What does it mean when we stop reading texts and instead offload that skill to AI? We desperately need another ChatGPT moment outside of text generation to wake people up and let them know how quickly generative technology will impact skills beyond writing. For $5 a month, anyone is now able to summarize and query a PDF using Adobe's AI Assistant. You can already do this with a number of foundation models, along with a slew of purpose-built AI-reading assistants. Who is talking about this? We've been so laser-focused in education on ChatGPT's impact on writing that we've missed generative AI's impact on a multitude of core skills, like reading.
Honestly, I think this a far more important conversation to have than about writing, and not just because there are risks to AI proliferation but it's the one area where I see room for AI to act as a useful prosthesis of sorts. We're actually deeply familiar with guides of various kinds intended to facilitate reading or to accelerate transmission of information. Some of them are inside of texts--table of contents, index, glossary, chapters, subheadings, abstracts, annotations, footnotes, etc. Some of them are texts that help with a text--concordances, summaries, commentaries, book reviews. We're familiar with the advantages and disadvantages of using something like "Cliff's Notes" or "For Dummies" guides prior to trying to read a text, but we also acknowledge the necessity of needing help simply by the fact that we teach classes *about* a particular text, that many things cannot be read in isolation or in solitude. For some texts, no one would argue that you have to make sense of it without assistance--Finnegan's Wake, for example. Many of us are operating with vast systems of paratextual knowledge--e.g., we know about the content of readings that we haven't done, and our knowledge is often basically correct. We know there's a value to reading a text deeply and well but we know it's not an infinite value--that there are trade-offs (of time, of efficiency, of necessity, and of affinity--no one wants to struggle profoundly with a reading that they have come to hate or feel alienated by).
What I find strange is precisely what you start with here in your title: literally no one is talking about this aspect of AI. But that is perhaps partly because we oddly treat reading as a lower-level pedagogical job, to be attended to in secondary education. There is very little conversation generally about how to read past high school, only a lot of moral panic about *whether* people are reading enough or reading the right things.
Between the submission of the first draft of my book manuscript (about gen AI and writing) and the final revision, I added two chapters on reading because I had a similar epiphany to what you articulate here, that students were being encouraged to avoid reading, denying them that critical thinking experience, where the intersection of reader and text allows a new idea not in the text to form. Without that process, those Ideas don't come into existence.
To me, it looked a lot like what's happened with writing instruction, allowing a simulation to substitute for the genuine article because that simulation can pass muster for the purposes of schooling. This attitude pre-dates gen AI, also, but gen AI accelerates things in a way that makes me scared we'll abandon some of the important experiences of reading the same way writing is at risk.
I appreciate your insights on this. The title popped up in my email today and I had to read it immediately. At my high school site we have been developing grade level teams to determine a focus language domain (ELD standards) for each grade. Each of our teams independently and overwhelmingly agreed that B.6: Reading Closely, was the most important skill that our students needed and are currently under prepared for. I'm sharing your article with all of them now. Thank you.
In the spirit of John Warner's argument that ChatGPT can't kill anything worth saving, I want to echo your point that generative AI as it currently exists is only good at summary and does not perform close reading and analysis well. That would mean the value of teaching practices that focuses on developing close reading skills should increase at all levels of instruction. If ChatGPT can do your homework, that means your homework has little educational value. In terms of reading, it doesn't seem that generative AI is providing anything substantively different than SparkNotes. The utility of close reading is that thinking deeply about a passage leads to insights about language and its relation to experiences grounded in social contexts. I find that a valuable skill, one that AI in its current forms has little ability to augment. If our response to generative AI is to refocus instructional time and effort on helping our students develop skills to closely analyze text and cultural artifacts, we will accomplish something that needed doing anyway.
Good points, all of them. I think using Hypothes.is this way is a great idea. While I am an instructional technologist now, I did my undergrad and graduate work in history. One of the pivotal moments of my undergraduate career was when a grad student taught me how to approach a book, H.M.D. Parker's Roman Legions. It had never occurred to me to look at the bibliography after reading the preface to get an idea of the depth and scope of the research. It was a valuable lesson, and the scene is still fresh in my memory. The point, of course, is that this is another thing that having an AI summary defeats. It wasn't that someone told me to do this, they sat down and showed me by example. That was valuable. I also wonder how much would have been lost in the summary of Parker's arguments about the Antesignani, which I recall puzzling me at first but were worth working through to understand something about how think about what sources tell us about Roman legions.
Thanks, Guy! I, too, read History as an undergrad and could have never understood Procopius's Secret History of Justinian if I didn't conduct close reading on my own and look at the work of other scholars and how they complicated/ illuminated aspects.
If students use AI to skip reading a text their professor considers central to attainment, that is a problem; if they use it to improve their understanding and focus their rereading, that is....awesome. Our underfunded school doesn't provide anything like that kind of support, and most of our students need more help with college-level reading comprehension than our faculty can provide.
I think that's ultimately the tension here. Students can use AI reading assistants in ways that support learning, not offload it. But doing so takes structure and intentional pedagogy. I worry that many underfunded schools won't be able to provide that structure in the first place and AI reading will become a sort of default that some educators expect, like spell check on Word Processors.
I am hoping an entity like Khan Academy (for altruistic reasons) or Pearson (for profit motives) will provide a purpose-built AI collaborative reading assistant. Ideally, it would also help the professor assess the reading assignments and make course corrections before students do poorly on the tests/essays/speeches the readings were to have informed.
"Learning has been reduced to a problem" - brilliant capture of this idea. It's been bothering me lately how so many non-problems, as Kate Manne calls them, get re-framed as problems in the pursuit of selling the idea of a solution.
For what it's worth, in my conversations with working professionals about how they feel about genAI, one of the reasonably common concerns is skill atrophy. Skills are valuable not only for their marketability, but also for the intrinsic satisfaction that executing them offers, and people are reluctant to give that up in exchange for a tidily finished product.
A counter argument might be to double down on tools or capture objectives achieved by them AI or LLMs. And in the process preserve the qualities of close reading you are trying to achieve?
I somehow see exponential potential in enhancing their learning ability with these new tools. But done proactively, not passively to speed read or summarize without comprehension. Hear me out (these are personal views without prejudice or conflict, based on my own teaching journey done in practice/industry).
On the assumption close reading is trying to achieve some of these:
- deepen students' understanding of a text,
- promote critical thinking, and
- develop analytical skills
E.g.
1. For AI-generated questions and prompts: Tools like TextHelp's Read&Write or Quillionz can automatically generate comprehension questions based on the text, encouraging readers to think critically about key concepts and themes.
2. Personalized recommendations: Platforms like Goodreads or Amazon's Kindle use AI algorithms to recommend books based on a reader's past preferences and reading habits, guiding them towards texts that align with their interests and reading level. Or just ask ChatGPT. Feynman's how do I understand this like I'm 5?
3. Interactive elements: Apps like Epic! or Novel Effect incorporate interactive features such as quizzes, annotations, and multimedia enhancements e.g. animations, fostering engagement and deeper exploration of the text.
4. Collaborative discussions: Platforms like Perusall or Padlet enable readers to annotate and discuss texts collaboratively in real-time, facilitating peer learning and the exchange of diverse perspectives.
5. Diverse perspectives: Tools like Microsoft's Immersive Reader or Project Naptha utilize AI to translate text into different languages, adjust reading levels, or provide alternative formats such as audio or braille, making texts more accessible to a wider range of readers and promoting inclusivity.
Now the cool stuff - To encourage critical thinking and analysis in AI-assisted reading:
6. Text analysis platforms: Tools like Voyant Tools (used your chapter- https://voyant-tools.org/?corpus=f31d7f49a48f6b8ffa04018c316e9795) or Lexos allow users to perform text analysis, including word frequency analysis, topic modeling, and sentiment analysis, providing insights into the text's themes, language use, and emotional tone.
7. Argument mapping software: Platforms such as Argumentative or MindMup enable users to visually map out arguments and counterarguments within a text, helping readers identify key points, evaluate evidence, and construct reasoned responses.
8. Annotation and note-taking tools: Apps like Hypothesis or Notion offer features for annotating texts and taking structured notes, facilitating active reading and the organization of thoughts and observations.
9. Socratic questioning bots: AI chatbots like Socrates (Socratic Lab) or IBM Watson's Debater (just sunsetted 1st May 2024) use natural language processing to engage users in Socratic questioning, prompting critical reflection and deeper exploration of the text's meaning and implications. There are others - Debate Devil, Debate AI, etc. 70+ References included here: https://topai.tools/s/debate-tool
10. AI writing assistants: Tools such as Grammarly or Hemingway Editor provide feedback on writing style, grammar, and clarity, encouraging writers to revise and refine their arguments and interpretations.
You dont need all. But the spectrum is indeed wide. Failing which many of what these tools do (objectives wise) can be prompted or programed into function via APIs e.g. Chat GPT 4, Gemini's, Claude equivalents.
While close reading emphasizes deep engagement with the text, the integration of AI-assisted reading tools can enhance this process and potentially lead to outcomes surpassing those of traditional close reading in several ways e.g.:
A. Efficiency: AI tools can quickly analyze large volumes of text, identify patterns, and generate insights that may not be immediately apparent through manual close reading alone, saving time and enabling readers to delve deeper into complex texts.
B. Personalization: AI algorithms can tailor recommendations, questions, and annotations to individual readers' preferences, learning styles, and comprehension levels, providing a more personalized and adaptive reading experience that meets the diverse needs of learners.
C. Accessibility: AI-driven features such as text-to-speech, translation, and adaptive formatting make texts more accessible to a wider range of readers, including those with visual impairments, language barriers, or learning disabilities, promoting inclusivity and equity in education.
D. Collaboration: AI-powered collaborative tools facilitate peer learning, discussion, and knowledge sharing among readers, creating opportunities for collaborative sense-making, collective problem-solving, and the co-construction of meaning beyond the limitations of solitary close reading.
E. Enhanced analysis: Text analysis and argument mapping tools enable readers to explore texts from multiple perspectives, uncover hidden connections, and critically evaluate arguments, fostering higher-order thinking skills such as synthesis, evaluation, and creativity that go beyond the scope of traditional close reading.
Not really Lynn. Just thinking no one has definitive answers/solutions (not looking for any either). So anything goes. I believe in possibilities too. Or leverage, which comes in varying forms. P.s. also been on both (1st) the sell side, then buy sides. Imperfect to the hilt! Guessing you probably know better too. What If this is the Wild Wild West? 😄
Sounds like we have had similar experiences and perspectives that only come from observing, learning, failing, and then adapting. Without uncertainty there are no possibilities, so it is more fun to think of it as the Wild West than trying to control things we can’t control. It is fun to explore the different points of view in these discussions. 🙏😊
Some great points made here, thank you, Marc. First, I want to state that this is another clear reason why we must teach AI Literacy to all students. I express AI Literacy as being comprised of Awareness, Capability, Knowledge, and Critical Thinking. Within Critical Thinking is the vital aspect of avoiding overreliance. "Overreliance" is a negative thing if we unwittingly lose skills and capabilities to a system such as generative AI. This is bad thing if it is not done purposefully and is done without taking second and third order effects into consideration. An example would be cursive writing. Anyone that is close to my age remembers have to take many classes devoted specifically to cursive writing. For a long time, even dissertations HAD to be hand written, because good handwriting was an important professional skill. Then, thanks to the proliferation of type writers, computers, and printers, that must have skill was "let go." - I'm not saying good reading ability is something to be let go. I am simply giving an example of overreliance and the importance of being aware of it so that it is purposefully addressed and considered.
We do need to inform student of the importance to good reading, but at the same time we in academia need to also be realistic with ourselves. I remember being a student and having too much reading to do. It was impossible. I often had to skip some sleep, skip meals, or workouts, or something else because I had too much reading to do. I dissentingly remember thinking to myself, "I wish I could read a summarized version of this with the specifics of what I need for the assignment." AI can help with that, but as you expertly pointed out, it comes at a price, meaning the student doesn't gain a deeper understanding. - Yet this is the reality of higher education and it has been for a long time. As with everything a proper middle ground is needed.
Judging from all I have been reading here and in the comments, may I suggest a paradigm shift in thinking that reading well is a skill to be acquired? While learning math and practicing the piano can surely be considered skills, reading depends on prior knowledge and language competence. There is much research that supports the finding that the best readers are the ones who know more about the topic being read than any other variable being tested. Use AI to provide background knowledge then? Perhaps, but I see that as more a teacher's responsibility as students need teachers to prepare them to do a reading. Use AI to simplify the language of a text? Maybe, but language modification can achieve only limited gains as it does not address the lack of knowledge issue. How then to use AI? As students read, they need the text EXPLAINED . . . to be connected to what they already might know about what they are reading. Bring on the AI bots that can do that and then let close reading proceed. Yes, that means using the explained text as a bridge to the more complex text not as the only text that is being read.
Excellent (and alarming) points. I can see these tools appealing very much to my college kids, and I selfishly am glad they are as old as they are and have developed some good close reading skills already. They enjoy fiction, and can make their way through course texts. Having these tools readily available for younger students still at the start of building those critical reading and comprehension skills is very concerning. I agree we’ll see long term impacts of this.
I agree with your take on this. As a just-retired English teacher, I saw kids reading less than ever, and am very concerned about the now relying on AI to read for them. I’m posting about these issues on my “AI is For Sheep” Substack.
If you substitute ‘walking’ for ‘reading’ in this piece, it becomes clearer how deskilling AI summaries are. If I never walked, how could I learn to actually walk? If you use a tool to do a task, the skill you learn is how to use the tool not the task. If the value of the tool use skill is greater than the skill it is a fair trade off; if not, you have lost out
Honestly, I think this a far more important conversation to have than about writing, and not just because there are risks to AI proliferation but it's the one area where I see room for AI to act as a useful prosthesis of sorts. We're actually deeply familiar with guides of various kinds intended to facilitate reading or to accelerate transmission of information. Some of them are inside of texts--table of contents, index, glossary, chapters, subheadings, abstracts, annotations, footnotes, etc. Some of them are texts that help with a text--concordances, summaries, commentaries, book reviews. We're familiar with the advantages and disadvantages of using something like "Cliff's Notes" or "For Dummies" guides prior to trying to read a text, but we also acknowledge the necessity of needing help simply by the fact that we teach classes *about* a particular text, that many things cannot be read in isolation or in solitude. For some texts, no one would argue that you have to make sense of it without assistance--Finnegan's Wake, for example. Many of us are operating with vast systems of paratextual knowledge--e.g., we know about the content of readings that we haven't done, and our knowledge is often basically correct. We know there's a value to reading a text deeply and well but we know it's not an infinite value--that there are trade-offs (of time, of efficiency, of necessity, and of affinity--no one wants to struggle profoundly with a reading that they have come to hate or feel alienated by).
What I find strange is precisely what you start with here in your title: literally no one is talking about this aspect of AI. But that is perhaps partly because we oddly treat reading as a lower-level pedagogical job, to be attended to in secondary education. There is very little conversation generally about how to read past high school, only a lot of moral panic about *whether* people are reading enough or reading the right things.
Good work!!! I have a draft on this subject in the works!!! Now I will pick up where you leave off.
Between the submission of the first draft of my book manuscript (about gen AI and writing) and the final revision, I added two chapters on reading because I had a similar epiphany to what you articulate here, that students were being encouraged to avoid reading, denying them that critical thinking experience, where the intersection of reader and text allows a new idea not in the text to form. Without that process, those Ideas don't come into existence.
To me, it looked a lot like what's happened with writing instruction, allowing a simulation to substitute for the genuine article because that simulation can pass muster for the purposes of schooling. This attitude pre-dates gen AI, also, but gen AI accelerates things in a way that makes me scared we'll abandon some of the important experiences of reading the same way writing is at risk.
I appreciate your insights on this. The title popped up in my email today and I had to read it immediately. At my high school site we have been developing grade level teams to determine a focus language domain (ELD standards) for each grade. Each of our teams independently and overwhelmingly agreed that B.6: Reading Closely, was the most important skill that our students needed and are currently under prepared for. I'm sharing your article with all of them now. Thank you.
In the spirit of John Warner's argument that ChatGPT can't kill anything worth saving, I want to echo your point that generative AI as it currently exists is only good at summary and does not perform close reading and analysis well. That would mean the value of teaching practices that focuses on developing close reading skills should increase at all levels of instruction. If ChatGPT can do your homework, that means your homework has little educational value. In terms of reading, it doesn't seem that generative AI is providing anything substantively different than SparkNotes. The utility of close reading is that thinking deeply about a passage leads to insights about language and its relation to experiences grounded in social contexts. I find that a valuable skill, one that AI in its current forms has little ability to augment. If our response to generative AI is to refocus instructional time and effort on helping our students develop skills to closely analyze text and cultural artifacts, we will accomplish something that needed doing anyway.
Good points, all of them. I think using Hypothes.is this way is a great idea. While I am an instructional technologist now, I did my undergrad and graduate work in history. One of the pivotal moments of my undergraduate career was when a grad student taught me how to approach a book, H.M.D. Parker's Roman Legions. It had never occurred to me to look at the bibliography after reading the preface to get an idea of the depth and scope of the research. It was a valuable lesson, and the scene is still fresh in my memory. The point, of course, is that this is another thing that having an AI summary defeats. It wasn't that someone told me to do this, they sat down and showed me by example. That was valuable. I also wonder how much would have been lost in the summary of Parker's arguments about the Antesignani, which I recall puzzling me at first but were worth working through to understand something about how think about what sources tell us about Roman legions.
Thanks, Guy! I, too, read History as an undergrad and could have never understood Procopius's Secret History of Justinian if I didn't conduct close reading on my own and look at the work of other scholars and how they complicated/ illuminated aspects.
From 31 years ago...
https://dailypapert.com/obsolete-skill-set-the-3-rs-literacy-and-letteracy-in-the-media-ages/
Discuss
If students use AI to skip reading a text their professor considers central to attainment, that is a problem; if they use it to improve their understanding and focus their rereading, that is....awesome. Our underfunded school doesn't provide anything like that kind of support, and most of our students need more help with college-level reading comprehension than our faculty can provide.
I think that's ultimately the tension here. Students can use AI reading assistants in ways that support learning, not offload it. But doing so takes structure and intentional pedagogy. I worry that many underfunded schools won't be able to provide that structure in the first place and AI reading will become a sort of default that some educators expect, like spell check on Word Processors.
I am hoping an entity like Khan Academy (for altruistic reasons) or Pearson (for profit motives) will provide a purpose-built AI collaborative reading assistant. Ideally, it would also help the professor assess the reading assignments and make course corrections before students do poorly on the tests/essays/speeches the readings were to have informed.
"Learning has been reduced to a problem" - brilliant capture of this idea. It's been bothering me lately how so many non-problems, as Kate Manne calls them, get re-framed as problems in the pursuit of selling the idea of a solution.
For what it's worth, in my conversations with working professionals about how they feel about genAI, one of the reasonably common concerns is skill atrophy. Skills are valuable not only for their marketability, but also for the intrinsic satisfaction that executing them offers, and people are reluctant to give that up in exchange for a tidily finished product.
"Non-problems" source: https://katemanne.substack.com/p/on-bodily-non-problems-with-a-name
A counter argument might be to double down on tools or capture objectives achieved by them AI or LLMs. And in the process preserve the qualities of close reading you are trying to achieve?
I somehow see exponential potential in enhancing their learning ability with these new tools. But done proactively, not passively to speed read or summarize without comprehension. Hear me out (these are personal views without prejudice or conflict, based on my own teaching journey done in practice/industry).
On the assumption close reading is trying to achieve some of these:
- deepen students' understanding of a text,
- promote critical thinking, and
- develop analytical skills
E.g.
1. For AI-generated questions and prompts: Tools like TextHelp's Read&Write or Quillionz can automatically generate comprehension questions based on the text, encouraging readers to think critically about key concepts and themes.
2. Personalized recommendations: Platforms like Goodreads or Amazon's Kindle use AI algorithms to recommend books based on a reader's past preferences and reading habits, guiding them towards texts that align with their interests and reading level. Or just ask ChatGPT. Feynman's how do I understand this like I'm 5?
3. Interactive elements: Apps like Epic! or Novel Effect incorporate interactive features such as quizzes, annotations, and multimedia enhancements e.g. animations, fostering engagement and deeper exploration of the text.
4. Collaborative discussions: Platforms like Perusall or Padlet enable readers to annotate and discuss texts collaboratively in real-time, facilitating peer learning and the exchange of diverse perspectives.
5. Diverse perspectives: Tools like Microsoft's Immersive Reader or Project Naptha utilize AI to translate text into different languages, adjust reading levels, or provide alternative formats such as audio or braille, making texts more accessible to a wider range of readers and promoting inclusivity.
Now the cool stuff - To encourage critical thinking and analysis in AI-assisted reading:
6. Text analysis platforms: Tools like Voyant Tools (used your chapter- https://voyant-tools.org/?corpus=f31d7f49a48f6b8ffa04018c316e9795) or Lexos allow users to perform text analysis, including word frequency analysis, topic modeling, and sentiment analysis, providing insights into the text's themes, language use, and emotional tone.
7. Argument mapping software: Platforms such as Argumentative or MindMup enable users to visually map out arguments and counterarguments within a text, helping readers identify key points, evaluate evidence, and construct reasoned responses.
8. Annotation and note-taking tools: Apps like Hypothesis or Notion offer features for annotating texts and taking structured notes, facilitating active reading and the organization of thoughts and observations.
9. Socratic questioning bots: AI chatbots like Socrates (Socratic Lab) or IBM Watson's Debater (just sunsetted 1st May 2024) use natural language processing to engage users in Socratic questioning, prompting critical reflection and deeper exploration of the text's meaning and implications. There are others - Debate Devil, Debate AI, etc. 70+ References included here: https://topai.tools/s/debate-tool
10. AI writing assistants: Tools such as Grammarly or Hemingway Editor provide feedback on writing style, grammar, and clarity, encouraging writers to revise and refine their arguments and interpretations.
You dont need all. But the spectrum is indeed wide. Failing which many of what these tools do (objectives wise) can be prompted or programed into function via APIs e.g. Chat GPT 4, Gemini's, Claude equivalents.
While close reading emphasizes deep engagement with the text, the integration of AI-assisted reading tools can enhance this process and potentially lead to outcomes surpassing those of traditional close reading in several ways e.g.:
A. Efficiency: AI tools can quickly analyze large volumes of text, identify patterns, and generate insights that may not be immediately apparent through manual close reading alone, saving time and enabling readers to delve deeper into complex texts.
B. Personalization: AI algorithms can tailor recommendations, questions, and annotations to individual readers' preferences, learning styles, and comprehension levels, providing a more personalized and adaptive reading experience that meets the diverse needs of learners.
C. Accessibility: AI-driven features such as text-to-speech, translation, and adaptive formatting make texts more accessible to a wider range of readers, including those with visual impairments, language barriers, or learning disabilities, promoting inclusivity and equity in education.
D. Collaboration: AI-powered collaborative tools facilitate peer learning, discussion, and knowledge sharing among readers, creating opportunities for collaborative sense-making, collective problem-solving, and the co-construction of meaning beyond the limitations of solitary close reading.
E. Enhanced analysis: Text analysis and argument mapping tools enable readers to explore texts from multiple perspectives, uncover hidden connections, and critically evaluate arguments, fostering higher-order thinking skills such as synthesis, evaluation, and creativity that go beyond the scope of traditional close reading.
Wow. Thanks for sharing your perspective. What a deep and complex thinker you are.
Not really Lynn. Just thinking no one has definitive answers/solutions (not looking for any either). So anything goes. I believe in possibilities too. Or leverage, which comes in varying forms. P.s. also been on both (1st) the sell side, then buy sides. Imperfect to the hilt! Guessing you probably know better too. What If this is the Wild Wild West? 😄
Sounds like we have had similar experiences and perspectives that only come from observing, learning, failing, and then adapting. Without uncertainty there are no possibilities, so it is more fun to think of it as the Wild West than trying to control things we can’t control. It is fun to explore the different points of view in these discussions. 🙏😊
Eye Eye Captain!!
Some great points made here, thank you, Marc. First, I want to state that this is another clear reason why we must teach AI Literacy to all students. I express AI Literacy as being comprised of Awareness, Capability, Knowledge, and Critical Thinking. Within Critical Thinking is the vital aspect of avoiding overreliance. "Overreliance" is a negative thing if we unwittingly lose skills and capabilities to a system such as generative AI. This is bad thing if it is not done purposefully and is done without taking second and third order effects into consideration. An example would be cursive writing. Anyone that is close to my age remembers have to take many classes devoted specifically to cursive writing. For a long time, even dissertations HAD to be hand written, because good handwriting was an important professional skill. Then, thanks to the proliferation of type writers, computers, and printers, that must have skill was "let go." - I'm not saying good reading ability is something to be let go. I am simply giving an example of overreliance and the importance of being aware of it so that it is purposefully addressed and considered.
We do need to inform student of the importance to good reading, but at the same time we in academia need to also be realistic with ourselves. I remember being a student and having too much reading to do. It was impossible. I often had to skip some sleep, skip meals, or workouts, or something else because I had too much reading to do. I dissentingly remember thinking to myself, "I wish I could read a summarized version of this with the specifics of what I need for the assignment." AI can help with that, but as you expertly pointed out, it comes at a price, meaning the student doesn't gain a deeper understanding. - Yet this is the reality of higher education and it has been for a long time. As with everything a proper middle ground is needed.
Judging from all I have been reading here and in the comments, may I suggest a paradigm shift in thinking that reading well is a skill to be acquired? While learning math and practicing the piano can surely be considered skills, reading depends on prior knowledge and language competence. There is much research that supports the finding that the best readers are the ones who know more about the topic being read than any other variable being tested. Use AI to provide background knowledge then? Perhaps, but I see that as more a teacher's responsibility as students need teachers to prepare them to do a reading. Use AI to simplify the language of a text? Maybe, but language modification can achieve only limited gains as it does not address the lack of knowledge issue. How then to use AI? As students read, they need the text EXPLAINED . . . to be connected to what they already might know about what they are reading. Bring on the AI bots that can do that and then let close reading proceed. Yes, that means using the explained text as a bridge to the more complex text not as the only text that is being read.
Excellent (and alarming) points. I can see these tools appealing very much to my college kids, and I selfishly am glad they are as old as they are and have developed some good close reading skills already. They enjoy fiction, and can make their way through course texts. Having these tools readily available for younger students still at the start of building those critical reading and comprehension skills is very concerning. I agree we’ll see long term impacts of this.
I agree with your take on this. As a just-retired English teacher, I saw kids reading less than ever, and am very concerned about the now relying on AI to read for them. I’m posting about these issues on my “AI is For Sheep” Substack.
If you substitute ‘walking’ for ‘reading’ in this piece, it becomes clearer how deskilling AI summaries are. If I never walked, how could I learn to actually walk? If you use a tool to do a task, the skill you learn is how to use the tool not the task. If the value of the tool use skill is greater than the skill it is a fair trade off; if not, you have lost out
https://bookshop.org/p/books/how-to-read-a-book-revised-and-updated-mortimer-j-adler/1408400
Tell your students to read this and they might see the importance and value of reading texts! this book really inspired my reading addiction!