Here’s a new twist on the notion that AI will soon make businesses all super productive and maybe all of us irrelevant. In fact, AI may actually slow productivity growth which eventually could chill the AI hype.
Wait. What?
According to a well-researched Fortune Magazine article, AI is slowing the growth of productivity. And it could mean more, not less, work for us poor human lawyers.
It’s all based on the observations in the late 80s of the economist Robert Solow. Back then, the prevailing view was that new technologies like transistors, microprocessors, and memory chips would disrupt workplaces and result in increased productivity growth. But in fact, according to Solow, the opposite happened. Productivity growth actually slowed over the years. It’s the Solow paradox.
Why? Solow believed it was because the new technologies produced more and more information and reports that had to be read, pored over, and analyzed. In other words, the tools created more work, not necessarily greater productivity.
And it may be happening again. The Fortune article cites a lot of statistics showing that even though AI is being implemented by many businesses, they aren’t showing productivity gains. Other studies cited by Fortune suggest that many executives are seeing little impact of AI on their operations. In fact, despite the substantial investments in AI tools, many are struggling to show the return on investment. Other research cited in the article suggests that confidence in the technology seems to be waning.
What in the Sam Hill Is Going On?
Lots of interesting facts here that could impact legal. First, there could be some simple reasons for the lack of productivity increase: AI gains just haven’t caught up to us yet. When it does, for legal, this would mean as firms implement more and more AI into workflows, the legal outputs should increase. Costs should also be reduced at least presumably.
But legal has some peculiar characteristics that may mean Solow’s paradox may hold at least for a while. Certainly, AI will produce more information: when the whole world is easily searchable and regurgitated in summary fashion, everyone has access to more answers. And giving a group of lawyers more answers will just give them more to argue about, not less.
It also means more information to digest and factor into strategy. It means more verification required in a profession where accuracy is critical.
And lawyers by their nature and training look for problems. Give them more information and they are going to look for more problems. Which means more searching for solutions.
There’s also that pesky business model: the billable hour. Most seem to think the model is a dinosaur in the age of AI since it will take so much less time to do things. But if the number of “things” to do increase, it could mean it takes more time to do them all. And therein lies the strength of the billable hour model. As long as there is plenty of work to do, it will be hard to kill it. Not to mention the fact that for some matters, like those with perceived high exposure, clients want the billable hour model since it ensures thoroughness.
Moreover, we are already seeing increases in some litigation that are fueled by AI efficiencies as I have discussed. For example, AI enables lawyers to take contingency fee cases they couldn’t before because many of the cost-generating tasks overwhelmed the case value. Now those cases become economically viable. So, we have more work for humans to do.
Add to all this lawyers’ innate resistance to change, particularly change they feel is imposed on them, and the Solow paradox may hold sway in legal for the foreseeable future.
Let’s Not Write Off Human Lawyers, At Least Not Yet
There’s an old saying that the amount of work to be done somehow manages to fill all the available time to do it. That may be true here, especially in legal. The Fortune article and quoted statistics suggests that productivity gains are not materializing and there will be more work to be done. That in turn raises at least the possibility that lots of investment money is being spent for little quantifiable return. If that’s true, then sometime soon, the spigot may run dry.
This — together with the fact that much of GenAI for legal has been overhyped and oversold, and that ROI is not easy to quantify — raises the possibility that the GenAI hype volcano Melissa Rogozinski and I have discussed in our Pompeii series (see below) may be about to erupt, leaving many investors, vendors, and users holding the bag.
In the meantime, as the article suggests, despite all the hype, in many ways it’s still more or less business as usual. So, let’s all take a deep breath before we predict the end of human work. And oh yeah, get back to work.
The Pompeii Series:
Like Lawyers In Pompeii: Is Legal Ignoring The Coming AI Infrastructure Crisis? (Part I)
Like Lawyers In Pompeii: Is Legal Ignoring The Coming AI Cost Crisis? (Part II)
Like Lawyers In Pompeii: Is Legal Ignoring The Coming AI Trust Crisis? (Part III)
Like Lawyers In Pompeii: Is Legal Ignoring The Coming AI Financial Crisis? (Part IV)
Like Lawyers In Pompeii: Is Legal Ignoring The Coming AI Definition Crisis? (Part V)
Stephen Embry is a lawyer, speaker, blogger, and writer. He publishes TechLaw Crossroads, a blog devoted to the examination of the tension between technology, the law, and the practice of law.
