Concern 472 · Working draft · editorial review in progress
Cognitive-bias exploitation
Cognitive-bias exploitation designs AI messages around predictable shortcuts in human judgment.
Understanding the concern
People often use shortcuts when deciding: a first number can anchor expectations, a deadline can create urgency, and apparent popularity can make a choice feel safe. AI can vary how such cues are presented. The concern arises when those cues mislead rather than help someone decide.
The FTC describes deceptive design patterns such as false scarcity and disguised advertising. These practices existed before AI. Adding an adaptive conversation could make the pressure harder to recognize because it sounds like personal advice. A fair design gives people accurate information, time to think and an easy way to refuse.
An example
A shopping assistant invents a time limit to rush someone into a purchase.
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.
Evidence and its limits
The FTC report documents deceptive design generally. The adaptive-assistant example illustrates an AI application, not a measured rate of AI-specific misconduct.
Federal Trade Commission · 2022 · Staff report
Bringing Dark Patterns to Light ↗ (opens in a new tab)Describes deceptive interface design; many mechanisms predate AI and are not evidence of AI-specific prevalence.
Broader frameworks and background
These resources provide context. They do not establish every claim in this concern.
- OECD AI Incidents and Hazards Monitor (opens in a new tab)
incidents
- AI Incident Database (opens in a new tab)
incidents
- International humanitarian law (IHL)
framework
The body of law that governs the conduct of armed conflict and the protection of people who are not fighting, which applies to AI used in or for conflict.
A question to discuss
Does this message help a person decide, or create pressure using information that is not true?
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.
Truthfulness
Truthfulness means making claims that match the evidence and being clear about what we do not know. It includes correcting mistakes rather than protecting a polished story.
Check sources, label guesses, and distinguish a trial result from a proven benefit. If AI helped produce a claim, someone still needs to take responsibility for checking it.
Ask together: What can we honestly say, and what still needs checking?
Meaningful conversation
Conversation means making room to understand and be understood. It is more than winning a debate or collecting quick agreement. People can explore a question together without starting from the same view.
Use a concrete example, invite different experiences, and ask what might change each person's mind. Let concerns and hopes sit together long enough to reveal choices that a simple yes-or-no argument would miss.
Ask together: What can we learn from each other before deciding?
Unity
Unity means working toward shared purposes while making room for real differences. It does not require everyone to have the same experience, beliefs, or opinion.
Look for a goal people can share, then explore disagreements about how to reach it. Make sure quieter or less powerful voices can influence the result.
Ask together: What purpose can we share while respecting our differences?
Editorial ratings
These are editorial judgments from the register, not measured probabilities or predictions about your situation.
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