BackData acquisition restrictions
Data acquisition restrictions
Risk Domain
AI systems that fail to perform reliably or effectively under varying conditions, exposing them to errors and failures that can have significant consequences, especially in critical applications or areas that require moral reasoning.
"Laws and other regulations might limit the collection of certain types of data for specific AI use cases."
Entity— Who or what caused the harm
Intent— Whether the harm was intentional or accidental
Timing— Whether the risk is pre- or post-deployment
Supporting Evidence (1)
1.
"There are several ways of collecting data for building a foundation models: web scraping, web crawling, crowdsourcing, and curating public datasets. Data acquisition restrictions can also impact the availability of the data that is required for training an AI model and can lead to poorly represented data."
Other risks from IBM2025 (63)
Lack of training data transparency
6.5 Governance failureHumanUnintentionalPre-deployment
Uncertain data provenance
6.5 Governance failureHumanOtherPre-deployment
Data usage restrictions
7.3 Lack of capability or robustnessHumanUnintentionalPre-deployment
Data transfer restrictions
7.3 Lack of capability or robustnessHumanUnintentionalPre-deployment
Personal information in data
2.1 Compromise of privacy by leaking or correctly inferring sensitive informationAI systemUnintentionalPost-deployment
Reidentification
2.1 Compromise of privacy by leaking or correctly inferring sensitive informationOtherUnintentionalPre-deployment