According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the word “Adversarial Machine Learning” means a practice concerned with the design of ML algorithms that can resist security challenges, the study of the capabilities of attackers, and the understanding of attack consequences. Inputs in adversarial ML are purposely designed to make a mistake in its…
Autonomy: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the word “Autonomy” means systems that maintain a set of intelligence-based capabilities to respond to situations that were not pre-programmed or anticipated (i.e., decision-based responses) prior to system deployment. Autonomous systems have a degree of self-government and self-directed behavior (with the human’s proxy for decisions).
Big Data: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the word “Big Data” means an all-encompassing term for large, complex digital data sets that need equally complex technological means to be stored, analyzed, managed, and processed with substantial computing power. Datasets are sometimes linked together to see how patterns in one domain affect…
Classifier: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the word “Classifier” means a model that predicts (or assigns) class labels to data input.
Data Poisoning: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the word “Data Poisoning” means a type of security attack where malicious users inject false training data with the aim of corrupting the learned model, thus making the AI system learn something that it should not learn.
Deep Learning: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the word “Deep Learning” means a subset of machine learning based on artificial neural networks that employs statistics to spot underlying trends or data patterns and applies that knowledge to other layers of analysis. Some have labeled this as a way to “learn by…
Differential Privacy: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the word “Differential Privacy” means a method for measuring how much information the output of a computation reveals about an individual. It produces data analysis outcomes that are nearly equally likely, whether any individual is, or is not, included in the dataset. Its goal…
Input Data: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the term “Input Data” means data provided to or directly acquired by an AI system on the basis of which the system produces an output.
Machine Learning: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the word “Machine Learning” means a branch of artificial intelligence (AI) and computer science which focuses on the development of systems that are able to learn and adapt without following explicit instructions, imitating the way that humans learn, gradually improving its accuracy, by using…
Model Training: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the term “Model Training” means the process to establish or to improve the parameters of a machine learning model, based on a Machine Learning algorithm, by using training data.
Model Validation: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the term “Model Validation” means confirmation through the provision of objective evidence that the requirements for a specific intended use or application have been fulfilled.
Natural Language Processing: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the word “Natural Language Processing” means the ability of a machine to process, analyze, and mimic human language, either spoken or written.
Predictive Analysis: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the word “Predictive Analysis” means the organization of analyses of structured and unstructured data for inference and correlation that provides a useful predictive capability to new circumstances or data.
Profiling: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the word “Profiling” means any form of automated processing of personal data consisting of the use of personal data to evaluate certain personal aspects relating to a natural person, in particular to analyze or predict aspects concerning that natural person’s performance at work, economic situation,…
Reinforcement Learning: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the word “Reinforcement Learning” means a type of machine learning in which the algorithm learns by acting toward an abstract goal, such as “earn a high video game score” or “manage a factory efficiently.” During training, each effort is evaluated based on its contribution…
Structured Data: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the word “Structured Data” means data that has a predefined data model or is organized in a predefined way.
Unstructured Data: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the word “Unstructured Data” means data that does not have a predefined data model or is not organized in a predefined way.
Synthetic Data: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the word “Synthetic Data” means data generated from data/processes and a model that is trained to reproduce the characteristics and structure of the original data aiming for a similar distribution. The degree to which synthetic data is an accurate proxy for the original data…
Transfer Learning: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the word “Transfer Learning” means a technique in machine learning in which an algorithm learns to perform one task, such as recognizing cars, and builds on that knowledge when learning a different but related task, such as recognizing cats.
Supervised Learning: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the word “Supervised Learning” means machine learning that makes use of labeled data during training.
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