This guide was created for teaching faculty and librarians. While we strive to offer valuable insights into the core concepts, practical applications, and ethical considerations of artificial intelligence (AI) in education, we acknowledge the dynamic and rapidly evolving landscape of AI technology. This guide is intended as a starting point for exploration and discussion, with the understanding that advancements in AI are continual and our knowledge is ever-growing. We encourage readers to view this resource as a foundation for further inquiry into the exciting and shifting frontiers of artificial intelligence in the academic world.
This LibGuide was developed by the PASCAL Training Working Group with some assistance from ChatGPT, a language model created by OpenAI.
Understanding AI is crucial for teaching faculty as it equips them with the knowledge needed to harness AI's potential in enhancing educational practices, addressing academic integrity concerns, and preparing students for an AI-driven future job market. Moreover, familiarity with AI enables educators to adapt teaching methodologies and leverage AI tools effectively to personalize learning experiences and improve student outcomes.
Last updated: 03/4/2024
Artificial Intelligence (AI) encapsulates the endeavor to engineer machines that replicate human intelligence. The formal inception of AI as a distinct field of study occurred in 1956 at a Dartmouth College workshop, marking the commencement of an academic and practical exploration into cognitive simulation. The trajectory of AI has been characterized by cycles of ambitious advancements and subsequent periods of disillusionment, known as "AI winters," due to unmet expectations.
In the contemporary era, AI manifests across a diverse spectrum of applications, including but not limited to, machine learning, natural language processing, and autonomous systems, exemplified by virtual assistants (like Siri and Alexa), personalized recommendation engines (as seen on Netflix and Amazon), and self-navigating vehicles.
Generative AI, a subset of AI, focuses on creating new content or data that is similar but not identical to existing data. It involves algorithms that can generate text, images, videos, and music that resemble human-like creativity. Tools like GPT (Generative Pre-trained Transformer) and DALL-E are prominent examples, showcasing the ability of AI to produce novel content based on learned patterns and data.
For a comprehensive list of terms, visit the Glossary of Terms tab.