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AI and Writing
AI and Writing is an introduction to Generative Artificial Intelligence (GenAI) and its emergent role as a tool for academic, professional, civic, and personal writing. Sid Dobrin examines GenAI from two the conceptual and the applied. The conceptual approach addresses the function of GenAI and the ramifications of its use as a writing tool – especially the ethical, social, and material issues it raises. The applied approach offers guidance to assist readers in using GenAI responsibly and authentically. In consideration of the rapid evolution of GenAI and the many unsettled questions about its role, Dobrin leaves room for readers to adapt to shifting technological and institutional conventions.
This book is intended for composition and writing-intensive courses, and for any readers with a general or professional interest in the role of GenAI in writing. While it is primarily designed for first-year writing courses, it’s also applicable to courses in advanced writing, professional writing, technical writing, business writing, and writing across the curriculum, as well as writing-intensive courses in other disciplines. In other words, it can be used in any course in which students are required to produce texts.
This book is intended for composition and writing-intensive courses, and for any readers with a general or professional interest in the role of GenAI in writing. While it is primarily designed for first-year writing courses, it’s also applicable to courses in advanced writing, professional writing, technical writing, business writing, and writing across the curriculum, as well as writing-intensive courses in other disciplines. In other words, it can be used in any course in which students are required to produce texts.
179 pages, Kindle Edition
Published August 15, 2023
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37 people want to read
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Displaying 1 - 13 of 13 reviews
February 8, 2024
AI opens up so many issues with plagiarism because the software is getting information from someone.
Best part of this was the comparison of taking a helicopter to the top of Everest and using AI for writing. Yeah, you got to the top/have a finished product but you can’t say you climbed it and you can’t say you wrote it.
Best part of this was the comparison of taking a helicopter to the top of Everest and using AI for writing. Yeah, you got to the top/have a finished product but you can’t say you climbed it and you can’t say you wrote it.
September 25, 2024
The book itself was excellent but I fo find myself not agreeing with many of the ideas it presented. Though this made for an excellent argument in my argumentative essay regarding AI being used in post secondary education.
December 4, 2023
I’m a college reading and writing professor, and this is EXACTLY what I’ve been needing to start integrating/addressing/managing all things AI-related in my pedagogy. Thank you!
July 22, 2024
I am just diving into the topic of GenAI so that I can better teach university research writing courses with a greater awareness of tools such as ChatGPT. I am not one of those teachers who wants to be a police officer who forbids use of GenAI. Instead, I want to understand GenAI and teach my students to use it responsibly.
(I cannot believe that I am overhauling my pedagogy AGAIN! I have been teaching college composition for 44 years, and I keep having to retool. But I believe that you have to keep up with the times. Change or stagnate. It's also good for my brain to be a lifelong learner. So here we go!)
I have ordered 3 other books on the topic: one that is focused on pedagogy and two that are more philosophical. I will probably read a book a month on this topic until I feel a little more familiar with the cultural significance of GenAI and a lot more savvy about the pedagogical uses of GenAI.
Dobrin helped introduce some key terms and concepts, but his book does not do a deep dive. It's more of a quick survey. But it's a good start for the uninitiated.
Ch. 1 Understanding Generative AI: This chapter establishes the context for the book by defining the main terms, presenting a history of AI, documenting it's prevalence among student use, pointing out some of the benefits (often ignored) alongside with some of the drawbacks (more discussed for now), and declaring the need to incorporate discussion and use into the classroom.
Ch. 2 Generative AI: More definitions and context. The chapter starts by listing some historical examples in literature and opera of automatons. Then there is a history of computerized intelligence forms, such as Turing's work. The second half of the chapter starts to explain 21st century efforts to develop generative artificial intelligence with some of the strengths and weaknesses. A notable weakness is hallucinations or images / texts that are incorrect.
Ch. 3 Integrity: This chapter takes a close look at the concept of plagiarism in its various forms and how GenAI challenges the current definitions and university policies / consequences for using GenAI. At the end of the chapter, Dobrin provides suggestions on how to document AI in MLA format and APA format.
Ch. 4 Writing with GenAI: This chapter explores how AI can help with various stages of the writing process: invention (generating ideas), arrangement (outlining), style (sentence construction and variety), revising, and editing.
Ch. 5 Prompts: This is a very short chapter that contains suggestions on how to prompt Generative AI so that the resulting text is accurate and specific.
Ch. 6 Visuals: I admit that I did not read this as carefully as the other chapters because as a writing instructor, my students are not going to submit visuals.
Ch. 7 Contexts of Use: Dobrin is spitballing a bit here. I wish his book had more chapters about pedagogy, which plays to his strengths. These other chapters seem like a way to make this a book-length effort. He's stronger in chapters 3, 4, and 5. I wish he would have elaborated there more.
Ch. 8 Career Readiness: This is another short chapter. Dobrin explores some possible jobs for people with skills in generative artificial intelligence. I'd rather read a book by a visionary and business professional to explore questions about how GenAI will tranform our economy (and thereby transforming higher ed). But it's good to get a brief look before doing a deep dive.
Ch. 9 Bias: This is a short chapter that identifies some forms of bias in GenAI, such as what kind of data is digitized in the first place and then how machine learning might examine some data more than others. Again, I would rather read a book by a computer programmer, information analyst, or other professionals who are saturated in this topic so that I can get more depth, detail, and nuance. This does gesture to the issue, but it's just a small taste.
Ch. 10 Materiality: This looks at big picture issues about the life cycle of GenAI and the hardward that uses it. Again, I would rather read something by an expert in digital culture. This is very short and just gestures to many issues about the material (software, laborers, hardware) of the exploding GenAI field.
(I cannot believe that I am overhauling my pedagogy AGAIN! I have been teaching college composition for 44 years, and I keep having to retool. But I believe that you have to keep up with the times. Change or stagnate. It's also good for my brain to be a lifelong learner. So here we go!)
I have ordered 3 other books on the topic: one that is focused on pedagogy and two that are more philosophical. I will probably read a book a month on this topic until I feel a little more familiar with the cultural significance of GenAI and a lot more savvy about the pedagogical uses of GenAI.
Dobrin helped introduce some key terms and concepts, but his book does not do a deep dive. It's more of a quick survey. But it's a good start for the uninitiated.
Ch. 1 Understanding Generative AI: This chapter establishes the context for the book by defining the main terms, presenting a history of AI, documenting it's prevalence among student use, pointing out some of the benefits (often ignored) alongside with some of the drawbacks (more discussed for now), and declaring the need to incorporate discussion and use into the classroom.
Ch. 2 Generative AI: More definitions and context. The chapter starts by listing some historical examples in literature and opera of automatons. Then there is a history of computerized intelligence forms, such as Turing's work. The second half of the chapter starts to explain 21st century efforts to develop generative artificial intelligence with some of the strengths and weaknesses. A notable weakness is hallucinations or images / texts that are incorrect.
Ch. 3 Integrity: This chapter takes a close look at the concept of plagiarism in its various forms and how GenAI challenges the current definitions and university policies / consequences for using GenAI. At the end of the chapter, Dobrin provides suggestions on how to document AI in MLA format and APA format.
Ch. 4 Writing with GenAI: This chapter explores how AI can help with various stages of the writing process: invention (generating ideas), arrangement (outlining), style (sentence construction and variety), revising, and editing.
Ch. 5 Prompts: This is a very short chapter that contains suggestions on how to prompt Generative AI so that the resulting text is accurate and specific.
Ch. 6 Visuals: I admit that I did not read this as carefully as the other chapters because as a writing instructor, my students are not going to submit visuals.
Ch. 7 Contexts of Use: Dobrin is spitballing a bit here. I wish his book had more chapters about pedagogy, which plays to his strengths. These other chapters seem like a way to make this a book-length effort. He's stronger in chapters 3, 4, and 5. I wish he would have elaborated there more.
Ch. 8 Career Readiness: This is another short chapter. Dobrin explores some possible jobs for people with skills in generative artificial intelligence. I'd rather read a book by a visionary and business professional to explore questions about how GenAI will tranform our economy (and thereby transforming higher ed). But it's good to get a brief look before doing a deep dive.
Ch. 9 Bias: This is a short chapter that identifies some forms of bias in GenAI, such as what kind of data is digitized in the first place and then how machine learning might examine some data more than others. Again, I would rather read a book by a computer programmer, information analyst, or other professionals who are saturated in this topic so that I can get more depth, detail, and nuance. This does gesture to the issue, but it's just a small taste.
Ch. 10 Materiality: This looks at big picture issues about the life cycle of GenAI and the hardward that uses it. Again, I would rather read something by an expert in digital culture. This is very short and just gestures to many issues about the material (software, laborers, hardware) of the exploding GenAI field.
March 17, 2025
In AI and Writing, Sid Dobrin offers an insightful and thought-provoking examination of how Generative Artificial Intelligence (GenAI) is reshaping the landscape of writing. This book is not just about the mechanics of AI-assisted writing but also explores its broader implications—ethical, social, and material—making it an essential read for writers, educators, and anyone curious about the future of storytelling. Key insights from AI and Writing:
AI as a Collaborative Writing Tool: Dobrin emphasizes that AI should not be seen as a replacement for human creativity but as a powerful collaborator. He explores how GenAI can assist in brainstorming, structuring narratives, and overcoming writer’s block, all while keeping the human writer in control of the creative process.
The Ethical and Intellectual Challenges of AI Writing: The book delves into important ethical concerns, such as authorship, originality, and the potential biases embedded in AI-generated content. Dobrin encourages readers to critically engage with these issues and to use AI responsibly in their writing practices.
AI’s Role in Different Writing Contexts: One of the book’s strengths is its broad application of AI across different writing domains. Dobrin discusses how AI is used in academic, professional, creative, and civic writing, showing its adaptability and the various ways it can enhance storytelling and communication.
The Material Implications of AI Writing: Beyond just words on a page, Dobrin examines how AI affects the economics of writing and publishing. He discusses how AI-generated content might impact traditional publishing industries, freelance writers, and academic institutions, highlighting the need for new models of authorship and compensation.
The Future of Writing with AI: Dobrin does not merely describe the current state of AI-assisted writing; he looks ahead, considering how AI might continue evolving. He raises questions about AI’s role in shaping narratives, its potential to democratize access to writing tools, and the ongoing debate over human versus machine creativity.
For writers—whether memoirists, novelists, or content creators—AI and Writing provides a balanced perspective on the benefits and challenges of AI in storytelling. It acknowledges AI’s transformative potential while cautioning against its pitfalls, making it a vital guide for those looking to integrate AI into their creative process.
If you’re exploring how AI can enhance your memoir-writing journey, this book offers a roadmap for using AI ethically and effectively while preserving the authenticity of your unique voice.
AI as a Collaborative Writing Tool: Dobrin emphasizes that AI should not be seen as a replacement for human creativity but as a powerful collaborator. He explores how GenAI can assist in brainstorming, structuring narratives, and overcoming writer’s block, all while keeping the human writer in control of the creative process.
The Ethical and Intellectual Challenges of AI Writing: The book delves into important ethical concerns, such as authorship, originality, and the potential biases embedded in AI-generated content. Dobrin encourages readers to critically engage with these issues and to use AI responsibly in their writing practices.
AI’s Role in Different Writing Contexts: One of the book’s strengths is its broad application of AI across different writing domains. Dobrin discusses how AI is used in academic, professional, creative, and civic writing, showing its adaptability and the various ways it can enhance storytelling and communication.
The Material Implications of AI Writing: Beyond just words on a page, Dobrin examines how AI affects the economics of writing and publishing. He discusses how AI-generated content might impact traditional publishing industries, freelance writers, and academic institutions, highlighting the need for new models of authorship and compensation.
The Future of Writing with AI: Dobrin does not merely describe the current state of AI-assisted writing; he looks ahead, considering how AI might continue evolving. He raises questions about AI’s role in shaping narratives, its potential to democratize access to writing tools, and the ongoing debate over human versus machine creativity.
For writers—whether memoirists, novelists, or content creators—AI and Writing provides a balanced perspective on the benefits and challenges of AI in storytelling. It acknowledges AI’s transformative potential while cautioning against its pitfalls, making it a vital guide for those looking to integrate AI into their creative process.
If you’re exploring how AI can enhance your memoir-writing journey, this book offers a roadmap for using AI ethically and effectively while preserving the authenticity of your unique voice.
March 15, 2024
AI and Writing removes much of the anxiety surrounding generative AI in education, offering insights that are both theoretical and practical. New technologies can sometimes be a barrier, but this book makes genAI feel more accessible. In some ways Dobrin’s work reads like an instruction manual for using AI. In other ways, this text deescalates the tendency to be reactionary toward AI, encouraging readers to instead proactively engage with AI – even providing exercises to help readers explore the theoretical and applied use of genAI. If you want to increase your understanding of the intersection between writing and generative AI, this book is for you.
August 8, 2025
I’ve been thinking a lot about how to incorporate AI into my writing instruction—it is here to stay and we need to figure out how it will impact our students and how to teach students to use it ethically. This was helpful. There are tasks, discussion questions and thought exercises. The material is easily accessible and broad enough that it is useful even as AI evolves at such a rapid crater (GPT5 is thought to be coming out this month…)
I could argue that this book is TOO broad and a bit basic, but I think it is a great starting point (see note above about rapid development).
I could argue that this book is TOO broad and a bit basic, but I think it is a great starting point (see note above about rapid development).
November 23, 2025
I appreciated this book for its technical definition and history of AI –– it helped me understand what AI is and how long it's been around (a lot longer than ChatGPT/than the general public has been aware of it). It's a slim book and I would have preferred more citations to track down some of the claims made, but as a HIGHLY readable starter to AI in the context of college-level composition, it can't be beat.
January 23, 2025
I found this to be a very broad and overly generic introduction to the ways that AI impacts writing. Dorbin does a good job posing provocative questions and I also appreciated the final chapter about AI and materiality. But when it came to exploring the impacts AI could have on various aspects of the writing process, I felt that book fell short of providing enough examples and clarity.
January 17, 2024
A great book to introduce you to the need-to-knows of AI in the college classroom
February 1, 2024
Genuinely one of the most engaging textbooks I've ever read, and I don't typically dabble in technology. Brief, to the point, but still fun and conversational. Easy for beginners to understand.
September 25, 2025
Very basic overview, with the interesting cautionary material relegated to the last few short chapters.
January 3, 2025
As an English professor, I was sent a review copy of this book by the publisher. Speaking from the perspective of someone who wants to be a published author and is very threatened by the idea of industry leaders resorting to AI to make a profit, thereby lowering the bar of quality to formulaic mediocrity while cheating artists out of a living--from this admittedly biased perspective, I found the book to be an enlightening read about the ways in which AI might be incorporated into writing.
More time could have been spent in the section on how AI will generate "new jobs" and what those new jobs will entail. I feel that the author brushed under the rug the very real concern that many people will be put out of work, not so much as a result of automation, but because greedy corporations will do anything to cut costs, hoarding money for the big guys on top while systematically firing the middle men and the people on the bottom who currently rely on those jobs for their livelihoods. I noted, cynically, that all the "new jobs" were in the tech field (for a time...until those jobs become impacted when supply outnumbers demand). Nothing was said about what people should do for work if they have no aptitude for or interest in the tech industry, nor indeed about what millions of people should do if their jobs disappear. Retrain in a different field? (On whose dime? Ours? Our companies'? I know which option I'd prefer.)
WARNING: A rant follows which has nothing to do with the content of this well-presented little volume. If you're not interested in a doomsday rant about AI, skip ahead to the last paragraph.
I feel strongly that the advent and rapid development of AI is a global crisis that needs to be addressed in a summit on an international scale. There are many benefits to this technology, yes, so long as the profiteers don't try to use it to line their pockets while disenfranchising most of humanity, as they are already doing. Ethical sanctions need to be put in place to ensure that humans have access to valuable and rewarding work. Either that, or we need a complete abolition of the money economy and instate a basic universal income for all citizens, so that everyone can benefit from automation without becoming homeless and obsolete in the process.
What is the point of life anymore if people can no longer pursue artistic endeavors because there is no need for us to do so, or--worse--we are not allowed by the gatekeepers of the creative industries to do so? After all, it will be so much cheaper to AI-generate a blockbuster guaranteed to sell tickets. And are we really willing to settle for machine-generated books, music, movies, art? (Frank Herbert's Dune comes to mind: "Thou shalt not create a machine in the image of man.") These sorts of questions are not trivial, and they are barely given any thought in this slim and optimistic volume.
So as a hopeful fiction writer, I continue to despair. As an underpaid part of America's workforce, I despair even more. This book didn't give me enough hope that the people who have access to and/or control of this technology really care about what happens to the rest of humanity.
As a college instructor, the book opened my mind to possibilities of how to accept and encourage students' use of AI. It feels a little bit like giving up and throwing in the towel, but if the whole world will be cheating and using this for writing whether I approve or not, then this book offers good tools for how to move forward. Most of my fatalistic musings lie outside the scope of what this book sets out to accomplish, which is to offer a guide for integrating AI into contexts where writing is required, while still avoiding plagiarism and emphasizing authorial control. I gather that Professor Dobrin also teaches English and writing. I congratulate him on his optimism and willingness to engage with this subject, and thank him for offering this book as a guide to students and teachers alike.
Comments welcome. Talk to me. :)
More time could have been spent in the section on how AI will generate "new jobs" and what those new jobs will entail. I feel that the author brushed under the rug the very real concern that many people will be put out of work, not so much as a result of automation, but because greedy corporations will do anything to cut costs, hoarding money for the big guys on top while systematically firing the middle men and the people on the bottom who currently rely on those jobs for their livelihoods. I noted, cynically, that all the "new jobs" were in the tech field (for a time...until those jobs become impacted when supply outnumbers demand). Nothing was said about what people should do for work if they have no aptitude for or interest in the tech industry, nor indeed about what millions of people should do if their jobs disappear. Retrain in a different field? (On whose dime? Ours? Our companies'? I know which option I'd prefer.)
WARNING: A rant follows which has nothing to do with the content of this well-presented little volume. If you're not interested in a doomsday rant about AI, skip ahead to the last paragraph.
I feel strongly that the advent and rapid development of AI is a global crisis that needs to be addressed in a summit on an international scale. There are many benefits to this technology, yes, so long as the profiteers don't try to use it to line their pockets while disenfranchising most of humanity, as they are already doing. Ethical sanctions need to be put in place to ensure that humans have access to valuable and rewarding work. Either that, or we need a complete abolition of the money economy and instate a basic universal income for all citizens, so that everyone can benefit from automation without becoming homeless and obsolete in the process.
What is the point of life anymore if people can no longer pursue artistic endeavors because there is no need for us to do so, or--worse--we are not allowed by the gatekeepers of the creative industries to do so? After all, it will be so much cheaper to AI-generate a blockbuster guaranteed to sell tickets. And are we really willing to settle for machine-generated books, music, movies, art? (Frank Herbert's Dune comes to mind: "Thou shalt not create a machine in the image of man.") These sorts of questions are not trivial, and they are barely given any thought in this slim and optimistic volume.
So as a hopeful fiction writer, I continue to despair. As an underpaid part of America's workforce, I despair even more. This book didn't give me enough hope that the people who have access to and/or control of this technology really care about what happens to the rest of humanity.
As a college instructor, the book opened my mind to possibilities of how to accept and encourage students' use of AI. It feels a little bit like giving up and throwing in the towel, but if the whole world will be cheating and using this for writing whether I approve or not, then this book offers good tools for how to move forward. Most of my fatalistic musings lie outside the scope of what this book sets out to accomplish, which is to offer a guide for integrating AI into contexts where writing is required, while still avoiding plagiarism and emphasizing authorial control. I gather that Professor Dobrin also teaches English and writing. I congratulate him on his optimism and willingness to engage with this subject, and thank him for offering this book as a guide to students and teachers alike.
Comments welcome. Talk to me. :)
Displaying 1 - 13 of 13 reviews