Description: An automated license plate recognition (LPR) system at The Landing car park in Christchurch, New Zealand, reportedly issued wrongful fines to dozens of parents dropping off and picking up children. The system allegedly misidentified multiple short visits as prolonged parking, which led to disputed penalties. The operator acknowledged potential errors but continued enforcement.
Editor Notes: Timeline notes: Reporting on this incident refers to an incident in October 2024. Reporting seems to have arisen in early February 2025. The incident date of 10/15/2024 is an approximation.
Entities
View all entitiesAlleged: Unknown license plate recognition developer developed an AI system deployed by Wilson Parking and Parking Enforcement Services, which harmed The Landing car park customers , Kindercare Wigram Skies parents and Christchurch drivers.
Alleged implicated AI system: Unknown license plate recognition technology
Incident Stats
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
7.3. Lack of capability or robustness
Risk Domain
The Domain Taxonomy of AI Risks classifies risks into seven AI risk domains: (1) Discrimination & toxicity, (2) Privacy & security, (3) Misinformation, (4) Malicious actors & misuse, (5) Human-computer interaction, (6) Socioeconomic & environmental harms, and (7) AI system safety, failures & limitations.
- AI system safety, failures, and limitations
Entity
Which, if any, entity is presented as the main cause of the risk
AI
Timing
The stage in the AI lifecycle at which the risk is presented as occurring
Post-deployment
Intent
Whether the risk is presented as occurring as an expected or unexpected outcome from pursuing a goal
Unintentional
Incident Reports
Reports Timeline
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Dozens of parents doing drop-offs and pick-ups at a Christchurch childcare centre have been wrongly fined for all-day car parking because of problems with a parking company's camera system.
The Landing car park in Wigram provides spaces for…
Variants
A "variant" is an AI incident similar to a known case—it has the same causes, harms, and AI system. Instead of listing it separately, we group it under the first reported incident. Unlike other incidents, variants do not need to have been reported outside the AIID. Learn more from the research paper.
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