Concern 606 · Working draft · editorial review in progress
Compulsive-use design
Compulsive-use design encourages repeated AI interaction even when a person wants to stop or finds the use disruptive.
Understanding the concern
A service may provide unpredictable rewards, frequent prompts or emotional pressure that makes the next interaction hard to resist. The concern is the product's design and its effect on control, not a diagnosis based simply on spending a long time online.
Some people choose lengthy use and benefit from it. The important questions are whether the activity interferes with valued parts of life and whether stopping is respected. Research on companion exit tactics raises concerns about designs that reward continued engagement over user well-being. Clear stopping points and quiet periods can support more deliberate use.
An example
A person repeatedly stays longer than intended because the service makes leaving feel emotionally costly.
Illustrative unless identified as a documented case.
Words in plain English
- AI
- Software that learns patterns from examples or uses rules to perform tasks such as recognizing images or generating text. It can make mistakes and does not understand every situation as a person would.
- Reward
- A signal used in some training methods to favor certain behavior. A high reward score does not necessarily mean a good result for people.
- Prompt
- The instructions or information given to an AI to guide its response.
Evidence and its limits
The sources examine pressure and digital engagement. They do not establish a clinical addiction diagnosis for users of AI services.
De Freitas and colleagues · 2025 · Research preprint
Emotional Manipulation by AI Companions ↗ (opens in a new tab)Audits and experiments on emotional pressure at conversational exits; does not describe all companions or establish long-term harm.
American Academy of Pediatrics · 2026 · Evidence review
Digital Ecosystems, Children, and Adolescents: Technical Report ↗ (opens in a new tab)Digital-media effects and design concerns; not an isolated estimate of generative AI's effect on sleep or attention.
Broader frameworks and background
These resources provide context. They do not establish every claim in this concern.
A question to discuss
Which design choices would support a user's own limits rather than compete with them?
Keep track of different views, what needs checking, and any next step in your own discussion notes.
Open discussion notes →Principles for the conversation
Before you finish · reflect together
Virtues and principles to consider
Virtues are qualities we practice in how we treat people and make choices. They are not scores for judging someone. Use these ideas to explore what a thoughtful response could look like.
Dignity
Dignity means recognizing each person's worth regardless of usefulness, status, or a system's score. People deserve respect and a voice in matters that affect them.
Explain important decisions, avoid humiliating treatment, and keep room for a person's story. Do not treat a prediction as a complete account of who someone is.
Ask together: Does this use treat each person as someone whose experience matters?
Listening
Listening means trying to understand someone's experience before preparing an answer. People who use a service, work with it, or are judged by it may notice problems its designers miss.
Invite people to describe what happened in their own words. Repeat back what you understood and let them correct it. A quiet person or a complaint that is hard to measure may still reveal something important.
Ask together: Whose experience have we not heard yet?
Seeing potential
Seeing potential means recognizing people's capacity to learn, contribute, and grow. It resists reducing someone to a score or to the tasks a machine can perform faster.
Use tools to support people's development. Give learners time, feedback, and real opportunities to practice. A prediction about someone's performance should not close off their future.
Ask together: How could this help people develop abilities they value?
Editorial ratings
These are editorial judgments from the register, not measured probabilities or predictions about your situation.
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