Non-negotiable
01
Conditions, not merit
A ledger may audit the circumstances under which work gets made. It may never grade the work itself.
DRAFT SPEC · v0.2
A disclosure standard for the conditions under which human work gets made in any organisation deploying AI. It never passes a verdict on the work itself.
If we measure AI success solely by head-count reduction and output volume, we fall victim to the exact trap Kennedy warned us about in 1968. But if we design our implementations to promote human agency, we turn technology into a tool that serves the human experience rather than exploiting it.
The Human Ledger is an attempt at the instrument that would make that difference visible. It has three layers, borrowed from the way the GHG Protocol is built:
Systemic bug
We identify an easy-to-measure metric → we bend our entire culture to maximise it → we destroy the qualitative things we actually care about.
That bug is why the principles come first. Somebody proposes a metric, everybody argues about the metric, and the argument slowly settles the principle without anyone having agreed to it. So the principles come first and the numbers second, and the numbers are negotiable.
The canon
Non-negotiable
01
A ledger may audit the circumstances under which work gets made. It may never grade the work itself.
02
The opposite of a human ledger is not an unmeasured world. It is a world measured privately.
03
There is no upside to exceeding a floor, so there is no incentive to fake one.
04
Offshored volume has to land on the ledger of whoever commissioned it, or the ledger becomes a laundering mechanism with a nice logo.
05
Some work only proves its worth later. Disclose how much room people have for it, and never measure what they do inside it.
↗
With the full argument for Principle One, and the two metrics it forced us to withdraw.
The standard
Hours, training, junior headcount, human authorship, rework and exposure: externally observable, the same in every industry, and set as floors.
Unfinished
These questions are open, and not as a figure of speech: I haven’t resolved any of them. If you have the answer, it belongs in the debate rather than in my drafts folder.
Question 01
There are only three answers. A government, and you get direction. Capital, and you get liability management. Nobody, and you get exploitation with good quarterly results. I don’t think there’s a fourth. My own view is that the pen belongs to a legislature for the disclosure standard and to nobody at all for the quality judgement. But that’s a position, not a settled fact.
Argue this on LinkedIn ↗Question 02
I suspect some of them collapse in the debate. I’d like to find out which, and I’d rather hear it from the people who would have to file the numbers, in a hospital, a law firm or a bank, than from people who simply like the idea of them.
Argue this on LinkedIn ↗Question 03
D&I and sustainability reporting only grew teeth when disclosure became mandatory and third-party assured. Self-reported human metrics are marketing.
Argue this on LinkedIn ↗Question 04 · the hardest
This is the one I’d most like help with, because a boundary that can be moved by a single majority isn’t a boundary.
Argue this on LinkedIn ↗What’s changed
This is a working spec, so the thinking moves, and when it does the old wording stays visible, struck through, with the date and the reason. Here is the latest change, with the earlier ones a click away.
Was Part I argued from the creative industries: Act III was written from the marketing front line, and Act IV ended with the ten-row creative table as the worked example.
Now Part I argues from work in general and closes Act IV on the six core conditions. The creative-industry material, including the original Act III and the table, sits unchanged in an annex at the end.
Was Premature, difficult and illegible work needs somewhere to survive until it becomes recognisable, and that describes most of the work that ever mattered.
Now Some work only proves its worth later. Disclose how much room people have for it, and never measure what they do inside it.
Was A one-line definition that measured operator time, and so duplicated Rework.
Now Exposure: the AI-mediated adverse events that land on people, counted by class of harm and disclosed by position relative to the system.
Was Judgement rate as a freestanding metric: a row of the Annex A table and Part II’s central number.
Now Judgement rate is the P2 cell of Exposure: the operator position.
Was Floors, not targets, with nothing said about which measures can carry a floor.
Now Procedural cells take real floors. Outcome counts are disclosed with their trend and never targeted.
Was Six conditions, with nothing said about reading one without the others.
Now Rework is read alongside human authorship and exposure for the same period. The core is a set, not a menu.
Was Trust delta: what happens to “trustworthy” and “authentic” as our AI content share rises.
Now Withdrawn. It breaks Principle One.
Was Originality distance: distance from category convention, and from our own last 12 months.
Now Withdrawn. It breaks Principle One.
Was Five principles, and ten metrics offered only as illustration.
Now Five principles and six disclosable conditions: hours, training, junior headcount, human authorship, rework, exposure.
Was A disclosure standard for the industries that manufacture attention, measuring the conditions of creative work.
Now A disclosure standard for the conditions of human work in any organisation deploying AI. One universal core, with sector annexes on top.
Sector annexes
An annex is a worked example: the same six conditions applied to one industry’s real P&L. The core stays the same from sector to sector and only the annex changes. The open ones have been left as gaps on purpose, because they need people who work in those sectors to write them.
Annex A · Written
Agencies, brands, studios and publishers: the canary rather than the subject.
Open
Hospital trusts, clinics, primary care, diagnostics.
Open
Law firms, in-house legal teams, courts and tribunals.
Open
Banks, insurers, asset managers, accountancy.
Open
Product and engineering teams, IT services.
Open
Schools, universities, training providers.
The list
Get new principles, revisions and the arguments that killed them, roughly once a month and never more often.