Tim Wu, in his recent book, The Age of Extraction: How Tech Platforms Conquered the Economy and Threatened Our Future, examines the timeline of a variety of platforms and the manner in which they consistently morph from being initially attractive, innovative, and genuinely helpful resources into systems that become confining, controlling, and ultimately draining for their users. Using examples that range from Facebook and Amazon to UnitedHealth he argues that this transformation, from open utility to extractive gatekeeper, is not an accidental side effect, but rather a predictable, structural characteristic of platform business models as they achieve scale and market dominance.
In considering the examples from Wu’s book it occurred to me that while he emphasized the major players a wide variety of people use, the same issues apply to smaller platforms. Those of us who write and use platforms to share our work (e.g., Substack, Reddit, Medium) have likely experienced the same timeline.
Many authors who write books with a similar message to The Age of Extraction do a great job of explaining the problem and its history, but even though they make an effort offer little as a remedy. I have read many such books. I typically find myself contemplating but failing to generate suggestions to augment what the author was able offer.
Like Wu, I bought into the original promise of the Internet as a leveling platform that would give content creators, sellers, and the “little guy” in general greater opportunities. In the early days (2002), I started a blog and did so from a server that was also my desktop computer (I worked at a University and had a dedicated IP which was more of the challenge than the ease with which any Mac could be used as a server). Things change. I now pay a hosting company a couple hundred dollars a year to allow me to run blog software and the related backend database and register my domain name. Still, as a hobby, once I pay for the space, I can function independently.
I believe the way we create and share content has changed. You can still do it, but it seems you have fewer and fewer regular readers. I have noticed a change that suggests more and more of my posts are read through search rather than by readers who regularly view the blog. I track hits out of curiosity and find little immediate interest in most posts. I check say a year or six months later and find that some posts have been read hundreds of times. Logically, I interpret this to mean I have written something that people found through search. I shouldn’t complain about this, but the switch from pure search to AI search now being developed by the big platforms means there will be far less attention to source material when an AI summary based on this homogenized and integrated material is made available. This is an emerging but I think obvious issue and a perfect example of what Wu means by platform extraction.
The big switch (another book) to focus on extractive platforms has resulted from a) integrative platforms such as those I have already mentioned hosting multiple content creators and b) a related move away from the use of RSS readers by individual consumers. I certainly understand the benefits of single-stop platforms that provide a convenient way to reach a wide audience. My complaint is based on the history of these platforms. The pattern of extraction is evident. Start by offering a service in which the platform and content creators share in the risk and the rewards, and once a critical mass for a network effect is achieved, reduce the benefits to the producers and to the consumers. Wu suggests Amazon makes a familiar example of this approach.
I do post my content to one of these community platforms and continue to post the same content to my own blog. Yes, this means I pay twice and I continue to be frustrated by this situation. One approach allows me to own my content and the other to reach a larger audience – for a price.
My solutions:
I do have suggestions for an alternative approach, but I understand that each requires an effort that most consumers are unwilling to invest. You can be your own platform with easy-to-use tools.
Use Google Alerts – Yes Google is a big company, but it does offer some beneficial services. Google Alerts might be imagined as a period search process based on specific interests you specify. You provide a typical search request, then select how often you want to receive the results. Updates are sent to you in an email periodically according to the time intervals you request. I have multiple alerts that generate a week list of new content. In this approach, you are following a topic rather than specific content creators.
RSS is still around and modern readers make the process easy to implement. With RSS, you designate the sources (e.g., specific blogs) you want to follow, and an RSS reader accumulates new content generated by these sources. You check in to your reader when you have time and see what is new. Some contend that Google’s abandonment of its very popular Reader in 2013 signaled the end of this tool category, but more modern alternatives have since emerged.
Yes, RSS readers do offer a subscription level and any provider realistically has costs. While the pro level offers great features, most users will find the free level meets their needs.
My preference is for web-based readers – the service is accessed through a browser rather than standalone apps. Feedly is my recommendation. I like Inoreader and Reeder (Apple) as apps.
I have written more detailed descriptions elsewhere (Feedly, Inoreader) and you could consult these sources if you need more information.
Summary
I didn’t really intend this post as a book review, but Tim Wu’s book is interesting and informative. As I suggested, the book identifies the typical timeline of extraction consumers should recognize and use to guide their decision making. Again, solutions, should that be what you are seeking, are not easy to imagine.
I think we have a classic “chicken and egg” problem with platforms versus independent sources. Content creators will go where their content is more likely to be consumed. Tools for sharing will exist and be improved where there are content creators and content consumers.
For the great majority of creators and consumers, the motivation of income is deceptive and a trap. Most writers would seem better off thinking of their goal as visibility rather than profit. Writing for a platform for the vast majority should be treated as a hobby, recognizing the reality of being trapped by the network effect.
I became interested in the development of writing skills through feedback focused on alternatives to the teacher or professor as editor. I worked with educators who developed writing skills and was acquainted with the time demands of providing feedback and had my own experience reviewing students’ theses and dissertations. When you have read the 200+ page dissertation of a Ph.D. candidate through a couple of drafts, you have put in some hours. I felt sorry for the English department English composition adjuncts paid a few thousand for each of 4 sections of 25 students and the time it would take to review multiple writing assignments. Still, you learn to write by writing, and feedback and rewriting in response to feedback are essential.
There are ways to provide an acceptable alternative source of feedback. Peers and now AI can critique writing, and while some more expert involvement is important, the quantity and diversity of learning activities required for skilled performance cannot consistently be monitored by instructors.
I began reviewing the research on peer editing because I was aware of the time issue faced by instructors, but also because I was interested in the role digital word processing tools could play in the feedback and revision processes. For example, Google docs offers a great way to add comments at precise locations in a document and to exchange related remarks as a document is passed back and forth between the writer and reviewer. Revision is efficient and can be explained if the editor wants to take a second look. I thought that Goodle docs offered an example of a tool that would improve the efficiency with which learners could interact with peers and then rewrite efficiently in response to comments.
As I reviewed the research literature, I came across some studies that changed my thinking on how I should advocate for peer feedback. These studies (see Cho references at the end of this post) demonstrated that peer editing also had an impact on the writing performance of the editors, and this benefit might be more important than the feedback a writer received from others. The Cho research focused on a specific population of writers generating a particular type of writing product, and understanding the focus of such research is always important in considering how and if findings might generalize to other situations. Cho focused on college students writing lab reports, i.e., the description and results of experiments performed in the lab. I know my own profession has an undergraduate course (Research Methods) with a core focus on the same type of writing task. Cho conducted several studies in which peer editing was a component. Students could either review their lab reports without feedback, with feedback, or with feedback after providing feedback on the same task to other students. The greatest difference was found when writers also provided feedback to others. When it came time to revise their own original drafts, the product they produced was judged to be superior, on average, to the products generated by those in the other groups. Moreover, statistical analysis showed that editing had a more powerful impact than having the edits of others to review.
The researchers offered two possible explanations for their findings. First, they proposed that the process of editing provides a perspective on how others might view a written product (audience effect). Writers are always told to consider their audience, but perhaps serving as the audience might provide insight into what that means for a specific written product. The other explanation involved what I would describe as a generative effect. Serving as an editor has some similarities to the research topics of writing to learn and teaching to learn. When you must externalize a position you take, this forces a concreteness and specificity you may fail to generate when just thinking about something. Having to put a position into words can lead to the understanding that you really can’t explain yourself or make you work to come up with a concrete way to express what you think.
This notion that working to improve understanding and develop proficiency seems to be raised repeatedly as educators grapple with the role AI should play in educational settings. For all of the ways AI might reduce “busy work,” there seems to be a related potential that AI provides a way to avoid the cognitive work so necessary in developing a cognitive skill. So, while AI may provide a way to provide feedback to students, there is also evidence that the work of providing feedback to others involves work that is productive both for others and for yourself. Educators face a significant challenge in communicating this reality to learners and other stakeholders.
When it comes to how we use technology, familiarity can limit analysis and exploration. I started thinking about this challenge when encountering the work of an academic who has examined the history of word processing. When I first wrote about word processing in the 1990s, the issues were similar to current topics of whether students should read from paper or screen and whether it was better to take notes on paper or on a laptop. There were comparisons of which method was more productive and efforts to account for the advantages that were identified. It was once similar with word processing. Should students learn to write on paper or using a computer? What were the advantages and disadvantages of each approach? How might the instruction of writing skills with computers be modified to take advantage of the unique capabilities of a digital approach? My thought is that many are now no longer aware of these questions and conclusions and that personal practice and instructional emphases may ignore key findings. This concern seems especially relevant given the new issues raised by the use of AI in writing and learning to write.
I decided to write again about this topic after listening to an interview with Matthew Kirschenbaum on the “This Week in Tech” network’s “Intelligent Machines” podcast focused on Kirschenbaum’s recent focus on the role of AI in writing and learning to write. The podcast guest was a member of the Modern Languages Association (MLA) panel, generating what are likely to become several influential position papers on learning to write and AI. This interview, which makes up maybe the first half hour of the podcast, is worth the attention of any educator trying to make sense of how AI will impact schools and universities. As part of the brief introduction of the podcast guest, Krischenbaum it was noted that the guest had recently written “Trach Changes: Literary History of Word Processing”.As I suggested, word processing had been a personal interest so I did purchase and read the book.
It wasn’t that the book wasn’t well written, but I did struggle to get through it. The podcast focus resulted in my misunderstanding of the topic of the book. The history of the transition from writing on paper and typewriter was of some interest, because I lived through that transition and the mention of technology hardware and software and the required skills involved in writing with a computer brought back plenty of memories. I was less interested in which noted author had made his or her transition from a notepad or typewriter to a word processor during their career. Concerns of the reading community related to how technology might influence literature likely offers similar insights into what some think about AI. A better example might be how Bob Dylan’s fans reacted when he switched from acoustic to electric guitar. What I had falsely anticipated was that the author would examine how digital storage and revision changed writing and the teaching of writing.
I imagined I would encounter an analysis of changes in personal revision, educator feedback and learner revision, peer revision, and possibly even AI as a sounding board for a writer’s efforts. These are the topics in what I see as the evolution of writing and writing education. I decided to generate a post that would offer my own thoughts about the role of word processing in the writing process. The podcast and the book on word processing are still worth your time.
Will digital tools change our writing?
I assume you complete many of the writing tasks you take on using a word processing application. Do you do this because you assume this approach makes you more efficient or do you assume this approach makes you a better writer? Maybe you have never even thought about these questions. However, when functioning as a teacher and asking your students to engage in activities in a particular way, it may be helpful to consider why the approach you expect students to use will be productive. Often, to realize the full potential of an activity, the details matter and some insight into why an approach is supposed to be productive may be helpful in understanding which details to track and emphasize. The following comments summarize some ideas about the value of word processing and of learning to write using word processing applications.
In learning, as in other areas of life, you seldom get something for nothing. Still, a logical case has been proposed for how simply working with word processing for an extended period may improve writing skills and performance. Perkins (1985) calls this the “opportunities get taken” hypothesis. The proposal works like this. Writing by hand on paper has a number of built-in limitations. Generating text this way is slow, and modifying what has been written comes at a substantial price. To produce a second or third draft requires the writer to spend a good deal of time reproducing text that was fine the first time, just to change a few things that might sound better if modified. Word processing, on the other hand, allows writers to revise at minimal cost. They can pursue an idea to see where it takes them and worry about fixing syntax and spelling later. Reworking documents from the level of fixing misspelled words to reordering the arguments in the entire presentation can be accomplished without crumpling up what has just been painstakingly written and starting over.
With word processing, writers can take risks and push their skills without worrying that they may be wasting their time. The capacity to save and load text from some form of storage makes it possible to revise earlier drafts with minimal effort. Writers can set aside what they have written to gain new perspectives, show friends a draft and ask for advice, or discuss an idea with the teacher after class, and use these experiences to improve what they wrote yesterday or last week. What we have described here are opportunities—opportunities to produce a better paper for tomorrow’s class and, over time, opportunities to learn to communicate more effectively.
Do writers take the opportunities provided by word processing programs and produce better products? The research evaluating the benefits of word processing (MacArthur, 2006; Wollscheid, Sjaastad, & Tømte, 2016) is not easy to interpret. Much seems to depend on the experience of the writer as a writer and familiarity with word processing, and on what is meant by a “better” product. If the questions refer to younger students, it also seems to depend on the instructional strategies to which the students have been exposed. It does appear that access to word processing is more beneficial for older learners and some even interpret this difference as having a neurological basis (Wollscheid, Sjaastad, & Tømte, 2016). General summaries of the research literature (e.g., MacArthur, 2006) seem to indicate that students make more revisions, write longer documents, and produce documents containing fewer errors when word processing. However, the spelling, syntactical, and grammatical errors that students tend to address and the revision activities necessary to correct them are considered less important by many interested in effective writing than changes improving document content or document organization. The natural tendency of most writers appears to be to address surface-level features.
Writers appear to bring their writing goals and habits to writing with the support of technology. Beginning writers and perhaps writers at many stages of maturity may not have the orientation or capabilities to use the full potential of word processing, and their classroom instruction may also emphasize the correction of more obvious surface errors. Thus, there are typically improvements in the products generated when working with word processing tools, but the areas in which younger writers seem to improve are not necessarily the most important ones
Many of the potential educational advantages of word processing appear only as students acquire considerable experience writing with the aid of technology and some question whether using a keyboard is better than a pencil for young writers (Wollscheid, Sjaastad, & Tømte, 2016). Perkins’s (1985) argument that writing with word processing programs will improve writing skills because word processing allows students to experiment with their writing makes sense only in situations in which students have written a great deal and experimented with expressing themselves in different ways. The fact that most research evaluating the benefits of word processing has examined performance over a short period of time, with students having limited word processing experience, thus represents a poor test of the potential of word processing (Owston, Murphy, & Wideman, 1992). Research based on a three-year study following elementary students as they learned to write with and without access to word processing opportunities has demonstrated a significant advantage for students with ready access to technology (Owston & Wideman, 1997). A recent study (Yamaç, et al., 2020) examining the benefits of consistent writing on laptops found a similar advantage in contrast to paper and pencil writing tasks for early elementary learners. These researchers point to social media activities such as blogs and multimedia writing with tablets as expanding the writing opportunities available in classrooms.
The National Assessment of Educational Progress (NAEP) demonstrates that in the U.S. greater experience writing with technology is predictive of schools with more proficient writers (Tate, Warschauer & Abedi, 2016). Studies such as this are still controversial as it is difficult to parse out other variables such as the income levels of the majority of students in different schools that may influence both access to technology and writing proficiency. Overall, the role of word processing in developing writing skills depends on the goals of the teacher and individual students, the social context provided for writing, and the amount of writing that students do with the assistance of word processing.
Summary
Many of the posts I write concern the cognitive processes involved in learning, thinking, and academic behavior. Often, I focus on how these processes are impacted for good or bad by involving technology. We seem to be past the point at which educators question writing on a computer, but the distinction I raised between opportunities get taken and desirable difficulty have yet to be resolved with writing. This is clearly the case when educators debate the role AI should play. My suggestions related to the opportunities get taken hypothesis should also be approached would even be that we examine whether the opportunities (often called affordances) of revision are actually employed. Do students get useful feedback from which they might learn to improve what they have written? Despite the likely benefit of revision, do students quantitatively do much revision? Perhaps like other ideals (tutoring, personalizing learning) that are impractical for one reason or another (e.g., cost, teacher time), AI might find a productive role in guiding revision experiences.
References:
MacArthur, C.A. (2006). The effects of new technologies on writing and writing processes. In C.A. MacArthur, S. Graham, & j. Fitzgerald (Eds.) Handbook of Writing Research, pps. 248-262. New York: Guilford.
Owston, R., Murphy, S., & Wideman, H. (1992). The effects of word processing on students’ writing quality and revision strategies. Research in the Teaching of English, 26 (3), 249–276.
Owston, R., & Wideman, H. (1997). Word processors and children’s writing in a high-computer-access setting. Journal of Research on Computing in Education, 30 (2), 202–220.
Perkins, D. (1985). The fingertip effect: How information-processing technology shapes thinking. Educational Researcher, 14, 11–17.
Tate, T. P., Warschauer, M., & Abedi, J. (2016). The effects of prior computer use on computer-based writing: the 2011 NAEP writing assessment. Computers & Education, 101, 115-131.
Wollscheid, S., Sjaastad, J., & Tømte, C. (2016). The impact of digital devices vs. Pen (cil) and paper on primary school students’ writing skills–A research review. Computers & Education, 95, 19-35.
Yamaç, A., Öztürk, E., & Mutlu, N. (2020). Effect of digital writing instruction with tablets on primary school students’ writing performance and writing knowledge. Computers & Education, 157, 1-19.
I began working on a post about the similarities of expressive writing and writing to learn some days ago. In the meantime, the stock market and the general attitude of the country took a decided nosedive. I could not ignore a possible interaction between this dramatic negative mood swing and the original focus of expressive writing so I will just recommend writing to those struggling to deal with our present political crisis and encourage you to read the rest of the post to learn why.
Dr. Jamie Pennebaker found a use for writing that produces both consequential and fairly consistent results. His results relate to clinical psychology which is somewhat outside my own background as an educational psychologist, but I at least can appreciate the impact of an intervention that can be classified as both consequential and fairly consistent as such outcomes are less common than others might imagine when it comes to impacting human behavior. Pennebaker asked college students to think of a traumatic experience from their own lives. His instructions – think about your feelings and emotions related to this experience. I want you to write about this experience for 15 minutes. I will have you do this for three straight days. What you write will be confidential – no one will read what you write. A control group (randomly assigned) was asked to write about their daily routine for the same periods of time. The researchers conducting this study then followed the number of student visits to student health in the following months and found that what Pennebaker eventually described as the expressive writing group had significantly fewer visits. Writing appeared to have an impact on mental health.
I know this seems on the level of magic or weird as I can imagine many reasons this connection might not materialize. Even if the treatment had an immediate consequence on the “problem” why would it follow that the results would be related to medical issues? What if the “problem” was an issue they experienced in their childhood? Why would such a random task during their college days have an impact?
I can’t answer these questions, but hundreds of follow-up studies have produced related results. Pennebaker and other researchers found that expressive writing could enhance immune function, lower blood pressure, reduce muscle tension, and even decrease doctor visits. These benefits were observed across various studies involving participants with both physical illnesses (e.g., arthritis, asthma) and mental health challenges. There has to be something to the benefits of writing.
I first encountered the concept of expressive writing not through my prior work as a psychologist, but because of an interest in the benefits of keeping a notebook. Pennebaker’s work was described in one chapter of Allen’s book “The notebook: A history of thinking on paper”. Once I became interested, I conducted literature searches that might point to an explanation for what about writing might produce this impact. Meta-analytical papers are relevant to the goal of why things work as they do because such papers examine many studies on a given topic, successful and successful experiments, and attempt from this variety of studies to determine what are the factors that contribute to successes and failures. The logic in this approach is that the differences are key to understanding why a technique might be successful and what are the boundary conditions.
The following are the suggested explanations for the benefits of writing.
Catharsis without social risk. You have likely heard of an LBGTQ+ individual “coming out”. This decision when public provides a release from feelings that you have to hide who you are and what you feel. Perhaps expressive writing works in a similar way even though writing is private. This is my example of how catharsis works and I hope this comparison is appropriate.
Cognitive-processing theory. Writing requires concreteness as the abstract and fuzzy ideas in your mind must be made concrete as the ideas are put down on paper. Pennebaker built a digital tool for identifying keywords and concepts in what was written (not in the original study promising anonymity). Those participants with more positive outcomes made greater use of causation words (e.g., because, cause, effect) and insight words (e.g., consider, know) in the content they produced. Perhaps writing helps work out why something happened to you and how significant long term consequences might actually be.
Self-regulation theory. Being able to label stressors and challenges may give the writer a greater sense of understanding and control reducing negative affect leading to greater confidence in better outcomes in the future.
Generative processing as a general explanation for the benefits of writing
I have tried to translate some of these clinical concepts into something more familiar to me. I see similarities in learning and study techniques described as generative learning. In past posts on generative activities, I have explained that the use of a self-imposed or assigned external task encourages productive mental activities. In other words, a learner has the capacity to apply process productively, but for one reason or another does not. The external task (e.g., answering questions, writing summaries, explaining to a peer) encourages these productive thinking behaviors in order to perform the external task and better understanding and retention is produced as a consequence. The cognitive processing of emotional issues may similarly be manipulated by a concrete external task (i.e., expressive writing). This way of thinking seems to fit with the theoretical proposals in the meta-analyses I listed and I think offers a tangible approach that is easier to understand and communicate.
I can’t help thinking about AI as I write this post. How might one encourage tangible “externalization” and processing of life experiences? You may have heard of ELIZA which while not AI could carry on a conversation of a sort through the use of some clever programming that used language patterns built on the input from a user to generate responses and encourage further input on their part. The Wikipedia link in the previous sentence offers more detailed information. Current large language models can now do far more. AI therapy exists and is controversial, but how different is chatting with CHATGPT and writing something you know no one will read?
What about Trump and the stock market? I will write something and put it on Facebook and I do hope someone reads it.
Sources:
Allen, R. (2024). The Notebook: A History of Thinking on Paper. Biblioasis. (Chapter 24)
Frattaroli, J. (2006). Experimental disclosure and its moderators: a meta-analysis. Psychological bulletin, 132(6), 823-865.
Fiorella, L., & Mayer, R. (2016). Eight Ways to Promote Generative Learning. Educational Psychology Review, 28(4), 717-741.
Guo, L. (2023). The delayed, durable effect of expressive writing on depression, anxiety and stress: A meta-analytic review of studies with long-term follow-ups. British Journal of Clinical Psychology, 62, 272–297. https://doi.org/10.1111/bjc.12408
Pennebaker, J. W. (1997). Writing About Emotional Experiences as a Therapeutic Process. Psychological Science, 8(3), 162-166. https://doi.org/10.1111/j.1467-9280.1997.tb00403.
This is a personal exploration of what I think about the role of AI in writing and reading. Once you begin exploring these topics I think you discover how nuanced they are. I do understand outlets for written content are being pressured or have decided on their own to take positions on what is allowed. I will offer a suggestion at a later point.
Writing
We all make observations based on personal experience. I am a writer and as an academic wrote research papers and a couple of textbooks. This writing was before AI and there were strict rules of personal accountability that applied that were severe enough that your career would be at stake if these expectations were violated.
As an educational psychologist I followed the literature on learning to write and the benefits of writing to learn. Writing is a procedural skill and as such requires the use of the skill to develop proficiency. I believe that this proficiency transfers to speech so there is no way I can imagine of developing important communication skills without spending time using the skill. In academic situations writing is a more efficient group activity than individual presentations so time must be invested. Writing to learn seems an efficient way to develop writing skills and has unique benefits as a way to process all experiences. Many of my posts focus on generative activities – external tasks that encourage productive cognitive skills – and writing makes a great example. Organization, integration, personalization all are required in writing and in understanding and application. Again, writing assignments are an efficient way of encouraging personal cognitive activity within a group setting.
These personal benefits aside how important is it that I write without assistance. “Without assistance” is key here as I can simply provide a prompt to an AI tool to create a product based on fairly basic expectations. This is one extreme of the AI in writing continuum. At the other end are spelling checking and the types of structural improvements I can apply with the assistance of Grammarly. In the middle are various strategies I might use to request AI to offer suggestions for topics and broad organizational ideas I might then implement myself. Closer to the “write it for me end” are requests for a product I might then paraphrase. My guess is that the line of acceptability is drawn somewhere within this continuum and will likely shift over time.
Reading
The basic question I am asking here is does it matter that the content I read was written unaided by a person? First, I should acknowledge that while I read a lot, I seldom read fiction. I seldom read content that depends on the creativity of the writer. I understand that is reasonable to recognize the beauty or creativity in much the same way different musicians can express the same underlying composition. I seldom focus on such skill in the authors I read. I want to understand why things are as they are whether it be history, science, economics, or politics. If facts are available, I want to know the facts. If opinion and logic are all we have, I want to understand the logic behind the valued opinions. Good writing is important in my ability to understand and process this content, but I am not certain that the human touch is required for a quality product.
Clearly, what AI is doing is summarizing massive amounts of content that was generated by humans and I do think that this source material is essential, but I am not certain that the translation process requires a human writer. Human writers will continue to be necessary to make the observations and run the experiments and explain what they have observed, but this type of communication is several steps down the food chain from my consumptions.
Why post this here?
I think outlets are making decisions about what role AI will be allowed to play. I think some outlets will opt for human writing only and I think this is fine if the goal is to focus on human unaided creativity.
I think there is a middle ground that has just recently occurred to me. I write based on a tradition that requires careful source citation. I still do that in some of posts here when what I write had its origin in a book or journal article. Why not indicate when a segment of what is posted was written by AI?
Out of curiosity I asked Perplexity if there were conventions for citing AI as a source. It turns out there are formal ways to cite AI content. I think there are ways to make AI content more obvious. One might indicate it as quotations that appears in an obvious way such as the italicized and indented style used in WordPress. Or, one could do something like the following. This is what Perplexity had to say about AI sourcing.
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To attribute AI-generated text in your writing, follow these guidelines:
1. **Explicit Mention**: Clearly state that AI assistance was used. For example, “This section was generated with the help of OpenAI’s ChatGPT” or “Drafted in collaboration with ChatGPT”[2].
2. **Citation Styles**:
– **MLA**: Format as: *”Description of chat” prompt. Name of AI tool, version, company, date, URL*. Example: “Explain how to bake a cake” prompt. *ChatGPT, Mar. 2025 version, OpenAI, 2 Mar. 2025, chat.openai.com/chat*[1][2].
– **APA**: Include the tool name, date, and URL. Example: *OpenAI. (2025). ChatGPT (Mar 2025 version) [Large language model]. https://chat.openai.com/chat*[2].
– **Chicago**: Example: *Text generated by ChatGPT, OpenAI, March 2025, https://chat.openai.com/chat*[2].
3. **Placement**: Place attribution prominently in an introduction, acknowledgment personal section, or footnote to ensure transparency[2].
4. **Accurate Language**: Use terms like “assisted by,” “enhanced with,” or “generated using” to describe the AI’s role without overstating its contribution[2].
This approach ensures ethical transparency while crediting AI appropriately.
Sources
[1] Citation and Attribution – Generative Artificial Intelligence https://libguides.brown.edu/c.php?g=1338928&p=9868287
[2] Demystifying Attribution: Giving AI Credit – LinkedIn https://www.linkedin.com/pulse/demystifying-attribution-giving-ai-credit-donna
[3] Used a AI-Detector on my own text that I have writen … – Reddit https://www.reddit.com/r/ChatGPT/comments/14cls37/used_a_aidetector_on_my_own_text_that_i_have/
[4] Using the AI Autofill Feature for Text Attributes – Help Center https://help.plytix.com/en/ai-autofill
[5] A Comparison of Several AI Techniques for Authorship Attribution on … https://www.mdpi.com/2227-7390/10/23/4589
[6] Is there any tool which can detect AI writing. Because ChatGPT itself … https://www.reddit.com/r/SEO/comments/13s5zb0/is_there_any_tool_which_can_detect_ai_writing/
[7] How To Identify AI-Generated Text? – Originality.ai https://originality.ai/blog/identify-ai-generated-text
[8] Measuring Attribution in Natural Language Generation Models https://direct.mit.edu/coli/article/49/4/777/116438/Measuring-Attribution-in-Natural-Language
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Summary
These are my personal thoughts about AI in writing and reading. I don’t see AI going away so I believe it is important to work out what is appropriate and what not. These are nuanced decisions, but a rationale for individual decisions should be stated. I propose that attribution is important when using AI to be read by others and provide and example of how this might be handled.
It’s not that I don’t find AI to be useful. I generate a half dozen images a month to embellish my writing. I search for journal articles I then read to examine an educational issue I want to write about. I examine what I have written to identify errors in grammar or syntax or even identify my use of passive voice which I still can’t figure out. My issue is the monthly subscription fees for the multiple tools that best suit these and other uses. It is simply difficult to justify the $20 a month fee which seems to be the going rate for each of the services and the level of use I make of each service.
I regard my use of AI as both a benefit to personal productivity, but also a subject matter I explore and write about. Writing about the intersection of technology and education is a retirement hobby and I don’t need to do what I do on a budget. However, I don’t think this is true for everyone and I can set as a personal goal an exploration of the financial issues others might need to consider. AI tools differ in how flexible they are. Often, the less flexible tools are optimized to accomplish a specific set of tasks and this narrow range increases ease of use. Users can find themselves evaluating the cost-effectiveness of options based on ease of use versus total cost.
Grammarly as an example
As someone who spends a great deal of time writing, it is worth my time to consider how AI tools can be used to improve the productivity of the time I spend writing and the quality of what I write. Grammarly is a tool suited to such goals. I have relied on both the free and pro versions of Grammarly for a quick way to edit my writing. This is a great product I find helpful. Again, the issue is the Pro version adds another $12 to the total of my monthly subscriptions bill. The free version is great for basic errors, but the pro version is necessary for complete sentence rewrites. It is helpful to compare what I said with the suggested rewrite to decide whether I want to accept the alternate version.
What I have been exploring lately is the use of more general-purpose AI tools (e.g., ChatGPT, Abacas.ai) as an alternative. I understood that many others were using such tools in this matter, but because I had already been using Grammarly I had not invested the time to explore how more flexible tools might be used to achieve similar goals. Here is the approach I have settled on. I use a multi-level prompt to specify what I want to learn from an evaluation of something I have written. I keep this prompt in a note app so that I can copy and paste the prompt at the beginning of the content I want to evaluate. The prompt appears below. The prompt is written to be flexible so that I can adapt it to different circumstances by adding or removing specific guidelines. For example, I realize I often write in passive voice and some tasks should not include text expressed in this way. The guideline “write in active voice” can be included when I think this approach is important. If writing for a specific age group might be a goal, a guideline related to this goal can be inserted.
To demonstrate what this prompt accomplishes, I will take what I written here to this point and apply the prompt.
Evaluate the following content using the following guidelines:
Correct spelling errors
Correct grammatical errors
Correct punctuation errors
Write in active voice
Suggest corrections
Only list the lines containing errors and the proposed corrections
1. **Original:** I examine what I have written to identify errors in grammar or syntax or even identify my use of passive voice which I still can’t figure out.
**Correction:** I examine what I have written to identify errors in grammar or syntax and even identify my use of passive voice, which I still can’t figure out.
**Explanation:** Added a comma before “which” to correctly punctuate the non-restrictive clause.
2. **Original:** It is simply difficult to justify the $20 a month fee which seems to be the going rate for each of the services and the level of use I make of each service.
**Correction:** It is simply difficult to justify the $20-a-month fee, which seems to be the going rate for each of the services and the level of use I make of each service.
**Explanation:** Added a hyphen in “$20-a-month” to correctly form a compound adjective and a comma before “which” to punctuate the non-restrictive clause.
3. **Original:** I regard my use of AI as both a benefit to personal productivity, but also a subject matter I explore and write about.
**Correction:** I regard my use of AI as both a benefit to personal productivity and a subject matter I explore and write about.
**Explanation:** Replaced “but also” with “and” to correct the parallel structure.
4. **Original:** Writing about the intersection of technology and education is a retirement hobby and I don’t need to do what I do on a budget.
**Correction:** Writing about the intersection of technology and education is a retirement hobby, and I don’t need to do what I do on a budget.
**Explanation:** Added a comma before “and” to separate two independent clauses.
5. **Original:** Grammarly as an example
**Correction:** Grammarly is an example.
**Explanation:** Added “is” to form a complete sentence.
6. **Original:** Again, the issue is the Pro version adds another $12 to the total of my monthly subscriptions bill.
**Correction:** Again, the issue is that the Pro version adds another $12 to the total of my monthly subscription bill.
**Explanation:** Added “that” for clarity and changed “subscriptions” to “subscription” for correct singular form.
7. **Original:** What I have been exploring lately is the use of more general-purpose AI tools (e.g., ChatGPT, Abacas.ai) as an alternative.
**Correction:** What I have been exploring lately is the use of more general-purpose AI tools (e.g., ChatGPT, Abacus.ai) as an alternative.
**Explanation:** Corrected the spelling of “Abacas.ai” to “Abacus.ai.”
8. **Original:** I understood that many others were using such tools in this matter, but because I had already been using Grammarly I had not invested the time to explore how more flexible tools might be used to achieve similar goals.
**Correction:** I understood that many others were using such tools in this manner, but because I had already been using Grammarly, I had not invested the time to explore how more flexible tools might be used to achieve similar goals.
**Explanation:** Changed “matter” to “manner” for correct word usage and added a comma after “Grammarly” to separate clauses.
The feedback I have received would normally have resulted in my making several adjustments. I have not done so for you to consider both the original and the suggestions. The feedback makes specific suggestions and I either copy and paste the suggestions to the original source material or simply retype what needs to be fixed. This is clumsier than just clicking on the recommendation offered by Grammarly and it often requires that I use the search function in a longer text to locate the offending sentence. When writing on my desktop machine I simply open a second window and move between one window with the AI feedback and the original document to make adjustments.
I have been working my way through a couple of new and popular books that consider the importance and perils of AI and that contain at least significant commentary on AI in education. There is not a lot in these books that is based on the research literature I tend to find most influential, but the authors have sufficient experience and opportunities to offer some very credible insights. This is not a book report, but I want to credit a few ideas that encouraged my own exploration.
This time of the year, I often suggest some topics educators might explore over the summer while they have a little more time. With the attention AI has received in the past year and a half, I likely made a related recommendation last year at about this time. Reading these two books (citations at the end of this post) would be very useful if you spend time reading related to your profession. Perhaps you read in a different area. Hopefully. I can offer a few insights that will be sufficient to encourage your own exploration of AI tools.
Ethan Mollick’s book, Co-Intelligence, is different in that it focuses on applications and ways to think about AI capabilities. Mollick offers interesting ideas that sometimes run in opposition to traditional advice. For example, it is OK to interact with AI tools as if they were a person even though you know they are not. Asking questions and making requests as you would with another person is just a practical way to explore AI tools. Mollick also suggests that we stop looking for how to do it techniques for AI. Instead, he suggests we explore. If you have the time, try to use AI whenever there seems some possible value and see what happens. In other words, once you get past the basics of how to use a given tool, explore. Value and issues will be different for all of us so the only way to make decisions is to spend time. Again, for educators, the summer seems a great time to explore. Finally, understand that your present experiences will be with AI tools that are the least powerful they will ever be. If you find something interesting, but flawed in some way, just wait until you see what will come next.
There were some other suggestions about prompts I found useful. Perhaps the most concrete example is what was described as chain of thought prompting. AI tools will try to provide what you ask for, but it may be helpful to provide the sequence you want the tool to follow if a given process seems useful
Sal Kahn, the creator of Kahn Academy, offers thoughts on how AI will be helpful in education in his new book “Brave New Words”. Kahnmigo, the adaptation of AI as a tutor within the context of the other opportunities for learners and educators provided by Kahn and colleagues received a good deal of attention. An interesting theme seemed how this AI tool was prepared to assist, but not do for you (my interpretation).
One example, which Kahn uses to start his book, I found particularly interesting and I have attempted to use as the basis for the implementation I will describe in the comments that follow, describes a collaborative writing experience in which the AI tool and a student were assigned personas of two individuals writing collaboratively. The two personas took terms introducing portions of a story with the other writer finishing the section of the story the other persona had initiated. Two collaborative writers with one controlled by AI and the other by a student.
My version
Several of my posts have considered AI as a tutor and I have tried to demonstrate how existing AI tools can be used to implement various functions provided by a human tutor. This post has some similar arguments. Here, I describe an effort to create something similar to what Khan described in his account of collaborative writing, but I am proposing an approach more focused on the strategy of writing to learn. The core idea of writing to learn is that the cognitive processes involved in explaining something by writing require beneficial cognitive activities that would be less likely to occur in more passive study strategies. So, I have been attempting to write a prompt in which I try to create a version of the Kahnmigo collaborative story writing example applied as a writing to learn task.
Kahnmigo was just announced Kahnmigo will be a free AI tool for teachers subsidized by Microsoft. Perhaps it would have made sense to use one of the Kahnmigo tools to implement what I have been working on. I will leave it to others to make such efforts. I wanted to try to create a similar approach using the AI services I have already been working with and paying for.
What follows was developed using the paid version of ChatGPT using the most recently available version – 4o. I think the following prompt illustrates the chain of thought approach (Mollick) and is similar in approach to the Khan collaborative writing example.
Prompt: Obviously this is longer and more detailed than how many would request action from an AI tool. This prompt was entered into the ChatGPT accompanied by the textbook chapter as a file to upload.
Create an activity in which two students work together to write a document. You will represent a graduate student studying educational technology and I will represent an undergraduate student taking a course preparing teachers to use technology in K12 classrooms. This interaction will be based on information from the attached document. The graduate student will first identify and list significant topics from this document. Then the grad student will identify a topic for the collaborative writing project from this list and suggest an outline. The grad student will then write the introduction to this topic. The graduate student will next write the first couple of sentences about the first item from the outline and then ask the undergraduate to complete writing comments to complete the comments about this section of the outline. Do not include examples or applications in the introductory sentences and allow the undergraduate to provide comments on these topics. Wait for the undergraduate to add their additional content before continuing. After the undergrad submits their additions, offer feedback that evaluates what the undergraduate student has added. What the undergraduate has said should be identified and then how well it summarizes what was included in the material to be read should be presented. Limit feedback to what the undergraduate writes for this section without including information the outline suggested should be included in other sections. The graduate student should then ask the undergraduate student if they want to continue. Do not continue until a response of yes is submitted. If the undergraduate student responds “yes”, the graduate student should move to the next item from the outline and continue the same sequence of interactions until all items from the outline have been completed.
AI response:
Significant Topics from the Document
1. Cognitive System and Learning
2. Memory Stores (Short-Term and Long-Term Memory)
3. Working Memory Constraints
4. Cognitive Processes and Mental Tools
5. Metacognition and Executive Control
6. Higher Order Thinking Skills
7. Meaningful Learning and Constructivism
8. Reception vs. Discovery Learning
9. Modeling Cognitive Behaviors
10. Authentic Activities
11. Project-Based Learning
12. Role of Technology in Learning
Selected Topic for Collaborative Writing Project
Higher Order Thinking Skills
Suggested Outline
1. **Introduction**
– Definition of higher-order thinking skills
– Importance in the 21st-century education
2. **Problem-Solving**
– Description and components
– Importance in education
3. **Critical Thinking**
– Definition and key elements
– Role in evaluating information
4. **Creative Thinking**
– Explanation and examples
– Relevance in innovative problem-solving
5. **Integration and Application**
– How these skills interrelate
– Examples of application in real-world scenarios
Introduction
Higher-order thinking skills (HOTS) encompass a range of cognitive processes that are essential for success in the 21st-century educational landscape. These skills go beyond basic memorization or recall of facts, engaging students in complex tasks such as analysis, evaluation, synthesis, and creation of new ideas. HOTS are critical in preparing students to navigate the vast amounts of information available today and to solve novel problems effectively.
Problem-Solving
Problem-solving is a foundational aspect of higher-order thinking skills. It involves identifying a problem, generating possible solutions, evaluating these solutions, and implementing the most effective one. In education, problem-solving skills enable students to tackle complex challenges and develop strategies that can be applied across various domains.
Your turn: Please add your comments about the importance of problem-solving in education and provide examples of how it can be incorporated into classroom activities.
Me – entered as a prompt:
The issue of whether or not problem-solving is domain specific has received a great deal of attention. Some content areas might be more directly focused on problem solving – e.g., coding, mathematics. If problem-solving is domain specific then the problem-solving skills developed in one area would not transfer to other areas in a positive way. Ths would suggest teachers in all areas should offer opportunities for problem-solving challenges related to what is studied in these areas.
AI: Feedback
Your addition about the domain specificity of problem-solving is excellent. It addresses a critical aspect of the debate on how problem-solving skills are best developed and applied. Your point about certain content areas, like coding and mathematics, being more directly focused on problem-solving is particularlyinsightful. Highlighting the importance of teachers in all subject areas providing problem-solving opportunities helps underline the necessity for a holistic approach in education. This aligns well with the document’s emphasis on the importance of developing these skills across various domains.
Would you like to continue to the next section on Critical Thinking?
Me: entered as prompt
Yes
AI:
Critical Thinking
Critical thinking is another crucial component of higher-order thinking skills. It involves the ability to analyze information objectively and make reasoned judgments. Critical thinking requires students to engage in reflective and independent thinking, assess the validity and relevance of information, and form well-supported conclusions. This skill is vital in today’s information-rich world, where individuals must navigate a vast array of sources and discern credible information from misinformation.
Your turn: Please add your comments about the key elements of critical thinking and its role in evaluating information, particularly in an educational setting.
ETC:
This interaction continues according to the instructions in the prompt. ChatGPT has a method for sharing a chat with the public. Here is the link that should display the additional content AI and I generated (public access to chat).
Related comments: Here are some related observations related to my experience.
This interaction is developed on the fly. Redo the entire process and the elements of the interaction may all be different. The topics, the outline, the prompts, and even the way the content is formatted on the screen will be different. The prompt is similar to a program in that it specifies a sequence of operations you want to the AI to follow. However, unlike a coded program, here you are asking for a series to be created rather than a series of actions to follow in a specific manner. The process of generation (it is generative AI) will work a little differently each time it is implemented.
I found the execution of the prompt varied with the AI tool I used. ChatGPT worked the best. I thought that NotebookLM would be an ideal way to implement this writing-to-learn task because of the way in which you can upload content to be the target of interactions with the AI. It is my opinion that the way Notebooklm works is easier to understand and explain. However, after an extended series of attempts to rework the prompt, I was unable to get the required sequence to work. NotebookLM would provide feedback in response to the first item from the outline and then stop.
This post is not an attempt to promote the specific prompt I wrote. I certainly don’t care if others try it with information sources of their choosing. This was an exploration for me and it is my hope others may continue in a similar way using my initial effort as a guide.
One final point I think is important. The approach I am describing here is using the interactive capabilities of AI to focus on an information source I trust. I am not asking AI to use its generic information base to provide the content to be learned. The nature of the interaction may not be perfect, but it primarily focuses on a vetted source and assumes learners have read this source.
Resources:
Khan, S. (2024). Brave new words: How AI will revolutionize education (and why that’s a good thing). Viking.
Mollick, E. (2024). Co-Intelligence: Living and Working with AI. Penguin
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