Thought logging

This is a blog and I describe it as a blog, but I have my own definition of the term.

It is a chronological record of my thoughts occurring to me on the day I bother to write.  It is like a diary in that sense.   I am not committing to any regular schedule of writing like what is supposed to happen with a diary or what is expected from a subscriber.   Long periods of no updates is not evidence that I have lost interest in blogging either.  This is a very personal project.

One of the things you may notice is that I like to hyperlink to my past blog posts.   This is partly a reminder to myself that I’m being redundant.  I do keep returning to old ideas and I like to think my newer thoughts add or correct what I have stated before.   However, this was a deliberate intention from the beginning.

Prior to starting this blog, I had a job building a web-based interface to a data base of historical data.   In that job, I got carried away with hyperlinking each data cell so that it goes to a different page specifically about that cell.   The entire site because a rich web of interconnections that jumped up and down and side to side and even epoch to epoch in such a way that each successive page had something to add to the hyperlinked entry.

I originally thought of using this approach to present my thoughts.  I think this approach better matches how I think about things.   I am aware of (though not skilled in) a good design for presenting a well constructed argument in good rhetorical fashion.   I am similarly familiar with good story telling practices.   Both are proven methods of holding an audience’s attention and persuading that audience either of the value of my argument or of the relatability of a story.

There are many blogs that specifically cater to external audiences.   They either deliberately or naturally adapt to gather a regular audience of followers or subscribers.   Usually they also strive to grow their reach with larger numbers of daily views or total views.

Somewhere along the line, the concept of monetization of content became a goal where more views translated to more income from advertisement revenue sharing with hosting service.   This never appealed to me so it amused me to see the controversies that occurred when hosting services changed rules for revenue sharing.

Once I realized that many people were basing their budgets on this arrangement, I gained a lot of respect for their making their blogging in to a way to make a living.   I am humbled by the fact that it didn’t occur to me first even as I heard of the concept of revenue sharing.

The monetization has become the presumed motivation for blogging.   Blogs are judged by their regularity of publishing new content and their consistency in quality and content.   The point of blogging now is to either make money or to build a brand that in turn will attract customers of services or products.

Most of that type of blogging has moved on to video formats, audio podcasts, or formats with rich media of photos, artwork, or animations.   Perhaps some text-only blogs also operate this way, but my impression is that text-only blogs are largely invisible to the larger audience.

One thing I noticed in my brief period blogging is the change in search engines.   When I started, my content was showing up regularly in search results in major search engines.  To be sure, my content would show up ranked low, but I could still find it after clicking a few “more” pages.   I also noticed others were finding my content from their searches.   That is not happening any more.   I suspect I may be shadow banned, but I think it is more a change in search engines.   Early on, the search engines had specific filters for blogs, and I don’t see that filter any more.   I think the earliest search engines were focused entirely on blogs because that was the largest source of publicly available text context because most publishers protected their content to be subscriber only.

Clearly, my observations about COVID19 are not showing up in anyone’s searches.  I’m not saying I have something to offer, but there are key words that should match searches for a very hot topic.   Perhaps this topic is so hot that my content is just pushed much further back in the search results.   I have tried to find it, going deep enough that the suggested content no longer has any relevance to my original search and still no reference to my content.

My thoughts are not as easily to discover as they once were.   I suspect I am permanently invisible to any search attempt.   My blogging is becoming as privately protected as I once hid my type-written papers back in the 1980s.   I find this liberating.   I can explore my thoughts more deeply with the comfort that no one will see it.

My goal for writing this blog is to connect my thoughts resulting from lessons I have learned.   The result is not publishable as a work of fiction, non-fiction, or even a memoir.  Yet, here it exists published in a blog.

There is no real point to it.   I get most of my pleasure from writing around 1500 words.  I get about the same amount of pleasure whether I end up deleting the post or publishing it.   The enjoyment came in the writing, and more specifically in the thinking that comes in response to what I just see myself write.

There is a small increment of pleasure for publishing something instead of deleting it.   The published content becomes something I can add as a hyperlink.   The act of adding the hyperlink reminds me of what I wrote before and that forces me to respond to my own writing.

A large segment of blogging and video blogging is the content where the author reacts to someone else’s content.   I do the same thing with my own content.

One of my pleasures of writing is that it seems the person actually typing the letters is distinct from the person who is reading these words as they are typed.   I’m talking to myself but it is often antagonistic as if I am having an argument with myself.   If there seems to be any consistency it is because the self with the pen (or the typing) always wins in the end.   That is also the self that decides to press the publish button.

My objective in this blog is not really to comment on current events.   It is not even to build some academic argument, or to build a fantasy world to set the groundwork for some future fiction.   It may end up doing either of these things, but it is really accidental.

The real objective is just to have a conversation with myself.   There is an inherent internal conflict within my own mind pulling me in opposing directions such as to be more emotional or to be more rational, or to let data suggest something remarkable or to force the data to fit with what I know to be mundane.

In my adult life (that I measure as starting when I was 12), I have actively trained my mind to be obedient to the scientific or the rational.   If something is a textbook as something that can specifically show up as a test question, I learn the answer and convince myself it is true.

As I started to work with data, I brought with it my training in science.   In particular, I recall the training to make measurements in laboratory settings and then to evaluate my skills in measurements by how well the measurements matched the theory.   If there was a deviation, I was taught to explain the deviations as some type of operator error or device error.   If the deviation from theory was too far off, I accepted a failing grade.

My earliest paying jobs involving data were in using simulations.   I adore simulation building and I discuss it here frequently where I dismissively refer to it as “dark data“.  Simulated data are computed from scientifically-accepted mathematical modeling.   When simulations go wrong it is because of an error in implementation either as a mistake in coding the equation, or using an incorrect numeric algorithm such as a bad random-number generator.   I also delighted in work in signal processing for both communications and control systems where the same criteria applied; implementation or operator errors are always the first suspect of any deviations from predicted results.

I started working first with raw data later in my career.   I approached it from the perspective of my background.   The raw data for some measurement had to pass some reasonable test.   A simple example is measuring parts of some whole but the sum of the parts differs from the measurement of the whole.   There must be some mistake somewhere.   My first inclination was to dismiss the error, either replacing the sum of the parts with the measurement of the whole, or to mark the entire measurement as somehow unworthy of consideration, and outlier to ignore.

I quickly learned this was a mistake and after that I resolved to never throw away any information.   I may choose to select one measurement over another, but I never hid the fact that conflicting measurements existed.    That is what started the obsession with hyperlinked data.   When I showed some conclusion that I was prepared to defend as correct, that conclusion had a hyperlink that I can follow in real time to bring up the conflicting information.    This is data that changed every day, so I never knew exactly what was thrown away until I looked at it and that is when I learned I could be wrong.   Sometimes, dismissed data due to inconsistency with the science is telling me something very important: that I am missing something.

Science whether for simulation, measurement validation, or signal processing may be correct as far as it goes, but our science is not complete, and certainly my grasp of the totality of science is incomplete.    Some of the things I learned from the outlier data I initially rejected were things that I could find with research.   There are specific behaviors of specific instances of phenomena are sometimes very different from the usual but is already documented.   In many other cases, I found things I learned to be true even though I couldn’t find any documentation of it elsewhere.

I learned to respect the outliers.   This blog is a consequence of that respect being applied to my own thoughts.   I have thoughts consistent and compatible with the modern world, and I have thoughts that are less so.  This blog pays respect to my thought outliers.   They may be telling me something that I shouldn’t miss.

These thoughts are outliers.   I am pleased that my blog is hidden so that most of my posts never show up in anyone’s searches.   But I am also pleased that the blog is public.   In case someone finds something I wrote to be interesting there exists a variety of posts to inform that reader where that thought came from.   I respect outliers.

Initially, the term blogging was a contraction of two words web logging.   I would like to return to calling it just logging.   Blogging was a novelty at first because web itself was still a novelty.   Now it is mainstream so there is no reason to give it a neologism.

I like calling this a thought log in analogy of log data recorded in equipment.   Initially these logs were diagnostic in nature, often used only to report exception conditions such as errors or failures.    Eventually, it began logging successes and this became important for real time monitoring.   As data storage and retrieval technologies improved, we began to record this real-time successful-operation logging for historical analysis.   In my opinion, this has become a boon to better understand how things are actually working and finding out that reality does differ from theory.   Sometimes this data leads to better theories.   Sometimes this data leads to accepting the mystery and allowing unexplained measurements to influence decisions.

We are hearing claims that certain technologies such as machine learning are becoming more human like.   These advancements are providing benefits to humanity (as well as risks).   Similar consequences will come from having humans behave more machine-like, in particular to have each human log their actual unfiltered thoughts and feed those thoughts into a some big data store.

The risk of one’s private thoughts being exposed is muted if all of one’s private thoughts are exposed, and if everyone else shared their own private thoughts more or less equally.  The same thing happens with machine data.   Looking at one machine’s log data may lead to deciding that there is some flaw in that machine, but we sometimes discover our misunderstanding of how things operate when we look at the logs of all the similar machines in similar circumstances.    The flaw is in the system, not the instance.


One thought on “Thought logging

  1. Pingback: Discourse Analysis of a Diary or Blog | Hypothesis Discovery

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