Kate Crawford
(7 articles)
Fairness-Aware Machine Learning
Focuses on developing algorithms that ensure equitable treatment and outcomes across different demographic groups.
Generality: 797
Black Box Problem
The difficulty in understanding and interpreting how an AI system, particularly ML models, makes decisions.
Generality: 850
Ethical AI
Practice of creating AI technologies that follow clearly defined ethical guidelines and principles to benefit society while minimizing harm.
Generality: 830
AI Governance
Set of policies, principles, and practices that guide the ethical development, deployment, and regulation of artificial intelligence technologies.
Generality: 860
Algorithmic Bias
Systematic and unfair discrimination embedded in the outcomes of algorithms, often reflecting prejudices present in the training data or design process.
Generality: 863
Responsible AI
Application of AI in a manner that is transparent, unbiased, and respects user privacy and value.
Generality: 815
De-Biasing
Methods and practices used to reduce or eliminate biases in AI systems, aiming to make the systems more fair, equitable, and representative of diverse populations.
Generality: 775