Except where otherwise noted this guides content is released under CC BY-SA 4.0 (Creative Commons Attribution-ShareAlike 4.0 International License).
Contributors to this guide include Katerina Allmendinger, Stephanie Bonjack, Xiang Li, Matthew Murray, Liz Novosel, Kate Tallman, & Natalia Tingle Dolan.
This guide offers information and resources to help users navigate issues regarding generative artificial intelligence (AI) in the academic and research context. For tools available at CU, go to the AI Tools List.
For CU Boulder's official policies, tools, and resources related to AI, visit:
Artificial Intelligence at CU Boulder
A wide range of sources were consulted to inform this guide, including scholarly literature, technique reports, websites, news, and videos. These sources are listed at the bottom of each page to provide further reading on the topics in this guide.
Due to the rapidly evolving nature of AI technologies, new developments emerge on a daily basis. Although this guide will be periodically updated, please note that some information may be outdated. We welcome your suggestions and questions.
Ithaka S&R has released a Generative AI Product Tracker that "lists generative AI products that are either marketed specifically towards postsecondary faculty or students or appear to be actively in use by postsecondary faculty or students for teaching, learning, or research activities." They update this list regularly and have information about using AI in higher education settings.
Artificial Intelligence is a complicated set of technologies. While it is not necessary to understand every detail, it is beneficial to have a basic understanding of some of the core concepts of generative AI to help you make informed and ethical decisions about using AI tools.
Generative AI is a type of artificial intelligence technology generates new content in a variety of forms, including text, images, audio, video and other formats. Generative AI generates new content by identifying information that exist in the dataset it was trained with. Generative AI fits into the field of deep learning, a subfield of machine learning, which, in turn, is a subcategory of the larger field of artificial intelligence.
Artificial Intelligence (AI) is a branch of computer science that creates machines and systems that can perform tasks that typically require human intelligence, including such features as perception, learning, reasoning, problem-solving, language interaction, and acting autonomously. AI has several sub-disciplines, including deep learning, machine learning, neural processing, robotics, expert systems, and natural language processing.
Machine Learning is a subset of AI that involves training algorithms to learn from data and make predictions or decisions without being explicitly programmed. There are different types of machine learning, such as supervised learning (algorithm is trained on classified and labeled data), unsupervised learning (algorithm is trained on unlabeled data), and reinforcement learning (algorithm learns from interacting with environment and receiving feedback).
Deep Learning is a subset of machine learning methods. It is a type of machine learning that uses artificial neural networks allowing them to process more complex patterns than machine learning. Artificial neural networks are inspired by and modeled after the structure of the human brain. They are made up of many interconnected nodes or neurons, which allows them to learn more complex patterns than traditional machine learning models.
Large Language Models are also a subset of deep learning. Large language models refer to large, general-purpose language models that can be pre-trained to solve common language problems such as text classification, question answering, document summarization, and text generation.
At the intersection between Large Language Models and Generative AI is the technology that powers Chatbot applications such as ChatGPT, Claude, and Microsoft Copilot.
The following short video distills the essence of Google's introductory AI course. It helps you understand the basic concepts of AI quickly.
