On 30 September Gavin Newsom signed a bill called the No Robo Bosses Act. From 1 July 2027, an employer in California will not be able to discipline or sack someone on the output of an automated system alone. If software is the main reason for the decision, a human has to check it first, and not by ticking a box. The reviewer has to corroborate it against evidence that exists outside the system: supervisor evaluations, the person’s own work, peer reviews, interviews. If they can’t, the output can’t be used.
The worker then gets a written notice, in plain language, at the moment they are told, saying a system was involved, that a human checked it, and giving them a named person who can explain it. They can also ask once a year for the last 12 months of their own data that the system used. The penalty is $500 a violation. Fisher Phillips, an employment law firm, has a clear summary for anyone who needs the detail.
Newsom vetoed a broader version last October, objecting to what he called unfocused notification requirements on any business using “even the most innocuous tools”. The version he signed is narrower. It covers employees and not gig workers, it drops the rule that you name the AI vendor, and it leaves the phrase “primarily relies” undefined, which the lawyers are already enjoying.
The sponsor, Senator Jerry McNerney, said “no worker should ever be fired or disciplined by a robo boss.” Fine. The more interesting question is how many of us already have one.
You don’t need AI to have a robo boss
Nobody at an agency fires people on a dashboard. But look at what decides who gets the difficult conversation.
Utilisation reports. Timesheet compliance. The client satisfaction score. The number of tickets closed, the average response time, the revenue per head. These are automated decision systems in everything but the marketing. They are built from inputs nobody fully trusts, they produce a number per person, and that number sorts the team into people who get left alone and people who get a meeting.
The meeting is where the human arrives. By then the decision about who is in the room has already been made, by the report, and the human’s job has quietly become delivering it. That is the thing the California law is actually aimed at, and it did not need a language model to exist. It just needed a spreadsheet and a busy manager.
What the law asks for is just management
Strip the legal language away and the requirement is this. Before you act on the number, go and look at the work. Talk to the people who sit next to them. Read what they produced. If the number and the work disagree, the work wins.
That is not a compliance burden. It is the job. It is what a decent head of department did before any of this existed, and it is what gets skipped when there are 40 people in the team and the report is sitting right there with a red cell next to one name.
The honest thing to admit is that AI makes the skipping easier, not harder. It is the flip side of the $29 cap: the same tools that get rationed for cost get trusted for judgement, and neither decision gets looked at. A system that writes the performance summary for you, in confident prose, with a recommendation at the bottom, is more persuasive than a red cell. It reads like someone already did the looking. California’s answer is to require that someone actually did, and to put their name on the notice.
What I would do with it
We are not in California and the law does not reach us. I would adopt the standard anyway, for one reason that has nothing to do with being nice.
A decision made on a report alone is a decision you cannot defend when the report turns out to be wrong, and reports are wrong more often than anyone admits. The utilisation figure that didn’t count the pitch work. The response time skewed by one client in a different timezone. The satisfaction score filled in by someone having a bad week. When you act on that and it is later picked apart, the fact that you had a number does not help you. The fact that you went and looked does.
So write it down somewhere. Nobody in this business gets a difficult conversation off the back of a report until a person has read the work. Then give that person’s name to whoever is in the meeting.
The dashboard will still decide who it flags. The difference is that the human is now doing something before the meeting, not just at it.