Last week, Representative Greg Casar of Texas introduced legislation intended to protect American workers from what he describes as the threat of mass unemployment caused by artificial intelligence. The proposal would tax certain uses of AI associated with job losses and use the proceeds to support employment. The premise reflects an increasingly common fear: if machines can perform more of the work people do today, there may eventually be far less work left for people to do.
There is plenty of reason to take that possibility seriously. AI is already performing tasks that recently required highly educated professionals. But legislation designed to protect existing jobs raises a more difficult economic question: does identifying the work AI can eliminate tell us very much about how much work people will ultimately have?
A View From Inside the Disruption
Stephen Lofchie has an unusually informed perspective on that question. One of the country’s leading lawyers in financial-services regulation, he has spent decades advising businesses operating in some of the most complicated areas of law. He also concluded years ago that much legal work was unnecessarily inefficient, began building his own regulatory databases, and eventually saw AI become capable enough that he helped create Caffrey.ai, an AI company for legal and regulatory professionals. He continues to practice law while helping develop technology capable of performing some of the work lawyers have traditionally been paid to do.
Lofchie has no illusion that AI will preserve every legal task or job. Yet when I asked what the profession might look like in the future, his prediction was not that lawyers would have less to do. “I think lawyers will be doing actually more,” he said. Understanding how both things can be true may tell us more about the future of work than counting the jobs AI can replace.
When Cheaper Work Creates More Work
Much of law appears particularly susceptible to AI because the work is built around language. As Lofchie puts it, “It’s words on a page and words over the telephone.” Lawyers absorb documents, research how laws have been interpreted, apply them to facts, and communicate their conclusions. Judgment is required, but much of the work leading to it has traditionally been performed by junior lawyers. AI can now do much of that “extremely well.”
If fewer lawyers can produce the same amount of legal work, fewer lawyers would seem to be needed. What that arithmetic misses is that demand is not fixed. “I think the cost of producing good legal work will go down,” Lofchie says, and “as costs go down there’ll be a demand for more of it.”
Clip from the interview.
Ty Greenberg, Chief Revenue Officer of Caffrey, who is leading the firm’s go-to-market effort, points to AI, crypto, and prediction markets, where new forms of economic activity do not fit neatly within existing laws and regulations, creating novel questions for businesses, lawyers, and regulators.
None of this establishes that increased demand will employ as many lawyers as AI displaces, and Lofchie makes no such prediction. But productivity lowers costs, lower costs increase demand, and solving problems through innovation invariably creates new problems to solve. The amount of human labor required to perform today’s legal work therefore tells us surprisingly little about how much legal work there will be tomorrow.
The Businesses That Don’t Exist Yet
The larger economic effect may come from the new activity that cheaper legal expertise makes possible. Regulatory complexity imposes costs before a business ever earns a dollar. “Think about a new startup,” Lofchie says. Can it afford law-firm partners charging $2,000 an hour simply to determine how to launch within the law? He calls that expense “a tremendous drain on a new business and the possibility of a startup, or even a new desk at a big firm.”
That is part of the opportunity Lofchie saw in creating Caffrey, which combines AI with the regulatory databases and systems he began developing years earlier. Greenberg says customers may see a profitable new business opportunity but first need to determine how to pursue it within the relevant regulations. Reducing the cost of answering those questions makes more opportunities worth investigating.
The implications extend beyond law. Every business has ideas that are never pursued because the expected return does not justify the cost of investigating them. For an entrepreneur, lowering that hurdle can make a new company viable. For an established financial institution, it might mean testing a new trading desk or entering a new market.
We can count the work AI replaces, but we cannot count the trading desks that were never opened, the companies that were never started, or the ideas that were never tested because finding out whether they would work cost too much.
What AI Makes More Valuable
As AI takes over more routine legal work, the lawyer’s role shifts toward what the technology does less well. Lofchie says lawyers, particularly younger ones, tend to overestimate the “pure words on a page element of lawyering.” Clients need more than the right legal answer; they need someone who understands their business and can exercise judgment about what to do with it. Greenberg says that even as AI performs more research and document analysis, demand for senior legal expertise is rising. For “bet the company” litigation, he notes, clients never wanted a junior associate making the critical decisions—and they aren’t likely to turn them over to AI either. As intelligence becomes cheaper, judgment, experience and trust should become more valuable. The resulting work should be better as well, because AI can perform far more research and analysis within the economic limits of an assignment, leaving the lawyer to apply human judgment to a richer body of information.
Lofchie is dismissive of lawyers who resist AI because it sometimes hallucinates or makes mistakes. “You don’t think first and second year associates make mistakes?” he asks. The appropriate response in either case is verification. Paradoxically, Lofchie believes that may become more important as AI improves. When a tool produces consistently impressive work, the temptation to trust it grows, making the occasional error easier to miss. That leaves another important role for expertise. The lawyer may spend less time producing the initial analysis but still needs to know enough to recognize when an authoritative-sounding answer is wrong.
Lofchie believes AI will “really reward active learners.” A lawyer can use it to understand a client’s business more deeply, explore an unfamiliar area of law, or quickly learn how another jurisdiction approaches the same problem. The advantage extends well beyond law. When information becomes cheaper and easier to acquire, the value of what someone already knows should decline relative to the ability to learn, ask the right questions and apply new knowledge. AI will therefore favor the curious over the complacent. The most successful knowledge workers will not be those who use AI simply to perform today’s jobs more efficiently, but those who use it to expand the range of problems they can solve.
The political appeal of protecting workers from technological change is hardly new. Yet the United States has prospered in large part because it has repeatedly allowed innovation to disrupt existing ways of working and doing business. Maintaining that balance is particularly difficult with AI, whose effects may be unusually rapid and far-reaching. As Congress considers taxing companies for replacing workers with AI, it should remember that protecting today’s jobs can also prevent tomorrow’s from being created.
Full Interview.
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