Description: A home value generated by a black-box algorithm was reportedly defended by the Castricum court, which was criticized by a legal specialist for setting a dangerous precedent for accepting black-box algorithms as long as their results appear reasonable.
Entities
View all entitiesAlleged: Castricum municipality developed and deployed an AI system, which harmed unnamed property owner.
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
7.4. Lack of transparency or interpretability
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
Human
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
Intentional
Incident Reports
Reports Timeline
In a seemingly routine case at the Amsterdam court of appeal, a judge ruled that it was acceptable for a municipality to use a black-box algorithm, as long as the results were unsurprising.
In 2016, the municipality of Castricum, a seaside …
Variants
A "variant" is an incident that shares the same causative factors, produces similar harms, and involves the same intelligent systems as a known AI incident. Rather than index variants as entirely separate incidents, we list variations of incidents under the first similar incident submitted to the database. Unlike other submission types to the incident database, variants are not required to have reporting in evidence external to the Incident Database. Learn more from the research paper.