I came to my interest in PKM as a retired educational psychologist with research interests in how students might take and use notes more effectively. This connection led me to translate the popular books on note-taking, second brains, and secondary topics such as whether notes should be taken on cards using a pen or on a computer into the descriptive models of note-taking and studying and research that were already familiar to me.
What I missed with PKM was the applied research I knew was so common in answering questions and suggesting ways to improve classroom-based note-taking. I had my personal experiences to provide some insights. Academic researchers use what I learned could be called PKM techniques in their profession. They read books and journal articles and take notes at academic conferences. They highlight and annotate and for years have used tools such as Endnote to track the references they have accumulated over years of work. Most of us just did these things without guiding models or books focused on “the process”. Even those of us who studied student note-taking were likely oblivious to the possible connections to our own daily behavior. We didn’t discuss related topics with colleagues or share recommendations for new reference managers. My personal experience in recent years is still an exception. When I talk with colleagues about my new interests and describe permanent notes or building a second brain their eyes glaze over. These folks are making a living with merit money depending on publication frequency and grant money secured and they are mostly oblivious to proposals for better knowledge management. I keep their reality in mind and it does make me wonder.
I know colleagues who have authored hundreds of publications. The Zettelkasten fans who point to the prolific publication record of Nikolas Luhmann have nothing on these scholars. Plus, the individual I have in mind collects the data necessary for these publications in addition to just writing. They do work with students so their situation while common may be a little different. However, to justify an approach anecdotally with Luhmann as the most common example opens a position taken to counter examples. There are many prolific counterexamples when it comes to knowledge workers.
The Knowledge workers I know have a body of information they have mastered and they tend to use this body in combination with just-in-time learning of material related to a topic that has caught their attention. They read constantly in narrow areas related to their work and the focus of this reading drifts about depending on the research that is their present focus. The component of PKM they tend to ignore is a way to connect over an extended period of time with novel associations that might lead to creative insights.
I do find some of the ideas and methods proposed by PKM and second brain advocates to be interesting. The point I am making concerns the lack of actual evidence regarding the proposed advantages of these techniques.
A category system for understanding and applying learning
I have come up with a potentially hierarchical system for the sources of information concerning learning. The items on this list differ in a variety of ways and different individuals likely value these levels to different degrees. Learning must be based in biology, but the success of a recommendation does not necessarily require a neurological basis. You can simply test a method against alternatives and determine which is most effective. Sometimes such tests at one level of my proposed hierarchy can be used to justify strategies at a different level. I think this is the case in using basic cognitive and memory research to provide insights into strategies to be tested at the applied cognitive strategy level and the applied cognitive strategy level has been used to justify strategies at the PKM and Second Brain level. However, speculative justification is not the same as actual experimental justification at the higher level. This is the issue I have with PKM and Second Brain proposals. As you move up this hierarchy, the complexity of the circumstances of application increases, and elements of this complexity may impact outcomes in ways that are not an issue at lower levels where these variables can be controlled. Things that work in the carefully controlled environment of the lab do not necessarily work outside of the lab. This does not mean the lab results are not real. It just means proposed applications need to be tested to see if potential and often unknown interacting factors can be ignored
Levels:
Personal Knowledge Management and Second Brain Strategies
Cognitive Note-taking strategy research
Basic Cognitive Memory and Comprehension research
Neuroscience
PKM strategies
For those who have read one or more of the personal knowledge management “how to do it” books, I will identify some of the recommended strategies I think should be tested. For others, I will try to include a few additional comments to offer a short idea of what these strategies recommend.
The notes intended to be retained should isolate specific concepts or ideas with enough context that at a later time the note taker or someone else with relevant background could understand the meaning of the note without access to the original context that prompted that note. Isolation of specific, meaningful ideas in storage is an important attribute of this strategy. (e.g., Atomic notes, permanent notes)
Immediately and over time, these isolated notes are to be connected with other notes (links). The connections are to suggest ways in which ideas relate to each other as similar, contribute to a process, or are part of an argument. Systems argue that important notes should immediately be stored as part of such relationships and new relationships can be added as they become apparent to the note-taker.
Individual notes are often also grouped by the addition of one or more additional tags common to other notes for which the tags are appropriate. Tags are an important way to search for and retrieve related notes.
Revisiting and reviewing are expected. Exploring the collection of notes as part of the process of developing the value of the stored information is an end in itself, not just something done when using stored information to accomplish a specific project. The review, which is sometimes random, increases familiarity and allows for the addition of new tags, links, and notes.
Note-taking and note-use are long-term processes in which notes are not necessarily taken with a specific purpose in mind. Tags, links, and other organizational strategies can be used to find relevant information when a novel purpose emerges.
My goal is not to challenge whether these tactics are beneficial. I am of the opinion that any external activity that results in analysis, decision-making, personalizing through summarization, or self-evaluation deepens understanding and improves retention. Simply put?—?thinking is good. A better way to explain my interest is whether the specific strategies I have mentioned are an improvement in comparison to what I would describe as a control condition. For example, do these tactics offer an advantage over the way say students traditionally take free-form notes and then review these notes from time to time? If the answer is yes, we should be emphasizing and teaching the PKM strategies to high school and college students. I think other control conditions may also be important. For example, in a recent post, I suggested that AI allows a learner to “chat” with stored notes and highlights and that using this means of interacting with content may have advantages over “manual” strategies emphasized by PKM enthusiasts. This approach might render many of the PKM strategies busy work.
As is so often the case with research, the investigation of one issue leads to the need to investigate related assumptions. For example, many have now concluded that reading from paper is advantageous to reading from a screen, and taking notes by hand is advantageous in comparison to taking notes with a digital device. However, with long-term goals for learning in mind and depending on the comparisons I have proposed, wouldn’t having stored information in a searchable and AI-accessible form be essential?
I wonder. There are so many areas in which developments and thought experiments can move faster than the research that would support or reject advocated practices. Ideal tests of some of the issues I have identified probably will not happen. Part of the rationale for PKM is to create a system for improved use of the learning experiences we have over long periods of time. Longitudinal research is expensive and fraught with problems of maintaining a commitment to treatment alternatives. How important are these issues and are they important enough to invest time and money? However, ideal approaches aside, I cannot find research that even considers the proposed benefits of the PKM component strategies I have identified over a short period. I think some of the issues I have identified warrant at least that level of commitment.
How much of the “building” part of building a second brain is necessary? With the opportunity to direct AI at accumulated resources, how much of the linking, tagging, reviewing, and re-expressing notes is productive? Some version of this question has long bothered me. I studied classroom note-taking as an academic and became familiar with the massive research base associated with different ways to take and use notes, the cognitive and metacognitive processes associated with activities in different note-taking approaches, and individual differences in the capacity and motivation to execute specific processes effectively. While there is a great deal of speculation, multiple books, and the sharing of numerous personal processes in online posts, where is the research on PKM and Second Brains? The research on learners taking and using notes in academic settings may offer a general structure, however there would seem important differences in the use of self-directed note-taking outside of an environment that involves processes that must accomplish goals set by others to produce products or perform tasks after short time intervals (the time between exams or writing assignments).
The terminology is different. You do not find classroom-oriented research considering fleeting versus permanent notes or the ideal types of tags and links to organize notes and prepare the user for future goals and tasks that often do not exist when the notes are taken. I try to translate the proposed strategies outlined in popular books for the audience that takes notes to benefit them under these circumstances (Ahrens, Doto, and Forte). Can the research on generative cognitive processes, metacognitive comprehension monitoring, and retrieval practice serve to determine if the recommendations made by these writers are reasonable? Perhaps the strategies for creating different types of notes (fleeting vs. permanent), strategies for linking and tagging, and reviewing to find new associations are just busy work.
Does AI provide an alternative?
MEM.AI was the first note-taking and storage tool I used that came with an embedded AI tool. The promotional material I read before investing time and money into MEM proposed that the availability of the embedded AI offered an alternative to the tags and links in a tool such as Obsidian. MEM.AI allows the manual assignment of something similar to tags and bi-directional links. The embedded AI did a couple of interesting things. As you built up a collection of notes, the AI offered suggestions based on the material you have accumulated. Similar notes were identified based on common elements of a new note and existing notes (see red box in the following image). You could link to suggested notes if you found the suggestions of value. Tags for a new note were proposed beyond any rags that were manually added (see red box in the following image) and any of these suggestions can be accepted. I have recently written about multiple ways note-taking systems can be augmented with AI, but MEM.AI is built with some of these processes assumed rather than potentially available through the creation of clever prompts. MEM.AI proposes that it creates a self-organizing workspace which seems a reasonable description.
MEM.AI has one more unique feature that seems a powerful use of the self-organizing workspace concept. There is a built-in word-processing capability called Smart Write. When you enter a forward slash / within any existing note or within an empty note, you can then enter a chat prompt. You can ask a question or make a request. With an existing note, the AI extends what already exists in what are often interesting and creative ways relying on what appears in the note you are working on and the corpus of notes you have saved. The output appears within that note and can be copied and pasted elsewhere or left as part of that note. It can be argued that this is a way to discover connections to other material more directly than what might have been manually indicated by creating a link to another specific note.
Here is an example.
The following (Permanentnotes) is a note I created with two tags. What you can no longer see is the / and prompt that was originally inserted after the second tag. The prompt entered after the / was “Does my idea that permanent notes move more of the thinking involved in transforming notes into a final written product earlier in that writing process make sense?” Smart Write added three paragraphs based on other stored notes.These paragraphs now appear in the original note (shown below). Not all of this content seems relevant, but connections were discovered and much of what was said could be used in writing about this concept. These additions were all based on previous content I added, but I did not have to manually find these connections.
Permanentnotes
This is a key insight. Permanent notes should be able to stand alone without reference to the original content for context. Perhaps it could be described as moving part of the writing process earlier in the transition from note-taking to a final written product.
#notetaking
#slipbox
Your thought about moving part of the writing process earlier in the transition from note-taking to a final writing product indeed makes sense and aligns with the ideas presented in the writing process model by Flower and Hayes (1981). The model emphasizes the importance of planning as a foundational step in effective writing, which involves setting goals, gathering information, and organizing ideas. By integrating permanent notes into this early stage, you essentially create a structured framework that facilitates the translation and reviewing phases of writing.
The approach of using permanent notes, akin to the slip-box system described by Ahrens, enhances this framework by allowing writers to develop a rich, interconnected repository of ideas and insights. This repository acts as an external structure that compensates for the cognitive limitations of the human brain, making it easier to retrieve and connect ideas when composing a draft. The slip-box method encourages a shift from merely capturing fleeting thoughts to actively engaging with and refining those ideas into coherent, stand-alone pieces of information.
Furthermore, this method aligns with the iterative nature of the writing process. As notes are continually reviewed and expanded, they can reveal gaps in understanding or suggest new lines of inquiry, prompting further research and reflection. This iterative engagement not only aids in the development of writing skills but also fosters deeper learning and insight generation, as noted by Ahrens. Thus, your suggestion to reposition part of the writing process earlier, in the context of note-taking and idea organization, is a strategic move that can significantly enhance both the efficiency and quality of writing.
Summary
I would argue that AI capabilities can substitute for or at least augment manual processes advocated by those arguing tags and links are an essential part of the Personal Knowledge Management process. To some extent, I have found the capabilities of the MEM self-organizing workspace to be more thorough in proposing connections than I would typically be on my own.
This brings me to an issue I consider in many applications of AI. This issue is whether the AI approach allows the user to avoid important activities that are important in and of themselves. Perhaps both the manual and AI approaches here allow a note-taker to produce comparable final written products if that was the goal. Whether the activities of exploring notes to make appropriate links and adding tags that identify key ideas encourage deeper thinking about the content seems a different issue. Again, this is difficult to know. One might make the opposite argument claiming that reviewing the text generated by the AI offers a different way to explore and find relationships within existing content and the process of considering what within this new material is relevant to the intended purpose of the prompt is a unique evaluative activity performed by the user. As I have already suggested, MEM.AI does not require that you take one approach or the other. So, explore. AI capabilities are being added to many note-taking tools and the potential is worth a look.
As we explore meaningful ways in which we can make use of the AI tools available to us at any given time, we must be aware of the limitations of AI and what the consequences of promoting the products we generate might be. My personal use of AI is to support the writing I do. This is what you are experiencing here. Misrepresentations would be embarrassing, but I write blog posts so the consequences at worst are not catastrophic.
I would not use AI to generate blog posts by entering a series of prompts to shape a product. What I want AI to do is to help me organize what I have learned and lessen the time spent translating the information I have collected into an external representation of my thinking. I use an approach that first requires me to read, highlight, and annotate sources (typically books and journal articles). Next, I export the residue of this process (the highlights and notes) into a tool that allows me to rework and connect these elements of information. Finally, I focused an AI tool on this content and prompted the tool to create a first draft product that fits some of the goals I have in mind. I use a series of technology tools in this process and I will identify several options for each stage I go through as this post unfolds. First, a couple of additional important concepts.
What I intend is a process focused on my personal decision-making and content vetting. As much as possible, I want to avoid AI hallucinations and I want to take advantage of my thinking and experiences while reducing the labor required to generate the words to externalize my thoughts. I also want to draw on concepts I might not recall at the moment of content creation but that take advantage of thinking I did at another point in time.
A couple of AI-related concepts that are important are Retrieval-Augmented Generation (RAG) and Source Grounding. RAG is a way of using AI to prioritize specified designated content in contrast to the massive summary of information used to train an AI model. I think of the goal in this way (my interpretation). I want an AI tool to use its language and communication capabilities to respond to my prompts. When possible, I want the tool to respond to my prompts using just the body of information I have provided. RAG is useful in several ways. Models are fixed at a specific point in time and new information may be available. The information used to train the model may be flawed or inaccurate relevant to a specific context of application and information can be prioritized to avoid the use of such an idea. My intent is related to this issue. I want the content produced to represent information and positions I support.
Source grounding is a similar issue but approached from the opposite direction. What sources were used by the AI tool to generate a specific part of the output? If you think in terms of notes and highlights, what was the section of highlights or the note associated with a given statement in the output?
This combination while not perfectly implemented in most tools, offers a reasonable way for an “author” to vet content they intend to take responsibility for sharing.
Specific tools and processes
Source material processing. Most of the information I write about I first encountered as a Kindle book or a journal article available to me as a PDF. I use tools to read and think about this material that allow highlighting and annotation and then the exporting of these notes and highlights containing metadata allowing identification of source and location from which the items were taken. Quantity is important here. I have a personal library of more than a hundred Kindle books and hundreds of journal articles. Kindle devices or apps allow both annotation and highlighting. I have used several pdf tools to do the same thing. Highlights is my present favorite. Again, what is essential is the opportunity to export the notes and highlights as a document I can then import for the next stage of the sequence.
Storage, post-processing, and retrieval. The popular term for describing the next stage of my process might be Second Brain. This is the notion that adults outside of a school environment have long-term learning needs – they learn something at one point in time and they could apply what they once learned after a considerable delay. Without external storage, what they once understood could easily be forgotten. What they once understood in a different context might still be useful if reworked for a different situation. Digital storage allows an external representation of what was once understood and encourages review activities encouraging new insights. Digital storage allows various approaches to search that can surface forgotten insights.
I have written frequently about the implementation of this concept. To keep things simple for this post, Obsidian is my tool of choice within this category. I can generate notes to be stored by this tool as I read. I can also copy and paste notes and highlights from other tools. ReadWise is a utility that makes this process even easier. It automatically downloads highlights and annotations I create while reading using Kindle and with an Obsidian plugin automatically checks for new highlights or notes and uploads these highlights and annotations to Obsidian. So, overtime my Second Brain grows both manually and automatically as I read.
3. Discovery, exploration, and first drafts. This is the point at which AI makes an appearance in how I get from reading and thinking to writing. Typically, second-brain advocates promote strategic exploration of second-brain content as the way to get to externalization through writing. Review your notes. Search for connections among your notes. Enter new notes based on these processes of review and connection. AI applications with RAG capabilities allow a user to explore the content they have identified in a different way. You can interact with this content directly and in a speculative way. You can propose requests for analysis or comparison. In my case, some of these highlights and notes are now at least five or more years old so sometimes I rediscover ideas that would not come to mind without this assistance. Tools that offer source grounding allow easy access to the specific pdfs and comments associated with a claim generated by the AI tool and make it easy to review the context and related arguments from the original sources. You can return to specific sections of material and consider it from a new perspective.
My hope is that the structure I offer here will encourage you to spend some time with the tools I identify. I have used the following AI tools and propose they are worth a try.
MEM.ai – an online note-taking and exploration tool with built-in AI capabilities
NotebookLM – an online note-taking and exploration tool with built-in AI capabilities
These tools are different in several ways that may be of interest. While Obsidian is an open source tool and so are the two plugins I have mentioned, the plugins require an OpenAI api that requires a subscription. I have found the use of this API is very inexpensive and far more so than the $20 a month plan for say ChatGPT. Obsidian is resident on your device. MEM.ai is an online service with a subscription price of a little over $8 a month when committing to the yearly plan. NotebookLM offers the easiest approach for source grounding and the other tools require playing with the prompt to get note titles and links. The automatic transfer of Kindle notes and highlights to the note-taking tool via Readwise only works for Obsidian. So, these AI tools will do similar things, but work in different ways with different financial costs.
Comparison with example
An example may make what I have described more concrete. Recently, I wrote a post comparing two books – The Anxious Generation and Unlocked – that offer very different perspectives on the dangers of screen time and social media to children and adolescents. I read both books generating highlights and notes and then wanted to write a post summarizing each and comparing the perspectives provided by he author. This post can be found on my blog.
I have since made use of the four AI tools I list here to generate a short first draft on this same topic. In each case, I used the following prompt:
Using my notes, write a 600 word comparison of how Haidt and Etchells describe the relationship between adolescent phone use and mental health.
I include the output from the four tools here. They are similar, but for sake of completeness all have been provided should someone want to compare and contrast the products. Of course, such comparisons are inexact as the same tool would produce slightly different outputs should the tool respond to the same prompt several times. I don’t really expect anyone to read the multiple versions of output, but recommend you read the prefacing description of the tool to determine if that tool might fit your circumstances.
NotebookLM
NotebookLM allows me to most easily demonstrate the combination of RAG and Source Grounding. The challenge within my workflow is moving content from Obsidian to NotebookLM. I have found a way to do this efficiently and explain this process in an earlier post.
If you are unfamiliar with NotebookLM, the image that follows offers a peek at the interface. NotebookLM is a web-based tool so what is displayed is what would be seen within your browser. I have started a notebook for the specific goal of comparing my notes on these two books and I have already uploaded my collection of notes and highlights into NotebookLM. The left-hand column indicates that four sources have been added. The text box for entering a prompt to “chat” with these resources appears at the bottom of this image.
In response to the prompt, the AI capabilities of NotebookLM generates a response. The following image is complicated but shows multiple things. There is the response to the prompt which I will provide following the image. Within this content, you should see small numbers associated with different sections of the output text. These numbers when selected open a window showing the segment of the source content that was used by the AI system to produce the output. The connection of something specific from the source material with a claim made in the output is what I mean by source grounding. As you can see, I then have access to the source content and can explore the context of the designated material if I want to consider whether I agree with the interpretation made by the AI.
NotebookLM prompt response
Differing Views on Phones and Mental Health
Jonathan Haidt and Pete Etchells both examine the relationship between screen time and adolescent mental health. Haidt, author of The Anxious Generation and The Anxious Generation 2, takes a strong stance, arguing that smartphones are detrimental to the mental health of young people. Conversely, Etchells, author of Unlocked: The Real Science of Screen Time, believes that current research does not support this view, suggesting instead that the relationship is more complex and nuanced than commonly portrayed.
Haidt contends that the introduction of smartphones, coupled with an increasingly safety-focused upbringing, has led to a decline in the mental well-being of Gen Z. He argues that several key factors contribute to this decline:
Social Deprivation: Smartphones supplant face-to-face interaction, leading to a lack of vital social skills development.
Sleep Deprivation: Smartphone use often extends late into the night, leading to insufficient sleep, which is crucial for adolescent development.
Attention Fragmentation: The constant stimulation from smartphones makes it difficult for adolescents to focus on tasks, potentially hindering academic performance and emotional regulation.
Addiction: The design of social media platforms exploits psychological vulnerabilities, leading to addictive patterns of use.
Haidt supports his argument by highlighting the correlation between the rise of smartphone use and the increase in mental health issues among adolescents. He points to 2012, the year when Facebook acquired Instagram and rates of depressive episodes began to rise, as a pivotal moment in this trend. He emphasizes the importance of face-to-face, synchronous interaction for healthy emotional development, a type of interaction that social media platforms largely fail to provide. Instead, social media, with its emphasis on likes, shares, and followers, fosters conformity and potentially harmful social comparisons. Haidt is especially concerned about the impact of social media on girls, noting that the worst years for social media use for girls are between 11 and 13. He advocates for delaying smartphone ownership until high school and restricting social media use until age 16. He also argues for phone-free schools and more opportunities for unsupervised play, allowing children to take risks and develop resilience.
Etchells, however, cautions against drawing simplistic conclusions about the relationship between screen time and mental health. He argues that many studies linking smartphone use to negative outcomes rely on self-reported data, which can be unreliable and influenced by prevailing societal narratives about screen time. He points out that large-scale, longitudinal studies that track actual smartphone usage over extended periods are scarce, making it difficult to establish causal relationships. He also emphasizes the importance of considering the context of smartphone use, rather than focusing solely on the amount of time spent online. Factors such as the specific apps used, the purpose of use, and the social context of online interactions can significantly influence the impact of screen time on mental well-being.
Etchells critiques the use of anecdotal evidence and alarmist headlines in the media, arguing that such stories, while compelling, can distort public understanding of the issue. He suggests that focusing on developing healthy screen habits, rather than demonizing technology, is a more productive approach. He advocates for a nuanced understanding of screen time, acknowledging both its potential benefits and risks.
Both Haidt and Etchells agree that more research is needed to fully understand the complex interplay between screen time and adolescent mental health. While their perspectives differ in terms of the severity of the issue and the proposed solutions, both authors offer valuable insights into a topic of increasing societal concern.
Smart Connections and Copilot
Smart Connections and Copilot are both plugins added to Obsidian and both rely on the OpenAI API (requires a subscription). It makes sense to simply suggest these plugins are options that do very similar things.
If you are unfamiliar with Obsidian, the following image is intended to show the basic functions. The left-hand (note folders) and middle column (a selected note) concern displaying, locating, and inputting notes. The right-hand column serves a variety of additional functions including accessing and using plugins. Two symbols in the red square at the top of this column allow the selection of either the Copilot or Smart Connections capabilities. The text box within the red square at the bottom is for the submission of a prompt to the AI plugin. The response to the prompt appears in the now vacant area above the prompt window.
Smart Connections Prompt Response
Based on your notes, Jonathan Haidt and Pete Etchells offer contrasting perspectives on the relationship between adolescent phone use and mental health. Haidt, in his book “The Anxious Generation,” argues that smartphones and social media have contributed to a surge in anxiety and depression among young people, particularly focusing on the impact of the widespread adoption of technology in the late 2000s and early 2010s. He proposes solutions such as delaying smartphone and social media access until high school, implementing phone-free schools, and promoting unsupervised play to address the mental health challenges faced by adolescents.
On the other hand, Etchells, in his book “Unlocked,” challenges the common narrative surrounding screen time and mental health. He argues that the issue is more complex than simply quantifying screen time and emphasizes the importance of how individuals engage with technology. Etchells suggests that some screen time can be beneficial and urges readers to reflect on their screen habits, considering factors such as content consumed, apps used, and context of use. He encourages a more thoughtful and intentional approach to technology use to support and improve mental health.
Haidt’s perspective is supported by research indicating a negative correlation between social media use and life satisfaction, particularly among younger adolescents. He highlights key dates associated with changes in technology, such as the introduction of iPhones in 2009 and the acquisition of Instagram by Facebook in 2012, correlating with a significant upturn in depressive episodes among Gen Z around 2012. Haidt’s argument is further reinforced by the addictiveness of social media, which exploits users’ identities and impacts emotional development.
In contrast, Etchells challenges the notion that screen time is a key driving factor behind the decline in mental health. He emphasizes the need to focus on how individuals engage with technology rather than solely measuring screen time. Etchells suggests that understanding and reframing screen habits, reflecting on behaviors, and being critical of information can help individuals leverage technology to support their mental well-being.
Overall, while Haidt highlights the detrimental effects of smartphone and social media use on adolescent mental health, Etchells offers a more nuanced perspective, advocating for a shift in focus towards healthy screen habits and intentional technology use. Both authors contribute valuable insights to the ongoing debate on the relationship between adolescent phone use and mental health, providing readers with different perspectives to consider when addressing this complex issue.
CoPilot Prompt Response
To write a comprehensive comparison of how Jonathan Haidt and Tim Etchells describe the relationship between adolescent phone use and mental health, we need to delve into their respective perspectives and analyses. Both authors have explored this topic, albeit from different angles and with varying emphases
Jonathan Haidt’s Perspective
Jonathan Haidt, a social psychologist, has extensively researched the impact of social media and smartphone use on adolescent mental health. Haidt argues that there is a significant correlation between increased smartphone use and the rise in mental health issues among adolescents, particularly anxiety and depression. He often cites statistical data and longitudinal studies to support his claims, pointing out that the surge in mental health problems coincides with the widespread adoption of smartphones around 2012.
Haidt emphasizes the role of social media platforms in exacerbating feelings of inadequacy and social comparison among teenagers. He suggests that the curated nature of social media content leads adolescents to constantly compare themselves to others, which can result in negative self-perception and increased anxiety. Furthermore, Haidt highlights the addictive nature of these platforms, which are designed to capture and hold users’ attention, often at the expense of real-world interactions and sleep, both crucial for mental well-being.
Tim Etchells’ Perspective
Tim Etchells, on the other hand, approaches the topic from a more nuanced and perhaps less deterministic angle. While acknowledging the potential negative impacts of smartphone use, Etchells is more focused on the context and manner in which these devices are used. He argues that smartphones are not inherently detrimental to mental health; rather, it is the way they are integrated into daily life that matters.
Etchells emphasizes the importance of digital literacy and the need for adolescents to develop healthy habits around technology use. He suggests that when used mindfully, smartphones can offer significant benefits, such as fostering connections, providing access to supportive communities, and serving as tools for creativity and self-expression. Etchells is more likely to highlight the potential for positive outcomes, such as increased access to mental health resources and the ability to maintain relationships across distances.
Comparative Analysis
When comparing Haidt and Etchells, several key differences emerge in their analyses of the relationship between adolescent phone use and mental health. Haidt tends to focus on the negative consequences, often presenting a more cautionary tale about the pervasive influence of smartphones and social media. His approach is data-driven, relying heavily on empirical evidence to underscore the risks associated with excessive use.
In contrast, Etchells offers a more balanced view, acknowledging both the potential harms and benefits of smartphone use. He advocates for a more individualized approach, considering the diverse ways in which adolescents engage with technology. Etchells is more optimistic about the potential for positive outcomes, provided that there is an emphasis on education and the development of healthy digital habits.
Both authors agree that there is a relationship between smartphone use and mental health, but they diverge in their interpretations and proposed solutions. Haidt calls for more stringent regulations and societal changes to mitigate the negative impacts, while Etchells focuses on empowering individuals through education and awareness.
Conclusion
In summary, Jonathan Haidt and Tim Etchells provide contrasting yet complementary perspectives on the relationship between adolescent phone use and mental health. Haidt’s analysis is rooted in caution and concern, highlighting the potential dangers and advocating for systemic changes. Etchells, meanwhile, offers a more hopeful outlook, emphasizing the role of education and personal responsibility in navigating the digital landscape. Together, their insights contribute to a more comprehensive understanding of this complex issue, underscoring the need for a balanced approach that considers both risks and opportunities.
MEM.ai
I started Mem.ai because it was from the beginning a note system that incorporated AI. I had to manually upload the notes I entered in Obsidian. Mem.ai proposed that the linking and tags advocated as so important in Obsidian were less necessary when one could apply AI capabilities to explore the stored notes. There seemed some logic to this proposal and I wanted to see what I thought after using both systems.
MEM.ai Prompt Response
Certainly! Let’s delve into a comparison of how Jonathan Haidt and Pete Etchells describe the relationship between adolescent phone use and mental health, using insights from your notes.
Comparing Perspectives: Haidt vs. Etchells on Adolescent Phone Use and Mental Health
The discourse surrounding adolescent phone use and its impact on mental health is a complex and multifaceted one. Jonathan Haidt and Pete Etchells offer distinct perspectives on this issue, each bringing unique insights into how digital technology influences the well-being of young people. While Haidt presents a more cautionary view, Etchells provides a nuanced analysis that considers both risks and benefits.
Haidt’s Perspective: A Warning on Digital Dangers
Jonathan Haidt, a prominent social psychologist, has been vocal about the potential dangers of smartphone use among adolescents. His perspective is largely shaped by the following points:
1. Correlation with Mental Health Decline: Haidt highlights a significant uptick in mental health issues, such as anxiety and depression, among teenagers starting around 2011. He correlates this trend with the rise of smartphones and social media, suggesting a causal link between increased screen time and deteriorating mental health.
2. Social Media’s Role in Psychological Distress: Haidt argues that social media platforms exacerbate feelings of inadequacy and low self-esteem, particularly among adolescent girls. The constant exposure to curated images and the pressure to gain social validation can lead to harmful comparisons and social anxiety.
3. Gender-Specific Vulnerabilities: Haidt emphasizes that adolescent girls are especially vulnerable to the negative effects of social media. He attributes this to the heightened focus on appearance and social comparison, which are more pronounced in female social media interactions.
4. Advocacy for Restrictive Measures: To combat these issues, Haidt advocates for delaying smartphone use among children. He suggests policies like “No smartphones before high school” to reduce exposure to potentially harmful digital environments and promote healthier developmental outcomes.
Etchells’ Perspective: A Balanced Approach
In contrast, Pete Etchells offers a more balanced view of the relationship between adolescent phone use and mental health. His analysis considers both the potential risks and the benefits of digital technology:
1. Empowerment through Connectivity: Etchells acknowledges that smartphones and social media can empower adolescents by providing access to information, educational resources, and supportive communities. This connectivity can foster a sense of belonging and enhance self-efficacy.
2. Importance of Digital Literacy: Etchells stresses the role of digital literacy in helping adolescents navigate the online world safely. By equipping young people with critical thinking skills and the ability to manage their digital presence, they can mitigate potential negative impacts.
3. Balanced Screen Time: Rather than advocating for strict limitations, Etchells promotes a balanced approach to screen time. He suggests that integrating both digital and physical activities can help adolescents develop a healthy relationship with technology.
4. Focus on Resilience and Adaptation: Etchells believes that with proper guidance, adolescents can develop the resilience needed to thrive in a digital world. By fostering emotional intelligence and critical thinking, young people can learn to navigate the challenges of social media and smartphone use.
Contrasting Approaches to Solutions
While both Haidt and Etchells recognize the significant impact of smartphone use on adolescent mental health, their approaches to addressing these challenges differ:
Restrictive vs. Empowering Solutions: Haidt’s approach is more restrictive, focusing on limiting exposure to technology as a means of protecting mental health. In contrast, Etchells emphasizes empowerment through education and digital literacy, advocating for a more nuanced understanding of technology’s role in adolescents’ lives.
Focus on Risks vs. Opportunities: Haidt’s narrative centers around the risks and negative outcomes associated with smartphone use, particularly for adolescent girls. Etchells, however, highlights the opportunities for empowerment and connection that technology can provide, suggesting that the benefits can outweigh the risks when managed appropriately.
Conclusion: Navigating the Digital Landscape
The contrasting perspectives of Haidt and Etchells underscore the complexity of the relationship between adolescent phone use and mental health. While Haidt’s concerns about the negative impacts are valid, Etchells’ emphasis on empowerment and education offers a hopeful path forward. Ultimately, the key lies in finding a balance that maximizes the benefits of technology while mitigating its risks, equipping young people with the tools they need to thrive in an increasingly connected world.
This comparison captures the essence of both authors’ views, providing a comprehensive look at their differing approaches to adolescent phone use and mental health. If there are specific points you’d like to adjust or expand upon, feel free to let me know!
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My goal is to offer some options you might consider. I find advantages and disadvantages with each approach and still use a couple of these tools when I think the first one could be improved.
The benefits and harms done by our devices and the ways we use them is one of those topics likely of at least marginal interest to most people. We wonder whether we have become too dependent and whether existing interests and capabilities have deteriorated. If we are a parent or educator we likely have additional unique interests. Have I messed up my kid by letting him or her use a phone without supervision? How do I keep my students on track in the classroom and are they using AI to complete my assignments quickly without any actual educational benefits?
My personal interest goes a bit further in that I spent my career preparing educators to use technology in their classrooms and I by training feel responsible for understanding the science behind recommendations made to others. So, I review the research on many topics. From this perspective, I would offer the following observation – it is seldom as simple as it seems. I know this to be true in the social sciences which would be the field covering phone use and the impact on development and learning. This is the case for many reasons and far from a topic I can thoroughly consider here. One comment I used to make to my own students may be helpful. For context, I was trained as a biologist who became a psychologist. My comment was – students tend to see a discipline like chemistry as more sophisticated and complicated than psychology. Consider that the chemicals in that beaker don’t decide whether they feel like reacting today. People are different.
Back to the issue of our devices and the research on how we are being impacted. I recently read a book by Jonathan Haidt titled The Anxious Generation. Many people must have read this book because it topped the New York Times best-seller list for several weeks which I interpret to mean many parents and educators are concerned and were attracted by the topic. Recommendations made in the book, for example, no phones in schools, have been implemented in many schools. I read Haidt’s book in response to such changes concerned my pro-technology advocacy should be tempered. I admit my initial reaction was that Haidt made a reasoned and evidence-based case. However, I have learned that such secondary sources need to be vetted and I was concerned by some of Haidt’s rationale which I would describe as “what else besides iPhones and Instagram” could explain the mental health issues of adolescent females. The “what else could it be” logic just seems weak. In reaction, I read a related, but less well-known book by Pete Etchells and as I suspected the issue is complicated.
What follows is my summary of the two books with some related comments.
Comparing Perspectives on Screen Time and Mental Health
Haidt’s “The Anxious Generation”
In “The Anxious Generation,” Jonathan Haidt really covers two broad problems he contends have changed the mental health development of children and adolescents. Children have been overprotected in their daily lives resulting in a lack of play and autonomy involving risks and consequences. In contrast, the author argues that the rise of smartphones and social media have been largely unmonitored and unrestricted with negative consequences to mental health. I will comment on both claims, but emphasize technology use.
Haidt highlights the following key points:
Slow-Growth Childhood: Human children have an extended childhood compared to other mammals, providing them with time to learn through play and social interactions. This extended childhood is crucial for emotional and cognitive development.
Importance of Play: Play-based childhoods are essential for healthy development, fostering skills such as emotional regulation, social competence, and creativity.
Safetyism: Haidt argues that the overprotective parenting style prevalent in the 1990s, termed “safetyism,” limited children’s opportunities for risk-taking and independence, further contributing to anxiety. Haidt uses example older folks will find familiar – e.g., playground equipment that is no longer allowed for safety reasons and reduced independence in moving about the neighborhood or in solo trips to the store.
Negative Impacts of Smartphones: These problems include:
Social deprivation: Replacing face-to-face interaction with screen time.
Sleep deprivation: Late-night phone use cutting into sleep at ages when necessary. The early school start for adolescents is an example of when this becomes a problem.
Attention fragmentation: Constant notifications and multitasking impairing focus.
Addiction: The design of social media platforms promoting addictive behaviors. Etchells will reject this notion if understood as a physiological addition as in drug use.
Puberty as a Sensitive Period: Puberty is a critical period for brain development, making adolescents particularly vulnerable to the negative effects of social media. Hence, experiences allowed at other ages may do less damage.
What evidence suggests that puberty is a “sensitive period” for social media use?
Brain Development: Puberty to a greater degree than the earlier period of childhood involves the pruning of neurons and the strengthening of connections, processes influenced by experiences. This heightened neuroplasticity implies that experiences during puberty, including social media use, can have a greater and more enduring impact on brain structure and function.
Orben’s Research: Amy Orben, found that negative correlations between social media use and life satisfaction were more pronounced in the 10-15 age group, encompassing puberty, compared to older individuals (16-21). This finding directly supports the idea of puberty as a sensitive period for social media’s influence on well-being.
Social Learning and Conformity: Adolescents are conformers, a process that social media platforms can strongly influence. Puberty marks a time when individuals are particularly sensitive to social cues and peer influence, seeking to establish their identity and social standing. Social media platforms, with their emphasis on likes, followers, and influencers, can hijack this natural drive for social learning, potentially leading to distorted perceptions and unhealthy comparisons. Giirls are most vulnerable to social media’s negative effects between 11 and 13, while boys experience this heightened vulnerability between 14 and 15. This timeframe aligns with typical puberty onset, further suggesting that the hormonal and social changes during this period make adolescents more susceptible to the pressures and comparisons prevalent on social media.
In conclusion, the sources provide converging evidence pointing to puberty as a “sensitive period” for social media use. This sensitivity stems from the interplay of rapid brain development, heightened social awareness, and the drive for conformity, all characteristic of adolescent development. This information suggests that social media use during puberty requires particular attention and potentially different approaches compared to other age groups.
Haidt makes use of historical data linking changes in mental health data over the years to changes in the technology available to young people. Much of Haidt’s argument about the damage done by access to the Internet is made by tracking mental health outcomes against dates associated with changes in technology. Gen Z started to reach puberty in 2009. iPhones became available in 2009. Social media capabilities such as retweets and likes became available in 2009. Front facing cameras in 2010. Facebook acquired Instagram in 2012. His challenge to critics is what else could have accounted for the changes in adolescent mental health that correspond to this time frame.
Recommendations: Haidt proposes four solutions to address this issue: no smartphones before high school, no social media before age 16, phone-free schools, and promoting more unsupervised play and childhood independence.
Etchells’ “Unlocked”
Pete Etchells, in his book “Unlocked: The Real Science of Screen Time (and how to spend it better)” offers a more nuanced view of screen time and its relationship to mental health.
Etchells first notes that the consequences of technology and social media likely include both positive and negative impacts so explanatory models must take into account both possible outcomes. Etchells’ key arguments include:
Screen Time is Complex: Etchells argues simply measuring the total amount of screen time is insufficient to understand its impact on well-being. What matters is how screen time is used, the specific apps and content consumed, and the context of use.
Limited Evidence for Strong Negative Effects: While some studies have shown correlations between screen time and mental health issues, the evidence is mixed, with many studies showing small or inconsistent effects. The existence of correlations even if the correlation reflected a causal relationship with negative changes in mental health as a consequence do not necessarily show large effects. The impact is typically small.
Etchells critiques the reliance on anecdotal evidence and highlights methodological limitations in much of the research. One of the most important methodological limitations appears to be whether self-reports versus verifiable behavioral data are used. Even though digital devices are great at recording data on use (consider your iPhone and your daily report of time spent on different apps) many studies ask users to estimate their time spent and activities experienced. When studies using self-report data are compared with studies using the more accurate data collected by the devices used, significant relationships are typically found only with the self-report data. Etchells speculates that user awareness of screen time issues and potential negative consequences results in participants in these studies interpreting negative personal experiences as an indication of too much screen time. How individuals feel about their screen use and their perceived self-control are more strongly related to well-being than objective measures of screen time.
Importance of Habits over Addiction: Etchells argues that framing excessive screen use as “addiction” is unhelpful, as it focuses on abstinence as the only solution. Instead, he advocates for viewing screen use as a set of habits that can be modified to promote well-being. The author argues that the assumption of a physiological explanation (probably dopamine) within the framework of addictions such as drug abuse is what readers of many of the negative books assume. Addiction tends to ignore agency and motivation. This is where the notion of habits also fits and solutions that are more nuanced with a focus on decision-making and awareness.
Oversimplification of “Screen Time”: Etchells argues that simply measuring the total amount of time spent in front of screens is too crude a metric to be meaningful. He emphasizes that “screen time” encompasses a vast range of activities, from educational apps to social media to video games, each with potentially different effects on well-being. He contends that focusing solely on duration ignores the crucial factors of content, context, and purpose of use.
Reliance on Anecdotal Evidence: Etchells criticizes the prevalent use of anecdotal stories to support claims about the negative impacts of screen time. While these stories can be compelling and relatable, he argues they often lack scientific rigor and can lead to biased conclusions. We like stories because we often can relate to such examples and do not necessarily make the same connections with the data in graphs and statistics. Of course, coming up with examples that fit a perspective does not necessarily fit what is most common in a sample of participants. He points out that reliance on anecdotes is particularly problematic in a relatively new field like digital technology research, where robust, longitudinal data is still limited.
Methodological Issues in Correlational Studies: Much of the research on screen time relies on correlational studies, which can only demonstrate associations, not causal relationships. Etchells highlights the problem of “third variables,” unaccounted-for factors that might influence both screen time and mental health, leading to spurious correlations. For example, pre-existing mental health conditions, family dynamics, or socioeconomic factors could contribute to both increased screen time and negative well-being outcomes, creating the illusion of a direct link where none exists. Correlations showing relationships do not necessarily convey the magnitude of an effect. A significant correlation in a large population may be associated with a very small impact.
Lack of Theoretical Framework: Etchells argues that the field lacks a robust theoretical framework to guide research and interpret findings. He suggests that without clear theoretical models, researchers are left to “grasp at straws,” making tenuous connections between screen time and a wide range of outcomes without a solid foundation for understanding the underlying mechanisms. This lack of theoretical grounding makes it difficult to develop testable hypotheses and draw meaningful conclusions. Haidt’s “what else could it be” argument fits here.
Ambiguous Terminology: Etchells points out the imprecise use of terms like “addiction” and “attention” in screen time research. He criticizes the tendency to label excessive screen use as “addiction” without sufficient evidence of a true physiological dependence. He also argues that “attention” is often used interchangeably with “self-control,” leading to conceptual confusion and misinterpretations of research findings.
Insufficient Attention to Positive Effects: Etchells argues that the focus on potential negative consequences of screen time has overshadowed research on its potential benefits. He acknowledges that excessive or problematic screen use can be detrimental, but he emphasizes the importance of recognizing the many ways in which technology can enhance learning, communication, and social connection. He encourages a more balanced approach that considers both the positive and negative aspects of screen time.
In conclusion, Etchells urges caution against drawing sweeping conclusions about the impact of screen time based on the existing research. He advocates for more nuanced investigations that consider the complexities of technology use, adopt rigorous methodologies, and develop strong theoretical frameworks to guide future research.
Comparing Haidt and Etchells
While both Haidt and Etchells acknowledge the potential downsides of excessive screen time, they differ significantly in their overall perspectives and conclusions:
Emphasis on Negative Effects: Haidt emphasizes the negative impacts of smartphones and social media, attributing a rise in mental health problems directly to these technologies. Etchells, on the other hand, acknowledges the potential for harm but argues that the evidence for strong negative effects is weak and often overstated.
Role of Social Media: Haidt sees social media as a particularly harmful force, promoting conformity, comparison, and addiction. Etchells recognizes these potential issues but maintains that social media can also have positive benefits, depending on how it is used. The existence of both positive and negative outcomes argues against simplistic abstinence/avoidance and urges more careful personal awareness and control.
Solutions: Haidt proposes strict limitations on smartphone access and social media use, advocating for a return to a more play-based childhood with less adult supervision. Etchells focuses on promoting healthy screen habits, emphasizing individual agency and self-regulation rather than strict restrictions.
Conclusion
Haidt’s “The Anxious Generation” presents a compelling, albeit alarming, argument about the potential downsides of technology for young people. However, Etchells’ “Unlocked” offers a more balanced perspective, urging caution against oversimplifying the complex relationship between screen time and mental health. The key takeaway is that understanding the nuances of screen use and focusing on developing healthy habits is crucial for mitigating potential harms and maximizing the benefits of technology. Both books highlight the importance of critical thinking and evidence-based approaches when evaluating the impact of technology on our lives.
Sources:
Etchells, P. (2024). Unlocked: the real science of screen time (and how to spend it better). Hachette UK
Haidt, J. (2024). The anxious generation: How the great rewiring of childhood is causing an epidemic of mental illness. Random House.
I have been reading Robert Haidt’s “The Anxious Generation”. This post is not a description of that book, but the book’s focus and content were the origin of my present topic. The book, which has topped the New York Times best-seller list for some weeks, focuses on the mental health damage of the way kids are raised in combination with the negative impact of social media. Haidt is particularly concerned about young girls and their susceptibility to the negative consequences of what becomes a damaging addiction to social media. While male and 75, I had an uneasy feeling Haidt could have been describing me and my preoccupation with a different online environment. Before I get to my personal insight, allow me to describe the characteristics Haidt argues drive the general problem that is the focus of his book.
Haidt proposes that the writings of B.J. Fogg have served as the bible guiding many social media entrepreneurs. I usually read the core literature associated with what I write, but Fogg’s book was priced at textbook levels and I decided I was very familiar with the central content (a different source). Fogg successful persuasion can be accomplished based on behavioral principles any college student who has taken the Introduction to Psychology course will recognize. His terminology is a little different. When I taught the Intro course, I described the process Fogg and Haidt emphasize as operant conditioning. A very simple version of the way operant conditioning changes behavior is captured in the sequence – stimulus – response – consequences. Behavior changes (response) are encouraged by positive consequences. When used to account for what seems an addiction to online social media in children, the response might be frequent checking of a social media account and the positive reinforcers (likes, comments, attention, etc.). Access to a phone (the stimulus) triggers the initial behavior generating the consequences.
The Fogg version is described in the following model.
Fogg uses a little different vocabulary. The external trigger is his term for stimulus and action is the behavior. Variable reinforcement is another concept from behavioral psychology that translates as a situation in which a behavior does not produce a consequence every time it is produced. This unpredictability increases the frequency of behavior. A common example is the way a slot machine works. A gambler would soon quit if previous experiences were always wins and now the machine stops paying out. You tend quit putting coins into a vending machine if the first attempt or maybe the second produces no soda or candy bar. If however, a slot machine generates wins now and then people keep feeding their coins.
Fogg and Haidt add one additional component to the model – investment. Social media often has another characteristic increasing holding power. The example of investments are everywhere online. Do you play that online game where you have to guess the spelling of a mystery word within so many tries? If you have a streak of days going, you have an investment that makes it very likely you will not miss a day. Do you take photos or use AI to create photos to embellish your posts? You are making an investment. Do you pay to add weapons or clothing (skins) in an online game? You are investing. When your identity becomes part of your participation in an activity, you are heavily invested. I would suggest making political comments on social media are a good example of being invested. Our political affiliations are part of our identities. Haidt argues that Instagram has such a powerful impact on young females (often negative) because the photo-heavy nature of the platforms triggers the role appearance has in the identity of young women.
Social media involves a switch from external triggers to internal triggers. Once you are involved, you don’t have to be sent a message that you have a new like or comment. You don’t have to see your phone sitting on your desk. Your thoughts lead you to get your phone out of your pocket or purse to check your accounts to see if anything new has shown up.
Haidt emphasizes the powerful impact of social media on the attention and mental health in children and adolescents. I saw a similarity in the application of the model and the arguments made to adults who write on blogs, Substack and Medium. I don’t think the negative impact holds in the same way because of the life experiences and brain maturity (frontal cortex and metacognition) of adults and draw the following parallels more out of amusement than concern. If there was one insight that triggered me to write this post, it was the recognition of identity in motivating behavior more so than the behavioral explanation. For those who write, writing for public consumption is part of personal identity. I think the behavioral impact on behavior is more powerful because of this self view.
Here is my attempt to apply the cycle of engagement (Haidt and Fogg) to writing:
1. Trigger
The cycle starts with a trigger that prompts users to take an action. Triggers can be:
External triggers: Notifications, emails, messages, ads, or reminders that tell users to open an app or take action. For example, a push notification letting you know someone liked your post.
Internal triggers: Emotions, thoughts, or desires that come from within, like boredom, curiosity, just wondering if there is something there. These feelings push users to check their phone or social media without an external prompt.
2. Action
After the trigger, the user performs an action. The action may be simple such as seeing if anyone has read your post or liked your content. There may be statistics or charts to check. The actions that are triggered can be more involved such as researching and writing another post.
3. Variable Reward
Once the action is taken, the user receives a reward, but to keep engagement high, the reward is often variable or unpredictable. This uncertainty makes the reward more powerful or resistant to extinction in behavioral terms.
Social rewards: Users may get more or fewer likes, comments, or shares on their posts each time, keeping them hooked. In some writing platforms, there is financial compensation to check.
4. Investment
The final stage of the cycle is investment, where the user puts something of value back into the platform. This investment can be time, effort, data, or emotional input, and it increases the likelihood that the user will return to the platform. Examples include:
Creating content: Posting a photo, video, or comment.
Personalization: Customizing a profile or favoriting the work of others.
Building relationships: Adding friends, replying to messages, or participating in communities.This investment helps users feel more connected to the platform because they’ve contributed, and it primes them for future triggers. As they invest more, they become more likely to engage again, as their investment increases the value of the platform to them
Financial commitment: Payment of a fee to participate.
Affirmation of identity: The content I generate and share demonstrates I am a writer.
5. Repeat
Once users have invested in the platform, they receive new triggers, starting the cycle all over again. Over time, this cycle builds a habit, with users increasingly relying on internal triggers, such as boredom or curiosity, to engage with the platform.
If you are a writer who contributes content online, you may see yourself in this description. With social media, such models are used to describe how participants are drawn into spending more and more time in such environments sometimes with negative emotional consequences. I will leave it to your own analysis to determine whether being drawn into a platform to which you contribute your writing impacts your emotional well-being.
Reference
Fogg, B.J. (2003). Persuasive technology: Using computers to change what we think and do (Interactive Technologies).
Many of us have now had the opportunity to spend considerable time with AI tools and have sorted out for ourselves what types of applications are most productive. For my personal use, I found the greatest value in the use of AI to analyze the notes and highlights I have accumulated over the years to search for insights I might use in my writing projects. I keep most of my notes in Obsidian and one of the more popular posts I have generated focusing on AI and personal notes explained my approach to using the Obsidian AI extension Smart Connections.
As I continue exploring, I have found another approach that others may find useful. This approach uses the Google AI tool NotebookLM. This tool is presently provided at no cost and is easy to use. There is a frustrating mismatch between how most of us use Obsidian and the structure of NotebookLM. Obsidian users typically create many short notes and then create links and tags to allow these notes to be stored and used in the most flexible manner possible. NotebookLM allows the uploading of considerable content into an individual notebook to be explored with AI chats, but limits the number of files that can be included. This combination – many small files in Obsidian and a limited number of files in NotebookLM notebooks – creates a challenge.
Here is my present solution. There is an extension for Obsidian (Better Export PDF) that allows the content from multiple files stored within an Obsidian folder to be exported as a single PDF. You can probably see where this is going. Export the many files in several folders as PDFs and then add these PDFs to NotebookLM.
The Better Export PDF in Obsidian
The following image was captured as I used Obsidian. You can see the multiple folders I have created. After One Better Export has been added to Obsidian, you first right-click (control click) on a folder to bring up various options. The one you want is Export folder to PDF.
Activating this option may leave you confused as the process takes some time to accomplish. You know when things are working properly when you see the names of individual files appear towards the top of the display (red box). When the process of concatenating the files has been completed the complete PDF file will appear in what initially appears as white space. Now you export this large file.
You complete this process additional Obisian folders until you have exported the large PDFs you want to explore in NoteBookLM.
NotebookLM AI Chat
The following image shows a notebook I have created based on three PDFs (Cognitive, Generative, Notetaking). A couple of hundred individual notes are included in these three large files. At the bottom of the image, you should find a prompt I have entered.
For AI tool users, everything should now be more familiar. NotebookLM has responded to my original prompt and I can accept some of the recommendations for related topics I might explore (not shown). NotebookLM offers a way to review the content the AI used to generate the prompt reply (numbers in the red box). Selecting one of these numbers takes you to the section in your input and allows you to explore that context.
Summary
So, this combination of Obsidian and NoteBookLM seems to work well. The key is the Obsidian extension Better Export PDF which allows many Obsidian notes to be combined to address the limited number of files NoteBookLM will accept as input. Give it a try.
In reading and then writing about Willingham’s The Reading Mind, the author makes some interesting arguments about the relationships between what we know and reading comprehension and between the time spent reading and what we know. As the reciprocal relationship implies, this is a cognitive explanation of how the rich get richer. The author throws in a related analysis of whether our commitment to spending time with technology has diminished the likelihood that we are now benefiting from this relationship. What follows is my embellished summary with a few updates.
I like to think of Willingham’s description of reading as explaining how the inputs to comprehension come simultaneously from opposite directions. The bottom-up inputs come from the page – letter/phoneme recognition, word recognition, word meaning, broader understanding. The top-down inputs come from stored information (memory) – general knowledge, specific knowledge, broad understanding of the passage being read, sentence meaning, etc. You probably recognize that these inputs are really the same series just listed in opposite directions. It turns out these inputs help each other out as many are being processed at the same time. Some of these interactions you may not recognize and may surprise you. For example, a letter at the beginning of a word can be identified faster than the letter in isolation. Others, you may recognize if I bring them to your attention. For example, the understanding of a sentence may help you assign meaning to an unfamiliar word in that sentence. The battle over what is commonly described as the “science of reading” is focused on the early bottom-up processes. Should early reading experiences emphasize associating sounds with word components or should word recognition and context receive greater attention? It might be helpful to understand why the science of reading may seem to change over time because effective reading depends on multiple processes acting to support each other. Many subskills end up being important. I am more interested here in the top-down processes. Once we get past learning the basics of reading, how does reading both depend on and develop what we know?
Willingham proposes that it is never possible for a writer to explain a topic in complete detail and an author must rely on what readers already know to fill in some elements from existing knowledge. So when a reader is exposed to new material understanding is dependent both on reading skill and existing knowledge. What we already know has a surprisingly large impact on what we comprehend and retain. This claim can be demonstrated on two levels – general knowledge and topic specific knowledge.
Anne Cunningham and Keith Stanovich conducted an interesting study of high school students in which they had the students take a test of general knowledge. General knowledge involves all kinds of random information. In their research, students were asked about factual knowledge of science, history, and literature and the accomplishments of people from history, science, sports, and music. It was not that the knowledge of the specific topics was necessarily important, but rather that the scores obtained were predictive of the level of general knowledge more broadly. The researchers also administered a standard test used to evaluate reading comprehension skills. These two variables – general knowledge and comprehension skill were strongly correlated. More capable readers probably have learned more from reading, but what they have learned may also be a factor in determining their reading skill. Such differences are partly responsible for the advantage some students gain from general life experiences that cannot be provided while in the classroom.
The advantage of what we know to reading performance is made clear in studies that investigate the importance of specific knowledge in understanding content related to that knowledge. Willingham used a study based on reader differences in understanding the game of soccer. This surprised me as I was aware of a very similar study based on the game of baseball. A general description of the clever methodologies of these studies will explain how reading skills and relevant knowledge were differentiated. These studies (Recht & Leslie, 1988; Schneider, Korkel & Weinert, 1989) were conducted with younger learners. Depending on the study, these learners were given a test to evaluate their knowledge of baseball or soccer. Scores on reading comprehension tests were also available. These two measures were used to identify four groups of learners – high on both measures, high on one measure and low on the other, low on both measures. After reading a story about part of a baseball game or a soccer match, readers were asked to recall as much as they could from the story. The grouping of readers allowed a way to statistically isolate the impact of reading ability from background knowledge on what was retained. Relevant knowledge was at least as important as reading proficiency to what was taken away from the reading experience. By the way, this type of research should be relevant to those who argue access to Google is equivalent to knowing things. What you can find through search does not offer the same benefit to immediate processing as what you already know.
Leisure Reading and Technology
Leisure reading plays a unique role to developing readers because the time devoted to leisure reading varies far more than the time spent reading in schools. As adults, if we read many of us only engage in reading that would fall in this category. If engaged in an educational setting, leisure reading augments assigned reading as a reading skill development opportunity and as an opportunity to expand the acquisition of general knowledge and that is important in improving the effectiveness of reading.
In the discussion of technology and reading, Willingham considers both whether reading from a screen offers the same benefits as reading from paper and whether our constant use of technology has displaced time spent reading. Willingham acknowledges the research that demonstrates a small benefit for reading from paper. Like my posts on this topic, he sees this difference to be of little consequence acknowledging that the root cause is unknown. My embrace of screen reading is related to the long-term advantages of the production of digital notes and searchable highlights that can be organized and efficiently searched.
The notion that screen time comes at the cost of reading time (displacement) was countered with what to me were some surprising data. In his focus on leisure reading, Willingham argues that Americans never did read much and that this amount of time has not diminished from pre-internet days. I checked Willingham’s sources on this topic and found a more recent survey of adolescent reading behavior (Rideout and colleagues 2022). Reading time has actually increased a bit, but the average daily reading time has now reached 34 minutes. Twenty-four minutes involve books (paper or ebooks) and the rest newspapers, blogs, and other long-form content. I don’t find this average that disturbing given students are also reading for their classes and may have homework. The more disturbing version of this basic statistic is the variability. Nearly 20% of adolescents indicate they read nothing beyond what is assigned at school. Recent data on adult behavior indicates that the average daily reading time is about 15 minutes. Adults don’t set a very good example.
Summary
Reading both is an important source for what we know and what we know benefits the level of reading proficiency we achieve. Reading is an activity we control as individuals and if we so choose we can benefit from spending leisure time in this way.
References:
Cunningham, A. E., & Stanovich, K. E. (1997). Early reading acquisition and its relation to reading experience and ability 10 years later. Developmental psychology, 33(6), 934.
Recht, D. R., & Leslie, L. (1988). Effect of prior knowledge on good and poor readers’ memory of text. Journal of Educational Psychology, 80(1), 16–20.https://doi.org/10.1037/0022-0663.80.1.16 (baseball)
Rideout, V., Peebles, A., Mann, S., & Robb, M. B. (2022). Common Sense Census: Media use by tweens and teens, 2021. San Francisco, CA: Common Sense Media
Schneider, W., Korkel, J., & Weinert, F. E. (1989). Domain?specific knowledge and memory performance: A comparison of high? and low? aptitude Children. Journal of Educational Psychology, 81( 3), 306–312. (Soccer)
Willingham, D. T. (2017). The reading mind: A cognitive approach to understanding how the mind reads. John Wiley & Sons.
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The technical storage or access is strictly necessary for the legitimate purpose of enabling the use of a specific service explicitly requested by the subscriber or user, or for the sole purpose of carrying out the transmission of a communication over an electronic communications network.
Preferences
The technical storage or access is necessary for the legitimate purpose of storing preferences that are not requested by the subscriber or user.
Statistics
The technical storage or access that is used exclusively for statistical purposes.The technical storage or access that is used exclusively for anonymous statistical purposes. Without a subpoena, voluntary compliance on the part of your Internet Service Provider, or additional records from a third party, information stored or retrieved for this purpose alone cannot usually be used to identify you.
Marketing
The technical storage or access is required to create user profiles to send advertising, or to track the user on a website or across several websites for similar marketing purposes.
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