AI 용어집
인공지능 완전 사전
Algorithmic Justice
Study of mathematical and statistical principles ensuring fair treatment of different groups by algorithms
Transparency and Interpretability
Development of methods to understand and explain the decisions of AI models
Data Bias and Representation
Analysis of biases present in training data and their impact on predictions
Responsibility and Auditability
Mechanisms for tracing algorithmic decisions and assigning responsibility for errors
Intersectional Equity
Consideration of combined discriminations based on multiple protected characteristics simultaneously
Detection and Measurement of Bias
Statistical tools and metrics to identify and quantify discriminations in AI systems
Algorithmic Bias Correction
Preprocessing, processing, and post-processing techniques to reduce inequalities in models
Ethics of Autonomous Systems
Ethical frameworks for AIs operating without direct human supervision and making critical decisions
Procedural Justice in AI
Fairness guarantees in algorithmic decision-making processes including voice and recourse
Ethical Impact Assessment
Systematic methodologies for assessing ethical consequences of AI deployments
Biais Cognitifs et IA
Interaction entre les biais psychologiques humains et les décisions assistées par algorithmes
Équité dans l'Apprentissage Fédéré
Défis éthiques spécifiques aux systèmes d'IA distribués préservant la vie privée