Concern 602 · Working draft · editorial review in progress
Persuasive pricing bots
Persuasive pricing systems may combine information about a customer with a tailored conversation to influence what they pay.
Understanding the concern
Dynamic pricing changes with conditions such as time or demand. Personalized pricing instead uses information about a person or group. When a conversational seller also adapts its pitch, the buyer may not know whether the offer reflects the product, the market or an estimate of what they can be persuaded to accept.
FTC research describes intermediary tools using personal data to influence prices and offers. It does not establish that every retailer does this or that every price difference is improper. Transparency about pricing and data use helps people compare options and understand whether the assistant represents their interests or the seller's.
An example
Two customers receive different offers without being told that personal data influenced the difference.
Illustrative unless identified as a documented case.
Evidence and its limits
The source reports initial staff findings about intermediary capabilities, not universal retail behavior or a finding that all dynamic pricing is illegal.
Federal Trade Commission · January 2025 · Staff research perspective
Surveillance Pricing Update and the Work Ahead ↗ (opens in a new tab)Initial findings about intermediary tools and personal data; not proof every retailer uses individualized prices.
Broader frameworks and background
These resources provide context. They do not establish every claim in this concern.
A question to discuss
What should a customer know about how an AI-assisted price or offer was determined?
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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