Building trust and responsible products without manipulation or dark patterns in the world of AI. BehaviorAI - Responsible AI design library
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AI is changing not only how we design products, but also the relationship between people and technology itself. Traditional UX is not enough to describe trust, agency, or decision making [EN/PL]
The team passes the legal audit with a clear conscience. The product still fails the user exactly where it was supposed to protect them. [ENG/PL]
One question has been coming back to me for a few weeks now. Is what we consider success in AI product design, meaning the removal of every possible friction, sometimes a mistake in our assumptions.
95% of companies see no measurable return on their AI investment. Because AI adoption isn't a technology problem, it's a behavior problem. [ENG/PL]
2 sierpnia zaczynają obowiązywać przepisy, na które czekałam od dawna, i które jednocześnie napawają mnie lekkim niepokojem.
"AI supporting people at work," not as a declaration, but as a concrete design pattern.
BehaviorAI Design Framework a methodology for designing AI interventions that starts with "why" before answering "what" and "how".
BehaviorAI Pattern Library a design pattern library organized around behavioral moments, not interface categories.
The ban regulates content. What actually shapes user behavior is somewhere else entirely, and no regulation will change that until we learn to name it.
The EU just published three icons for labelling AI-generated content.The EU just published three icons for labelling AI-generated content. Looks like a compliance detail.
AI adoption problems get diagnosed as model issues or UX friction. This article is about the third cause: the one no benchmark surfaces and no A/B test catches.
Automation does not eliminate effort. It moves it. Building good AI experiences requires understanding not just clicks, but the cognitive processes that produce them.
AI adoption is not a tech problem. It’s a behavioral design problem..
System 0 is an invisible layer of technology that selects, organizes, and translates information before a person even has time to think about it independently.
The real value is not in browsing more patterns. Designers need to see not only what a solution looks like, but also why it works, what trade-offs were made, and where it might fail.
You see “thinking”. You feel like the system understands. This is an illusion and we design products as if it were true.
As digital product creators, we’ve grown accustomed to one primary paradigm: artificial intelligence is supposed to make life easier. The user asks, the AI answers instantly.
Dark patterns have long been used to subtly manipulate users into making decisions that benefit platform creators, often at the expense of user privacy, time, or mental health.
Artificial intelligence in many solutions is becoming a co-participant in decision-making rather than a mechanism operating in the background of a product.
When a user interacts with an AI system, they rarely start with a blank page.
Przez lata wyszukiwanie było jedną z najbardziej stabilnych interakcji cyfrowych. Pole tekstowe, lista wyników, zestaw filtrów. Użytkownik zadawał pytanie, system odpowiadał
