Researchers Warn Fun Chatbot Designs May Mask Data Disclosure Risks

Mobile apps and chatbots often use interactive tools to hold attention, but these same features may affect how carefully people treat their personal data. A team from Penn State and the University of South Dakota wanted to see whether interactivity distracts users from privacy risks or helps them become more alert.

The Fitness App Experiment

To explore this, 216 participants in the U.S. were asked^[1] to go through a simulated sign-up process for a fitness app. The app requested sensitive details such as body weight, health conditions, and exercise habits. Some versions of the app responded in a basic question-and-answer style, while others created a more connected conversation by referring back to earlier answers. A second variation added images — in some cases a static picture, in others a zoomable one — to test the effects of visual interactivity.

What Happened When Users Engaged

The study found that interactivity made the app seem playful, and this sense of fun reduced the amount of concern people expressed about their privacy. When the conversation felt more connected, users reported lower privacy worries than those who experienced a simple exchange. Statistical analysis showed that the flow of messages increased the feeling that the system was paying attention, which made the app feel more enjoyable, and this enjoyment in turn pushed privacy concerns to the background.

Visual Tools and the “Sweet Spot” Effect

Adding pictures had a different effect. A simple pop-up image boosted playfulness ratings from around 3.9 to 4.45 on a seven-point scale. But when zoom features were added, ratings slipped closer to 4.1. This suggests a sweet spot: one layer of interactivity can enhance enjoyment, but piling on too many options makes the experience less engaging.

Combined Features and Unexpected Results

When both conversational and visual tools were used together, the outcomes were mixed. Strong conversational design on its own gave people a strong sense of connection. Adding visual features reduced that effect, but when the conversation was simple, the images helped strengthen it. This shows that different forms of interactivity can either cancel each other out or complement one another depending on how they are combined.

Why Intrusiveness Was Low

Across all versions, participants rated the app as not particularly intrusive. On average, intrusiveness stayed below 3 on a seven-point scale, even though users were sharing sensitive health details. The researchers noted that positive feelings of playfulness often overshadowed discomfort, highlighting how easily enjoyment can shift attention away from privacy.

Implications for AI Chatbots and App Design

These findings challenge the idea that conversational AI makes people more thoughtful. In practice, the back-and-forth exchanges that feel natural may actually reduce vigilance. This is especially important in generative AI, where users often become absorbed in long conversations and may not pause to consider what information they reveal.

Building Responsible Interactions

For designers, the results point to the need for balance. Playfulness can help users stay engaged, but it should not be allowed to hide the risks of disclosure. Small design choices, like inserting a pause through a rating request, could remind users to reconsider what they are sharing. As apps and AI systems continue to compete for attention, developers will need to combine enjoyment with safeguards that keep users aware of their privacy.

Notes: This post was edited/created using GenAI tools. Image: DIW-Aigen.

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