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From hype to productivity

Technologists talk about the five phases of technology hype and legal tech is no exception

The biggest event in the legal technology calendar is ILTACON, held every August. The International Legal Technology Association is a member-led organization of legal and technology professionals supported by the vendors and consultants in the industry. This year alone, more than 4,000 people descended on Washington, D.C. for a week of educational sessions, networking, training and demos. Both innovation and artificial intelligence were once again scattered throughout the week’s agenda, but some of the intense hype I remember from last year seems to have worn off.

Back in 1995, Gartner realized that the amount of media hype and the excessive enthusiasm surrounding new and emerging technology affected society’s adoption of that innovation. The hype cycle is now pretty much an institution in the high-tech industry and helps explain how a technology evolves over time. Insiders use a roller-coaster-looking image to show the life cycle of a technology and make predictions about when an innovation will mature and achieve mainstream adoption. I think of the hype cycle as a graphical representation of Amara’s law: “We tend to overestimate the effect of a technology in the short term and underestimate its effect in the long term.”

There are five key phases to Gartner’s hype cycle for a technology. The first is the “technology trigger” where early and overly excited media interest in brand new technology happens. This enthusiasm and excitement about the latest and greatest builds into the hype that we have all seen for things such as machine learning, blockchain and AI. This hype infects the industry, its end users and investors, which in turn feeds the media even further with more hype, and builds into what is termed the “peak of inflated expectations.”

That occurred at last year’s ILTACON where it was standing room only at the machine learning and AI sessions talking about neural networks and the power of algorithms. Looking around at this year’s conference, it seemed to me that we have finally peaked with artificial intelligence, blockchain and machine learning. Not that there isn’t still some residual enthusiasm about these technologies and their possibilities; it’s just that the talks this year struck me as being more focused on the hard and unsexy work that people are undertaking to understand the practical applications.

If that’s correctly reading where we are, then we’re heading into the “trough of disillusionment” over the next couple of years as stories of implementations that fail to deliver reach that same media and interest begins to wane. Excessive enthusiasm will be replaced with excessive disappointment in the stories that the media begins to report. But we shouldn’t mistake the trough of disillusionment with “it’s not going to happen.” Rather, it is about resetting those expectations from the inflated hype to the realities of what the technology can do.

Early adopters will use this time to explore the technology and understand where the opportunities lie. Take the recent announcements by 12 financial regulators around the world, including the OSC, and technologists to create a “global sandbox” (the Global Financial Innovation Network) to test out emerging technologies such as blockchain and AI or the new blockchain consortiums of Enterprise Ethereum Alliance and the Global Legal Blockchain Consortium. These early adopters are diving into the technology to figure out how to embed it into their products and services to be ready for the mainstream adoption that will surely follow.

Machine learning and AI both rely on good data to train and power up the algorithms. The data is used by humans to train the algorithms to get smarter and faster over time. So, these early firms and technology companies are taking this time to pull the quality data together and to methodically train and adjust the algorithms to do a certain thing well (such as find all change control provisions across a set of agreements). They are figuring out where the most value for lawyer and client adoption will be.

Most of this work, however, is not interesting enough for the media’s need for click-bait headlines. Little will be heard about this painstaking work performed behind the scenes until there is enough evidence and excitement about its actual outcomes. Complex problems require complex solutions (before simplification can happen) and this work is rarely done in the full glare of an overhyped media train. Slowly but surely, however, the initial kinks in the technology will be ironed out by the clever minds of our industry.

This journey up the “slope of enlightenment” is where the commercial viability of the innovative technology crystallizes for those in the sandboxes of learning. New iterations get produced that improve the technology — it’s not yet plug and play, but more early adopters and interested parties are convinced that they should take a closer look. However, conservative organizations and investors remain skeptical and tend to wait until a further phase before jumping aboard.

The “plateau of productivity” is the final step in the hype cycle. Here, the innovative technology gets operationalized by the early adopters and built into the products and services of our every day. Rather than position themselves to be on the selling side of these types of solutions, this plateau is where most buyers sit. These buyers are happy to wait until the innovative technology has been packaged up into neat little products that are stable and ready for prime time. They want simple solutions that can be plugged in and deliver the expected benefits described on the tin. But it also means that any competitive advantage in developing firm-specific versions of the technology to package up and sell to clients has by now been lost.

It is helpful to recognize that our own legal technology industry falls prey to the same hype cycles as the emerging tech in consumables. As we know by now, humans are horrible at making predictions, particularly about the future. And Gartner’s hype cycle with its predictions about when an innovation will reach mainstream adoption should always be taken with a healthy pinch of salt. But our tendency to overhype the short term should not also blind us to the deceptive growth of technology and its cumulative impacts on how it will change lawyer behaviours and the nature of legal services in the long term.

Kate Simpson is national director of knowledge management at Bennett Jones LLP and is responsible for developing the firm’s KM strategy and initiatives. Opinions expressed are her own.


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