Deceptive Patterns
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Fairness by design: Combatting deceptive AI-driven interfaces

Author
Fabien Lechevalier and Marie Potel Saville
Date
1 Aug 2025
Publisher
Cambridge Forum
Focus
AI & Automation
Category
Academic Scholar

Introduces “Fairness by Design” and Amurabi’s “Fair Patterns” prototypes, showing how interface design can counter dark patterns. It explains how AI may amplify manipulation and explores design solutions that foster transparency, trust, and user autonomy.

Manipulation and deception were not born with AI: online architecture of choice can be harmful when it contains dark patterns or deceptive designs. These techniques deceive or manipulate users through interfaces that have the substantial effect of subverting or altering users’ agency, decision-making, or choice as part of their online activities. But AI has the potential to further enhance this manipulation increase its sophistication and scale. This article presents the principle of ‘Fairness by Design’ as a potential solution as well as a set of interface prototypes inspired by it and developed within Amurabi’s R&D Lab. These solution prototypes are called ‘Fair Patterns’. Fair patterns make it possible to implement the principles of transparency, trust, and autonomy by providing the right level of information at the right moment in the user journey, in clear language and without cognitive overload.