Teaching with AI
Authors: José Antonio Bowen, C. Edward Watson, José Antonio Bowen, C. Edward Watson
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Overview
This book explores the transformative impact of AI on higher education, focusing on the practical implications for faculty and students. It aims to equip readers with the knowledge and strategies to navigate the rapidly changing landscape of AI in teaching, learning, and academic work. Our target audience includes college and university faculty, instructional designers, administrators, and anyone interested in understanding how AI will change human thinking, reshape the future of work (especially for new graduates), and transform education. The book’s relevance stems from the urgent need to address the challenges and opportunities presented by the rise of AI in education. We offer a framework for understanding how AI works, how to leverage it effectively, and how to mitigate its potential downsides, particularly concerning issues like cheating and bias. It emphasizes the development of AI literacy as a core skill for both faculty and students, preparing them for a future where collaboration with AI will become essential. We argue that instead of resisting AI, educators should embrace it as a tool to enhance teaching, personalize learning, and support student success. The book offers practical guidance on redesigning assignments, assessments, and grading rubrics to account for the capabilities of AI and to prioritize human-centric skills and knowledge. We also suggest strategies for promoting academic integrity in the age of AI, fostering creativity, and leveraging AI for feedback and role-playing. It recognizes the anxieties surrounding AI and provides concrete steps for educators and students to adapt to this new era. It ends with a challenge to reimagine education for a future where humans and AI collaborate to enhance human thriving. It provides specific examples and templates to get faculty started working with and understanding current AI.
Book Outline
1. AI Basics
AI, like the internet before it, has the potential to revolutionize everything. While the internet changed our relationship with knowledge, AI will change our relationship with thinking. It’s crucial to consider how AI develops to mitigate potential negative consequences.
Key concept: AI is one of the most important things humanity is working on. It is more profound than electricity or fire.
2. A New Era of Work
AI is changing the nature of work across various sectors, impacting white-collar jobs significantly. Those who can effectively work with AI will have a significant advantage in the future job market. AI will likely change every job, not just eliminate them. This includes higher education.
Key concept: See the patient, not the technology.
3. AI Literacy
AI literacy involves problem formation, asking better questions, and iteration. These skills are essential for leveraging AI effectively and are at the core of a liberal arts education.
Key concept: If I had an hour to solve a problem and my life depended on it, I would use the first 55 minutes determining the proper question to ask.
4. Reimagining Creativity
AI can enhance human creativity by generating numerous ideas quickly and without inhibition. It’s important to embrace the process of ideation and collaboration with AI to maximize its creative potential.
Key concept: It’s like collaborating with an alien.
5. AI-Assisted Faculty
AI can assist faculty with tasks like research, writing, interfacing with students, classroom discussions, and designing new assignments, allowing them to focus on higher-level tasks and customization.
Key concept: So you can do more of what AI can’t.
6. Cheating and Detection
Cheating with AI is a significant concern, and while detection tools exist, their accuracy is variable and raises ethical and equity issues. AI detection is an arms race and easily bypassed.
Key concept: This is the worst AI will ever be.
7. Policies
Effective AI policies should promote AI literacy, address equity, and be grounded in shared values and learning goals rather than focusing solely on prohibition and policing AI’s use.
Key concept: Hybrid writing . . . will be the norm. Trying to determine where the human ends and where the artificial intelligence begins is pointless and futile.
8. Grading and (Re-)Defining Quality
Grading needs to be rethought in the age of AI, shifting focus towards higher-order thinking and recognizing work that goes beyond AI’s capabilities. C-level work is what AI can do now. What are we teaching students to do that is better than C work?
Key concept: Quality also marks the search for an ideal after necessity has been satisfied and mere usefulness achieved.
9. Feedback and Roleplaying with AI
AI can be used for feedback, role-playing, and tutoring, offering students personalized support and creating opportunities for more engaging learning experiences.
Key concept: Admitting mistakes is a fundamental skill too few of us learn. In part, this is because we’ve been taught it’s wrong to be wrong.
10. Designing Assignments and Assessments for Human Effort
Assignment design should motivate human effort by focusing on purpose, self-efficacy, and agency. Clarity, checklists, and feedback mechanisms can guide students and increase learning.
Key concept: Don’t let what you cannot do interfere with what you can do.
11. Writing and AI
AI’s impact on writing necessitates a focus on the process of writing, utilizing tools like version history and requiring drafts. Assignments should emphasize the human element, like local, unique, and personal experiences, as well as critical thinking and ethical considerations.
Key concept: There is no hiding the fact that writing well is a complex, difficult, and time-consuming process.
12. AI Assignments and Assessments
AI can enhance a wide range of assignments and assessments, from presentations and creative projects to more complex tasks like game design and field research. All assignments should teach AI literacy.
Key concept: We surpass the AI by standing on its shoulders.
Essential Questions
1. How does AI compare to the internet in its transformative potential, and what key lessons can we learn from the rise of the internet?
AI’s transformative potential is immense, impacting all aspects of life, including higher education. This book argues that AI’s impact on thinking is analogous to the internet’s impact on knowledge. It compels us to consider how AI’s evolution will reshape education, work, and even our understanding of creativity. The book emphasizes learning from the internet’s rise, highlighting the need to anticipate rapid changes and interconnectedness to navigate AI’s trajectory effectively.
2. How is AI reshaping the future of work, and what skills will be essential for success in this new era?
The future of work is rapidly changing due to AI. This book highlights how AI is impacting white-collar professions, altering job requirements, and emphasizing the need for AI literacy. It raises critical questions about job security, the development of human-AI collaboration skills, and the implications for education and training. It suggests that all jobs will change and that those who cannot think with AI will be at a significant disadvantage.
3. What constitutes AI literacy, and how does a liberal arts education prepare individuals for it?
AI literacy is not just about technical understanding but involves critical thinking, problem-solving, prompt engineering, and iteration. This book argues that the liberal arts play a crucial role in cultivating these skills, emphasizing the importance of asking better questions and adapting to new information. Better questions are how AI will enable better human thinking.
4. How can AI enhance and challenge human creativity, and what are the implications for education and the arts?
AI can significantly augment human creativity, and this book encourages educators and students to embrace this potential. It challenges traditional notions of creativity, highlights the value of AI’s uninhibited idea generation and its ability to push boundaries, and explores how AI can facilitate new forms of creative expression. AI enables the divergent thinking part of the creative process, forcing humans to curate better and make better decisions.
5. How should grading and our definition of quality evolve in response to AI’s ability to perform college-level work?
AI-driven automation and personalized feedback require a reassessment of grading and quality. This book suggests moving beyond AI-level (C-work) by focusing on higher-order thinking skills, unique human insights, and deeper analysis. It emphasizes defining clear criteria for evaluating student work that distinguishes human capabilities from AI outputs and then guiding students to reach those higher levels of thinking.
1. How does AI compare to the internet in its transformative potential, and what key lessons can we learn from the rise of the internet?
AI’s transformative potential is immense, impacting all aspects of life, including higher education. This book argues that AI’s impact on thinking is analogous to the internet’s impact on knowledge. It compels us to consider how AI’s evolution will reshape education, work, and even our understanding of creativity. The book emphasizes learning from the internet’s rise, highlighting the need to anticipate rapid changes and interconnectedness to navigate AI’s trajectory effectively.
2. How is AI reshaping the future of work, and what skills will be essential for success in this new era?
The future of work is rapidly changing due to AI. This book highlights how AI is impacting white-collar professions, altering job requirements, and emphasizing the need for AI literacy. It raises critical questions about job security, the development of human-AI collaboration skills, and the implications for education and training. It suggests that all jobs will change and that those who cannot think with AI will be at a significant disadvantage.
3. What constitutes AI literacy, and how does a liberal arts education prepare individuals for it?
AI literacy is not just about technical understanding but involves critical thinking, problem-solving, prompt engineering, and iteration. This book argues that the liberal arts play a crucial role in cultivating these skills, emphasizing the importance of asking better questions and adapting to new information. Better questions are how AI will enable better human thinking.
4. How can AI enhance and challenge human creativity, and what are the implications for education and the arts?
AI can significantly augment human creativity, and this book encourages educators and students to embrace this potential. It challenges traditional notions of creativity, highlights the value of AI’s uninhibited idea generation and its ability to push boundaries, and explores how AI can facilitate new forms of creative expression. AI enables the divergent thinking part of the creative process, forcing humans to curate better and make better decisions.
5. How should grading and our definition of quality evolve in response to AI’s ability to perform college-level work?
AI-driven automation and personalized feedback require a reassessment of grading and quality. This book suggests moving beyond AI-level (C-work) by focusing on higher-order thinking skills, unique human insights, and deeper analysis. It emphasizes defining clear criteria for evaluating student work that distinguishes human capabilities from AI outputs and then guiding students to reach those higher levels of thinking.
Key Takeaways
1. AI Enhances Human Creativity
AI augments, not replaces, human creativity. While AI excels at generating numerous ideas, human judgment and critical thinking are crucial for refining, selecting, and implementing the best solutions.
Practical Application:
In product design, involve AI early for brainstorming and generating diverse ideas, but human designers make critical decisions regarding feasibility, aesthetics, and user experience. AI can create the initial iterations but humans define what better looks like.
2. Human Expertise Remains Essential
AI can automate routine tasks, but human expertise remains crucial for complex problem-solving, critical thinking, and decision-making.
Practical Application:
A manager uses AI tools to summarize reports, analyze data, and schedule meetings, but focus on higher-level tasks like strategic planning, team building, and creative problem-solving that require uniquely human skills.
3. AI Literacy is a Core Skill
AI literacy is a crucial skill for navigating the future. It involves understanding AI’s capabilities, limitations, and societal impact, preparing individuals for a world where AI is ubiquitous.
Practical Application:
Educational institutions should incorporate AI literacy training across disciplines, emphasizing critical thinking, ethical considerations, and the ability to use AI responsibly in any context, both academic and professional.
4. Focus on Process, Not Just Product
Focus on the process of learning and doing, not just the product. This book suggests structuring assignments to promote active learning, critical thinking, and engagement, reducing the temptation for students to rely solely on AI.
Practical Application:
Design assignments that emphasize personalized learning experiences, including personal reflections, unique problem applications, ethical considerations, and real-world problem-solving, to increase student engagement and make cheating less appealing.
5. Thoughtful AI Policies are Needed
Rather than simply banning AI, we need to develop thoughtful, transparent policies that promote its ethical and responsible use. Policies should guide effective AI use, not just police cheating.
Practical Application:
Colleges and universities should establish policies that promote AI literacy and outline acceptable uses of AI. Policies should be transparent and student-centered and reflect what is happening in the workplace. Policies should emphasize learning and AI literacy as the primary goal.
1. AI Enhances Human Creativity
AI augments, not replaces, human creativity. While AI excels at generating numerous ideas, human judgment and critical thinking are crucial for refining, selecting, and implementing the best solutions.
Practical Application:
In product design, involve AI early for brainstorming and generating diverse ideas, but human designers make critical decisions regarding feasibility, aesthetics, and user experience. AI can create the initial iterations but humans define what better looks like.
2. Human Expertise Remains Essential
AI can automate routine tasks, but human expertise remains crucial for complex problem-solving, critical thinking, and decision-making.
Practical Application:
A manager uses AI tools to summarize reports, analyze data, and schedule meetings, but focus on higher-level tasks like strategic planning, team building, and creative problem-solving that require uniquely human skills.
3. AI Literacy is a Core Skill
AI literacy is a crucial skill for navigating the future. It involves understanding AI’s capabilities, limitations, and societal impact, preparing individuals for a world where AI is ubiquitous.
Practical Application:
Educational institutions should incorporate AI literacy training across disciplines, emphasizing critical thinking, ethical considerations, and the ability to use AI responsibly in any context, both academic and professional.
4. Focus on Process, Not Just Product
Focus on the process of learning and doing, not just the product. This book suggests structuring assignments to promote active learning, critical thinking, and engagement, reducing the temptation for students to rely solely on AI.
Practical Application:
Design assignments that emphasize personalized learning experiences, including personal reflections, unique problem applications, ethical considerations, and real-world problem-solving, to increase student engagement and make cheating less appealing.
5. Thoughtful AI Policies are Needed
Rather than simply banning AI, we need to develop thoughtful, transparent policies that promote its ethical and responsible use. Policies should guide effective AI use, not just police cheating.
Practical Application:
Colleges and universities should establish policies that promote AI literacy and outline acceptable uses of AI. Policies should be transparent and student-centered and reflect what is happening in the workplace. Policies should emphasize learning and AI literacy as the primary goal.
Suggested Deep Dive
Chapter: Chapter 3: AI Literacy
This chapter provides practical guidance on prompt engineering and using AI effectively for different tasks, which is crucial for educators and students alike.
Memorable Quotes
Introduction. 11
AI is a technology that is going to change everything—and not just education.
AI Basics. 20
AI is one of the most important things humanity is working on. It is more profound than electricity or fire.
AI Basics. 28
AI is also generative of misinformation.
Reimagining Creativity. 62
AI is going to make us all more creative.
Cheating and Detection. 106
This is the worst AI will ever be.
Introduction. 11
AI is a technology that is going to change everything—and not just education.
AI Basics. 20
AI is one of the most important things humanity is working on. It is more profound than electricity or fire.
AI Basics. 28
AI is also generative of misinformation.
Reimagining Creativity. 62
AI is going to make us all more creative.
Cheating and Detection. 106
This is the worst AI will ever be.
Comparative Analysis
“Teaching with AI” distinguishes itself by its practicality and focus on higher education. Unlike broader AI books like “Power and Prediction,” which explore societal implications, or technical guides like “Deep Learning with Python,” Bowen and Watson directly address the anxieties and opportunities AI presents to educators. It shares some thematic similarities with Cathy N. Davidson’s “The New Education,” which also advocates for pedagogical transformation, but “Teaching with AI” offers more concrete, AI-specific strategies. While agreeing with other scholars about the potential of AI for personalized learning (e.g., Sal Khan’s work on Khan Academy), it also uniquely emphasizes the importance of fostering critical thinking and AI literacy as core skills in this new era.
Reflection
“Teaching with AI” provides a valuable, timely starting point for understanding AI’s implications for higher education. It rightly highlights the need for AI literacy, adaptation, and reframing pedagogical approaches. However, the rapid pace of AI development may render some specific tools and strategies outdated quickly. While the book successfully addresses immediate anxieties surrounding cheating and bias, a deeper exploration of long-term ethical and societal implications would enrich the discussion. Its focus on practical applications is a strength but also a potential weakness if not paired with ongoing critical engagement with evolving AI capabilities and research. We need to reimagine education for a future in which all of us will be thinking and acting with AI.
Flashcards
What is the key difference between machine learning and expert systems?
Machine learning uses probability and statistics, while expert systems rely on pre-defined rules and logic.
What characterizes a foundational model in AI?
Deep neural networks with many layers, trained on vast datasets.
What does GPT stand for?
Generative Pre-trained Transformer
What is a key challenge associated with the ‘generative’ nature of AI?
Unpredictability and a lack of reliability, sometimes leading to the generation of false information (hallucinations).
What are parameters in an AI model?
Internal variables in a neural network that can be tuned to adjust the output.
What are tokens in the context of AI language models?
Representations of words or data used by AI.
What are the key components of AI literacy?
Problem formation, question refinement, prompt engineering, and iteration.
How should grading be adapted in the age of AI?
Focus on higher-order thinking, creativity, and work that demonstrates value beyond AI’s capabilities.
What are the three key internal drives for motivating human effort?
Purpose, self-efficacy, and agency.
What are the essential elements of a well-crafted AI prompt?
Task, format, voice, and context.
What is the key difference between machine learning and expert systems?
Machine learning uses probability and statistics, while expert systems rely on pre-defined rules and logic.
What characterizes a foundational model in AI?
Deep neural networks with many layers, trained on vast datasets.
What does GPT stand for?
Generative Pre-trained Transformer
What is a key challenge associated with the ‘generative’ nature of AI?
Unpredictability and a lack of reliability, sometimes leading to the generation of false information (hallucinations).
What are parameters in an AI model?
Internal variables in a neural network that can be tuned to adjust the output.
What are tokens in the context of AI language models?
Representations of words or data used by AI.
What are the key components of AI literacy?
Problem formation, question refinement, prompt engineering, and iteration.
How should grading be adapted in the age of AI?
Focus on higher-order thinking, creativity, and work that demonstrates value beyond AI’s capabilities.
What are the three key internal drives for motivating human effort?
Purpose, self-efficacy, and agency.
What are the essential elements of a well-crafted AI prompt?
Task, format, voice, and context.