AI Ethics

AI Alignment

AI alignment is the study and practice of making artificial intelligence systems behave in ways that accord with intended goals, preferences, constraints, or...

AI SafetyMachine Learning

AI Anxiety

The term "Artificial Intelligence" (AI) anxiety describes the fear, stress, distress, and trepidation that people feel in response to the development and...

Artificial Intelligence

AI Fairness 360 (AIF360)

AI Fairness 360, abbreviated AIF360, is an open-source Python and R toolkit, originally created by IBM Research and released in September 2018, that detects...

AI Tools & ProductsOpen Source AI

AI and religion

See also: Religion ChatGPT Plugins AI and religion refers to the use of artificial intelligence within religious life and to the responses that faith...

Artificial Intelligence

AI bias

AI bias (also called algorithmic bias) is systematic, repeatable error in artificial intelligence systems that produces unfair, discriminatory, or skewed...

AI SafetyArtificial Intelligence

AI consciousness

See also: Artificial intelligence, AI ethics, AI safety, Large language model AI consciousness refers to the ongoing scientific and philosophical debate about...

AI SafetyArtificial Intelligence

AI ethics

AI ethics is the field that studies the moral principles, values, and frameworks governing how artificial intelligence systems are designed, built, deployed,...

AI SafetyArtificial Intelligence

AI regulation

AI regulation is the body of laws, binding rules, technical standards, and government enforcement mechanisms that oversee how artificial intelligence systems...

AI SafetyArtificial Intelligence

AI safety

AI safety is the research and practice of preventing or reducing unacceptable harm from artificial intelligence systems. It includes technical research,...

AI SafetyArtificial Intelligence

AI-generated content

AI-generated content (also called AIGC or synthetic media) is text, images, video, audio, music, or code produced wholly or partly by artificial intelligence...

Artificial Intelligence

Algorithmic bias

Algorithmic bias is the tendency of a computer system to produce systematic, repeatable errors that advantage some groups of people over others. The term...

AI Policy & RegulationMachine Learning

Algorithmic fairness

Algorithmic fairness is the study of how automated decision systems can be made to produce decisions that are equitable across protected attributes such as...

AI SafetyMachine Learning

Amanda Askell

Amanda Askell is a Scottish philosopher and artificial intelligence researcher who works on fine-tuning and alignment at Anthropic, where she leads the team...

AI SafetyPeople

Amazon Mechanical Turk

Amazon Mechanical Turk (MTurk) is a crowdsourcing marketplace operated by Amazon in which businesses and researchers ("requesters") post small paid tasks that...

AI HistoryAI Tools & Products

Anthropic Long-Term Benefit Trust

The Anthropic Long-Term Benefit Trust (LTBT) is a Delaware purpose trust that holds a special class of Anthropic stock and uses it to elect a portion of the...

AI CompaniesAI Safety

Automation Bias

Automation bias is the tendency for humans to favor suggestions and outputs from automated decision-making systems over contradictory information from...

Machine Learning

Autonomous weapons

Autonomous weapons, usually discussed under the label lethal autonomous weapon systems (LAWS), are weapon systems that, once activated, can select and engage...

AI Policy & RegulationAI Safety

BBQ (Bias Benchmark for QA)

BBQ (the Bias Benchmark for QA) is a hand-built evaluation dataset that measures whether a question answering (QA) language model relies on social stereotypes...

AI BenchmarksAI Safety

Bias

See also: Bias-Variance Tradeoff, Fairness (Machine Learning), Neural Network, Activation Function, Weight Bias in artificial intelligence carries three...

Machine LearningNeural Networks

Blueprint for an AI Bill of Rights

The Blueprint for an AI Bill of Rights is a non-binding policy framework released by the White House Office of Science and Technology Policy (OSTP) on October...

AI Policy & Regulation

BookCorpus

BookCorpus (also written BooksCorpus, and sometimes called the Toronto Book Corpus) is a text dataset built from free, self-published English-language ebooks...

Data & DatasetsNatural Language Processing

C2PA (Coalition for Content Provenance and Authenticity)

The Coalition for Content Provenance and Authenticity (C2PA) is an open technical standards body that develops Content Credentials, a cryptographically signed...

AI Policy & RegulationGenerative AI

COMPAS (recidivism risk assessment)

COMPAS (Correctional Offender Management Profiling for Alternative Sanctions) is a proprietary actuarial risk-assessment instrument used by United States...

Charity

See also: Charity ChatGPT Plugins Charity, nonprofit, and humanitarian work has become one of the most visible testbeds for applied artificial intelligence....

AI Tools & ProductsChatGPT

Collective Constitutional AI

Collective Constitutional AI (CCAI) is a 2023 research project by Anthropic and the Collective Intelligence Project (CIP) that sourced the value principles, or...

AI AlignmentAnthropic

Confirmation Bias

Confirmation bias is the tendency to search for, interpret, favor, and recall information in ways that confirm one's preexisting beliefs, and in artificial...

AI SafetyData Science

Content Authenticity Initiative

The Content Authenticity Initiative (CAI) is an Adobe-led community and implementation effort for attaching verifiable origin and editing information to...

AI Policy & RegulationGenerative AI

Content provenance

Content provenance is the set of techniques, standards, and policies for recording and disclosing the origin, authorship, and edit history of digital media....

AI Policy & RegulationGenerative AI

Copyright and AI

Copyright and AI is the body of law, agency practice, and litigation that governs how copyright applies to systems that learn from existing works and produce...

AI Policy & RegulationGenerative AI

Counterfactual Fairness

Counterfactual fairness is a formal definition of algorithmic fairness rooted in causal inference: a prediction is counterfactually fair toward an individual...

Machine LearningStatistics

Coverage Bias

Coverage bias is a type of selection bias that occurs when the method used to collect data systematically excludes part of the target population, so the sample...

Data & DatasetsMachine Learning

Deepfake

A deepfake is synthetic media in which a real person's face, voice, or body is digitally replaced, manipulated, or fabricated using artificial intelligence,...

Artificial IntelligenceComputer Vision

Demographic Parity

Demographic parity, also called statistical parity or acceptance rate parity, is a fairness criterion in machine learning that requires a model's predictions...

Machine Learning

Differential privacy

Differential privacy is a mathematical definition of privacy that guarantees the output of an analysis is essentially unchanged whether or not any single...

Computer ScienceStatistics

Disparate Impact

Disparate impact is a legal and statistical concept describing situations where a seemingly neutral policy, practice, or algorithm produces disproportionately...

AI Policy & RegulationMachine Learning

Disparate Treatment

Disparate treatment is the intentional, less favorable treatment of an individual because of a protected attribute such as race, gender, age, religion,...

AI Policy & RegulationMachine Learning

ELIZA effect

The ELIZA effect is the tendency of people to attribute understanding, empathy, and other human mental states to a computer program on the strength of its...

AI HistoryConversational AI

Effective Altruism

Effective altruism (often abbreviated EA) is a philosophical and social movement that uses evidence and careful reasoning to identify the most effective ways...

AI Safety

Effective accelerationism

Effective accelerationism (often abbreviated e/acc) is a techno-optimist ideological movement that advocates for the maximum acceleration of technological...

Artificial Intelligence

Emily M. Bender

Emily M. Bender is an American linguist and a professor in the Department of Linguistics at the University of Washington, where she directs the Computational...

Natural Language ProcessingPeople

Equality of Opportunity

Equality of opportunity is a group-fairness criterion in machine learning that requires a classifier's true positive rate (TPR) to be equal across all groups...

Machine Learning

Equalized Odds

Equalized odds is a group fairness criterion in machine learning that requires a classifier's true positive rate (TPR) and false positive rate (FPR) to be...

Machine Learning

Existential risk from AI

Existential risk from artificial intelligence (also called AI x-risk) is the hypothesis that the development of sufficiently advanced artificial intelligence...

AI SafetyArtificial Intelligence

Experimenter's Bias

Experimenter's bias (also called the observer-expectancy effect, experimenter expectancy effect, or experimenter effect) is a type of cognitive bias in which a...

Machine LearningStatistics

Explainable AI

Explainable AI (XAI) refers to artificial intelligence systems and techniques designed so that humans can understand how and why the system reaches its...

Interpretability

Facial Recognition

Facial recognition is a biometric technology that identifies or verifies the identity of an individual by analyzing patterns in a digital image or video frame...

AI Tools & ProductsComputer Vision

Fair use

Fair use is a limitation on the exclusive rights of copyright owners in United States law, codified at 17 U.S.C. 107. It permits unlicensed use of copyrighted...

AI Policy & RegulationLegal AI

Fairlearn

Fairlearn is an open-source Python toolkit for assessing and improving the fairness of machine-learning models with respect to sensitive attributes such as...

AI Tools & ProductsMicrosoft

Fairness Constraint

A fairness constraint is an explicit mathematical condition imposed on a machine learning model during training, evaluation, or post-processing that forces its...

Machine Learning

Fairness Metric

A fairness metric is a quantitative, mathematical measure used to evaluate whether a machine learning model's predictions or decisions treat different...

Machine LearningModel Evaluation

Federated Learning

See also: Machine learning terms, Differential privacy, Deep learning Federated learning is a machine learning technique that trains a shared model across many...

Deep LearningMachine Learning

Feedback Loop

See also: Machine learning terms A feedback loop in machine learning is a cycle in which a deployed model's predictions influence the real world, and the...

Machine Learning

General Data Protection Regulation (GDPR)

The General Data Protection Regulation (GDPR), formally Regulation (EU) 2016/679, is the European Union law that governs how the personal data of individuals...

AI Policy & Regulation

Group Attribution Bias

Group attribution bias is the tendency to assume that what is true of one member of a group is true of the entire group, or that a group's collective decision...

Machine Learning

Human-in-the-loop

Human-in-the-loop (HITL) describes any arrangement in which a person is a required participant in an automated system's operating cycle rather than a bystander...

AI Policy & RegulationAI Safety

Implicit Bias

Implicit bias is an umbrella term that, in artificial intelligence and machine learning, refers to systematic tendencies operating below the surface of...

Machine Learning

In-Group Bias

In-group bias (also called in-group favoritism or in-group preference) is the systematic tendency to favor members of one's own social group over members of...

Machine Learning

Incompatibility of Fairness Metrics

The incompatibility of fairness metrics (also called the impossibility theorem of fairness or fairness trade-offs) is the proven mathematical result that...

Machine Learning

Individual Fairness

Individual fairness is the principle in machine learning that any two individuals who are similar with respect to a task should receive similar algorithmic...

Machine Learning

Interpretability

Interpretability in artificial intelligence concerns what people can learn about a system's behavior, predictions, or internal computations, and whether that...

Machine LearningModel Evaluation