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“The era of LLM dominance in legal contract review is upon us”.

Oh, just listen to the tiny, AI violins. Some legal technologists have presented a “groundbreaking comparison between large language models and “traditional legal contract reviewers” — being junior lawyers and legal process outsourcers — benchmarking then against a “ground truth” set by senior lawyers.

It did not go well for the meatware.

The researchers collated and anonymised ten “real-world” procurement contracts — NDAs were deemed a bit easy — and fed them to a selection of junior bugs, LPOs and large language models.

The buried lead: variance increases with experience

An interesting finding, noted but not explored by the paper, was a variance measurement across the categories of human reviewers: the least qualified, the LPOs had an “alpha” variance of 1.0, implying complete agreement among them about the issues (a function, we suppose, of slavish and obedient adherence that is beaten into LPO businesses). This dropped to 0.77 for junior lawyers and further still to 0.71 for senior lawyers.

You read that right: experienced lawyers were least likely to agree what was important in a basic contract.

This says one of two things: either lawyers get worse at reading contracts as they get more experienced — by no means out of the question, and would explain a few things — or there is something not measured in these key performance indicators that sets the veterans apart. That, maybe, linear contract analytics is the proverbial a machine for judging poetry, and isn’t all there is to it.

Hold that thought.

Results: all hail the paralegals?

In any case, for accuracy the LPO paralegals did best, both in spotting issues and in locating them in the contract. (How you can spot an issue but not know where it is we are not told). Junior lawyers ranked about the same as the chatbots. Perhaps to spare their blushes the report does not say how the vets got on.

But it shouldn’t surprise anyone that all the machines were quicker that the humans of whom. LPOs were by far the slowest. There is a cost to obliging humans to behave like robots.

Clear implication: as we can expect LLMs to get better over time, the meatware’s days are numbered.

Now, if you ask an experienced lawyer to craft a set of abstract guidelines that she must hand off to low-cost, rule-following units, but for whose operation she remains accountable, expect her to draw her boundaries conservatively.

There being no “bright lines” wherever there is scope for nuance or call for subtlety, she will stay well inside it, not trusting a dolt — whether naturally or generatively intelligent — to get it right.

This is common sense and little more than prudent triage: well before any practical danger, her amanuenses must report to matron for further instruction. She can then send the machine back into the fray with contextualised instructions, or just handle anything properly tricky herself. This is all good best-practice outsourcing, straight from the McKinsey playbook.

Now, a standard-form contract without at least one howling error is unknown to legal science, so she should expect an assiduous machine reader, so instructed, to be tireless, and quickly tiresome, in rooting out formal discrepancies and bringing them to her attention.

Contrary to modernist wisdom — viz., thou shalt not rest until all problems are solved — descending the fractal tunnel of error is, largely, a bad idea. These are the things an experienced lawyer rolls her eyes at, takes a moment sanctimoniously tut about, but then lets go. Usually, she will not register that the “issue” was even there. This is noise: instinctive, formalistic fluff, well past a seasoned professional’s ditch tolerance.

Q: What’s the difference between an LLM and a trainee?

A: You only have to punch information into an LLM once.

This, perhaps, accounts for that mysterious variance among experienced lawyers. Contract review, end of the day, is an art, not a science. Much of a contract is filler better satsficing than optimising much less perfecting. Sometimes you take a point, sometimes you don’t. Some like the comfort of redundant boilerplate, others cannot abide it. Harbouring different traumas and scars from their life experience, different individuals — and institutions — are fearful about different things.

Does it matter that your contract has a counterparts clause? Does it matter that it doesn’t?

A busy-body LLM that catches every blemish and cannot take a view as often creates a problem as a solution. This kind of literalness rubs off, or is beaten out of, junior lawyers as they develop. But mechanical ducks like LLMs have an insatiable thirst for it.

For what we are fighting here is not bad lawyering, nor bad machines nor bad intentions but bad process design. Supporting it with machinery will make things worse. This is the lesson of the sorcerer’s apprentice.

The oblique purposes of formal contracts

T{{{2}}}here is one peculiarity that a literal approach to contract review cannot address, but we should mention: sometimes a contract’s true significance runs tangentially to its content. The forensic detail is not always the point.

Sometimes the act of finely thrashing the details out even frustrates the true purpose of the contract, which is to fulfil a sociological function. As a commitment signal or competence signal.

A basic example: European financial services regulations require institutions to have written contracts with all customers, as a regulatory end in itself. They are less prescriptive about what the contracts should say. You must, therefore, have a written contract to do business. To meet that end, any delay in finalising the contract in the name of “getting it right” is cause for regret.

In other cases contracts act as a mating ritual, of sorts: a performative ululation of customary cultural verities meant signal that yes, we care about the same things you do, are of the right stuff, the same mind and our ad idems are capable of consensus. Again, it matters less what the contract says then it is there.

If it is that — most NDAs are that — then descending into the subterranean pedantry and exactitude that an LLM offers, in the service of “picking up things that even a trained paralegal might not” can be even counterproductive. The point is to carry out the ritual; accord these pleasantries the required respect but to not labour them.

Now. That aside: with high-volume, low-risk legal processes — especially where they do not play a part in the courting rites — the name of the game is not fast, efficient and precise negotiation, but no negotiation. Negotiation is the problem. If you find customers regularly negotiate your standard terms of business, or you get regular snarl-ups on procurement processes and end-user sale contracts you have bad contracts. Fix them.

This might be a matter of formal redesign, or persuading legal to come to Jesus on the preposterous width of the exclusion of liability and indemnity — but the answer is not to excellently negotiate individual contracts. This leaves you with two enduring problems: first, your portfolio of homogenous customer sale contracts are not homogenous; secondly, you have now overlaid administrative machinery upon a bad process — that generates non-standard contracts — that will be hard to remove. By appointing unskilled bureaucrats and technocrats to oversee and manage that process, and likely other unskilled bureaucrats to oversee and monitor them , you have institutionalised bad process.

John Gall’s Systemantics captures this well. Temporary fixes have a habit of becoming permanent. Bureaucrats are butterfly collectors: they do not give up responsibilities without a fight. Before long, this process will have itself sedimented into the administrative sludge that weighs your organisation down.

LLMs can’t function by themselves (yet: we are not quite at the point of skynet, however much techno-utopians might hanker for it). They imply not saved legal cost, but “waste” transferred: it will be diffused among software-as-a-service providers, the firm’s procurement complex, internal audit, operations and, yes, legal who will still have to handle exceptions, manage and troubleshoot the system, vouch for it, periodically certify its legal adequacy and present it to the opco

LLMs as finite. They necessarily mimic what has gone before. While yes alpha go might engineer a novel strategy in a zero sum game, it is not so easy on in the non linear infinitude of life. An LLM that purports to improve on its training material will be distrusted it doesn’t understand, so what good had it got of reimagining?

The perfect LLM serves up an archetypal sample of what you already have.