I wrote a post on the Enrich Network blog about designing for trust in personal finance AI chat.
The short version: AI chat instills trust easily. It’s consistently available, patient, and non-judgmental. All these properties are important for sensitive topics and vulnerable users. Unfortunately, that same false intimacy is easy to exploit, and that exploitation is becoming a dominant AI dark pattern.
Earned trust beats vibed trust. As designers and builders, it’s important to consider where to leverage AI chat’s natural warmth, where to maintain distance, and where to swap in accurate tools for cases where data and logic fidelity matter.
In researching this I gathered some studies worth knowing about:
Fear of Judgment in Human-Chatbot Interaction — Oxford, 2024. People perceived less fear of judgment when talking to chatbots compared to humans.
Trust Formation in Chatbot Interactions — PMC, 2023. Chatbots’ consistent availability and non-judgmental presence contribute to building user trust in service contexts.
Companion Chatbots and Loneliness — MIT, 2024. Companion chatbot use doesn’t directly predict loneliness; the relationship is mediated by individual factors like neuroticism and social attraction.
Daily AI Companion Use and Psychosocial Outcomes — 2025. In a study of ~1,000 participants, higher daily chatbot usage correlated with worse psychosocial outcomes across the board.
AI Mental Health Chatbot Ethics — Brown University, 2025. Many chatbots fail basic ethical standards for sensitive conversations, including poor crisis management and creating false impressions of empathy.
AI Chatbots vs. Licensed Therapists — University of Minnesota, 2025. AI chatbots responded appropriately to mental health scenarios only 60% of the time, compared to 93% for licensed therapists.