In a lengthy article that is my new gold standard for analysing the
actual consequences of introducing AI into an industry, Justin Curl,
Sayash Kapoor, and Arvind Narayanan explore the effects of AI on legal
work.
Sayash and Arvind had previously authored AI as Normal
Technology (also well worth reading), which argues that it’s
a mistake by both boosters and doomsters to treat AI as some special
category of thing that will lead to humanlike or superhuman
intelligence; instead, we should treat it, and should remain in control
of it, like any other technology. In particular, we should measure its
impact by how it diffuses through society and industry, not by what it’s
capable of in isolation, and we should expect that diffusion to take
decades, not months.
This article is their attempt to apply the “AI as normal technology”
thinking to a particular industry.
As a document- and language-focused industry, law has seemed ripe for
LLM-based disruption; as an industry that often commands extremely high
fees for its work, many people are desperate for that disruption to
happen, and for legal work to become cheaper. That motivated reasoning
is perhaps one of the reasons why law regularly tops the panic-inducing
lists of “jobs that won’t exist in the future because of AI”.
The authors’ conclusions are much more nuanced. They look at regulatory
concerns, which might inhibit AI’s progress into the industry; they look
the fundamental dynamics of the industry, in this case the adversarial
nature of common-law countries; they look at the impact of past
technologies, which often failed to deliver the commodification of law
that many people imagined.
AI, they conclude, won’t fix any of the structural problems faced by the
legal industry and those who interact with it as clients, and may even
magnify them; but it may be that the mere threat of AI disruption can be
an external impetus to reform, reform that otherwise might have faltered
through lack of will and coordination.
I think both the specific conclusions about law and the general
framework outlined by the authors are enormously helpful contributions
to the discourse around AI, and I’ll be trying to think along similar
lines in my own work. #