Your reasoning works if you think of "robotic takeover" as some isolated event that threatens existing politicians. I see it as gradual change.

It could start with politicians leaning on AI to make better-informed economic decisions, or to predict the voters response to proposed policies. That would force other parties/governments to either do the same or fade to obscurity. This change would be spread out over longer period, but I don't see politics as safe haven.

I really don't see 'vote for algorithm x' as an option in any democracy.

I looked up lawyers too (https://willrobotstakemyjob.com/23-1011-lawyers). Given the fact that a lot of the legal research and discovery work that lawyers do is already being done by software instead of junior level humans, I think that number is completely wrong. A lot of legal work outside of negotiation is essentially data transformation and interpretation which is exactly what machine learning is good for. Law is probably second to accounting for massive disruption in the next few years, but it's a close call.

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.

Try teachers. 'Teachers and Instructors, All Other' has 0.85%, although teachers assistants don't do so well.

According to this data - the safest is Recreational Therapists. However I suspect you are correct about Politicians...

Sales Engineer was the lowest I could see - 0.4% risk of automation.

Much better than 3.5% for lawyers and 13% for software developers.