A Few Reading Notes

Conversations with Large Language Models

Periodically throughout this textbook, we have interactions with artificial intelligence (AI) tools. For clarity purposes, we will often use our versions of company logos to illustrate who engaged in the conversation and with which AI Tool. Mostly, we rely on the three primary foundation models at the time we dove into this project:

• Anthropic’s Claude
• Google’s Gemini
• X’s Grok
• Meta’s Llama
• OpenAI’s ChatGPT

We use the logos to show their un-edited responses. Please note that these are variations of their logos and not the company’s actual logos. In addition to using the logos, we also have pictures of ourselves with the interactions to make it clearer who is writing within the text with these conversations:

• Dr. Sanae Elmoudden
• Dr. Jason S. Wrench

Figures and Images

When thinking through the images we have used in this book, we wanted to ensure that the book was true to the world of AI but also remained a traditional textbook feel. For this reason, we have included Figures and GenAI Art (Generative AI Art). Figures are either actual photographs that we have used with a license appropriate for this book or figures that were created by the authors using traditional art software (primarily Adobe Illustrator or Photoshop). GenAI Art, on the other hand, are designated as such because some form of text-to-image software generates them. We use a range of different text-to-image generators within this text, but you can learn which one we used in the description and licensing behind each image.

You may be wondering why it matters. As of right now (early 2025), the U.S. Copyright Office has offered guidance on what is copyrightable and what is not related to text-to-art end products.^[1] As of right now, Figures can be licensed under existing copyright like we have done here. GenAI Art cannot be licensed because it cannot have a copyright. This legal differentiation between the two may change in the future, but this is how it stands right now.

A Note on Our Use of Generative AI

In writing this book on AI literacy, we found ourselves in a unique position: discussing tools that could also help create the work itself. We believe transparency in our process is essential in a text focused on developing a critical understanding of these technologies.

Throughout the development of this book, we employed various generative AI tools to enhance our writing process. These tools served as collaborators in several ways:

• Outlining chapters and structuring complex ideas
• Generating illustrative case studies and examples
• Helping define technical terminology in accessible language
• Breaking down complicated technical concepts into more digestible components
• Editing our work once we had drafted something in Word or other apps before it was placed into Pressbooks

We used multiple generative AI platforms throughout our work, allowing us to experience and showcase the strengths and limitations of different systems. Where specific AI tools were utilized, we’ve made efforts to identify them clearly. For instance, all AI-generated images in the book include metadata showing the specific model used in their creation. Similarly, the transcribed conversations with various AI models that appear in the text are identified as such.

It would have been paradoxical to write a book about AI literacy without engaging with the very tools we discuss. However, we want to emphasize that although generative AI played a supporting role in our process, the final product represents our vision, expertise, and judgment. Every AI-generated element was critically evaluated, often extensively revised, and ultimately shaped by our perspectives and standards. Just as we don’t exhaustively catalog every research database or editing software used in our process, we haven’t documented every instance of AI assistance—such documentation would be impractical and would detract from the content itself.

The text you are reading is not a compilation of AI outputs, but rather a work that used these technologies as tools within a larger human-directed creative and intellectual process. The analysis, arguments, and educational approach reflect our own thinking and pedagogical goals. In an age where the boundaries between human and machine-generated content can blur, we believe this kind of transparency about process is not just ethical but essential to the very AI literacy we hope to foster.

Acknowledgments

This book represents the culmination of a year’s worth of research, writing, and collaborative effort. Such an undertaking would not have been possible without the support and contributions of many individuals and institutions.

First and foremost, we wish to express our profound gratitude to our families, whose patience, understanding, and encouragement sustained us throughout this intensive writing process. The countless hours spent researching and drafting often came at the expense of family time, and their unwavering support made this work possible.

We are indebted to our colleagues at SUNY New Paltz and St. John’s University. The intellectual community, constructive feedback, and institutional support provided by these academic homes have been invaluable. Special thanks to the faculty and staff who engaged with our ideas, challenged our thinking, and created the supportive environment necessary for this project to thrive. And thank you for listening to all our ramblings about AI over the past few years.

We extend our sincere appreciation to Allison Brown and the entire team at Milne Publishing for believing in this project and providing us with the platform and freedom to explore this evolving field. Their commitment to open educational resources and willingness to support innovative projects like this one show their dedication to advancing accessible education in emerging areas of study.

This book would not exist without the groundbreaking work of the AI researchers, developers, and thought leaders who have pushed the boundaries of what’s possible. Their innovations have not only given us fascinating tools to analyze but have reshaped how we think about technology, creativity, and human-machine collaboration. While too numerous to name, we are grateful to all those in the AI community whose work has inspired, challenged, and informed our thinking.

We thank our students, whose curiosity, questions, and engagement with these technologies remind us why AI literacy matters. Their perspectives informed this book’s creation, and this project celebrates them.

Jason S. Wrench, SUNY New Paltz

Sanae Elmoudden, St. John’s University

Dedication

To the visionaries and pioneers of artificial intelligence—from Alan Turing and John McCarthy to Marvin Minsky and beyond—whose foundational work, bold imagination, and relentless curiosity opened pathways that seemed impossible only decades ago.

Your dreams have become our reality. Your future is our reality.