Concern 853 · Working draft · editorial review in progress

Trademark and passing off

Trademark and passing-off concerns arise when AI-made names, logos or messages mislead people about who supplied or endorsed a product.

Understanding the concern

A trademark helps people recognize the source of goods or services. An AI tool might suggest a logo that resembles an existing brand, or generate an advertisement that appears to come from a trusted business. The concern is confusion about origin or endorsement, rather than ownership of every similar-looking image.

Think of a shop putting another bakery's sign over its door. Customers may rely on that sign when deciding what to buy. Using an AI generator does not remove the need to check how branding will be understood. A mention of a brand in criticism, news or comparison can raise different questions from presenting a product as that brand's own.

An example

A generated advertisement uses a familiar logo so prominently that customers think the brand sponsors an unrelated service.

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 source explains trademark principles. Infringement and passing-off tests, exceptions and remedies differ by jurisdiction; the example is illustrative.

  • World Intellectual Property Organization · Official explainer

    Trademarks ↗ (opens in a new tab)

    Explains protection of signs distinguishing goods and services. AI examples are illustrative applications, not adjudicated cases.

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Broader frameworks and background

These resources provide context. They do not establish every claim in this concern.

A question to discuss

Could an ordinary customer mistake who made, sold or endorsed this product?

Keep track of different views, what needs checking, and any next step in your own discussion notes.

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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.

Justice

Justice means fair treatment, fair procedures, and attention to who receives benefits and burdens. It asks whether people with less power can be heard and seek repair.

Look at outcomes across different groups and individual cases. Provide a usable way to challenge decisions and correct harm. Equal wording in a policy does not guarantee equal treatment in practice.

Ask together: Who benefits, who bears the cost, and who can challenge the decision?

Accountability

Accountability means being answerable for decisions and taking responsibility for repair. It requires more than saying that the software made the choice.

Name the person or team responsible, keep useful records, and give them authority to correct problems. Make the route to a complaint clear to the people affected.

Ask together: Who will answer for the outcome and help put things right?

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?

Editorial ratings

These are editorial judgments from the register, not measured probabilities or predictions about your situation.

Severity
Serious · 3/5
Likelihood
Documented · 3/5
Time horizon
Now
Register risk score
9
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