Introduction

Learning Objectives

1. Understand the social and educational context of the chapters of this book.

2. Explain why ethics is important when discussing GenAI Tools.

3. Explain the difference between commercial and open technologies.

Introduction (Meta-Introduction, if you will)

You walk onto campus (or log onto Canvas, if you are in an online class) on the first day of the semester. You have anxiously been awaiting the start of this course because you heard that the content was exciting and the teacher was engaging. Additionally, you are eagerly anticipating the vibrant and energetic discussion you and your classmates have during class. You are excited to learn anything you can in this course because it is fundamental to your career path.

After you settle in (or start scrolling on the syllabus), you notice something. Your instructor has an entire section on Generative AI use. For such an important class, you are surprised and bewildered that your teacher not only supports Generative AI tools, but has guidelines on how to use them. You thought that using Generative AI tools in any way constituted cheating. After all, what about the many issues surrounding Generative AI? And other teachers in previous courses took a hard line against it! Has this teacher gone soft? How are you going to know that your classmates are using AI according to your instructor’s guidelines? How are you going to know that you are using AI ethically?

This book is meant to answer some of these questions.

How This Book Came to Be

Laurie Bridges from Oregon initiated the creation of this textbook to address the urgent need for an accessible Open Educational Resource (OER) on AI and Ethics for undergraduate students. This project quickly attracted twelve diverse authors from around the globe, all bringing unique perspectives on artificial intelligence and its ethical implications in education. This collaborative effort ensures a comprehensive exploration of AI's ethical dimensions, enriching the textbook with a wide array of insights.

My academic journey is deeply rooted in the principles of information literacy, where I see generative AI as both a significant asset and a substantial ethical challenge. From my perspective, generative AI offers incredible opportunities for innovation in data and information management. At the same time, the multitude of generative AI tools in the world presents complex ethical dilemmas that require careful consideration and responsible handling.

Why the Emphasis on Ethics?

Ethics can be a complicated subject. Whenever you read a novel about corporations or nation-states, ethics are seen as an idea that is shunned because it is not realistic. Every person wants to be ethical, but we all fall short. So, why bother?

In my personal life and the work that I do for other people, I try to eschew virtue-based assignations of my work and my tools. I do not want an Ethical Guide to Research. I want a Guide to Research that I can use ethically. I do not want a Best Practices-based Archival Management presentation. If the Archival Management presentation is truly based on best practices, that should be self-evident. It should not have to be in the title. 

In the same way, ethics should not be a unilateral standard, the end goal of all of our work. Instead, it should be a way of working. It should influence the style, tone, and content of our work. This is why I support this book on Ethics and AI in Higher Education. When you know the implications of ethics on generative AI, including some unethical aspects of generative AI use, you will be able to make informed decisions and alter your practices accordingly.

One of my foundational principles for my projects in digital initiatives in libraries and technology integration in education is that all of these should be oriented toward humans. To put it concisely, technological success is not about the technology. It is about the user. By the same token, ethical issues do not only put responsibilities on corporations or on artificial tools. The user is responsible for being informed about the ethics of certain tools. They are also expected to use ethical practices and workflows when creating projects. Ethics should not be ignored because they are lofty. Acting according to ethical principles is part of every person's responsibility to each other. 

A Comprehensive Treatment of Ethical Use of AI in Higher Education

Rather than having discrete chapters with little or no relation to each other, each chapter has been designed to work with the rest. All authors wrote their chapters knowing what the other authors would be writing. In this way, they could make sure that their chapters meshed well without overlapping in their content.

Additionally, it provided a way for the chapters to be divided into several broader categories. Hopefully, the coverage of each of these categories will provide a comprehensive discussion of the importance of ethics related to AI tool use in higher education.

I. Foundations of AI and Ethics

In order to understand how ethics and AI intersect, you first must have at least a basic knowledge of what AI and ethics are. It is assumed that the reader may have a basic use history of generative AI tools, but if you do not, that is not a problem. Even if you have used generative AI tools before, you may not know the machinations behind its functions. Therefore, the first few chapters of this book will emphasize the nature of AI and its ethical considerations. It will discuss the basic principles of generative AI and their ethical implications. This will set us up for the next section, which will discuss the ethical implications of the integration of AI into multiple settings, including education and the workforce.

II. Ethical Considerations in AI Deployment

The second section of this book addresses concepts such as confidentiality laws and best practices, privacy concerns about data and conversation content, and the necessity of data protection, both in AI systems and through proactive actions on the part of the user.

While recognizing the need for generative AI innovation, this section will seek to describe a balancing act. The push for change and advancement, particularly in regards to a relatively new technology, should be met with the imperative of ethical AI use in all environments. This means that not only should the creator act ethically, but also should all of the users of AI tools. The last chapter in this section will describe the fundamentals of digital literacy and explore how they can be implemented in ethical and informed AI engagement.

III. Perspectives on AI and Ethics

The third section of this book will focus on examples and quasi-”case studies” from students and faculty. This section will demonstrate how students can collaborate with their educators so that all AI tools are used ethically and responsibly. Separate chapters will consider both of these groups’ insights on the ethical use of AI and its impact on their educational experiences. Hopefully, they will give you some inspiration as to how you can use artificial intelligence while still upholding academic integrity.

Another chapter will discuss how administrators view and support ethical AI practices within educational institutions. It will explain how, why, and in what context academic institutions’ policies regarding AI use are created. 

IV. Institutional Response and Policy Development

Section four will discus developing and scaling AI training for faculty. This may seem to be a strange chapter in a book for students on using AI in their educational endeavors, but hopefully knowledge about how educators are trained can help you see their perspective and priorities when making decisions regarding AI use in courses.

Many policies are created with the origins and development of AI technologies in mind. For example, some institutions refuse to use a particular tool because they have serious qualms about the ethical implications of how that tool was created. This is not because they believe that those who use tool are unethical, but only that they believe the data recorded in the tool was gathered using unethical means. Appendices

After the chapters in this book come the appendices. The first two appendices will be simple lists of tools and workflows you can use to guide the ethical implementation of AI in education. The tools and workflows in these appendices can all be used for free. They are either open access, open source, or have free tiers that have a wide range of capabilities for the foreseen future. Only companies that are responsible for their users in this manner have been included in these appendices.

Open AI (vs. OpenAI)

One of the most frustrating parts of this moment in educational history is the fact that it is being led by an organization whose name is misleading about its current intents, purposes, and processes. When OpenAI was founded, it was a non-profit organization that explored the implications of many types of AI tools for the public good. It collaborated with many organizations, including Microsoft, to formulate potential products for a variety of modalities and media, including music, images, and text.

However, it eventually became a for-profit company around the same time that Dall-E 1 came out. The board of the organization realized that with the amount of public interest in their product, they could easily charge for access and make a lot of money. They became further entrenched in the for-profit sector when they created a paid tier of ChatGPT.

One of my commitments to those whom I advise regarding AI toolis that the cost will be as little as possible. For some projects or uses, that means buying a $20/month ChatGPT Pro subscription. But for many other people, the products and workflows they want to facilitate can be easily provided using free or open AI tools. My emphasis is to provide ethical, affordable, equitable, and inclusive AI products, tools, services, and consulting advice. 

“Open AI” as a product or service does not have a broad or accepted definition. However, it is a concept that we should be considering. Open source AI, free AI, and commercial AI products that offer viable free tiers should be used, especially in educational contexts, before commercialized AI products that often focus on capitalizing on the hype and do not fulfill their promises. Often, a highly-skilled user can create higher-quality products than commercial “fine-tuned” AI tools by simply using best practices prompt engineering and a well-configured workflow of open and free AI tools.

Chapter Structure

Before we continue on to the actual content of the book, let us explore the structure and main themes of the book. First of all, the focus of this book is the ethics of using AI tools in education. Notice that the focus is not “How to convince students and teachers to use AI in education.” Nor is it, “Why AI is unethical in education or the workplace.” We neither want to support or speak against the use of AI in higher education. Instead, we would like to present facts for you to create your own understanding.

Each of these chapters were created by focusing on a problem that the author could see in their line of work or their chosen perspective. The text, examples, resources, and theories proposed in each chapter were specifically selected to help the reader resolve that problem. After each chapter, a set of discussion questions selected by the author and reviewers will provide the opportunity for readers to consider the central ideas. They may also help the reader examine how to use these ideas in their work and projects.

While we would like this to be a formal-sounding textbook, we also want this book to be a useful source of information. Therefore, we will start each chapter with a scenario that will illustrate that chapter’s main issues. We will also try to use as straightforward language as possible. While technology necessarily has some complex ideas, we will take the time to explain each component of each type of tool, product, and workflow. In this way, all readers will be able to confidently follow a clear ethical process or roadmap for many scenarios and tools they will encounter in their educational and workplace careers.

To further assist in comprehension and preparedness for application of these principles, each chapter will include as many references and examples as possible. There are many examples of each principle, but we will try to provide the most explanatory and typical examples.

Finally, much of the learning that occurs when reading textbooks occurs outside of the text of the book itself. Thinking on, and applying, the content in the book requires some consideration of how you can best apply the ideal concepts described in the book to your current situation. This may necessitate some compromise or some alterations to provide the ideal qualities in your workflow. For example, if one of our suggestions does not align with an institutional policy, you may or may not have to change their actions or tools to fit that policy. With the plethora of free and open access generative artificial intelligence tools available to the public, your possible courses of action are quite varied. Always follow institutional policies, and state and federal laws, if they conflict with our suggestions.

Disclosure of Generative AI Use

With the strength of our opinions and our knowledge about the integration of generative artificial intelligence into education, the reader should not be surprised that we are all quite adept at utilizing it ethically. Each of our institutions has its own generative AI policy. Furthermore, while there are recommendations and best practices, AI-Infused Higher Education is a relatively new phenomenon. Thus, the “best practices” recorded in this book can more appropriately be called “good faith” or “well-intentioned” practices. There are multiple philosophies and perspectives, even among proponents of AI in education, that can lead to different workflows and priorities when working with AI. Therefore, you should not judge another user’s well-intentioned and transparent use of generative AI, as long as that use is ethical.

That being said, each of the authors in this book has used generative AI in some form for the creation of their chapter. If we have not used it for the text, we certainly have used it for images, data processing, researching, experimentation, or any other type of information processing, ingesting, arranging, or presenting. As you read this book, you may see phrases highlighted in pop-up boxes with probable definitions. This is also powered by artificial intelligence. When you do write-ups or create question responses, you may have writing suggestions given to you by artificial intelligence. These are all illustrations of how even when you are trying your hardest, there is no way to completely escape the presence of generative artificial intelligence.

Each chapter will include a disclaimer of how the author(s) utilized generative AI and other tools to create their chapter’s content. Here is my disclaimer: I used ChatGPT to create the outline for this chapter. However, only two of the resulting outline headers remained in the chapter. Furthermore, I added two or three headers after the tool was done. I also used generative AI to create the first drafts of the assignment prompts below.

Discussion Questions

1. Evaluate the impact of AI on privacy within educational environments, considering both benefits and risks.
2. How can digital literacy among students and faculty be enhanced to promote ethical AI usage?
3. Analyze a case study of AI-enhanced learning, focusing on the ethical considerations addressed.
4. Design a policy proposal to ensure academic integrity in the context of AI-assisted assignments.