The legal community needs to navigate the world of Artificial Intelligence, which is a big forest of academic and commercial work around “the science and engineering of making intelligent machines”
Google Plays Go, Wins! No, that’s not another unpublished Dr. Seuss book. It’s the dramatic outcome of artificial intelligence research at Google’s Deep Mind subsidiary, whose AlphaGo program recently won five straight against the top-ranked Go master in Europe. The game of Go is 2,500 years old and, despite its simple rules, is many orders of magnitude more complex than chess.
What is most remarkable about AlphaGo’s victory is that AlphaGo was not “taught” how to play Go. Instead, its multilayer neural network learned how to play, and then how to win, by playing millions of games and observing the winning strategies.
Ten years ago IBM Deep Blue defeated the reigning world champion chess player. Five years ago, IBM Watson defeated the two best Jeopardy players. One year ago Google Deep Mind learned to play, and win, 46 old Atari arcade games. Today, Deep Mind plays Go, wins. (Facebook AI Research is playing Go too, and you can watch.)
These stunning and rapid advances in software that does what humans do, but better, invite not only an optimistic question — what next? — but also a worried warning. In an editorial accompanying publication of the AlphaGo research, the journal Nature wrote:
As the use of deep neural network systems spreads into everyday life — they are already used to analyze and recommend financial transactions — it raises an interesting concept for humans and their relationships with machines. The machine becomes an oracle; its pronouncements have to be believed.
When a conventional computer tells an engineer to place a rivet or a weld in a specific place on an aircraft wing, the engineer — if he or she wishes — can lift the machine’s lid and examine the assumptions and calculations inside. That is why the rest of us are happy to fly. Intuitive machines will need more than trust: they will demand faith.
So, what does this mean for law?
The other day, a search for “artificial intelligence in law” produced 86,400 results from just the News section of Google’s vast index. From the Web as a whole, 32.8 million results and from Videos — 261,000, beginning with Jude Law’s role as Gigolo Joe in the movie A.I. (thank you, RankBrain).
The first News story was “Law firm bosses envision Watson-type computers replacing young lawyers,” reporting on the answers to one question in the recent Altman & Weil survey of law firm leaders. As wittily argued by Ryan McClead, “the question is flawed on many levels [and]… it’s time to cut the hysteria surrounding artificial intelligence in law.”
Yes, there’s something going on here. But we need to parse the pile a bit. What is Artificial Intelligence (AI)? What is AI doing in law? Who is doing it? And where is it headed?
What is this thing called AI?
AI is a big forest of academic and commercial work around “the science and engineering of making intelligent machines,” in the words of the person who coined the term artificial intelligence, John McCarthy. A thorough and hype-free review of AI in business was published recently by Deloitte, Demystifying Artificial Intelligence, suggesting the term “cognitive technologies” to encourage focus on the specific, useful technologies that emerge from the broad field of AI.
However labeled, the field has many branches, with many significant connections and commonalities among them.
Lawyers do not need robots or machine vision, but other branches of AI are indeed useful. Practical use of cognitive technologies in legal services is by no means new, nor did it begin when IBM’s general counsel predicted that Watson could pass the bar exam by 2016.
Artificial intelligence is hard at work in the law — for example, in legal research, ediscovery, compliance, contract analysis, case prediction and document automation — though often there is no “AI Inside” label on the box.
Machine learning, expert systems and other AI techniques enable lawyers to devote more of their time to more valuable (and interesting) work. Mining documents in discovery and due diligence, answering routine questions, sifting data to predict case outcomes, drafting contracts — all are faster, better, cheaper and becoming more so with the assistance of intelligent software.
