Marie Potel-Saville on Fair Patterns
Podcast via https://linkeddataorchestration.substack.com/p/fair-patterns-designing-for-human
Description
= Fair Patterns: "a free public database of regulations, legal cases, publications, and NGO activity around dark patterns". [1]
George Anadiotis:
"Potel-Saville was looking for the gap between what the law said and what the internet did to people. She found it immediately. The term was “dark patterns.” And her first instinct – the instinct of a lawyer and a builder – was to ask a question nobody in the field had thought to ask: what’s the antidote?
That question eventually became Fair Patterns, a multimodal AI platform that detects online manipulation and addictive design at scale. Fair Patterns went live in January 2026, and recently won the 2026 Digital StartUp award in cybersecurity and sovereignty. It is trying to redefine digital products and online experiences.
...
Potel-Saville defines dark patterns in deliberately simple terms. A dark pattern, she says, is “an interface that makes you do something you wouldn’t have done if someone had asked you the question – if you had understood what’s going on.”
Simplicity is a deliberate response to the field’s complexity. Researchers, regulators, the FTC, the European Data Protection Board have all researched dark patterns. The level of scientific sophistication is impressive, but the problem keeps spreading. As Potel-Saville puts it, “you’re always running behind the reality.”
The everyday examples are familiar enough that most people have stopped noticing them: cookie banners architected to make rejection take three extra clicks; free trials that quietly convert to paid subscriptions with cancellation flows designed to exhaust you; geolocation requests framed so that refusing feels like you’re breaking something.
The legal landscape in Europe has been building toward explicit prohibition. GDPR and the Unfair Commercial Practices Directive apply to dark patterns through general principles. The Digital Services Act goes further, expressly prohibiting them in Article 25.
The Digital Markets Act has a dedicated anti-circumvention provision. The EU AI Act prohibits dark patterns in AI systems under Article 5. And the Digital Fairness Act – still in project stage, expected for proposal by mid-2026 – is intended to fill the remaining gaps, particularly around addictive design.
...
An ontology built without a concrete purpose – however rigorous – risks becoming an intellectual exercise that documents a problem without touching it. The Ontology of Dark Patterns Knowledge was created with a precise legal purpose: to counter the argument that “dark pattern” was too vague a concept to prohibit.
By encapsulating all the fragmented taxonomies into a unified formal structure, the ontology gave regulators and litigators a foundation to say: this category is real, defined, and actionable. The broader body of research, while meticulous on naming, root causes, and legal grounds, produced almost nothing on solutions.
...
The concept of a fair pattern, as Potel-Saville defines it, is an interface that empowers you to make your own free and informed choices. This sounds obvious – until you spend five minutes cataloguing how rarely it describes the web you actually use.
The theoretical basis draws on behavioral science. Humans are cognitively vulnerable online in ways that are well documented and systematically exploited: information overload, default bias, the salience bias that makes us interact with what is visually prominent rather than what serves our interests.
The default bias example is almost embarrassingly effective: pre-ticked boxes. “Very few humans untick them. Very, very few”, Potel-Saville notes. The resulting unwanted purchases ran to billions of pounds in the UK alone. Minors face a compounded version of this vulnerability.
Addictive Design vs. Dark Patterns Addictive design engineered to exploit dopamine response works on adults; it works on teenagers and children with far less resistance. The prefrontal cortex – the seat of impulse control – does not fully mature until around age 25. That is not a side effect. It is, in the case of Meta’s internal strategy documents, the stated intent.
A fair pattern addresses this at the design level. The principles are specific: symmetrical buttons for accepting and rejecting, with equal visual prominence, equal contrast, no dissuasive micro-copy on the rejection option. Plain language, not legalese, following the ISO plain language norm that has existed since 2023.
Just enough information to support genuine decision-making, but not so much that information overload becomes its own manipulation. And crucially, no nudging: the goal is not to steer users toward a “better” choice, but to make the actual choice genuinely theirs.
Fair patterns work differently for addictive design. The mechanism is not deception but compulsion: dopamine loops that bypass deliberate decision-making. A fair pattern for a social media feed might offer users an upfront time-selection tool: set fifteen minutes before you start, receive a prompt when the time expires.
“You make a conscious decision and you enjoy the digital product, but you know where to stop. You’re the master of your own decisions”, as Potel-Saville put it.
...
What Potel-Saville argues for, and what Fair Patterns is attempting to instantiate, is a structural remedy built into the technology itself: a human safety layer embedded across the digital stack, the same way security has become embedded rather than bolted on.
“We need tech to protect ourselves from tech,” Potel-Saville says. “It’s a bit of an irony, but that’s the world we live in.”
The community forming around that proposition is broader than the client list might suggest. Senior figures from large organizations contact Potel-Saville weekly not as prospective customers, but asking what they can do to help. People from MIT. Former White House officials. People from Japan, Australia, Latin America.
“I think we’re creating way more than a product and even way more than a category. There’s a movement being created”, Potel-Saville notes.
The resources hub at fairpatterns.ai reflects this: a free public database of regulations, legal cases, publications, and NGO activity around dark patterns – a knowledge commons for anyone working on the problem, not just Fair Patterns clients."
(https://linkeddataorchestration.substack.com/p/fair-patterns-designing-for-human)