BespokeThurgood Marshall was not just a justice on the U.S. Supreme Court, he was the lawyer that led many of the civil rights cases striking down de jure racism in the United States. While he successfully prosecuted many cases, he is perhaps best known for the Brown v. Board of Education landmark decision in 1954. The Supreme Court unanimously ruled that “separate educational facilities are inherently unequal” and, therefore, racial segregation of public schools violated the equal protection clause of the 14th Amendment.

Justice Marshall’s strategy to bring down racist practices in the United States is still studied today as a model for how to run an activist program through the court system. But today’s court system is far more complex, and the contexts in which activists bring their challenges far more convoluted, than at any time in the past. If a few years from now you were faced with a challenge of the type that Justice Marshall faced, could you run a similarly successful campaign?

The Maker Era

We have entered the maker era. You can buy a 3D printer, put it in your basement, and within minutes you can make or replicate replacement parts, toys, or your own inventions. Connect your computer and software, and now you are in the business of designing whatever you want. Once you are satisfied with the design, you can send the file to a commercial manufacturer or license it over the web. You are in competition with the global world of manufacturing.

What if you are a nascent clothing designer? New nanotechnologies allow you to spray on clothing. You can add colors, create texture and design combinations, and even build in special features (anti-perspirant?) into the new shirt. If you don’t like what you created, simply peel it off, dissolve it, and start over again.

If you aren’t interested in manufacturing or clothing, perhaps you would like to use software to mine behavior? Go to the internet and you can download software that lets you analyze text, apply machine learning, and find secrets hidden in the words. You can analyze sentiments, build behavioral paradigms, and test your ideas without leaving the comfort of your office.

Lawyers often struggle to comprehend how fast the world is moving around them. 3D printing, nanotechnology, and artificial intelligence are just three of the many areas rapidly scaling from the laboratory to real life. Yet most lawyers are still in the quill and paper era, trying to master Word and occasionally venturing into Excel or PowerPoint.

Most law and technology posts focus on simple automation or perhaps elementary artificial intelligence applications, such as finding all bankruptcy cases with certain elements. The “scary” futurists speculate about robotic lawyers sitting next to human lawyers as they compete for the next case that comes over the transom.

In this essay, I’m going to take you on a bit of a journey into the future. Let’s imagine how a clever software engineer with knowledge of the law and a lawyer with a bent for social justice could start a movement in the 21st century.

The Designer’s Lawsuit

Thurgood Marshall faced a significant challenge in the 1930s, 1940s and 1950s when he was attacking racism as a lawyer for the NAACP. He had to maneuver key issues through federal district courts and appellate courts, often hostile, to get those issues before the U.S. Supreme Court. To do so, he relied on research, experience, intuition, and luck. Could he do it differently in the 21st century?

Imagine using computational linguistics and machine learning to look at all the reported opinions relevant to the issues you wanted to get before the U.S. Supreme Court. The software “reads” the opinions and the briefs, finding those obscure connections you couldn’t find even you if you had the time to read the hundreds of thousands of pages.

To make the analysis more interesting, you also look at databases built from the biographies of the judges who may sit on the case at each federal court level. The databases include all the information about the judge’s experience (undergraduate school and major, law school, etc.), training (law firms, government positions, etc.), and personal characteristics (age, gender, etc.). It also includes everything the judge has written or said that is public, outside of opinions. Speeches, law review articles, and op-ed pieces sit in the database.

While it may seem like you have the relevant information you need, you don’t stop there. You pull together information on the community where each judge lives. What is the political sentiment within the community? Is it affluent? What religions predominate? You dig deep into the community to understand how it may affect the judge’s thinking.

You also look at the national climate. Where have the trends been going—are the people in the United States moving in your favor or against you on the issues? Are there similar issues from which you can gain guidance? What about legislative movements at the local or national level?

With this massive database, you turn loose your machine learning software again on a small subset, the “training” database. The algorithms (and you use many, stacked to mimic the way the human brain processes information—as best we can tell) run through the information over and over again. The algorithms are learning, attempting to “understand” the data. You ask questions and the algorithms respond.

As the algorithms respond you check the results. You reject most responses and inform the software of its hits and misses. Over time, the hits grow and the misses shrink. The algorithms seem to be organizing information the way an expert might. You reach the point where you think the algorithms are ready for the big time.

You turn them loose on your large data set and wait to see what happens. As the results start to come in, you see that the algorithms have identified some court possibilities you would have picked, but there are some unexpected choices as well. In fact, it turns out the unexpected choices rank higher on the probability of success than your expert choices.

That was the easy part. The next step is to ask the software to design the lawsuit. What arguments will work best in each court? Which arguments should be emphasized and which added as “just in case.” Again, you find some of the picks familiar, but some are unexpected. In fact, there are a few creative uses of arguments that came out of cases decided long ago, but that seem to fit with the times.

With knowledge of the arguments, you turn the work over to the next program: the legal argument drafting program. For many years now, software has been writing corporate earnings articles and recaps of sports games without human intervention. The software takes the financial results or the game record and, using some training on writing styles (a dash of Hemingway mixed with a bit of Lardner), turns out articles that people can’t distinguish from articles written by journalists.

That software has now been trained on legal writing styles. Using opinions by Holmes, Jackson, Hand, and Posner, you have trained the software to write like a judge (or, perhaps, like some judges wish they could write). With the legal arguments preferred by the machine learning algorithms, the legal argument drafting program turns out a passable first cut at a motion for summary judgment. You can use that to back into a complaint. Once you know the district judge and she issues her opinion, you can use the software again to churn out the first draft of your appellate brief. You have designed your first lawsuit. (And before you yell at me about all the professional responsibility issues involved, please remember the spirit in which this essay is intended – to spark interest in what types of analyses will be possible, not to suggest ways to improperly create and file claims.)

Don’t Wait, Dive In

The designer lawsuit is, of course, a thing of the future. The software we have today can do bits and pieces of what I have described, but we still have a way to go before all of those pieces can knit together a new case tweaked for what may work best in each court. Still, we are closer than what many lawyers think.

The point of this exercise is not to scare lawyers into thinking software will replace them soon. It also isn’t to add on to the fatalist pile the thought that lawyers will soon become extinct, or nothing more than the handmaidens of computers.

I do hope the story has piqued your interest in staying current with what software can do. The amount of data available to lawyers is vast and far beyond what we can reasonably consume and use to help our clients. It grows much larger each day. As tools come online that can help us digest that mass, to not use them approaches the irresponsible. That information contains judicially recognizable information that may tip the balance in an argument. It puts judicial decisions in the context of what is happening in society (and if you still think judicial decisions aren’t political or are limited to extending law on the books, then I apologize for rudely dragging you into the real world).

We have entered the augmented age, where humans plus computers can take us further, faster, than humans or computers can go alone. If you believe that is fantasy, think about what you hold in your hand: a smartphone you can talk to that reaches out to all the data on the internet to answer your question. In seconds, Siri or Cortana translates your spoken request to digital commands, processes them, and come back with an answer or at least relevant web sites. Your mind has been augmented, through the smartphone, by the internet. That connection grows closer and stronger each day

When will we have designer lawsuits? Five years? Ten years? Longer? We don’t know and the correct answer isn’t relevant. The designer lawsuit will not be like falling off a cliff: one moment you do all the work and the next the computer does it for you. We will creep closer a step at a time, with the steps coming quickly at some points. Whenever the time comes, you will be much better off for having kept pace with the changes, than trying to quickly run to catch up. No matter how fast you are, you will not succeed.