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Artificial Intelligence (AI) in Research

This guide provides an overview of AI and its applications to research across scholarly fields, including AI programs at UB and ethics, attribution, and APA guidelines..

Welcome to the AI Guide from Wahlstrom Library at UB

This guide is designed to support your interest in Artificial Intelligence (AI), from its definitions and history to using and citing AI tools. 

The tabs on the left of this page can help you navigate through the guide. Be sure to reach out to the librarians through the Chat if you would like more information (or stop by Wahlstrom Library anytime).

AI: Historical View

Stanford University Professor John McCarthy is credited with introducing the term Artificial Intelligence (AI) in 1955 to describe the concept of intelligent machines. Over the decades since, AI in science, engineering, and research across the disciplines has developed from creating and adapting machines that mimic human behaviors to those that demonstrate the capacity to learn. 

Generative AI Basics

Generative AI refers to machine learning models that go beyond making predictions from datasets to generating new objects that are based on the datasets the AI models were trained on. 

Machine Learning Systems

Machine learning systems allow for the creation and management of code, using libraries or frameworks, and development of machine learning technologies. The following list includes some examples of deep learning and large language models.

AI Programs at University of Bridgeport

Artificial Intelligence (AI) in Research © 2025 by Mary Lamothe, PhD is licensed under CC BY-NC-SA 4.0