Definition
Explainable AI (XAI)
Methods that make an AI system's decisions understandable to people, rather than leaving the model a black box.
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Related terms in AI Fundamentals
Ensemble methodsCombining several models and merging their predictions to get a result that is more accurate than any single model.Ethical AIDesigning and deploying AI in ways that respect human values, fairness, transparency, and the wellbeing of the people it affects.EU AI ActEuropean Union regulation on AI, including transparency rules for AI-generated content.Expert systemAn early style of AI that mimics a human expert using a knowledge base of facts and hand-written if-then rules.Federated learningTraining a model across many devices or servers that each keep their own data, so the raw data never has to be pooled in one place.Few-shot learningWhen a model learns a new task from just a handful of examples, often given right in the prompt.Fine-Tuned LLMA large language model that has been further trained on a domain-specific dataset — in Videra's case, behavioral health conversations between providers and patients — to make its outputs more accurate and contextually appropriate for that domain than a general-purpose model.Fine-tuningTaking a pre-trained model and training it further on data for a specific task or domain so it performs better there.