Similarly, when the World Wide Web first began to dawn on the collective consciousness, no one had a clue what it would become and ultimately empower. (Remember “brochureware?”) It takes time to figure out that global real-time connectivity is actually about activities like collaboration, online communities, and the immense power that the disappearance of constraints of time and distance impose. Not to mention creating the fertile soil for entirely unprecedented and hitherto-unthinkable businesses, like Airbnb, Uber, eBay, Facebook, Google, and the granddaddy of them all, Amazon.
So we direct your attention to this wisdom embedded in the McKinsey article. You may debate their precise timeframe for adoption and the transition from “invention” to “invisibility,” but it’s a useful construct for thinking about tools like Watson:
New technologies introduced into modern economies—the steam engine, electricity, the electric motor, and computers, for example—seem to take about 80 years to transition from the laboratory to what you might call cultural invisibility. The computer hasn’t faded from sight just yet, but it’s likely to by 2040. And it probably won’t take much longer for machine learning to recede into the background.
The “invisibility” observation is particularly subtle.
AI is one of those fields that seems to have had so much promise for so long, with so little to show for it, that it has reduced even its true believers to the point of exhaustion. McKinsey frankly acknowledges this, hearkening back to the bona fide pioneer Alan Turing, who did his most inspired work in the World War II era, three-quarters of a century ago, saying, “But [neural networks and other] techniques stayed in the laboratory longer than many technologies did and, for the most part, had to await the development and infrastructure of powerful computers [in just the past few decades].”
Or, in the far pithier and more memorable phrase which now has a thousand fathers, “It’s only AI when you don’t know how it works; once it works, it’s just software.”
Does, then, IBM Watson “work?”
Without a doubt.
Here are my top takeaways from the Watson meeting:
- The firms attending agreed unanimously and without reservation that Watson is already having the greatest impact on knowledge work of any previous technology, by an order of magnitude. Watson is not only a big deal, it’s the Real Deal.
- Given the immense resources IBM has and promises to continue to put behind it, the position of commercial leader in this class of powerful technologies is Watson’s to lose; the conversation will be shaped around Watson and not something else.
- In other words the conversation has shifted from “Is Watson for real?” to pragmatic and operational issues centered on questions such as how much it would cost for a given law firm to develop its own proprietary “instance” of Watson and whether lawyers would actually use it.
- Because no law firm has yet adopted it, not surprisingly, there are no successful “use cases” in law so far, and lawyers are trigger-happy at jumping to the self-satisfied conclusion, “I told you so.” I firmly believe that’s a highly perishable, wasting argument: My own intuitive prediction is that in 6—12 months, that will no longer be true.
Readers of Adam Smith, Esq., and technologists who have had encounters with Law Land, know a few other things as well, which explain why as of mid-2015 the immense promise and potential of Watson have yet to yield a concrete case study of its deployment in legal.
The first and most pragmatic is that IBM has prioritized several knowledge domains, notably medicine, consumer-facing applications, finance, and banking risk/compliance, well ahead of law. Law isn’t a top five and probably isn’t a top ten priority for IBM Watson at the moment.
Second is everything we know about law firms’ approach to technology over the past four or five decades of experience: We prefer to be brutally late to the party. Refreshingly, more than a few of the firms in attendance last week vowed this time would be different for them.
Third is the fruit of the #1 lesson law firms learned in the wake of the GFC: Clients, not firms, are calling the shots. (Or, to use a corporate governance analogy, at least they have majority control of the seats on the Board.) No one for a moment doubts that clients will deploy Watson before law firms, including the single most critical species of client for most of BigLaw, banks. For once it would behoove us to respond with alacrity and nimbleness in place of denial, resentment, and behind-the-lines guerrilla resistance.
I mentioned the Wright Brothers earlier and alluded to their being oblivious as to potential military uses of their invention. To state the blisteringly obvious. that didn’t stop more than a few folks from coming up with such uses, in an escalating spiral of reliability, effectiveness, power, and just plain fearsomeness. Given IBM’s focus on other knowledge industries ahead of Law Land, it’s only being fair (and not unkind) to say that IBM’s degree of sophistication and depth of thought about potential legal-vertical uses for Watson is not much more advanced than the Wright Brothers on aerial warfare.
I have news for you: That’s not actually IBM’s job, and not IBM’s problem. It’s our job and our challenge.
At this point the most realistic way to think of IBM is as an arms dealer, ready and willing to sell instances of Watson to anyone interested.
Why wouldn’t your firm want to explore what’s possible? Because I guarantee you others will be doing just that. Some of them, I’ll wager, were at last week’s event.
Watson sounds really neat, but will it really make more of an impact on law practice than other machine learning systems? I’m unconvinced.
There is no current single overarching best machine learning technology, rather different best approaches depending on the problem, and constant advances in understanding of what the best approach for a specific problem is. IBM is devoting a lot of resources to Watson, but other big companies are also pouring money in to machine learning (e.g., Google, Microsoft, HP, Facebook, Baidu, Amazon). Perhaps as important, lots of companies are building machine learning technology for specific verticals (like us with contract review). Current machine learning is quite problem-specific, and these companies are getting experience honing their technology for their particular use cases. Will Watson’s technology really be better for specific verticals (like law, or sub-areas within law) than companies focused on those specific verticals?
For a much more detailed analysis of these points, see my recent post “One Ring to Rule Them All? Will IBM’s Watson Transform Contract Review and Law Practice?”:
http://info.kirasystems.com/blog/one-ring-to-rule-them-all-will-ibms-watson-change-law-practice
I have read the ASE posts on Watson and machine learning as using Watson as an example, in fact as almost surely the only example most of us would recognize by name; not as an endorsement much less a prediction.
The McKinsey article contains some additional information that strikes me as crucial, specifically the need for users of “machine learning”, especially in areas like Law, to have access to two classes of personnel: “Quants” and “Translators.” The harder position to fill will be your translator, who will need to be able to work both directions with something like equal facility. It is not just explaining to the C-suite what that graph actually says and why you should find its results reliable, it is being able to take strategic directions of the company and explain to the Quants what is required. If the problem is not understood properly, if there is not clarity by all parties as to what counts as an answer to the problem, then the Quants will go off and do their thing, and it may be some fair time before anyone knows whether the problem has been addressed in ways that are in fact useful.
Where will one find / how will one develop the Translators?