While bias audits are important, the EU AI Act does not mandate engaging a third-party auditor; registration, risk management systems, and technical documentation are required.

In the context of AI, particularly generative models, "hallucination" refers to the generation of outputs that are not based on the training data and are factually incorrect or non-existent. The scenario described involves the generative AI tool providing incorrect and non-existent information about restaurants, which fits the definition of hallucination. Reference: AIGP BODY OF KNOWLEDGE and various AI literature discussing the limitations and challenges of generative AI models.

An AI system that can provide a rationale for its specific outputs is considered explainable because it offers understandable reasons for its decisions.

The AI system uses historical patient data to assess probabilities and uncertainties in diagnosing diseases, which aligns with a probabilistic model.