What is Personal data in AI recommendation and decision systems?
Personal data in AI recommendation and decision systems is any information relating to an identified or identifiable person that is used, inferred, ranked, or acted on by systems that recommend content, products, services, or decisions. It matters because these systems can create privacy, fairness, and explainability risks that trigger data protection and discrimination compliance obligations.
In Depth
In practice, this term covers inputs such as profile data, behavior logs, device identifiers, and transaction history, as well as outputs and inferences that are tied to an individual’s preferences, eligibility, risk, or predicted behavior. Compliance teams need to understand not only what data is collected, but also how it is combined, retained, shared, and used to drive profiling or automated decision-making.
This matters because personal data in recommendation and decision systems can fall within GDPR and UK GDPR processing rules, including lawfulness, fairness, transparency, data minimisation, purpose limitation, and rights handling. It is also relevant to guidance on AI model development and deployment under GDPR, automated decision-making, algorithmic discrimination, AI recommendation and decision systems, and sector-specific requirements such as employment, lending, healthcare, and financial services oversight.
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