Artificial Intelligence (AI): any system that demonstrates behavior that can be considered intelligent
Expert System: a system that is coded to perform a specific skill based on the knowledge of experts in the field
General AI: artificial intelligence that can do anything a human can (General AI does not yet exist.)
Machine Learning (ML): a system learning something without being programmed with that information or skill
Modern AI: the current form of artificial intelligence where computers are programmed to be able to learn from data using neural networks
Neural Network: a type of artificial intelligence based on the design of the human brain, where nodes (like neurons) are connected by links that fire based on inputs
Convolutional Neural Network (CNN): a neural network that takes lots of information (such as all the pixels in an image) and decides what is important in order to classify it
Creative Adversarial Network (CAN): a type of generative adversarial network where the discriminator has to determine if the art is real and classify it by style, so that the generator must try to create art that is real but does not fit into existing styles
Generative Adversarial Network (GAN): a type of AI with two neural networks, a generator that tries to create art, and a discriminator that tries to determine what is real art, so that the generator must create convincing works
Deep Neural Network (DNN): a neural network with multiple layers
Recurrent Neural Network (RNN): a neural network that can consider data in a sequence or over time
Traditional AI: the earliest form of artificial intelligence, in which computers were programmed by humans with rules to try to make them behave intelligently
Weak AI: artificial intelligence that can complete a specific task
Artificial Intelligence in Education (AIEd or AI-Ed): using artificial intelligence technologies or methods for education
Branching Teaching Program: a program to teach where the student sees a frame, answers a question, and is directed to the next appropriate frame
Intelligent Tutoring System (ITS): a system that is able to provide individualized instruction to students using knowledge of the content area, a model of pedagogy, and/or a model of the individual student
Interactive Learning Environment (ILE): a system to support education that provides access to quality materials for learning and teaching
Learning Analytics: use of large sets of data about students to improve education
Algorithmic Music: music composed or created using algorithms
Virtual Music: Music composed by a computer that imitates the style of human-composed music but is not an exact replica
AI Alignment: the measure of how well AI does what we, as humans, want it to do
AI Effect: the effect where people stop calling a technology "artificial intelligence" after it has been around long enough that they accept it as something a computer can do
Black Box: a system where the inner workings are hidden, so users do not know how decisions are made
Completeness: a system's ability to discover all the possible solutions to a problem
Singularity: the theoretical point where AI is capable of improving itself or creating AI more powerful than itself
Soundness: a program's ability to not draw wrong conclusions
Technology Drift: the change over time as technologies start to be used for purposes other than what they were built for
Turing Test: a proposed test that can determine whether a machine is intelligent by comparing its responses to human responses