Reverse Privacy Paradox
The reverse privacy paradox is a pattern, described by Zhang and colleagues in research on LLM-based conversational agents, in which users appear to disregard privacy concerns in the moment of use while still recognising those concerns exist and being willing to adopt privacy-protective behaviours if options are made clearly available. It reverses the classic 'privacy paradox' framing (where users claim to value privacy but behave carelessly) by locating the issue in the design of privacy interfaces rather than user apathy. In accessibility practice, it is particularly relevant for neurodivergent users who may over-share during emotional distress or hyperfixation, and argues for highly visible, low-friction privacy controls rather than buried settings hidden behind dark patterns.
Category: Privacy · AI · Human-Computer Interaction
Related: Privacy · Dark Patterns · AI Chatbot · Large Language Model