Artificial intelligence (AI) and the library

Ideas for how AI can be useful, from March 2023.

An overview for general readers on how this generative AI chatbot works.

A more in-depth look at how ChatGPT creates text.

"AI is based on algorithms that respond to models and data, and often misses the big picture and most times can’t analyze the decision with reasoning behind it. It isn’t ready to assume human qualities that emphasize empathy, ethics, and morality."

"The impact of AI could be significant, with industries ranging from: finance, healthcare, manufacturing, retail, supply chain, logistics and utilities, all potentially disrupted by the onset of AI technologies."

Start by Sharing These Guidelines with Your Class

Basic guidance for students, but check with your instructor for each class.

The study showed that digital natives are not familiar with educational technologies.

Resources for teaching about AI, aimed at high school students.

Learning activities aligned with the ACRL Information Literacy Framework.

Overview of studies that show AI-associated vocabulary is increasingly used in scholarly papers.

Over 100 sample syllabus policies on use of AI in coursework.

Padlet collecting many university policies.

An interactive tool for developing syllabus statements on generative AI.

Outlines nine areas of ethical concern around AI.

"While AI is often thought of as human-free machine learning, the technology actually relies on the labor-intensive efforts of a workforce spread across much of the Global South and often subject to exploitation."

"The part that artificial intelligence plays in climate change has come under scrutiny, including from tech workers themselves who joined the global climate strike last year. Much can be done by developing tools to quantify the carbon cost of machine learning models and by switching to a sustainable artificial intelligence infrastructure."

"A new tool lets artists add invisible changes to the pixels in their art before they upload it online so that if it’s scraped into an AI training set, it can cause the resulting model to break in chaotic and unpredictable ways."

"Use that’s fair in a personal or academic context may not be fair if it is practiced on a commercial scale."