AI Liability: Human Accountability for Algorithmic Errors

Home » Latest » Running Your Practice » Guarding the gate: Human responsibility in algorithmic liability AJS is a level 2 BBBEE legal practice management and systems solution provider with branches in all major centres.... Read More When AI makes a multi-million-Rand mistake, the machine won’t take the stand. Its human gatekeepers will. It begins, as these things often do, with a persuasive dashboard and a boardroom full of people delighted to discover that accountability can apparently be automated. The model is faster than the analysts, cheaper than the consultants and, according to the vendor’s slide deck, “transformative”. Nobody asks which particular form of transformation is on offer. Bankruptcy is also transformative. Just for clarification’s sake. Then the system misprices a risk, rejects the wrong customer, invents a legal authority, or approves a transaction that detonates several hundred million rand. The incident committee assembles. The engineers blame the data. The business blames the vendor. The vendor points to clause 47.3(b), where liability was humanely euthanised in eight-point font. The algorithm, displaying admirable executive composure, says nothing. Obviously. That silence is the point. An AI system can generate an output, but it can’t owe a fiduciary duty, face a regulator, lose a practising certificate, or explain itself under cross-examination. Legal and business accountability can’t be outsourced to a probability engine. Somewhere behind every consequential automated decision sits a chain of human choices: what to buy, what to train, what to test, what to monitor and, crucially, when to stop. South African law doesn’t need to pretend a machine is a person before it can allocate blame. Existing principles of contract, delict, company law, consumer protection, data protection, and professional negligence already ask stubbornly analogue questions: who owed the duty, who authorised the conduct, who could foresee the harm and who failed to act reasonably? POPIA is especially awkward for anyone hoping to blame the robot. Its architecture places responsibility on the responsible party, and section 71 regulates certain decisions based solely on automated processing where those decisions have legal or substantial effects. Even where an exception applies, safeguards matter. “The model decided” isn’t governance. It’s a confession that the organisation designed a decision process without a responsible adult. King IV reaches the same destination from the boardroom. Technology and information governance belong inside corporate governance, not in an IT subcommittee scheduled after lunch when everyone’s already emotionally unavailable. Directors may delegate implementation. They can’t delegate the governing body’s obligation to oversee risk, performance, and ethical conduct. The practical liability chain may include the developer, provider, deployer, professional adviser, executive committee, and board. Contractual indemnities can redistribute financial exposure between them, but indemnities don’t turn negligence into innocence. Nor do they impress regulators, courts or customers forced to discover that “human in the loop” meant an exhausted graduate with no authority and 600 alerts. South Africa has already received two unusually theatrical demonstrations of human responsibility in automated work. In Mavundla v MEC: Department of Co-Operative Government and Traditional Affairs KwaZulu-Natal, the Pietermaritzburg High Court confronted a filing in which seven of nine cited cases didn’t exist. The court criticised the conduct, made a personal cost order for additional appearances and referred the matter to the Legal Practice Council . The fictional authorities were machine-shaped, but the professional consequences were entirely human. The judgment’s most useful lesson isn’t that lawyers should fear AI. It’s that supervision can’t be performed retrospectively, usually after a judge has become the quality-assurance depa