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,” and 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 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
• proofreading
• bug-fixing and debugging software
• testing code snippets
• 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;
• data augmentation;
• noise reduction and pathology prediction;
• personalized treatment plans;
• clinical support;
• research and development of new drugs.

Even more hands-on patient help, such as the tasks normally undertaken by nurses and other practitioners, is becoming transformed by GenAI, including:

• patient data analysis;
• predicting potential complications;
• real-time suggestions for interventions and medication dosages;
• documentation assistance, including clinical notes from voice recordings and summarizing patient interactions;
• simulating patient scenarios for training;
• patient communication, including real-time translation services;
• generating personalized patient education materials.

What about those in Career and Technical Education? It will also be transformative, though in very different ways. Those in the automotive repair industry 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 (helping with customer communication and outreach, for example), 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 might help you do your job better in the future.

Principles for Using AI in the Workplace

Let’s discuss how to use AI tools effectively in your future career. Think of these as your ground rules for working with AI–straightforward principles that can help you use these tools confidently and responsibly.

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

Principle 1: Invite AI to the Table

Think of AI as another tool in your professional toolkit–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. Like driving, at first it feels overwhelming, but with practice, it becomes second nature.

Principle 2: Be the Human in the Loop

Here’s the most important part: while AI is your assistant, you’re always the boss. Unlike a calculator that just gives you math answers, AI needs your judgment and oversight. You need to:

• Check if its information is accurate
• Make sure what it suggests is ethical
• Use your own expertise to decide if its suggestions or outputs make sense

This is especially 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.

AI is like having a very knowledgeable intern: helpful, but you need the expertise to know when they’re right or wrong. That’s why your coursework (that laborious stuff you sometimes won’t feel like doing) matters; it builds the foundation you need to use AI effectively in your career.

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, and 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 a course’s AI policy so be aware of your instructor’s preferences!

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 AI. 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, you 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 AI tools even more deliberately.

It’s probably 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.

Unlike most workplace scenarios, classroom environments want to assess student learning so they’re prepared for the future. This means instructors must be able to see the labor—i.e., 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.

But what’s becoming clear is that using AI effectively requires human input on many different levels (remain the human in the loop), and, if you want to be successful in the future, the difference between you and someone you’re competing with will be how much base knowledge + AI savviness you have when problem-solving. The base knowledge part requires a deep familiarity with the models and concepts relevant to that domain—and this is what your instructors want to help you with. It’s true, to a certain extent, that computer programmers for example can “program with words” and increasingly rely on higher-order thinking rather than just typing out routine functions again and again. 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. 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.

The difference between a model or concept in each course vs. busy work will sometimes be obvious, but at other times it won’t. In a math course, understanding how basic algorithms and matrices work, for example, is incredibly important for understanding how machine learning works and provides insight into a completely different way of processing information, which in turn will allow you to prompt AI in powerful ways. In a writing course, knowing there are such things as the rhetorical appeals and different genres is a massive unlock for many things. In a philosophy course, you become more aware of the ethical frameworks companies use to align AI, and you learn what ideas and concepts are relevant when asking whether an output is ethical.

Higher education is beginning to adjust to this new world in which chatbots can help students at any moment. This may help reduce the amount of busy work you feel in the classroom. At the same time, you will be expected to demonstrate what choices you’ve made in order to solve certain challenges, that will take work and struggle, and course policies and sanctions are there to provide guardrails to ensure that happens.

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 incredibly important 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