2.4 · Accountability, Transparency & Algorithmic Auditing

When AI Causes Harm — Who Answers?

12 minCourse 02

When an AI system causes harm — a biased hiring decision, a discriminatory credit refusal, a misdiagnosis, a financial loss — the question of legal liability is complex, contested, and rapidly evolving. Understanding the current legal landscape is essential for anyone deploying AI in a business context.

The Liability Gap

Traditional product liability law was designed for physical products. When a toaster catches fire, the manufacturer is liable under established frameworks. When an AI model makes a discriminatory decision, liability is far less clear — it may sit with the developer, the deployer, the data supplier, or be distributed across all three.

  • ◆AI Developer: Liable if the harm results from a defect in the model, training data, or its documentation
  • ◆AI Deployer: Liable if the harm results from inappropriate deployment, insufficient human oversight, or failure to follow the developer's instructions
  • ◆Data Supplier: Potentially liable if poisoned, biased, or incorrect training data caused the harm
  • ◆User: In professional contexts, the person or organisation relying on AI output may bear liability for how they use it
Where EU Liability Law Landed

The proposed EU AI Liability Directive — which would have introduced a "rebuttable presumption of causality" for harm caused by non-compliant AI — was withdrawn by the European Commission in its February 2025 work programme. Liability for AI harm in the EU now flows primarily through the revised Product Liability Directive (EU) 2024/2853, which explicitly treats software and AI systems as products and which member states must transpose by December 2026, alongside national negligence and anti-discrimination law. The practical lesson survives the withdrawal: document your diligence as if you will one day have to prove it.

Existing UK Law: What Applies Now

In the UK, AI-related liability currently flows through existing frameworks:

  • ◆Consumer Rights Act 2015: AI outputs may be considered services; if substandard, consumers may have remedies
  • ◆Equality Act 2010: Discriminatory AI decisions (in employment, services, housing) are actionable regardless of whether AI or humans made them
  • ◆GDPR / UK GDPR: Individuals affected by unlawful automated decisions may claim compensation for material and non-material damage
  • ◆Common law negligence: Professionals who rely on AI outputs without appropriate care may be liable for negligent advice
✓ The Practical Implication

As an AI deployer, you bear significant liability for what your AI systems do — even if someone else built them. Documenting your due diligence, bias testing, human oversight processes, and governance decisions is not bureaucracy: it is your legal defence.