One of us Neota Logicians had the great privilege last week to attend the College of Law Practice Management Futures Conference 2014. The College is unique among legal industry organizations in bringing together exceptionally experienced and engaged people who see many dimensions of legal services—law firm lawyers, the full range of other law firm professionals (COO, CKO, CMO, CIO), law school professors, legal marketing professionals, alternative legal services providers, consultants, software companies, and others.
There’s been excellent coverage of the Conference as a whole: Jordan Furlong, Five For The Future; Liam Brown, Old Dog Learns New Tricks; Ron Dolin’s blog Think Outside the Bar; and Storify’d tweets and other resources at Robert Richards’ Legal Informatics Blog. (If we missed others, please let us know so we can update this post.)
Friday morning began with three fast, focused talks: Ron Dolin of Stanford Law School, Carla Goldstein of Bank of Montreal, and Neota Logic’s Michael Mills, who essayed an eight-minute answer to the question What’s Wrong With Law Practice?
Here’s our answer:
Let’s start with a diagram—the revenue and cost lines of the profession.
What happened to these lines in the Great Reset?
First, the top line was shoved downward by cost-conscious general counsel.
No surprise, law firms cut costs—mostly support staff and space—to push the cost line down and preserve margin. Alternative legal services providers, from Axiom to UnitedLex, did the same, just more aggressively.
Second, we got process engineering, the Disciples of DMAIC. And we got project management.
With these tools, we have the least-cost people doing only the stuff the client really needs, in the right order, with minimal handoffs and rework. And we shoved that red line down again.
Keep in mind … this analysis applies to not-for-profit organizations too. Change “revenue” to “funding” and “profit margin” to “cash cushion” … and then squeeze the lines much closer together.
So, this is better, but not good enough. What’s still wrong? The straight lines.
The cost per unit of output has shifted downward. An hour costs $600 instead of $800, and that hour produces two-tenths of a contract rather than one.
But when quantity climbs, total costs climb at exactly the same rate. Every unit of output costs the same as the last one.
That’s not how the big boys do it.
The great engine of Microsoft is that the marginal cost of delivering another copy of Windows is close to zero. Not zero, there’s lots of R&D for the next version. But the average unit cost declines as quantity rises, so quantity is a good thing. Economies of scale, as Henry Ford taught us.
Alas, quantity in legal services is not necessarily a good thing. We have the diseconomies of scale—internal coordination costs, quality variation—but not enough of the economies, other than marketing. In short, we missed the industrial revolution.
Forget about billable hours, alternative fees, self-regulating self-protecting monopolies, partnerships, ABS’s. The problem is constant cost.
So how do we fix this?
Law doesn’t need blast furnaces or warehouses. We’re the pure digital product—lightweight, malleable, portable, computable.
Ray Kurzweil’s graph shows computers getting way smarter, long before we get to the Singularity.
Thanks to Moore’s Law, we’re nearly up to mouse brain level. Fortunately, that’s more than enough for lawyers.
What should we do with these electronic mouse brains? We should think about law as code.
Traditional lawyers see law as text.
Untraditional lawyers see law as rules and many other forms of rigorous expression.
And that’s a form in which the law can be worked by a computing engine
It’s true that in the software world “Artificial Intelligence is whatever hasn’t been done yet,” but AI is a fertile field in many disciplines—robotics, machine learning, and expert systems among them.
We lawyers don’t build cars, so we don’t need physical robots.
Classification, one of machine learning’s big tricks, is taking over e-discovery, indeed would have taken over entirely but for the Luddite resistance of many lawyers and clients. And companies like KMStandards, Diligence Engine, Seal, and eBrevia are doing creative work with machine learn algorithms in areas other than e-discovery.
Prediction, another of machine learning’s tricks, is making ground fast in law with Lex Machina, Dan Katz, and others.
Maybe, as IBM’s general counsel said recently, Watson will pass the bar exam in a few years. (Or perhaps before Watson signs up for his bar review course, the profession will finally concede that the exam is a worthless measure of fitness to practice, as Watson’s ability to pass it would prove.)
Machine learning is truly a marvel in all its many manifestations—from giving vision to robots to helping oncologists at Sloan-Kettering devise treatment protocols. However, machine learning’s probabilistic answers and dark algorithms don’t do the job when people want to know:
- precisely
- what to do
- now
- about this problem
- under these circumstances
Lawyers are at heart skeptics and determinists, and clients are busy and result-minded. For those sorts of problems and people, we need expert systems. Here’s a practical definition:
There are precedents. Lawyers like precedents, don’t they? So here’s one that’s 3,700 years old.
In this 13-foot-long Egyptian scroll is a set of rules for diagnosing and treating battlefield wounds, probably written for surgeons in the Pharaoh’s army.
Expert systems, in case you haven’t noticed, are everywhere.
In the pocket of your doctor’s white coat:
Doing your tax returns.
Expert systems aren’t much help in the high-touch, high-EQ parts of what lawyers know—counseling, negotiating, and advocacy.But in the rest—law & policy, documents, and processes—expert systems (including their offspring document automation and computable contracts) are true force multipliers.
How is the knowledge of experts captured, encoded and delivered?
Law can be devilishly complex. Here’s a flow chart of the law on medical benefits for veterans discharged with less than perfect disciplinary records. (That’s a lot of veterans.)
No wonder the VA makes wrong decisions so often.
But a team of Georgetown Law students built an expert system called MIDAS that mastered this morass of law for veterans’ advocates.
Here’s one among the students’ many decision trees
We can code the law. Why should we?
Yes, to fix the cost line, to bend it down into a happy curve.
But also because, despite the much talked about surfeit of lawyers and law students, there is a vast unmet demand for legal services.
Yes, even in big organizations. Every day thousands of decisions that have legal dimensions and create legal risks are made without legal guidance. General counsel are as cost-pressured as their outside counsel, and they can’t be everywhere.
Those folks can and will take care of themselves.
But the millions of people who cannot afford a lawyer to guide them through the perils of housing court, domestic violence, immigration, and even simple contracts mostly cannottake care of themselves.
This image is from Nigeria, from the organization known simply as Access to Justice.
As Stephen Mayson said at the College Futures Conference a year ago, to assure the “legitimate participation of citizens in society” is a fundamental purpose of law. And as Ron Staudt said this year, technology is critical to narrowing the justice gap.
There is work to be done. Go forth and invent! Like these folks:
Do not be frightened. It’s an exciting future. There is no need to light matches.Do not be frightened. It’s an exciting future. There is no need to light matches.
