Algorithm: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the term “Algorithm” means: An algorithm consists of a set of step-by-step instructions to solve a problem (e.g., not including data). The algorithm can be abstract and implemented in different programming languages and software libraries.
Classification: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the term “Classification” means: A classification system is a set of “boxes” into which things are sorted. Classifications are consistent, have unique classificatory principles, and are mutually exclusive. In AI design, when the output is one of a finite set of values (such as sunny,…
Federated Learning: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the term “Federated Learning” means: Federated learning is a machine learning model which addresses the problem of data governance and privacy by training algorithms collaboratively without transferring the data to another location. Each federated device shares its local model parameters instead of sharing the…
Generative Adversarial Network (GAN): According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the term “Generative Adversarial Network (GAN)” means: Generative Adversarial Networks, or GANs for short, are an approach to generative modeling using deep learning methods, such as convolutional neural networks. Generative modeling is an unsupervised learning task in machine learning that involves automatically…
Human Values for AI: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the term “Human Values for AI” means: Values are idealized qualities or conditions in the world that people find good. AI systems are not value-neutral. The incorporation of human values into AI systems requires that we identify whether, how, and what we…
Human-Centric AI: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the term “Human-Centric AI” means: An approach to AI that prioritizes human ethical responsibility, dynamic qualities, understanding, and meaning. It encourages the empowerment of humans in design, use, and implementation of AI systems. Human-Centric AI systems are built on the recognition of a meaningful…
Language Model: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the term “Language Model” means: A language model is an approximative description that captures patterns and regularities present in natural language and is used for making assumptions on previously unseen language fragments.
Large Language Model (LLM): According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the term “Large Language Model (LLM)” means: A class of language models that use deep-learning algorithms and are trained on extremely large textual datasets that can be multiple terabytes in size. LLMs can be classed into two types: generative or discriminatory. Generative…
Model: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the term “Model” means: A function that takes features as input and predicts labels as output. Typical phases of an AI model’s work flow are: Data collection and preparation, Model development, Model training, Model accuracy evaluation, Hyperparameters’ tuning, Model usage, Model maintenance, Model versioning.
Neural Network: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the term “Neural Network” means: A computer system inspired by living brains, also known as artificial neural network, neural net, or deep neural net. It consists of two or more layers of neurons connected by weighted links with adjustable weights, which takes input data…
Scalability: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the term “Scalability” means: The ability to increase or decrease the computational resources required to execute a varying volume of tasks, processes, or services.
Socio-Technical System: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the term “Socio-Technical System” means: Technology is always part of society, just like society is always part of technology. This also means that one cannot understand one without the other. Technology is not only design and material appearance but also sociotechnical; that is, a…
Technical Interoperability: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the term “Technical Interoperability” means: The ability of software or hardware systems or components to operate together successfully with minimal effort by an end user.
Value Sensitive Design (Values-by-Design or Ethics-by-Design): According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the term “Value Sensitive Design (Values-by-Design or Ethics-by-Design)” means: A theoretically grounded approach to the design of technology that accounts for human values in a principled and systematic manner throughout the design process.
Auditability of an AI System: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the term “Auditability of an AI System” means: Auditability refers to the ability of an AI system to undergo the assessment of the system’s algorithms, data, and design processes. This does not necessarily imply that information about business models and Intellectual…
Standard: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, “Standards” are a set of institutionalized agreed-upon rules for the production of (textual or material) objects. They are released by international organizations and ensure quality and safety and set product or service specifications. Standards are the result of negotiations among various stakeholders and are institutionalized…
Accessibility: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the term “Accessibility” means: Extent to which products, systems, services, environments, and facilities can be used by people from a population with the widest range of user needs, characteristics, and capabilities to achieve identified goals in identified contexts of use (which includes direct use or…
Accountability: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the term “Accountability” means: Accountability relates to an allocated responsibility. The responsibility can be based on regulation or agreement or through assignment as part of delegation. In a systems context, accountability refers to systems and/or actions that can be traced uniquely to a given entity….
AI (or Algorithmic) Bias: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the term “AI (or Algorithmic) Bias” means: Harmful AI bias describes systematic and repeatable errors in AI systems that create unfair outcomes, such as placing privileged groups at systematic advantage and unprivileged groups at systematic disadvantage. Different types of bias can emerge…
Attack: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the term “Attack” means: Action targeting a learning system to cause malfunction.
