PRESENTATION BY JOHN O. MCGINNISGEORGE C. DIX PROFESSOR IN CONSTITUTIONAL LAW AT NORTHWESTERN PRITZKER SCHOOL OF

LAW

Machine Intelligence and the Legal Profession

Accelerating Computational Power

Machine Intelligence has continued to become ever more powerful

Moore’s Law has held for 40 years

Improvements in software and connectivity are force multipliers

Accelerating Computational Power

Exponential growth is likely to continue through other means, like carbon nanotubes and optimal computing

Accelerating Computational Power

Machine intelligence has moved from formal systems to systems with more uses in everyday life and in the profession of law1997 – Big Blue beats World Chess Champion Gary Kasparov2011 – Watson beats Jeopardy Champion Ken Jennings2013 – IBM builds a division around Watson’s analytics2016 – Law firms hire Ross, a service based on Watson’s analytics

Predictive Coding

Source: Lit i View

After being trained by lawyers on a sample of relevant documents, machines are responsible for finding other documents in discovery

Predictive coding is advancing One 2011 study indicated that:

Manual reviewers identified between 25% and 80% of relevant documents, while technology-assisted review returned between 67% and 86%

Technology-assisted review required human review of just 1.9% of the documents

Courts are increasingly granting requests from parties to use predictive coding in litigation

Common methodologies: Concept Searching Contextual Searching Metadata Searching

Predictive Coding

Law firms have problems creating disruptive technology in their field

It is not lawyers, but other businesses that are leaders

Important Players:

Predictive Coding

Legal Search

Computerized legal search has been around for 40 years, but it has been focused on key words

Now the movement is toward semantic search Using IBM’s Watson, a team of students at University

of Toronto launched ROSS Intelligence in 2015 with support from global law firm Dentons

LexisNexis TotalPatent includes a semantic search option

Moneyball comes to lawDefined by the Gartner IT Glossary as:

“Any approach to data mining with four attributes: An emphasis on prediction; Rapid analysis measured in hours or days (rather than the

stereotypical months of traditional data mining); An emphasis on the business relevance of the resulting

insights (no ivory tower analyses); and An increasing emphasis on ease of use, thus making the

tools accessible to business users.”Law firms can use predictive analysis for:

Targeting lucrative clientele Pricing matters based on past performance Predicting outcomes of litigation

Legal Predictive Analytics

Legal Predictive Analytics

In 2015 LexNexis bought out Lex Machina, a company with substantial data

Legal Predictive Analytics

Docket Alarm’s Patent Trial and Appeals Board analytics program allows users to generate reports on judges, as well as parties, firms, and technology areas to see who settles the most and at what stage.

Transactional Documents

Legal Document generation is occurring at both high and low ends

Legalzoom creates documents, such as wills, for the masses

Startup Documents has created a program to generate and store documents for startups wishing to incorporate, grow, and maintain their businesses

RocketLawyer provides individuals and businesses with legal document generation and enforcement services

Linear v. Accelerating World

Once computation gets into a space, it does not stopImproves search, document generation, predictionEven brief writing may be invaded in the decades to

come

Evidence for Effect Already

1. Decline of incomes of “small” lawyers2. Stagnant associate salaries3. Drop in talented people applying to law

schools – their own future prediction4. Huge increase in start-ups in legal space

The Stanford Center for Legal Informatics hosts a curated list of 551 companies “changing the way legal is done”

The list includes 153 document automation companies, 42 legal research companies, and 38 analytics companies

Evidence for Effect Already

Long-term Changing Composition

Technology is more likely to displace lawyers in low-value and simple matters Innovation happens at the low-end first i.e., drafting standard legal forms, areas of law where

patterns and past data can predict the outcome of a case Lawyers in relatively stable areas of law like trusts and

estates will be severely disrupted

Technology is not likely to displace lawyers in high-value and complex matters Specialists in novel areas of law will still be needed Lawyers in areas of fast-changing law, like much of financial

regulation, will be largely unaffected

Machines cannot substitute for trial lawyers – but predictive analytics will help convergence on value of lawsuits, reducing the need for trials

Premium on psychology and bonding, getting clients to take sensible actions

Long-term Changing Composition

Embracing Technology

Instead of trying to slow down computation, lawyers should relax ethical rules to permit others to own law firms. See changes in Britain and Australia.

Only firms with substantial capital will be able to innovate

Roadblocks to Innovations

1. Unauthorized practice of law rules not likely to slow innovation

Legislators have pushed back on behalf of constituents In any event, most computerized service can be used as inputs into

lawyers’ work and the effect will mostly be the same Use of technology can also be placed offshore to evade restrictions

2. Rules structuring legal partnerships pose great threat to innovation

Model Rules of Professional Conduct 5.3, 5.4, 5.5, and 5.7 restrict the ability of companies to earn profits from providing legal services

Makes it difficult for law firms to raise capital to innovate and collaborate with innovators

Makes it more likely that lawyers will try to slow down innovation