Being a practicing lawyer is steeped in tradition and all kinds of archaic things (wigs?). What I meant by 'lawyer' is not paralegal or research but being admitted to the bar and allowed to practice law. I really don't see a computer getting a pass on that anytime soon simply because the bar association is made up of lawyers.

That research can be aided and may be done by a computer is beyond dispute at this point, but that job is called being a 'paralegal'.

Being a paralegal is usually a step to becoming a lawyer so I can see a bit of a continuity problem there.

The continuity problem will crop up across lots of disciplines, though. When we automate, we'll probably start out at the lower ends of every discipline, crowding out juniors where they'd normally onboard. That won't be too threatening to senior stakeholders in the discipline, either, so they may let it happen. And then automation will creep its way up the value chain; there'll be strong pressure for it to do so, because with automation making the onramp harder to get onto, there will be an increasing scarcity (and thus increasing profit motive) to climb the value chain.

We, at Doctrine (doctrine.fr), are "automating" the search/discovery/legal monitoring. So, we are disrupting the low-level, groundwork so lawyers can focus on higher level tasks.

This was what I was telling my friend: management, legal research, and medical diagnosis are places where machine learning will flourish in the incoming years as (I hope I'm not oversimplifying this) those processes depend on looking up specific cases and inferring a condition from them.