Editing Responsible Ai (section)

== <span style="color: #FFFFFF;">Remembering</span> ==
* '''Responsible AI''' — A framework for developing and deploying AI systems that are fair, accountable, transparent, and respecting of human rights and values.
* '''AI Safety''' — The field concerned with ensuring AI systems behave as intended and do not cause harm, especially as they become more capable.
* '''Bias''' — Systematic and unfair discrimination in AI outputs, often reflecting biases present in training data or model design.
* '''Fairness''' — The principle that an AI system should not discriminate against individuals or groups based on protected attributes (race, gender, age, etc.).
* '''Transparency''' — The property of AI systems being understandable, with decisions that can be explained and audited.
* '''Explainability''' — The ability to provide human-understandable reasons for why an AI system made a specific decision.
* '''Accountability''' — The principle that someone is responsible for AI system decisions and their consequences.
* '''Privacy''' — Protection of individuals' personal data from unauthorized collection, use, or disclosure by AI systems.
* '''Differential privacy''' — A mathematical framework for adding calibrated noise to data to protect individual privacy while preserving statistical utility.
* '''Adversarial robustness''' — The ability of a model to maintain correct behavior under adversarial inputs designed to fool it.
* '''Misuse''' — Intentional use of AI systems for harmful purposes (misinformation, surveillance, autonomous weapons).
* '''Hallucination''' — AI-generated content that is factually incorrect, posing risks when AI outputs are trusted without verification.
* '''Model card''' — A documentation framework for AI models describing their intended use, performance, limitations, and ethical considerations.
* '''Algorithmic auditing''' — Independent evaluation of AI systems for bias, discrimination, or safety violations.
* '''AI Act''' — The European Union's comprehensive AI regulation framework, classifying AI systems by risk level.
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