Combining Our Forces

In the dawning era of artificial intelligence, humans must learn to harness the power of the machine
IN “AUDITABLE CONTRACTS: Moving from Literary Prose to Machine Code,” Kingsley Martin of the Thomson Reuters Legal Executive Institute writes about a spectrum of contracts that are highly suited to computer analysis.

“Auditable contracts” are within this spectrum; they “can be reviewed by a computer system with a high degree of accuracy to determine, for example, the presence or absence of clauses, discrete items of information (such as names, dates and figures), and examine the nature of contractual language,” Martin writes.

“Of course, you can hear a loud chorus of lawyers saying: why should we draft in a manner that makes the agreement more amenable to computer analysis,” he continues. “The task of auditing entire portfolios of agreements, analyzing their contents, and seeking to optimize their value can be greatly enhanced with high-performance, scalable computer programs,” and in a fraction of the time. 

The computer wins the move, which brings us to chess.

In a recent edition of his “Waking Up” podcast, philosopher and neuroscientist Sam Harris reminds Russian chess player Garry Kasparov, “You will go down in history as the first person to be beaten by a machine in an intellectual pursuit where you were the most advanced member of our species.” 

Kasparov beat IBM’s Deep Blue in 1996, then lost to it a year later. He had wanted a so-called “rubber match” to clinch his victory forever, but it is the loss that will be remembered in perpetuity.

Now Kasparov has written Deep Thinking: The Human Future of Artificial Intelligence (PublicAffairs, May 2017), “not to settle old scores … but to say that we should not be paralyzed by a dystopian vision of the future — worrying about killer AI and super-intelligent robots, which is like worrying about overcrowding on Mars.” Kasparov suggests “combining our forces” instead, that is to say, human and artificial intelligences. 

On the podcast interview, Kasparov describes his “change of heart: while writing the book I did a lot of research ... and I changed my conclusions. I am not writing any love letters to IBM, but my respect for the Deep Blue team went up, and my opinion of my own play, and Deep Blue’s play, went down. Today you can buy a chess engine for your laptop that will beat Deep Blue quite easily.” 

In Kasparov’s view, humans “are not consistent, we cannot play under great pressure. Our games are marked by good and bad moves — not blunders, just inaccuracies. They remain unnoticed in human chess, but are very damaging when you are facing a machine.” 

Kasparov and others have developed chess games/programs in which humans team up with computers. Are there analogies for contract automation, and elsewhere in the law? To answer that question, lawyers must ask themselves what they do better than machines, such as managing relationships and exercising judgment; humans can also analyze artificial intelligence and the like for their clients’ benefit. Then we need to decide what computers do better or more efficiently than humans, and how lawyers can then use AI to advance their clients’ best interests.

In Deep Thinking, Kasparov assesses the talents of computers and machines. Point: “Computers have a certain advantage in games where streaks of lucky or unlucky cards or dice rolls can influence the decision-making of humans.” Counterpoint: “We do not calculate every decision by brute force, checking every possible outcome. It is inefficient and unnecessary to do so, because generally we get by pretty well with our assumptions.”

Writes Kasparov, “We are entering a new era, and … it very much depends on us, on our attitude and our ability to come up with new ideas. It’s up to us to prove that we are not redundant.” 

Jean Cumming is the Editor-in-Chief of Lexpert, a suite of award shows and online and print publications from Thomson Reuters.
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