lawtalkinghuman

When the alternative is being surrounded by rabid AI enthusiasts who absolutely lose their shit whenever anyone says "no" to them, being left behind is a great choice.

AI has clearly wrecked your ability to read.

If you're a UK media outlet accusing a Big Four accounting firm and a Russian billionaire of tax fraud and you've got it wrong, you can bet there will be a case filed incredibly quickly in the High Court.

And the practical effect of this is you get a race to the bottom: countries compete on how lax they are going to be in enforcing GDPR so as to attract American tech companies.

The Data Protection Commission in Ireland are remarkably lax about enforcing it because the government quite likes the tax revenue that Google, Apple and Meta brings them.

No, the clue is in the name, "General Data Protection Regulation". If it were a directive, it would be called GDPD.

Someone having share options in a company means they have skin in the game, which means you can trust their opinions more.

Someone betting—sorry, investing in a prediction market—means you can have even more confidence in their convictions.

But someone having a Patreon account for people to voluntarily donate money to them means they can't be trusted.

I have tested Lexis AI once for a legal research point. I wasn't particularly keen on putting the exact details of an actual problem in, but I gave it a summary version.

It didn't feel drastically different from using ChatGPT with the ability to search the web, except it was searching material on Lexis, both statute/case law and commentary. It dug out some commentary that confirmed my prior hunches, but also pointed to some cases that weren't in any way relevant.

Otherwise, all the experimentation I've done is with non-confidential material using public LLMs.

Just because the citation exists, what the LLM says it stands for and what it actually stands for are not the same.

For testing, I've asked (admittedly last-gen) LLMs to generate legal opinions regarding issues in commercial English civil litigation, and I received back cases where the citation is real, but the area of law (family law) is not relevant as family courts apply a very different set of procedural rules.

(If you squint a bit, they sometimes might be relevant... and could be useful for a particularly creative litigator to make a novel argument on behalf of a very risk tolerant client. But you would very much want to go read those cases and think quite hard about them.)

It’s almost as if all the guardrails aren’t real.

The answer is: the market will work it out eventually. Clients will push for more work to be fixed-fee/outcome-based rather than billed hourly. There'll be some small firms who'll successfully grab lots of lower value clients who are willing to use digital tools to handle their work and don't particularly care about having a big fancy office in London or New York if it means lower bills (and they can then basically use the relationship they've had providing the supervised online service to be the first point of call when said client wants something that's less off-the-shelf and needs more work).

Also, an interesting example: in English litigation (where, broadly, loser pays unlike America where each side pays), maximising billable hours is not always a viable strategy for anybody if those costs aren't recoverable on success. Someone involved in large-scale commercial litigation involving disclosure of millions of documents who doesn't use algorithmic document classification (now pretty broadly accepted as normal) potentially runs the risk of a judge determining that the costs of going through all the documents by hand isn't recoverable. Insurers/litigation funders aren't going to want to risk padding the costs so much that the judge prevents them from recovering their stake in the litigation.

Customers using their own LLMs: yep, they might do that. I think the pitch from the legal LLM providers is "we've got legally trained people doing RLHF to make it more accurate" mixed in with "also we've got a partnership with Lexis/Westlaw/etc. so we can do legal research that's better than what's on the open web", with a little bit of "if you get sued for professional negligence, 'I used the legal AI thing that's built into Westlaw' is gonna be more convincing to a judge and jury (and your insurance company) than 'I used ChatGPT, yes, like the app you've got on your phone'...".

> That's why the EA guys are off beng quants.

Or in prison for fraud.

Yes, that's the general rule.

You then get lots of interesting exceptions and difficulties in applying that rule: who pays when you have multiple potential defendants (but some of them have died or gone out of business or are in a different jurisdiction), or there are fiddly causation issues, or the defendant is an organisation that's vicariously liable for their employee/contractor/authorised religious leader/any number of other relationships, or there's insurance involved, or there's some third party interest, or the purportedly tortious act was mandated by some law or other obligation, or the government decides to set up some kind of alternative process of compensation which may or may not indemnify the tortfeasor, and so on and so on.

When dealing with the not-so-straightforward cases, appellate courts do look at questions like "is this a fair and equitable distribution of the cost?" and legal scholars compare the pros and cons of tort liability to other mechanisms (compensation by the government, industry self-regulation, no-fault/strict liability, mandatory insurance etc).

If my goal is not seeing AI slop, I don't particularly care whether it is honestly labelled or not.

The difference is OneDrive is moderately useful.