this post was submitted on 18 Sep 2026
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[–] jbloggs777@discuss.tchncs.de 4 points 3 days ago (2 children)

Too many lawyers already do half-assed work, and they have already been doing it faster with LLMs. Laymen usually won't know the difference.

If specialist skills and tools can lead to less shoddy results in spite of endemic human incompetence or similar, it will be better for the average consumer of legal services.

And in the hands of competent and engaged lawyers, better tools are a huge boon.

A game changer (already) is that laymen can often now avoid lawyers altogether as complex laws, contractual terms and procedures can now often be explained in plain english/dutch/swahili by chatbots, helping them to make better and timely decisions.

Note: This is a world-wide phenomenon, with judges, paralegals, prosecutors, police, and end users also reaching for or being impacted by AI these days.

[–] CapuccinoCoretto@lemmy.world 3 points 3 days ago* (last edited 2 days ago)

Not coincidentally we're seeing the erosion of the rule of law as a global phenomenon.

[–] FatCrab@slrpnk.net 1 points 2 days ago

I am not as optimistic about the real value of this as you are, but my practice is, ironically, IP and general advanced software counseling specialized in ML and decentralized/distributed network tech, so ymmv. Nevertheless, I think the increasing prevalence bodes poorly for the industry and consumers for two very specific reasons. For the industry, a major part of making good lawyers is by having green lawyers be shit lawyers under close supervision and lots of repetition. The rise of legal AI has already totally short circuited that fundamental process quite a bit. The other concern i have is that consumer reliance on these technologies actually pressures legal systems to converge towards greater convolution and arbitrary heterogeneousnes. This is bad because it (a) makes human inspection less and less feasible, (b) introduces a great many failure points that we'll never be able to discern until it's too late because of (a), and (c) makes the surviving equivalent of practitioners (and even automated systems) more vulnerable to the myriad issues with hyperspecialization. It is noteworthy that these are very similar issues facing the software industry.