Latest · AI oversight & governance
Greece told every public body to list its AI, but the list is the easy part.
A national register asks the questions human oversight exists to answer. Many bodies will answer them like an inventory.
We write about keeping people in charge of artificial intelligence (AI), getting found by AI search (generative engine optimization, GEO), sharper design practice and accessibility.
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Latest · AI oversight & governance
A national register asks the questions human oversight exists to answer. Many bodies will answer them like an inventory.
Role profiles, a checklist and a job description template for the AI Act’s rule on who oversees high-risk AI, which applies from December 2, 2027 in areas such as hiring, credit scoring and public services.
Υπόδειγμα όρων για φορείς του δημοσίου που προμηθεύονται συστήματα τεχνητής νοημοσύνης: δοκιμή πριν από την παραλαβή, με όριο που ορίζει ο φορέας εκ των προτέρων.
Τα έντεκα στοιχεία που ζητά ο νόμος για τη δήλωση στο Μητρώο, με υπόδειγμα, συμπληρωμένο παράδειγμα και μια δοκιμή ανθρώπινης εποπτείας μίας εβδομάδας.

My AI fact-checker caught 108 of 108 planted errors and missed my real one. Seven steps for an audit that tests the errors you actually make.
Most of the debate about AI writing is about who wrote the draft. The check that matters comes after it — a gate no unverified claim gets through.
Part three of the GEO series was meant to be about measurement. Here is the instrument for tracking AI citations, and the number it returned for my own site.
One piece for each topic we write about, chosen as the best way in.
AI oversight
The framework behind our AI oversight work: five capabilities and one test that shows where oversight fails.
GEO
Why AI search skips content it can't identify, and what to make explicit so it gets quoted.
Design practice
A repeatable way to evaluate a product and prioritize fixes in under two hours.
Accessibility
Why overlay widgets add legal risk instead of removing it, and where the real problems hide.
The annotations live in Figma. The handoff fails three sprints later, in a ticket where nobody has the Figma file open.
A framework for designing and testing the interfaces through which people oversee AI systems. It sets out five capabilities drawn from the AI Act’s article on human oversight, one condition underneath all five, and a behavioral test that shows where the oversight you have documented fails.
The AI Act’s rule on telling people when they are dealing with AI has applied since August 2, 2026. Most of what it asks is decided on the screen: the wording, where it sits and whether everyone can perceive it.
Accessible components are a good start. Whether the product works for everyone is decided in how they are put together: the flows, the content and the choices no library makes for you.

Better screens rarely move a design career. I look at what does, and why the work many of us are proudest of is not it.
Overlay widgets promise compliance in one line of JavaScript. The evidence points the other way — they attract complaints, and they make the underlying problems harder to find.

A contrast or focus-order fix takes minutes in Figma. Found later in code, the same issue costs a ticket, a rebuild and a retest.
Ποιος ελέγχει τι, γιατί ο νόμος δεν ορίζει κανένα ποσό προστίμου και τι εκθέτει πραγματικά τα e-shops και τις επιχειρήσεις.
The testing is the easy part. What clients actually pay for is a document their team can act on — and that is where most audits fall down.
Structured, machine-readable content is what AI engines cite. It is also, almost line for line, what accessibility has been asking teams to do for years.
AI engines cite what they can name with confidence. If your content doesn’t make its entities explicit, it doesn’t get quoted — however good it is.
Twelve months after the deadline, most of the pressure is not coming from regulators. It is coming from procurement, customers and competitors.
A practical, repeatable process for designers who want a fast, no-fluff way to evaluate a product and prioritize fixes.
What 235 unnamed layers taught me about the gap between having design standards and actually keeping them.
After 18 years and six enterprise rollouts, why design systems are a smarter bet than ever in the age of AI.
How delaying inclusive design quietly erodes product quality, user trust and revenue — and what it costs to catch up.
We keep designing for someone who doesn't actually exist. A case for designing to the edges instead of the mythical average.
A few alt-text fixes don't make you compliant. What the EAA actually asks of digital teams — and how to get ready.
New articles as they go live, and the Room to Disagree newsletter on designing human oversight of AI.
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