Artificial intelligence (AI) refers to an evolving set of technologies, dating back to the 1950s. Today, AI encompasses a broad set of technologies that rely on large amounts of data to make predictions or decisions. Over the past twenty years, as the ability to produce and store vast amounts of data has increased dramatically, so have the possibilities of building technologies that incorporate AI, like more precise GPS navigation, email spam filters, and search engines.
One reason Artificial Intelligence tends to be a confusing concept is that AI is an umbrella term, like the term “transportation,” which has meant different things over time (bicycle or spaceship!), and certainly means different things in different contexts (rickshaw or jet!). Given the vagueness of the term AI, continuous changes to the technologies, and misrepresentation by the media, there is a lot of uncertainty about what AI is and is not. Various industries and applications use AI, including customer service, fraud detection, medical diagnostics, and media recommendation systems.
Over the past year, a subset of AI known as “generative AI” has captured the public imagination and caused understandable concern among some educators. Generative AI technologies include conversational chatbots (such as ChatGPT and Gemini) and image generation tools (such as DALL-E and Midjourney). Chatbots are based on a technology called large language models. For example, ChatGPT is a chatbot by OpenAI based on the large language models GPT-3, GPT-3.5, and GPT-4, and Gemini is a chatbot by Google based on the large language model PaLM. Other generative AI tools can be used to generate code, music, and video.
(From AI Pedagogy Project, created by the metaLAB (at) Harvard)
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To cite in APA: Wheatley, A & Hervieux, S. (2020). The AI family tree [diagram]. The LibrAIry. https://thelibrairy.wordpress.com/2020/05/12/the-ai-family-tree/
Artificial Intelligence: (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.
Source: https://www.investopedia.com/terms/a/artificial-intelligence-ai.asp
Deep Learning: Deep learning is a collection of algorithms used in machine learning, used to model high-level abstractions in data through the use of model architectures, which are composed of multiple nonlinear transformations.
Source: https://www.techopedia.com/definition/30325/deep-learning
Machine learning: Machine learning facilitates the continuous advancement of computing through exposure to new scenarios, testing and adaptation, while employing pattern and trend detection for improved decisions in subsequent (though not identical) situations.
Source: https://www.techopedia.com/definition/8181/machine-learning
Natural language processing: Natural language processing (NLP) is a method to translate between computer and human languages. It is a method of getting a computer to understandably read a line of text without the computer being fed some sort of clue or calculation.
Source: https://www.techopedia.com/definition/653/natural-language-processing-nlp
Neural networks: A neural network, in general, is a technology built to simulate the activity of the human brain – specifically, pattern recognition and the passage of input through various layers of simulated neural connections.
Source: https://www.techopedia.com/definition/32902/deep-neural-network
Pattern recognition: In IT, pattern recognition is a branch of machine learning that emphasizes the recognition of data patterns or data regularities in a given scenario. Pattern recognition can be either “supervised,” where previously known patterns can be found in a given data, or “unsupervised,” where entirely new patterns are discovered. The objective behind pattern recognition algorithms is to provide a reasonable answer for all possible data and to classify input data into objects or classes based on certain features.
Source: https://www.techopedia.com/definition/8802/pattern-recognition-computer-science
Full list of terms and definitions are available here. (Credit: McGill University Libraries)
