AI Ethics
Equal Opportunity
Equal Opportunity is the principle that all individuals should have the same chances to access employment, education, and other resources without discrimination.
AI Ethics
Equalized Odds
Equalized Odds is a fairness criterion in machine learning ensuring that a model's true positive and false positive rates are equal across different demographic groups.
AI Ethics
Ethical AI
Ethical AI is the practice of designing and deploying artificial intelligence systems that prioritize fairness, transparency, accountability, and respect for human values.
AI Ethics
Existential Risk
Existential risk is the potential threat that could cause human extinction or permanently and drastically curtail humanity’s future development.
AI Ethics
Explainability
Explainability is the ability to clearly describe how a system, model, or decision-making process works and why it produces specific outcomes.
AI Ethics
Explainable AI
Explainable AI is artificial intelligence designed to provide clear, understandable insights into how it makes decisions or predictions.
AI Ethics
Fairness Metrics
Fairness metrics are quantitative measures used to evaluate and ensure equitable treatment and unbiased outcomes in algorithms and decision-making systems.
AI Ethics
Feature Importance
Feature Importance is a technique used in machine learning to identify which variables most influence the outcome of a predictive model.
AI Ethics
Formal Verification
Formal Verification is a mathematical process used to prove or disprove the correctness of a system's design against specified properties or requirements.
AI Ethics
Group Fairness
Group Fairness is a principle ensuring that different demographic or social groups receive equitable treatment and outcomes in algorithms, policies, or decision-making processes.
AI Ethics
Human-Compatible AI
Human-Compatible AI is artificial intelligence designed to align with human values, ethics, and well-being to ensure safe and beneficial interactions.
AI Ethics
Impact Assessment
Impact Assessment is the systematic process of identifying and evaluating the potential effects of a project, policy, or activity on the environment, society, or business outcomes.
AI Ethics
Individual Fairness
Individual Fairness is a principle that ensures similar individuals receive similar treatment or outcomes in decision-making systems.
AI Ethics
Inner Alignment
Inner Alignment is the process of ensuring that a machine learning model’s internal objectives align with the intended external goals set by its developers.
AI Ethics
Interpretability
Interpretability is the ability to understand and explain how a model or system arrives at its decisions or outputs.
AI Ethics
ISO/IEC 42001
ISO/IEC 42001 is an international standard that provides a framework for managing artificial intelligence (AI) systems responsibly and effectively.
AI Ethics
Lethal Autonomous Weapons
Lethal Autonomous Weapons are military systems capable of selecting and engaging targets without human intervention.
AI Ethics
Malicious Use
Malicious use is the intentional exploitation of software, systems, or data to cause harm, unauthorized access, or damage.
AI Ethics
Manipulation
Manipulation is the act of skillfully influencing or controlling people, situations, or information to achieve a desired outcome, often without full transparency.
AI Ethics
Mesa-Optimization
Mesa-Optimization is the phenomenon where an AI system develops its own internal objectives or goals distinct from those originally programmed by its creators.
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