NotebookLM Mindmaps

I investigate AI developments from two perspectives. First, what tools and applications will be personally beneficial? Second, what tools and applications can I write about that would be of value to those who read my posts? The following description fits both categories at the present time, but I expect it would end up more in the second category should Google move it out of beta into a paid category expected to be $20 a month. If it becomes part of the Google for Education suite, I can imagine it having great value to those with access to these services.

My present personal AI interest is in focusing AI on the resource material I have accumulated. What I mean by this is that I take notes and highlight while I read and have done so for 50 years. For the period of that time that I could read journal articles and books in digital form, I typically could export my notes and highlights and accumulate this personalized material. I have collected this content, but now I can use AI to target this content with retrieval augmented generation (RAG). I can “chat with this content” which offers me control over AI that I think is important and different from just interacting with the general knowledge base on which AI was trained. I want to generate insights and produce written products based on content and specific ideas within that content I have personally vetted. The broader application I see for what I am describing here involves an educator offering students access to content the educator has collected. An even broader application might focus on content collected by a team with a common interest.

This post described the use of Google’s NotebookLM as a tool suited to the implementation of this idea. I have described in a previous post how I get the content I want NotebookLM to focus on into that AI service in a previous post. Here I want to explain how “Mind Mapping”, a new capability of NotebookLM, can be used to explore a body of content.

So mind mapping is a way to identify the structure of ideas within content. I would have preferred Google called their implementation concept mapping, but this is not what they did. Concept maps can be a way for some to convey the structure of ideas to someone else or it can be a task in which someone creates a mind map to demonstrate how they see ideas to be related. The reason I would have preferred concept mapping is that the Google NotebookLM capability identifies concepts and then generates a simple structure of how these concepts are related. Think of it this way. I can feed in a large collection of information I have collected and then had NotebookLM show me how this content could be organized. In addition, it will provide summaries of the nodes that it has identified and allowed me then to explore the content I fed in that were judged to justify parts of the summary. 

The following image shows NotebookLM already loaded with hundreds of notes and highlights (left hand column) and the button (red box) that will generate this first level of the mind map. To break one of the initial notes into subnodes, you click on the caret associated with a note.

Selecting one of the nodes will reveal a summary of the content making up that higher-level category. In the following image, the summary is based on the category Generative Aspect (red box).

Within the summary, you should be able to identify numbers that represent the source from the content referenced by that section of the summary. Selecting a number will display that note or section of original content. 

One final feature is also quite useful. NotebookLM suggests questions related to the content displayed you might want to ask. It also provides a text box you can use to enter a prompt suggesting a question of your own. 

Summary

NotebookLM now includes a mind mapping tool that identifies and organizes concepts from the content it has been fed. The nodes identified can be used to provide summaries of that content and to interact with that summary and the content on which the summary was based. To fully appreciate what this allows it may be useful to imagine that hundreds or thousands of notes could be submitted by a user and processed in this manner. 

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Technology and the Writing Process

This post assumes you understand the basics of what is referred to as the “writing process” and perhaps have read my previous post explaining what the writing process is and why it is valuable to educators and researchers. One additional role I proposed in that post was that the components of the writing process would be helpful in identifying technology tools that would support the various components of the Writing Process. This post identifies these tools and explains how they might be applied. 

Before I get to my effort to associate specific technology tools with specific writing processes, I thought it useful just to make a case for writing using a word processor. The benefits are too easy to overlook, and opportunities may be ignored. 

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. One interesting proposal by Perkins (1985) is called 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 slower, 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. You can pursue an idea to see where it takes you 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.

What Perkins proposed was that 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. The same is true for writing outside of an academic setting. Is not a bad idea to set a written product aside and then return to read it once more before sending it off. Often, errors become apparent and new ideas surface.

Do writers take the opportunities provided by word processing programs and produce better products? The research evaluating the benefits of word processing (Bangert-Drowns, 1993) is not easy to interpret. Much seems to depend on the experience of the writer as a writer and technology user 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. General summaries of the research literature (Bangert-Drowns, 1993) 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. This is especially true with less capable writers. 

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

Tools specific to writing components

Here are the types of tools we see as supporting individual writing processes. We list tools using general terms as specific examples of a given category come and go. Our online resources include more detailed information about specific tools you might try.

Planning – Research

Authors write based on what they know and what they can discover. What they discover could come from books, conversations with others, data collection and analysis, or Internet searches. Internet searches are a common practice, and some writing environments embed search access within the writing environment and even suggest topics and links based on the content being written. Of course, opening a browser or a second tab when writing in a browser in order to conduct a search is a simple matter. For those of us writing in specialized areas and needing source material such as scientific sources more powerful fused search tools are available and it seems new ones emerge daily. Google Scholar provides access to the resources I cite. I can search for research publications on a specific topic and use a hit on a useful resource to locate even more recent sources that cite the initial find. There no restrictions or subscriptions that apply to Google Scholar so there is no reason to not give it a try. Research Rabbit, LitMaps, Semantic Scholar, and several similar tools compete for the attention of researchers. 

Locating information to be used in a future project or to improve an existing project also typically involves temporary storage of content and the information necessary for the attribution of useful sources. There are certainly nondigital ways to accomplish these tasks. Information could be entered in a notebook. There are now many digital tools that can be generalized to store notes or are specialized in some way. Writing systems may have built-in note taking, storage, and organization tools. Perhaps you have taken notes on cards. There is a digital equivalent. Scrivener is a writing environment and like writing tools, you would be more likely to have used is really a combination of tools. These “cards” can be organized and reorganized and offer the advantage of being searchable and other opportunities not available in the paper equivalent; e.g., copy and paste from source content, search, audio or image storage, duplication and off-site storage of resources so the work completed is not lost. The idea is that you can accumulate these “notes” and then organize them for use as you write. 

Perhaps you just use a notebook to accumulate notes as you prepare for a writing task. There are many tech tools that serve a similar function and offer some enhancements not available with paper resources. Apple Notes comes with the Apple OS and iOS so that you can access your notes across Apple devices. Apple has taken to describing this tool as a way to store “forever notes”. With what could be unlimited storage, why discard notes after the project the notes were intended to support is finished? Perhaps the notes might be useful in the future. To make this practical, the tool must be capable of more than storage. You need to be able to find what you stored when useful and this involves powerful search, tags, and collections. There are many tools based on a similar concept (e.g., Evernote, OneNote, Notion, Google Keep). 

Ideas as building blocks

One subcategory of note taking tools encourages the isolation of individual ideas or concepts. Think of note cards. I prefer to imagine Lego Blocks as ideas proposing that anyone familiar with these blocks appreciate how the blocks can be reused to build many different things. For those who are already familiar with what has become a popular self-improvement genre, the ideas as building blocks might alternately be described as smart notes, permanent notes, or atomic notes. For those really into this perspective on taking notes, there are differences among these terms, but all are similar enough I am not going to get into nuances. The atomic note is perhaps the most basic of these ideas and proposes that the note taker should create exactly one note for each idea, and write it as if you’re writing so you or someone else would understand this idea in the future. Use full sentences, include references. What you get from this process over time is an accumulation of ideas (lego blocks) that you can organize in different ways to accomplish different tasks. Connections among these ideas are to be explored repeatedly over time and potential meaningful associations are to be stored with links or tags. There are two important ideas here – a) identify and store useful ideas and b) revisit your collection repeatedly overtime to identify interesting connections among these ideas. 

My favorite tool for this style of notetaking is Obsidian. I might have also described Obsidian under a later heading (organization) because of the process of idea organization via links and tags, but the notion of saving isolated,  but connectable concepts is so unique I decided to focus on it at this point. There are other ways to keep individual ideas both without technology (note cards), but the search and interconnection possibilities among other technology facilitated writing tools offer unique benefits over long periods of time and with a large amount of content..

Referencing

A bibliography generator is also helpful when creating a large project. Citation information from sources can be stored as the sources are being read and this makes the eventual compilation of a reference list far more efficient than attempting to assemble such a list when the project is nearing completion.

Planning – organization

Most students are familiar with outlining. Incorporating an outlining tool in a writing environment allows the writer to plan the structure of the document. Often the outline entries become headings within the document, and the writer can move back and forth between the outline view and the extended text as an aid to organizing a major project. This capability helps the writer to escape the detail level and regain a sense of the overall purpose and structure of a document which research on the writing process argues is a unique challenge. It helps the writer answer questions such as “Do I want to discuss this issue at this point or would it be better to address it at a later point?” It is also possible to reverse this process – write first and outline later. This is a way to examine the structure of what has been written with the potential outcome of moving content around to provide a more logical structure. Again, I note at this point that Google docs and Microsoft 365 will generate an outline based on the structure of headings that have been used in a document. This outline is quite useful when working with a long document to quickly locate segments you want to edit or adding some new content you have just discovered, but examining the structure of the outline is also helpful.

A tool often serving a similar function allows the writer to create what are called either concept or mind maps. A map consists of nodes representing ideas and links joining the nodes. As a college student, you may have encountered textbooks in which the author or authors incorporated concept maps to represent the organization of core ideas within each chapter. The idea was to help you understand the big picture by isolating the core ideas and to show how the core ideas are related. In this case, the map was intended to help you see the structure around which much additional information was probably organized. A concept mapping tool can provide a related benefit to an individual or group attempting to organize ideas for a project.  The reader and writer both benefit from a well articulated structure; the reader in interpreting the product and the writer in creating the product. 

The map including concepts (nodes) and a system of organization (links) need not be completed simultaneously. In a technique such as brainstorming, an individual or small group might first quickly throw out ideas that are represented as key terms or nodes. The concepts represented by the nodes might then be discussed, prioritized (some might be deleted), and structured (linked). Much in the way an outline identifies topics and subtopics, additional nodes might then be added and linked to specify details.

Translation and Editing –  tools supporting content generation and simultaneous correction of writing errors. 

Applications used in translation often incorporate tools to ease and correct the process. Such tools can check spelling, suggest appropriate words (dictionary, thesaurus), and identify faulty grammar. The editorial tools may signal suggestions automatically (e.g., misspelled words are underlined) or offer suggestions when assistance is requested. Grammarly is a great tool for identifying surface level errors. This may be the perfect example of a productivity tactic that simply could not be implemented when writing without technology. Even the free version of Grammarly will alert a writer to spelling, punctuation, and grammatical errors and the paid version will both identify and make improvements. Grammarly implements these capabilities using AI and as with any AI use, it is important to consider whether AI limits the practice or development of an important skill. More on this topic at a later point 

Tools that allow voice input would also fall within the translation category. While most of us have probably used voice input when engaged in tasks we would probably not define as writing (asking a question through the Amazon Echo or Apple Siri, requesting a search through Google, sending a text that serves as a note while driving), text input is available as a way to generate the initial input when engaged in more traditional writing activities. It is a different experience and messy, but it is worth exploring.

Reviewing

My comments when describing the components of the writing process model differentiated editing and revision with the primary distinction being what I would describe as depth – surface (e.g., spelling, grammar) and deep (e.g, organization and logic) and the time of changes made either delayed or immediately. Often the delay allows input from other individuals with perhaps the input from others more likely to encourage structural or logical improvements. 

Reviewing – sharing

Sharing a draft allows the generation of feedback from someone other than the author. While this can be accomplished in many ways, the opportunities we want to identify here allow multiple individuals to access an online file. Depending on the service, the “editor” might then download the file for commenting or interact with the file online. Sharing printed copies has long been a possibility, but digital products allow greater convenience and a higher level of interactivity. 

Reviewing – commenting

Some digital writing environments allow the author to specify constraints (permissions) that control the extent to which a reviewer can interact with the shared document. For example, the author might allow read only access, commenting (comments are not actual modifications of the existing text), or modification of the text (sometimes as suggestions that be accepted or rejected). Read only access would require that the editor provide feedback separated from the original document; e.g., comments in an email. Comments might be added as text or sometimes audio that is linked to specific locations in the original document, but are available to the author in a sidebar. Finally, actual modification of the text may be possible. Such modifications might involve the embedding of suggestions in the text. When I do this for my students, I usually change font color so the author can easily identify my recommendations. The most advanced systems even combine comments and suggestions. An editor can change the original document and offer a comment to explain the modification. The author can then review these comments and decide either to accept or reject each suggested change. Accepting a suggested change modifies the document. Rejecting a change returns the document to the state that existed before editing. Reviewing a suggested change even when rejected may encourage the author to generate a change more to the author’s liking. Note that the options we describe here are not available in all writing environments, but are also not hypothetical possibilities 

Educators must consider how best to support the writer.  For example, the educator may prefer to rely on comments rather than suggested revisions if it becomes obvious that the author is simply accepting everything the teacher proposes as an improvement rather than using the suggestions to guide rewriting.

AI facilitated writing

While I have already hinted at ways in which AI can be applied, this mentions have involved tools integrating AI in a limited way. You can turn this relationship around and allow the writer to control general AI services to perform a wide range of writing tasks and subtasks. What many educators most fear is that learners who need to develop writing skills or demonstrate their understanding of a topic through a writing assignment will simply turn over the task to AI with the engagement the teacher intended. 

Such concerns are warranted. Early on (meaning a couple of years ago), I wanted to test how far I could push a general AI tool by seeing if I could get the tool to write an Introduction to Psychology textbook. I would describe the approach I took as AI first in which I worked through a process of steps I would take, but asked the AI tool to perform a step and then I evaluated and modified the effort produced. So, what are the topics or chapters that should appear in this type of textbook? Create an outline for the chapter on learning. Using the topics identified as behavioral theories of learning, expand these topics to explain each topic to the length of a typical college textbook and at that level off complexity. No one would be fooled by what was produced, but this was some time ago and with some work a product could be produced. 

I am not advocating anything like this, but I do think I gained some insight from the process. To some extent, there were hints of the Writing Process components in what I was doing. Asking for an outline of topics I could consider was an alternative to my planning a structure on my own. My personal expertise does not extend to all of the topics covered by a survey course so asking for an outline for each chapter would likely identify topics I had not considered and would need to spend time investigating to guide what I might write in these areas. I did not ask for a review and edit of what I had AI generate for the samples I had AI create, but I have since explored how AI might be applied to perform such functions

Perhaps my present position on AI would be to explore the role AI could play in performing or facilitating the performance of specific components of the writing process. I think it reasonable to investigate how I might work collaboratively with AI in performing these different processes. This seems different from recommending that AI should substitute for learning to perform these processes or maybe it could be imagined as a way to use AI to perform certain processes when a learner focuses on performing other processes.

Reference
Bangert-Drowns, R. (1993). The word processor as an instructional tool: A meta-analysis of word processing in writing instruction. Review of Educational Research, 63 (1), 69–93.

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Linear narrative chains

I have become fascinated with what I now call linear narrative chains (Hays and colleagues, 2008). The phrase is appropriately descriptive in how we experience life including reading and listening to lectures and explains why reprocessing such inputs is important to understanding and learning. What the phrase indicates is that inputs come at us as a sequence of events and ideas. This is obvious when you consider reading a book or listening to a lecture, but it also applies to the events of daily life. One thing follows another.

An important insight related to learning is that what is stored when imagined by cognitive psychologists and to some extent supported by neuroscientists is best understood as a network with links among nodes differing in strength. It follows that some sort of processing and organization is necessary to get from the form of the input to the form of the storage.

When I first encountered this notion of changing information formats, I was reminded of something I used to present to my educational psychology classes. There appear to be different types of memory stores. What might be described as knowledge is stored as a web of concepts connected by links — semantic memory. We also store inputs using other formats, with the most relevant one for this description being episodic memories. I liked to describe episodic memories as stories as this was a convenient way to explain an approximation of this concept. We like stories, and the value of stories can be noted in the way we interact with others. Often, one person tells a story, and then the other individuals respond with a story of their own both to indicate they understand and to further the interaction. We often include stories in writing and teaching as a way to provide examples of ideas. Episodes are stored with our cognitive web linked with the abstract nodes of semantic memory.

Episodic memories (stories) have a time course or sequence. What I speculated about for my class was that stories are often processed into semantic memory and one of the issues with learning from experiences including class lectures was whether the lecture as story was processed into semantic memory. I asked about how students studied their notes and whether they repeatedly went through them and could even imagine where specific items, perhaps a graph, appeared in a location within their notebook. I suggested that this capability indicated at least some aspects of an episodic representation was being retained. The content stored in that fashion may not have been processed for understanding.

When are academic episodic representations converted? I suggested for some this may happen at the time of an exam. A question might refer to an example from class and ask for an application. If the class example had not been processed during the lecture or during study as related to a concept or principle, the student would have to go through this process of abstraction and organization in trying to answer the question.

External activities to encourage processing

I often write about generative activities — external tasks that change the probability of desirable cognitive behaviors involved in understanding and learning. The idea here is that we can understand and learn by self-imposed and self-guided thinking, but this may not happen for a variety of reasons. External tasks can be provided to increase probabilities. Questions are an easy example. Questions encourage different types of processing depending on the type of question. Some encourage recall, and others encourage application.

Some generative activities might have value in converting a linear input. Creating an outline requires a hierarchical organization of ideas. Something closer to the desired output as a web would be mind mapping or concept mapping. If you are unfamiliar, I would recommend Davies ( 2011) as a resource that would explain more than you probably want to know about mind mapping, concept mapping, and argument mapping. Among other things, I learned from this source was that there are differences among these tactics and many subtleties or variants of each. Some researchers and educators who apply concept maps go deep into fine details.

One differentiation among those who conduct concept mapping research (the general term I have always preferred) is whether maps are constructed by learners or constructed and provided by teachers/authors. Concept mapping assignments would be a type of generative activity and encourage the translation of a linear input into a representational web. The provision of a mind map in support of a linear narrative is different and is an attempt to show the structure that the presenter imagines as a way to encourage the learner to consider relationships among ideas that might expand whatever organization of ideas the learner had already established.

Smart notes and the creation of web structures

I am making a transition here that the uninitiated may have trouble following. Some of these who have made the study of note taking a serious focus have developed approaches that are quite different from the continuous paraphrasing and summarization that most learners use in recording notes in a notebook or on a laptop. I think of a smart note (a formal term as used here) as a concise note focused on a specific idea with enough context that it will still convey the original meaning at a future date to the note taker or others with a reasonable background. Think of a smart note as a building block that can then be combined with other smart notes in a cumulative way. The idea of specificity is that a given block can be combined with other such representations in a variety of ways. You can build different structures from different combinations of ideas. Notes are connected in several ways. Some of the possible connections can be attached as metadata — tags and links among notes.

Hopefully, the similarity between such notes and links and concept maps might now become apparent.

A web of notes within Obsidian

Obsidian is my personal note-taking tool, and it fits well with the idea of isolating specific ideas or concepts and then identifying connections between these specific notes over time. Rather than focus on using this tool as a learner, which has been the focus of multiple posts in the past, my intent here is more on the potential of sharing the structure of personal notes with others. So, in keeping with the theme of converting linear narrative chains, how might an instructor or author share the structure behind what they might present as a lecture or written product?

I briefly mentioned how a colleague who teaches history shares his background content with students in a previous post. Here, I want to describe the use of a mapping tool, Canvas, available as an extension to Obsidian. Obsidian includes its own tool for creating a map of notes and connections, but Canvas is more typical of what I have already described as a tool for concept mapping.

The following image shows a Canvas concept map I quickly created to show I might share the web of ideas that might be the basis for a couple of presentations I might offer describing the behavioral and cognitive models of learning. I had to find a workaround for the way Canvas was designed to work. The intention is that a Canvas web would show the entirety of notes. So, if you imagine a note consisting of a paragraph of content, you might have Canvas nodes representing concepts (as is the case in my example) linked with visible nodes containing entire paragraphs. This works fine if you are in control of a device as you can shrink and expand the content that appears on the screen very easily and expand a portion of the display if you need to make the paragraph larger so you can read it. I used a different approach, repurposing a typical text note as a node descriptor and then a link. The link would reveal the linked note layered on the basic map (second image).

To make this work in practice, you would have to pay for an Obsidian service ($8 a month) called Publish. Obsidian is a device-based tool, but Publish offers a web-based interface and storage option that allows others to view your Obsidian vault (a collection of notes). 

There are likely multiple ways in which an individual could generate a shareable web experience for students. I have been focused on how I might do such a thing based on the note tool (Obsidian) I use. As another example example, in a previous post, I explored how Padlet could be used by a middle school or high school teacher to share a web of concepts and notes. 

Summary

Students experience information as linear narrative chains even though the information within is likely based on a web of concepts and ideas. Since human memory is more web-like, the learner must transform a sequence of ideas to fit within his or her personal webs. Concept maps have been used to encourage the building of a personal web and can also be used for the author/teacher to share his/her web to assist in the construction of a personal representation. Note-taking tools based on the identification and linking of core ideas (Smart Notes) offer a related experience on the part of learners and possibly with some adaptations provide a way to share the structure the author/teacher used to generate their presentations. 

Resources:

Ahrens, S. (2022). How to take smart notes: One simple technique to boost writing, learning and thinking.

Davies, M. (2011). Concept mapping, mind mapping and argument mapping: what are the differences and do they matter? Higher education, 62, 279-301.

Hay, D., Kinchin, I., & Lygo-Baker, S. (2008). Making learning visible: The role of concept mapping in higher education. Studies in Higher Education, 33(3), 295–311.

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Considering AI in Writing and Reading

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.

————————————————————————————————

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. 

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AI in Readwise

 How do most Readwise users use the service? Is it the central location in which you suck in the notes and highlights from the multiple tools you use to read the multiple categories of content you consume to review and work with that content or is it a relay station between these sources and the tools you use to store, organize, expand on, and apply this content? I can’t really remember what I was thinking when I first paid the subscription price, but over the majority of the time I have used Readwise, it was mainly as a relay station. 

For those who have never tried Readwise, it may be unclear why you would want to pay the price of a subscription. The first paragraph of this post may have meant little to you even though I think it represents a reasonable description of the ways Readwise is used. Consider this example. I have made use of Kindle for years and have a collection of more than 300 books. I highlight a lot while I read and add occasional annotations. Most of this content is nonfiction and the source for what I write about. All of these highlights and annotations are out there somewhere, but how do I locate what might be helpful when it is scattered across so many sources many of which I might have read years ago? Readwise accepts the highlights from each of these books that is automatically output from Kindle and this entire body of material ends up in Readwise and can then be searched.

Now, somewhere along the way, Readwise added Readwise Reader and this addition became a major tool.  With Reader I found a “read it later tool” I used mainly to collect web content I could highlight and annotate and then send the content I added or identified through the relay system to Readwise or export it depending on my whim of the moment. 

Without describing other content sources, I hope you get the idea. Readwise allows the collection of highlights and notes from many different content sources. 

AI Chat within Readwise

Now, like many other digital tools, Readwise has added AI. This makes sense as the AI can be used to chat with all of the content or if you choose certain designated content that has been accumulated. The AI is easy to use, similar to other AI chats, and is powered by OpenAI’s GPT-4o model. If you are a Readwise user you may not have noticed this recent addition (see the red square enclosing the small word chat at the top of the following image). I have also used a red box to call your attention to import. I will get to an important import issue at another point, but wanted to make certain you see how to get to the import options.

Selecting chat will bring you to the following page. Here you find the typical request for a prompt and some suggestions. The suggestions will change as you make use of this feature.

As an example, I entered a prompt related to a recent topic I have been exploring. I don’t generate my posts using AI, but I sometimes ask for something written in a format I might use as a model. Within the content the AI generated, you will see link (blue color). Selecting a link will show the highlight or note within Readwise that was used to encourage a that part of what the AI wrote (the second of the two images appearing below). You can get the full set of content stored on Readwise from the displayed snippet of text by selecting the snippet.

If you are a Readwise user, I assume you can easily explore the AI chat just following the simple process I have outlined. This is not intended to be a full Readwise tutorial, but many can be found by searching online.

One additional comment

Most of what I write is not based on books, but rather on journal articles. I am an academic and this is typical of how we work. We read articles from many journals and for the last 10+ years I have read nearly entirely from pdfs of journal articles. This is what I can access through my university library and more suited to my work that even getting up from my desk and walking across my office to pull a journal off a shelf. I don’t want to highlight on paper because I want highlights and notes in a digital format.

I could have included the highlights from the hundreds of journal articles I had read in Readwise to create a massive collection of content I could explore via chat. However, I have not used a pdf reader that generates highlights in Readwise if I try to import the pdfs. This appears to be a common problem as I have explored this issue online. I will first note that you can highlight pdfs within the Readwise/Reader environment, but this has not been part of my workflow. I have found a way to fix the problem which I will describe here, but it is unlikely I will now import one by one my large collection of highlighted and annotated pdfs to Readwise. I will explain the hack I have discovered for others who may want to do so.

You should recall at the beginning of this post I showed the import link for Readwise. This link will bring up the many import options. I automatically import from Reader and Kindle. There is an option to import from pdfs. It is a one pdf at a time approach and requires that the pdfs with the highlights have been stored in the correct format. The import options are shown below.

I have multiple tools to highlight and annotate pdfs. Most recently, I have used Bookends and Highlights. Both are software for the Apple environment and work great on an iPad with an Apple Pencil. Unfortunately, the storage format is not acceptable to Readwise.

However, I found that I can open my highlighted and annotated pdfs in Preview which is the universal Mac tool for opening many different data files. It turns out you can export from Preview in multiple PDF formats and the first one I tried created a file that would be read by Readwise.

So, there is a way for those frustrated with the specific demands of Readwise.

Summary

Readwise if a powerful tool that stores the highlights and notes that have been added to a wide variety of content sources (e.g., web pages, Kindle books, Apple books. pdfs). Recently, an AI chat capability has been added to Readwise and can be used to interact with the content stored by Readwise. Because the quantity of this content is immense and represents what a user has found interesting or useful, being able to ask questions of this content offers very interesting possibilities. The AI chat capability is easy to explore and may even represent a selling point for those considering paying the subscription to use Readwise and Readwise Reader. 

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The Space Between Encountering Information and Application

One way to characterize Personal Knowledge Management (PKM) is to suggest it involves the analysis of actual and potential tactics applied between encountering information and the application of that information. I came to this topic with a background in the development and evaluation of technology tools for academic studying which involves considerable overlap with PKM. I think it fair to say that studying offers an advantage to interested parties because it has a superior theoretical framework and a large volume of theory-driven research. PKM seems to have developed within a framework I could describe as logical rather than research-based, but it is related to methods of considerable longevity (e.g., commonplace books, note-taking within procedural systems such as the Zettelkasten). 

This post was prompted by the announcement and availability of a new version of Mem.ai. There are many digital note-taking tools available, but for some time I have concentrated on two – Obsidian and Mem.ai. My rationale has been that I wanted to invest sufficient time in creating and using a personal knowledge management system so that I could offer credible comments on the tools I use and the tactics that are recommended and that I have employed. Part of this involves building a significant collection of notes over an extended period of time. Many recommended practices cannot really be evaluated with a small body of material used for a short period of time. 

When I started using Mem it was because I wanted to explore how AI could be applied within a PKM system. With time, Obsidian extensions allowed several different ways to add AI to Obsidian so there was no longer a unique difference, but I have continued to use both nonetheless. 

Comparing Obsidian and Mem.AI

When comparing how Obsidian and Mem serve writers between reading and writing, there are distinct approaches each platform takes to facilitate the transition from note-taking to writing.

Obsidian

Obsidian is known for its flexibility and emphasis on linking notes to create a network of ideas. It supports a bottom-up approach to writing, where notes are interconnected through backlinks and tags, allowing users to discover relationships between ideas organically. This method aligns with the slip-box or Zettelkasten approach, which encourages the creation of permanent notes that can stand alone and be easily integrated into future projects. Obsidian’s use of markdown files and its ability to handle large volumes of notes make it a powerful tool for writers who prefer a structured yet flexible environment for developing their ideas.

Mem

Mem, on the other hand, focuses on enhancing the linking capability through AI-driven suggestions. It extends beyond manual tagging and keyword searches by proposing related ideas and documents, which can come from the user’s own mems or those shared by team members. This AI-driven approach aims to improve the retrieval and linking of information, making it easier for writers to access relevant content and insights. Mem’s design is centered around the concept of a “second brain,” where storage, retrieval, and linking are optimized to support the writing process.

Key Differences

  • Linking and Organization: Obsidian relies on manual linking and tagging, while Mem uses AI to suggest connections.
  • Flexibility vs. Automation: Obsidian offers more flexibility in how notes are organized and linked, whereas Mem provides automated suggestions to enhance the linking process.
  • User Experience: Obsidian’s interface is more suited to users who prefer a hands-on approach to organizing their notes, while Mem’s AI features cater to those who appreciate automated assistance in discovering connections.

Both platforms offer unique advantages depending on the writer’s preferences and workflow. Obsidian is ideal for those who enjoy a more manual and customizable approach, while Mem provides a more automated and AI-enhanced experience. 

When is the process the product?

Part of the marketing for the original Mem.ai made the argument that the AI capabilities freed users from some of the process requirements of other note-taking tools. The differentiation of notes into folders and the connecting of notes by manual links was not necessary. You could search and chat with your notes to accomplish your goals. Such capabilities were there (@ in Mem to create a link instead of the [[]] in Obsidian), but were claimed to be unnecessary.

The AI can do it for you is what concerns practitioners in some domains for some purposes. Educators may be concerned that students use AI to complete homework assignments. Writing assignments can easily and reasonably be completed by giving an AI tool a prompt. With writing there are two interrelated problems. As a skill writing needs to be learned, so practicing the subskills (procedures) involved in skilled writing are not practiced when the work is done by the AI. A separate concern is that writing is a way to process the content that can be the focus of the assigned writing task and this processing does not happen when the AI provides and assembles the content. There are counters to these concerns as AI can contribute in different ways allowing some subskills that are involved to be ignored so that others can be emphasized, but this possibiity is making my example unnecessarily complicated.

With note-taking, I think of the argument for what I am calling the manual approach is based on the assumed value of generative cognitive processing. I describe a generative activity as an external task that is likely to increase the probability of an internal (cognitive) process. When proposing an example of a generative activity, I use questions. In theory, connecting new concepts with experiences is an important learning process. Individuals may or may not do this on their own. If I request that they provide an example of concept XXX, it is fairly likely they will think and come up with something. Hence, questions function as generative activities

The organization of notes into folders or categories and the searching for connections to be made permanent with links involves thinking and decision-making that is less likely without the commitment to tasks that require such thinking. These actions may also serve generative functions. While educational researchers have proposed and evaluated many manual processing activities associated with note-taking as part of studying, to my knowledge such research does not exist for some of the procedures recommended by recent, digital note-taking gurus (see an earlier post on the lack of such research). So, unlike the abundant research on the benefits of provided and self-generated questions, the specific activities associated with digital (and manual) note-taking skills are largely untested. This is partly the reason I continue to duplicate my collection of notes within both Obsidian and Mem. Personal experience is a weak research tool, but better than nothing. 

This is what I mean by questioning whether the processing requirements of the various note-taking tools strongly contributes to the eventual application. The recent development of systems such as Obsidian and Mem seem more likely driven by the long-term use of information in comparison to what might be associated with academic studying, Purpose and length of the exposure to use processes may be important differentiators. What is interesting about Mem is that it has come out with the argument that AI can eliminate many of the activities focused on and debated by Obsidian users.

Summary

This post attempts to identify and differentiate two note-taking and note-using approaches that can be associated with two specific products. While both systems can now be used in the same ways, the proposed differences are interesting. How important are the manual actions AI can eliminate? I will offer one observed advantage to the AI capabilities that can be applied with either system, with the large collection of notes I have now accumulated, I have found that AI prompts surface useful notes I would not have identified based on the manual links I had accumulated. I suppose there might have been benefit in a continuation of exploration by the use of links, tags, and search, but I must deal with the reality I could not necessarily make the effort. Perhaps continuing to use both and adding links to connections identified by AI makes the most sense.

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Disciplinary Perspectives on Taking and Using Notes

I have found myself exploring and writing about the interrelated topics of personal knowledge management, second brains, and note-taking for the past several years. As I have spent time on these interests, it became obvious that there were multiple disciplinary perspectives on these topics. In addition, the different disciplines seem mostly oblivious to each other as indicated by the lack of cross-referencing evident in their written materials. There are sometimes references to historical connections which I will identify, but for anyone interested in these topics I would suggest there are benefits for exploring more than a single point of view.

The Perspectives

Here are the descriptive labels I have decided to use for what I claim to be different perspectives. Hopefully, the labels offer some insights into the categories I have in mind.

  1. Academic studying – this perspective provided my personal background for this general topic. The focus of this perspective is learning in formal academic environments with the goals of the acquisition, understanding, and application of information to examinations and projects. While the general goal of education is focused on the long term and preparation for life, note-taking has a more immediate focus. I am of the opinion that the great majority of what I would describe as research is focused on topics within this category. Most of this research is based on a cognitive perspective on learning and application.
  2. Organizational Knowledge Management – Organizations have a need to develop, preserve, and apply knowledge. For multiple practical reasons (e.g., changeover in personnel), this knowledge should be externalized for the benefit of the organization. The generation and use of this shared knowledge originate with individuals. Personal knowledge management (PKM) can be individualized or integrated with the more general needs of a given organization. Procedures for accomplishing these goals are the subject of scholarship and training in the formal programs preparing individuals for careers in organizations (e.g., business schools), but it is my impression that scholarship is less empirical than that applied by those with an academic studying perspective and more anecdotal and based in logical argumentation.
  3. Knowledge Management Entrepreneurs – I struggled with a way to describe this perspective. It seems to me that there has been a recent and identifiable group of individuals offering self-help books and consulting expertise to those interested in Personal Knowledge Management. This category resembles the organizational knowledge management perspective but does not share the same group focus. The perspective emphasizes the collection, organization, exploration, and application of information over an extended period of time to accomplish personal goals. Of the three groups I have identified, those individuals promoting techniques and processes are the least likely engaged in what I would describe as formal scholarship.

Historical Antecedents

While not absolutely consistent, there are frequent references to similar individuals, practices, and models that can often be identified among these perspectives. Here is my own list of such sources.

  1. Vannevar Bush’s article “As we may think” describing the manner in which individuals and organizations might use a yet-to-be-developed technology (the Memex) to take on information overload and how a knowledge worker might explore, retain, organize, and apply information. 
  2. Commonplace books are journals, diaries, or notebooks maintained by individuals. A famous historical example would be the Leonardo Di Vinci notebooks still available in different formats (Amazon source).
  3. Luhmann’s Zettelkasten. A zettelkasten is a card-based note-taking and note-linking system now often adapted to digitization and computer applications. It did not originate with Nikolas Luhmann, but I have connected the approach with his name because his prodigious use of the system as a scholar seems the example so many use. 
  4. The encoding and external model of note-taking (e.g., Rickards & Friedman, 1978) is the basis for much of the empirical research from the academic studying perspective. It proposes that learners could possibly benefit from both the thinking required in taking notes (the encoding process) and/or by having an external record available for review (external storage). This basic differentiation has been applied to such topics as whether taking notes by hand is more or less effective than taking notes using a keyboard (encoding), the best ways to work with the external notes (e.g., retrieval practice), and individual differences in both what is stored and how what is stored is used. For example, the Cornell note-taking method is an example of a system for both taking and using notes. 

Examples from the different perspectives

I have written extensively about a couple of these perspectives in previous posts so rather than repeat myself and increase the length of this post I will link to some of these earlier posts.

  1. Academic Studying – History of Note-Taking Research, Note-taking as a Generative Activity, Cornell Notes and Beyond
  2. Organizational Knowledge Management – this perspective is a little more challenging as I have not written about it before. Here is a source you can explore without having journal access – Towards a Co-evolution of Organizational and Personal Knowledge Management Systems. Also see Pauleen (2009) – this is the introduction to a special issue on personal knowledge management. 
  3. Knowledge Management Entrepreneurs – Creating, Storing, and Using Smart Notes, Evaluating Tech Tools for Adults

Why consideration of the different perspectives might be useful?

Having asked you to recognize the multiple perspectives that I have identified, I owe you some explanation for why I think anyone interested in taking notes should expand their awareness of the background content available on this topic. I have found a couple of personal opportunities. First, the work from the perspective of academic studying has been far more carefully evaluated and useful in answering questions of why and if specific activities work. The knowledge management entrepreneurs offer specific “how to do it” suggestions and have strongly promoted the use of technology tools in PKM. The organizational knowledge management perspective extends the note-taking and PKM for life-long learning expanding core ideas beyond the academic classroom setting. 

The links I provide here should open to many other resources on the perspectives I have identified.

References not linked

Pauleen, David (2009), “Personal knowledge management: putting the ‘person’ back into the knowledge equation”, Online Information Review, vol. 33, no. 2, pp. 221–224, doi:10.1108/14684520910951177.

Rickards, J. P., & Friedman, F. (1978). The encoding versus the external storage hypothesis in note taking. Contemporary Educational Psychology, 3(2), 136-143.

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