Saying so, and the tools that cannot prove it

The cheap version of a hard conversation

People mind less about talking to an automated system than teams expect. What they mind is being deceived about it, and being unable to reach a person when the automated answer is wrong.

Which gives three things to provide, and they are not expensive:

1. That it is automated. One line, at the point of contact, in the customer’s language.
2. How to reach a person. Not buried, not conditional on failing a series of prompts. A route that works.
3. On what basis a decision was made, if the decision affected them. Not the model’s internal workings: the inputs and the rule. “Your claim was routed for manual review because the amount exceeded the automatic threshold” is a complete and honest answer.

The economics are one-sided. An undisclosed automation that is discovered costs an apology, a news cycle in some cases, and a durable loss of trust. Disclosure costs a sentence.

What not to do

Do not give the automation a human name, a photograph and a first-person voice that implies a person exists. A name and a face land in the reader’s mind before any badge does, and by the time they read the small print they have already formed the belief. If it is a system, let it read as a system.

Do not claim a person reviewed something when the review was a click. If a human sign-off is part of your compliance story, the sign-off has to be a real act with real time in it, or the story is false in a way that will not survive an investigation.

Do not present a confidence figure to a customer. It looks like a measurement of correctness and it is not one.

Internally, tell people before

The team whose work changes should hear it from you before they see it in their queue. Say what is changing, what is not, what you do not yet know, and when you will next update them.

The temptation is to promise that nobody’s job changes. Do not promise what you have not been told. If the intention is to redeploy people rather than reduce headcount, say so and name who decided it. If nobody has decided yet, say that instead: “no decision has been made and I will tell you when one is” is uncomfortable and it is believed, which is more than can be said for reassurance that later turns out to be wrong.

This is not only ethics. A team that suspects an automation is aimed at them will not tell you about the exceptions, and the exceptions are the project.

Provenance and watermarking

For images, audio and video, content-provenance standards such as C2PA attach signed metadata describing how a file was produced. This works when it is preserved, and metadata is routinely stripped by platforms, re-encoding and screenshots. It is a useful chain-of-custody tool inside a system you control and a weak guarantee out in the world.

For text, be blunt: there is no reliable way to detect whether text was machine-generated. Published detectors report accuracy figures that do not hold on ordinary edited writing, and studies have found they flag writing by non-native English speakers at substantially higher rates, because the features they key on (limited vocabulary variation, regular sentence structure) describe careful second-language writing as much as they describe a model.

The consequences are practical. Never use a detector to accuse anybody of anything, in a school, a workplace or a hiring process. And do not rely on one to police your own outputs.

So disclosure cannot be something a reader tests. It has to be something you record: a field on every generated artefact saying which system, which config version and which run produced it, kept with the artefact and available on request. That record is the honest substitute for a property nobody can measure from the outside.

Where the line sits for you

Write your own rule down, before you need it, and make it short enough to remember. A serviceable one:

Anything a person receives that appears to come from us says whether a machine wrote it. Any decision affecting a person can be appealed to a human being, and we can say what the decision was based on. We do not pretend a system is a person, ever.

Three sentences. They will settle more arguments than a policy document, because they can be quoted from memory by somebody making a decision at speed, which is when these questions actually arise.