48 Principles for Using AI in the Classroom and How to Acknowledge It

This chapter offers a practical guide to navigating AI in both your college courses and your future career. Whether you’re excited about AI, skeptical of it, or somewhere in between, you’ll need to understand how these tools fit into your academic and professional life.

In this chapter, we’ll cover:

• How AI is changing different career fields, from healthcare to automotive repair
• The different ways you might work with AI (as a “centaur,” “cyborg,” or even a thoughtful “resister”)
• How to follow your college’s AI policies while still building valuable skills
• Clear guidelines for properly citing and acknowledging AI use in your coursework

By the end, you’ll have a clearer picture of how to approach AI tools thoughtfully.

Why do I need to understand generative AI?

College courses aim to provide students with durable skills, meaning those strategies and critical thinking skills that translate most obviously into workplace environments. Today we’re seeing a transformation in professional workflows because of how generative AI (GenAI) and other forms of machine learning can augment what professionals do.

In May 2024, Microsoft reported that GenAI usage doubled in the previous months, “with 75% of global knowledge workers using it.” Those who do say it saves time, focus, become more creative, and make their work more enjoyable. In August 2024, another report showed that 86.5% of employees in some fields used GenAI at work.

Here’s how some work departments are using it, covering a range of backgrounds from marketing and business to STEM-related fields such as computer programming:

• social media content
• planning and building marketing strategies
• search engine optimization (SEO)
• content ideation (brainstorming, etc.)
• writing content
• content research
• bug-fixing and debugging software
• code generation and research
• drafting messages to customers
• analyzing customer feedback

Those in healthcare may think this is all about writing and coding, but AI is transforming the healthcare industry as well. In addition to the above, AI models are now:

• automating documentation;
• helping with data entry and extraction;
• managing communication;
• monitoring regulatory compliance;
• helping with administrative workflows and task prioritization;
• facilitating patient outreach;
• image enhancement for better diagnosis;
• noise reduction and pathology prediction;
• personalized treatment plans;
• clinical support;
• research and development of new drugs.

Perhaps you’re considering something in the trades and think this is all about writing tasks. Not at all. Those in the automotive repair industry, for example, will begin seeing GenAI:

• analyze vehicle data, symptoms, and repair history to suggest potential issues and solutions more accurately;
• interpret complex diagnostic codes and sensor readings;
• analyze images or descriptions of parts to identify them accurately;
• anticipate parts needs based on common repair patterns, improving inventory management;
• create realistic simulations and training scenarios to practice complex repairs;
• help mechanics explain technical issues to customers in simpler terms;
• provide estimated repair times and costs more accurately;
• analyze repair shop data to optimize workflow.

This technology will have some similarities across all industries, especially when producing and analyzing content, but we are also seeing a wide variety of applications as they become adapted to individual professions. Whatever career you’re interested in, it’s worth learning how AI is impacting the field.

Principles for Using AI in the Workplace

Before discussing how to think about GenAI in college, it will help to briefly suggest some strategies for using AI tools effectively in your future career, since you’re preparing precisely for that situation (and many of you are working right now). Below we offer a few straightforward principles for using these tools confidently and responsibly. Note that this chapter assumes you have some familiarity with how LLMs work; if you need to review the limitations and risks associated with GenAI, refer back to that chapter.

Professor Ethan Mollick, who studies how people work with AI in higher education and the workplace, suggests two key principles in his book “Co-Intelligence” that can help you get started:

Principle 1: Invite AI to the Table

AI can often be treated as a crucial resource in your professional toolkit. It’s often like having a really smart assistant. The trick is to get in the habit of asking yourself, “Could AI help me with this task?” The sooner you start practicing with these tools, the more natural they’ll feel to use as they get more advanced.

Principle 2: Be the Human in the Loop

Inviting AI to the table must be coupled with critical awareness. While AI is your assistant, you—the human—need to provide oversight and steering. Unlike a calculator that just gives you math answers, successful and ethical use of AI often requires your judgment and oversight. Depending on the task, you will frequently need to:

• check if its information is accurate (accuracy and hallucinations);
• make sure what it suggests is ethical;
• use your own expertise to decide if its suggestions or outputs make sense (relevance).

Of course, this is also important while you’re in college. You need to build up your own knowledge and skills first. AI should help you apply what you know, not replace your learning. For example, if you’re studying automotive repair, you need to understand how engines work before using AI to help diagnose problems. Or if you’re in healthcare, you need to understand basic medical concepts before using AI to help with patient care. More on that below.

Centaurs, Cyborgs, and Resisters: Understanding Your AI Style

How you use AI may depend on your comfort level. Some people blend AI seamlessly into their work, others prefer a clear boundary between human-created and AI-generated content, others may take a more antagonistic stance towards these tools. Mollick uses the metaphors of centaurs and cyborgs to describe these approaches. We’re adding the third category, resisters.

Centaurs

A centaur’s approach has clear lines between human and machine tasks, like the mythical centaur with its distinct human upper body and horse lower body. Centaurs divide tasks strategically: the person handles what they’re best at while AI manages other parts. Here’s Mollick’s example: you might use your expertise in statistics to choose the best model for analyzing your data but then ask AI to generate a variety of interactive graphs. AI becomes, for a centaur, a tool for specific tasks within their workflow.

Cyborgs

Cyborgs deeply integrate their work with AI. They don’t just delegate tasks, they blend their efforts with AI, constantly moving back and forth between human and machine. A cyborg approach might look like writing part of a paragraph, asking AI to suggest how to complete it, and revising the AI’s suggestion to match your style. [Warning: Cyborgs may be more likely to violate academic integrity so be aware of your instructor’s AI policy. See below for more guidance.]

Resisters: The Diogenes Approach

Mollick does not suggest this third option, but we find that it’s important to recognize that some students and professionals feel deeply uncomfortable with even the centaur approach, and our institution and faculty will support this preference as well. Not everyone will embrace GenAI. Some may prefer to actively resist its influence, raising critical awareness about its limitations and risks. Like the ancient Greek philosopher Diogenes, who made challenging cultural norms his life’s work, Resisters might focus on warning others about AI’s potential downsides and advocating for caution in its use. Of course, those taking this stance should understand the tool as well as centaurs and cyborgs. In fact, Resisters may need to study these tools even more deliberately.

It’s not practical to identify always as a cyborg, centaur, or resister. These are styles of interacting with an emerging technology, not identities. The most sophisticated cyborgs will occasionally become centaurs, sometimes even resisters when the situation calls for it. Likewise, someone who feels more attracted to the resister mode will have to grok what it means to be a cyborg or centaur if they intend to offer critical guidance to others.

Principles for Using AI in the Classroom

Educational environments foster durable skills that prepare you for workplace and lifelong success. However, there is a key difference between these environments: as you’re learning certain skills, instructors need to be able to assess the choices you’re making, often under challenging circumstances, to offer guidance about how to succeed.

This means instructors must be able to see the labor—the choices a student made in order to figure out how to respond to a challenge. This usually requires effort, what some like to call “friction,” and it’s often uncomfortable at first. It also takes time. GenAI can often reduce that friction and it feels so easy to outsource your thinking and time (the fancy term is “cognitive offloading”).

Why instructors want to see your work

It’s true, to a certain extent, that computer programmers can program with words and increasingly rely on higher-order thinking rather than just typing out routine functions again and again (see: Cursor, Replit, and other software that can build entire apps and websites with simple prompts). Many operations are becoming higher-order. But accessing those higher-order ways of thinking (prompting with models and concepts in mind) is what you need to acquire proficiency in first. It’s why you’re in college. Without those tools and frameworks, you’ll be as replaceable as another worker who can type things into a chatbot. But with those tools and the comfort of working with them in challenging environments, you will better unlock the potential of AI. It’s hard to overemphasize how important this basic concept is: relying too heavily on AI during parts of your college workflow and learning can lead to your own “deskilling” through cognitive offloading. But using these tools in certain parts of your workflow can also boost learning.

What it takes to comprehend (and not just vaguely recognize) the concepts and models taught in each course often requires wrestling with challenges unassisted by AI. On the other hand, sometimes—and at certain parts of your course workflow—assistance can be incredibly effective. Your instructor may ask you to practice the rhetorical appeals with a custom AI chatbot, for example, before demonstrating your proficiency by drafting an essay unassisted. It’s increasingly common for higher ed instructors to build AI assistance within their course expectations but also expect unassisted work at certain points. It’s your job as a student to remain aware of their course and assignment expectations regarding AI. If you’re not sure, ask.

Higher education is beginning to adjust to this new world in which chatbots can help students at any moment. These tools may help reduce the amount of busy work you feel in the classroom; no one enjoys struggling with tasks they find unenjoyable or meaningless. At the same time, you will be expected to demonstrate what choices you’ve made in order to solve certain challenges, that will sometimes take work and struggle, and course policies and sanctions are there to provide guardrails to ensure you’re prepared for greater challenges ahead.

Understanding AI Syllabus Policies

This final section offers guidance on how to understand AI course policies at CWI. There are three options that your instructors choose from: 1) most restrictive, 2) moderately restrictive, and 3) least restrictive. In each part below, you will find the official language followed by some guidance on how to interpret what’s allowed and what’s prohibited. Note that any use of GenAI that impacts a submission must be accompanied by an acknowledgement statement.

Acknowledging and Citing Generative AI (GenAI) in Academic Work

This final section offers guidance on how to acknowledge and cite GenAI when it impacts something you submit in a course. AI Acknowledgement Statements are increasingly an expectation in many courses and professional environments. At CWI, it’s essential to include these statements in order to comply with academic integrity.

Monash University provides helpful recommendations for how to acknowledge when and how you’ve used generated material as part of an assignment or project. If you decide to use generative artificial intelligence such as ChatGPT for an assignment, it’s a best practice to include a statement that does the following:

• Provides a written acknowledgment of the use of generative artificial intelligence.
• Specifies which technology was used.
• Includes explicit descriptions of how the information was generated.
• Identifies the prompts used.
• Explains how the output was used in your work.

The format Monash University provides is also helpful. Students can include this information either in a cover letter or in an appendix to the submitted work. Your instructor may provide more guidance on where to include the acknowledgement statement.

Academic style guides such as APA already include guidelines for including appendices after essays and reports. Review Purdue Owl’s entry on Footnotes and Appendices for help.

A Checklist for Acknowledging Generative A.I. (GenAI) Tools

Liza Long developed the following checklist to provide guidance on using and acknowledging AI in a course:

1. Check with your instructor to make sure you have permission to use these tools.
2. Reflect on how and why you want to use generative artificial intelligence in your work. If the answer is “to save time” or “so I don’t have to do the work myself,” think about why you are in college in the first place. What skills are you supposed to practice through this assignment? Will using generative artificial intelligence really save you time in the long run if you don’t have the opportunity to learn and practice these skills?
3. If you decide to use generative artificial intelligence, acknowledge your use, either in an appendix or a cover letter.
4. Always check the information provided by a generative artificial intelligence tool against a trusted source. Be especially careful of any sources that generative artificial intelligence provides.

References

Monash University. (n.d.). Acknowledging the use of generative artificial intelligence. https://www.monash.edu/learnhq/build-digital-capabilities/create-online/acknowledging-the-use-of-generative-artificial-intelligence