go, the wisdom jobs will stay.”
Will tomorrow’s lawyers be computer programmers?
We might be witnessing a sort of stratification of human roles within the legal community.
At one level, some of tomorrow’s law school students might very well replace a significant part of their coursework with programming and analytics classes. They’ll be the ones creating and improving the algorithms that help us sift through decades and centuries of legal records to find the most relevant information for modern cases.
At the next level, we’ll have lawyers whose jobs are to sift through the pared-down information provided by analytics platforms and come to somewhat more human conclusions about what it means today, rather than what it meant yesterday.
To cap things off, we’ll still almost certainly need legal professionals with charisma, oratory and negotiation skills and, of course, reception to civil rights movements and watchdog groups.
These are the people who keep their finger on the pulse of the nation and its ever-changing socio-political priorities — people who can speak to judges, juries and district attorneys with confidence and ultimately make their cases to a receptive public.
In the end, it’s likely we’ll begin seeing dual majors emerge in this field: course loads that prioritize analytics and programming skills alongside the stuff legal dramas are made of, like powerful rhetorical skills, a mind for fairness and a general concern for the public good.