Accountability - Accountability in AI means that identifiable people and organizations can be called upon to explain and justify decisions within their roles, demonstrate...
Activity Bias - Activity bias occurs when data or conclusions disproportionately reflect highly active users while less active or inactive users are poorly represented.
Adaptive dynamic programming - Adaptive dynamic programming is a model-based reinforcement-learning approach that learns how an environment behaves from experience and uses dynamic...
Adaptive learning - Adaptive learning, in the machine-learning sense used here, updates a predictive model during operation so that it can respond to changing patterns in...
Adversarial Autoencoders - Adversarial autoencoders are autoencoders trained both to reconstruct their inputs and to make their collective latent codes resemble a chosen probability...
Adversarial Domain Adaptation - Adversarial domain adaptation is a family of methods that trains a useful predictive representation while making it harder to identify which domain supplied...
Adversarial example - An adversarial example is an input deliberately modified to cause a machine-learning model to produce an incorrect prediction or other unintended behavior.
Adversarial loss - Adversarial loss is a training objective derived from a competition between models or model components.
Adversarial search - Adversarial search is decision-making by exploring possible actions and the responses of other agents whose interests conflict with yours.
Adversarial Training - Adversarial training is a model-training approach that uses deliberately challenging, permitted modifications of training inputs to improve resistance to...
Adverse impact ratio - An adverse impact ratio compares the selection rate for one group with the selection rate for a reference group.
AI governance - AI governance is the system of decision rights, responsibilities, policies and oversight through which an organization directs its development, acquisition...
AI principles - AI principles are high-level commitments intended to guide how artificial intelligence is developed, deployed and used.
AI risk management - AI risk management is the ongoing work of identifying, assessing, responding to and monitoring risks associated with developing or using AI.
AI safety - AI safety is the study and practice of preventing or reducing harm arising from AI systems and their use.
Algorithmic aversion - Algorithmic aversion is reluctance to rely on an algorithm, particularly when people reject its recommendations after seeing it make mistakes despite...
Alignment - In AI, alignment is the aim of making a system's behavior consistent with intended goals, human values and relevant constraints.
Amplification Bias - Amplification bias occurs when processing by an AI system increases a skew or association relative to a stated reference distribution.
Analytics - Analytics is the systematic examination of data to answer questions, understand patterns and support decisions.
Anonymization - Anonymization is the process of changing information about people so that they are no longer identifiable within the relevant context and applicable standard.
Artificial narrow intelligence - Artificial narrow intelligence, or ANI, is AI whose capabilities are concentrated on a defined task or limited range of tasks.
Asymptotically unbiased estimator - An asymptotically unbiased estimator is a sequence of statistical estimation rules whose bias approaches zero as the sample size grows without bound, under...
Attack - An attack is a deliberate attempt to compromise a system, its information or its operation.
Audit log - An audit log is a record of selected system events and activities that provides evidence for later review.
Authenticity - Authenticity is the property of being genuine with respect to a stated origin or identity.
Automation bias - Automation bias is a tendency to give automated recommendations undue weight when making decisions, including accepting an incorrect recommendation despite...
Automation Complacency Bias - Automation complacency bias concerns over-reliance on automated systems that weakens active checking and can leave people less prepared to perform or...
Autonomy - Autonomy in an AI system is its ability to select and carry out actions toward a goal without a person directing every step, within a defined scope.
Availability - Availability is the property of information or a service being accessible and usable by authorized users when needed, within an acceptable time.
Back-testing - Back-testing evaluates a model, forecasting method or decision procedure using historical observations to examine how it would have performed.
Bayes risk - Bayes risk, in the machine-learning sense used here, is the smallest expected loss achievable by a prediction rule given the available information, the...
Behavioral Bias - Behavioral bias, in the source terminology used here, concerns systematic differences in user behavior across platforms, contexts or populations represented...
Bias - Bias is a systematic tendency, distortion or preference whose meaning depends on context.
Bias detection and mitigation - Bias detection and mitigation is the process of identifying relevant systematic distortions or unfair patterns in an AI workflow, investigating their causes...
Bias (math) or bias term - A bias term is an adjustable constant added to a model's weighted input.
Bias mitigation algorithm - A bias mitigation algorithm is a computational procedure intended to reduce a specified unwanted bias or fairness disparity in data, model training or outputs.
Bias testing - Bias testing is a structured examination of data, models or AI-enabled decisions for specified systematic distortions or unfair patterns.
Bias-variance trade-off - The bias - variance trade-off describes how a learning method's systematic prediction error and sensitivity to its training sample can interact.
Biased estimator - A biased estimator is a rule for estimating a population quantity whose expected result differs from that quantity under the specified sampling model.
Biometric data - Biometric data are measurements or representations of a person's biological or behavioral characteristics used in automated recognition.
Breach - A breach is a loss of control over, compromise of or unauthorized access to protected information or systems.
Broad artificial intelligence - Broad artificial intelligence is a context-dependent term for AI that handles a wider range of tasks, information types or domains than a narrowly...
Business process management - Business process management, or BPM, is the systematic examination, design, operation and improvement of an organization's recurring work processes.
Business rule - A business rule is a precise statement that defines or constrains an aspect of how an organization operates.
Calibration - Calibration describes how well predicted values agree with observed outcomes in a defined population and setting.