Concern 860 · Working draft · editorial review in progress
Deployer liability
Deployer liability concerns the responsibility of an organization that chooses and uses AI, even when another company built the tool.
Understanding the concern
A hospital, employer or public agency decides where a system fits into real work. It may choose the data, set thresholds, train staff or ignore warnings. Those choices can contribute to harm independently of a defect in the underlying model. Buying a product does not answer every question about safe and lawful use.
Consider a company using a ranking tool to reject job applicants. Responsibility may depend on employment law, the employer's actions and the facts of the case. A hiring manager cannot assess those issues by reading the vendor's accuracy score alone. The practical question is who had the power and duty to check the use and respond when problems appeared.
An example
An employer keeps using an unsuitable screening tool after learning that its test excludes qualified applicants with disabilities.
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.
- Model
- The learned part of an AI system. It uses patterns found during training to produce an answer or prediction.
Evidence and its limits
Employment is one concrete example, not a universal liability test. Duties differ across sectors and jurisdictions; a vendor contract does not settle all rights of affected people.
US Equal Employment Opportunity Commission · Official legal explainer
What are my responsibilities under federal employment discrimination laws? ↗ (opens in a new tab)Describes covered employment duties. Specific AI disputes still require analysis of the relevant law and facts.
Broader frameworks and background
These resources provide context. They do not establish every claim in this concern.
- EU AI Act — high-level summary (opens in a new tab)
regulation
- Council of Europe AI Convention (opens in a new tab)
regulation
- 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.
- Deciding under algorithms: artificial intelligence and the protection of civilian infrastructure in armed conflict (opens in a new tab)
guidance
- ICRC law and policy hub on AI (opens in a new tab)
guidance
People and organizations cited
Public writing, not endorsement, partnership, or affiliation.
International Committee of the Red Cross
A question to discuss
Which decisions were under the deploying organization's control, and what should it have checked before and during use?
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.
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.
About the register and scoring →More ways to explore
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