Machine Learning
AI algorithms that improve through experience.
How the laws define this
Every cited authority establishes that machine learning centers on algorithms or computational techniques that enable systems to learn from data or experience. Most sources, including the Draft Artificial Intelligence Responsible Use Principles, IAEA Guidance on AI Applications in Nuclear Safety and Security, and Regulations for Use of Artificial Intelligence in Courts, 2026, explicitly define it as a subset or branch of artificial intelligence designed to make predictions, identify patterns, or execute decisions. The primary divergence lies in how these instruments describe the autonomy of the learning process. The N.C. State Government Responsible Use of Artificial Intelligence Framework, the Draft Artificial Intelligence Responsible Use Principles, and the Regulations for Use of Artificial Intelligence in Courts, 2026 highlight that systems learn or act without being explicitly programmed. In contrast, the New York FY2025 Budget - Deepfakes Provisions (Election Law Amendment) frames this operational freedom as making decisions with minimal human intervention, while ISO/IEC standards omit programming or human intervention criteria.
Synthesised from the 8 statutory definitions below. Each one is quoted in full, with its source.
Definitions (8)
Machine Learning is the study or application of computer algorithms that improve automatically through experience. These algorithms build a model based on training data to perform a specific task, such as aiding in prediction or decision-making processes, without necessarily being explicitly programmed to do so.
Machine Learning is a subset of AI that enables systems to automatically learn and improve from experience without being explicitly programmed. It involves algorithms that build a model from sample data, known as 'training data', to make predictions or decisions.
A process where computational techniques enable a system to improve its performance through experience, typically by learning from data.
A branch of AI that employs computational techniques to enable systems to learn from data or experiences.
A subset of artificial intelligence that enables systems to learn from data, identify patterns, and make decisions with minimal human intervention.
Machine Learning (ML) refers to technologies that learn how to complete a particular task based on large amounts of data, a key sub-field of Artificial Intelligence.
A foundational technology for AI systems addressed by the standard, involving algorithms that allow systems to learn from data.
A subset of artificial intelligence that involves training algorithms on data to enable systems to learn patterns, make predictions, or take actions without explicit programming.
Related Terms
Machine Learning (ML)
A subset of AI enabling systems to learn from data, identify patterns, and make decisions with minimal human intervention....
Neural Network
Layered computational model learning patterns from data....
AI (Artificial Intelligence System)
Any software, machine, or system simulating humanlike cognitive functions like learning or reasoning....
learning systems
Computational systems using data and algorithms to adapt behaviour over time....
Artificial Intelligence (AI) System
A machine-based system that makes predictions, recommendations, or decisions influencing environments based on human-defined objectives....