Strict liability
A form of liability that does not require the claimant to prove fault or negligence by the defendant; it attaches to certain activities or products regardless of the care taken. The revised PLD is a strict-liability regime for defective products: a claimant need not prove the manufacturer was negligent, only that the product was defective and that the defect caused the damage.
Defined in 3 GAGE programs, which carry 4 distinct definitions of it. The wording above is taught in EU AI Act Implementation Expert.
How each discipline defines it
The same term does different work depending on who is using it. These are the definitions as each program teaches them, unedited.
A form of liability that does not require the claimant to prove fault or negligence by the defendant; it attaches to certain activities or products regardless of the care taken. The revised PLD is a strict-liability regime for defective products: a claimant need not prove the manufacturer was negligent, only that the product was defective and that the defect caused the damage.
A liability regime requiring only proof that a defined category of activity caused a defined harm, with no inquiry into whether the responsible actor exercised reasonable care. Fairness under a strict liability regime is determined by how the category is scoped, not by conduct in the individual case.
A liability rule under which a claimant need only show a defective product caused harm, not that the defendant was careless. The revised EU Product Liability Directive extends this to software and AI.
Liability without the requirement to prove fault, negligence, or intentional wrong. The Revised PLD imposes strict liability on producers: a claimant need only prove the product is defective, that damage occurred, and that the defect caused the damage. No proof of the producer's culpability is required.
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- Who Pays When the Agent Errs III · The Law and the Regulators, Certified Agentic AI Governance Professional (CAAGP)
- Who owns the output: IP, training-data provenance, and the liability chain when AI work goes wrong · Evidence Engineering, Certified AI Governance Professional (CAIGP)
- Product Liability for AI (the Revised PLD) · Regulatory Interplay and Liability, EU AI Act Implementation Expert
- The AI Liability Landscape: Proving Fault When AI Causes Harm · Regulatory Interplay and Liability, EU AI Act Implementation Expert
Where it shows up at work
A definition is where Strict liability starts. The lessons above teach it inside the competencies below, which are what job descriptions ask for and what the GAGE credential records. Every link here is drawn from the same careers map that builds a role's readiness check.
Classifies a system by role and risk tier, knows which obligations bind on which date after the Digital Omnibus, and what evidence conformity needs.
One lesson on this page teach it as a primary outcome.
Reviews purpose, data, affected people, accuracy, bias, security, oversight, vendors and law for a use case, scores likelihood and impact, and documents residual risk.
One lesson on this page teach it as a primary outcome.
Decides what a person affected by an AI decision must be told, how an output can be explained, and how they can challenge it.
One lesson on this page teach it as a primary outcome.
Roles that hire for it
Each role page shows the full competency set, what the seat decides, and a readiness check against your own evidence.
- AI Regulatory Counselneeds it at depth · 14 open postings this week
- Senior AI Compliance Analystneeds it at depth
- AI Governance Managerneeds it at depth
- AI Governance Analystneeds working knowledge · 3 open postings this week
- Chief Privacy Officer, AI privacy editionneeds it at depth
- AI Compliance Managerneeds it at depth · 2 open postings this week
How job descriptions say it
Postings rarely use the textbook word. These are the phrases the careers map reads as asking for the competencies above.
Where the frameworks place it: Regulation (EU) 2024/1689; Regulation (EU) 2026/1744; NIST AI RMF MAP and MEASURE; ISO/IEC 42005.
One interview question about it
Classify a specific AI system under the EU AI Act and name the obligations that follow, including what applies now and what is deferred.
Asked of candidates for eu ai act obligations and timelines. Answering it in your own words is exactly how a GAGE topic is passed, and the credential records the pass where an employer can check it.
If you come from another field
Some backgrounds already carry this competency, and the readiness check gives credit for it.
- A law degree (JD, LLB or LLM), no AI work yet carries it as a claim to back up: The EU AI Act reads like the statutes you were trained on; the content is new, the method is not.
- Privacy and data protection carries it as work you can show: A DPIA is an impact assessment; the AI version adds accuracy, bias and oversight.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.