Month: September 2025

Everyone today is talking about Artificial Intelligence, yet few understand how it works. The average person on the street thinks it is somehow programmed in … giving it actual instructions of what to say and do in a given situation. 

That might make intuitive sense, but it is not how it works. Instead, the computer is given a large training set of inputs and outputs and algorithms to process them … kind of like the way you may have done your statistical testing back in college.  One of the first applications of AI was OCR: optical character recognition.  The idea was to take a printed sheet of paper and produce a text file of the characters. 

This is a relatively well-defined training experience: there are only a limited number of characters and context can give the computer hints as to whether it is the letter “I” or the character “1”.  These systems are now reliable.  Speech recognition was next, with huge business implications for legal and medical professions.  While speech recognition is pretty good and in so many systems, it also depends upon a “training set” to learn.  If the software was trained on British voices, it would have trouble understanding Americans.  Accents from the deep south are humorous examples.

Facial recognition was next and while China used it to keep track of their citizens, MIT researchers discovered that it did not work reliably on people of color.  Once again, the problem was the training set did not include enough people of color.

But AI has its challenges when a new situation does not “map” to some part of the training set or when those designing the training algorithms never anticipated the use case.  In these cases, AI produces general nonsense and probably can’t be trusted.  My wife Susan asked ChatGPT for a list of public swimming pools in our area and it offered a list of the nearby private hotel pools. 

Modern prognosticators seem obsessed with the prediction that AI will develop a sense of itself and result in some level of revenge against its creators.  Movies have long suggested this theme.

Those of you who care about how AI learns should watch the movie Ex Machina where the AI is a beautiful young lady robot named AVA.  She is being tested by a young programmer to see if she can pass for being human … aka the Turing Test … but she learns by being tested and in short order realizes she is being tested and then logically deduces that there might be something bad that happens if she fails the test.

I have watched this movie about a dozen times and each time I discover more about how the process of the Turing Test taught her more and more about her situation and eventually led to her asking two key questions: First, “What will happen if I fail your test?” He replies, “I don’t know.”   She then asks the second question, “Why should anything happen to me based upon a test?”

Do you remember that wonderful movie War Games and how the computer learned that the path it was on lead nowhere?  It was the youngster played by Matthew Broderick who thought by learning the trick behind playing Tic Tac Toe, the computer would learn the game of thermonuclear war would also have no winners … which then stopped the escalation with the computer’s famous line: “Strange game … the only winning move is not to play.”

Spoiler alert … the movie Ex Machina does not end well.  I personally believe everyone today needs to watch this movie and think about where we are all going with AI. 

Yes, of course, there will be some good outcomes with AI, but more often than not there will be some very disruptive ones too.

 

 

We all know technology is evolving.  Clocks went from sundials to pendulum-driven clocks, then spring wound, and on to smart watches or phones.  Music went from phonographs, to radio, to vinyl records, to cassettes, to CD, to iPods and now streaming apps with smart speakers.  Much of this occurred in my lifetime.  Today, I am intrigued by the evolution of something seemingly simple: Laundry Detergents. 

My first memory of laundry detergents was in the 70s when they were powder you would scoop from a container or pour from a box.  They were messy and sometimes left clumps of congealed power on your clothes. The 80s brought liquid formulas prized for their ability to dissolve quickly and remove grease stains.

However, that popularity came with a cost: large plastic packaging and heavy bottles made them less than ideal for storage, transportation, or the environment. I remember lugging the heavy jug to the basement of our dorm where the washers were located.  Maybe the benefit was some good exercise, but it did not contribute to a good laundry day experience.  Nor did they cart the hefty plastic jugs home from the grocery store. 

An ‘80s Amway advertisement for their detergent piqued my interest. It claimed that other liquid laundry detergents contained enormous amounts of water to make you feel you were getting more for your money, while theirs had little water. Therefore, you could use less, extending your value and lightening your load. I never knew if the claims were true, but they made sense.

In the 2010s, pods revolutionized detergent delivery, offering convenience, single-use, mess-free, lightweight, and easy storage.  The premeasured doses in dissolvable films eliminated the guesswork on how much to use.  However, they were not perfect – early safety concerns arose as children were attracted to the candy-like appearance of the colorful pods.  However, over time, packaging and public awareness have improved, and pods have become a staple in many homes. 

This year, I discovered the latest evolution in laundry: lightweight, eco-friendly detergent sheets. These thin, biodegradable sheets, which resemble paper napkins, contain concentrated detergent and completely dissolve in water during the wash cycle. Being lightweight with minimal cardboard packaging, no plastic-bottle waste, and a significantly smaller carbon footprint, they are environmentally friendly. They’re also ideal for small spaces, travel, or for anyone who doesn’t enjoy carrying heavy plastic jugs. Currently, you may have to search the shelves to find the small packages of sheets, but I believe over time, they will take over the detergent section and free up a lot of space currently devoted to bulky jugs of laundry detergent.

As sustainability, simplicity, convenience, and effectiveness take center stage in household products, we can expect to see even more innovations in detergents. But for now, laundry sheets represent the latest chapter in a long story of soapy ingenuity.

I have been using this term in recent conversations about AI and drawing blank stares.  Perhaps that is because the word has only recently become a frequent term as the graph shows.  This coincides with my professional career so that could be why I use it to categorize the kind of data needed to get the maximum benefits from AI, and the kind of problems you have if the data is not curated.

Going back to basics, the dictionary defines curation as the action or process of selecting, organizing, and looking after the items in a collection or exhibition.  Each of these steps is deliberate and REQUIRES qualified professional judgement. There are of course still matters of opinion, but the removal of unqualified or aberrant candidates is critical to the quality of the collection.

The current frenzy over the latest craze in AI ignores this step and assumes the code can generate only curated candidates for later analysis.  That may be true if the candidates come from a nested set of known equations and you simply are trying to bound or predict the solution space … but no!  Stop the insanity … more bad data does not help!

Medical records can be an extremely beneficial dataset because almost all the information in them has been curated.   You still have the vagaries of human complexity and the randomness of the healing process, but at least you seldom get data that should be thrown out because it is nonsense. 

Let me illustrate my point with a common area in which I use AI: preparing my lessons for Sunday School.  I am trying to go back to the Hebrew, search for the cultural and historical contexts, and also surface scholarly arguments about almost everything including authenticity, meaning, and modern interpretation.  What I most often run into is party lines within religious denominations … each trying to defend an article of faith in that tradition.

It is almost as if each denomination recognizes that if you pull just one block out of their stack of theological arguments and resulting dogmas the stack will fall for their congregants.  The idea of continual interpretive relevance falls to defending past statements and beliefs.  Stagnant, rigid, and virtually universal points of view are the only things you see.

Therefore, when you use any modern AI tool to ask theological or contextual questions you get the codified, curated (according to their perspective) talking points.  These may still be relevant to today … but maybe not.

Please stay with me.  Can you see the crucial curation step here?  There was a deliberate step to curate what people should know and believe about something.  Does that curation step reflect a modern mind and or the context of the person asking the question?

Probably not … so AI just spits out the traditional answers to the question and in all too many cases misleads the user.

This is why I have been warning my friends in the military to beware of their AI systems usefulness because it is likely trained on data curated by our perspectives of combat ethics and tactics. 

I love the movie Down Periscope where the admiral asks Kelly Grammer to think like a pirate, and he does and as a result wins the war game exercise where his old diesel sub outflanks the modern nuclear attack subs which are faster and more powerful.

Curation … is it in the data we are using?  And, if it is there, who and for what purpose was that data curated?  These questions will surface whether the AI can be trusted at all.

 

It is high time we all pulled back from our frenetic raping of the planet to consider the broader questions of whether we should do something in the first place.  My blogs have been emphasizing that we need to redefine lifestyle expectations for our home and work environments, possibly redesigning our communities to eliminate anything but mass transit.  We should be walking to work and other venues outside our home.

But, once we define our home sustainably, we should be asking whether and how we heat and cool them for comfort and safety.  Europe is locked into that debate now and listening to both sides will be helpful.  Should we even use air conditioning?

It is a simple fact that summer heat waves kill people.  A large power outage decades ago in France proved that killing over 1,000 senior citizens caught in their homes while their children partied in the Mediterranean.  A similar event occurred about two decades ago on the Gulf Coast of this country with the same dire outcomes.

Air conditioning helped develop the South, but nobody was asking the question whether we should be doing that.  I grew up in New York where heat waves occurred every summer, but lasted only 5-10 days.  I worked in the city, and the heat there was unbearable due to heat island effects … the sun baked all those buildings, streets, and sidewalks, and the heat they absorbed during the day, they reradiated all night, making it oppressive.

Even so, I grew up in New York City without air conditioning.  Yes, there were nights I slept under a thin sheet and sweated all night, but that was just how it was.  Nobody asked whether we should air condition, but we did when my parents could afford it.

There is no reason to avoid these questions, but we should be aware of the politics that dominate how they are solved these days.  Someone is always going to suggest that comfort is an inalienable right and therefore the government should provide it at little to no cost.  After all, this is no different than other public safety concerns.

When put to a vote, those who are already paying almost nothing into the system will of course vote to get one more freebie.  Why not?  Let the rich pay for it!

Therefore, as we ask and answer these existential questions, we should be asking the more underlying key questions about how society can best afford these essential services.

Personally, I believe we must go back to densely built communities with centralized heating and cooling systems. Thermal storage then makes perfect sense.  The idea of putting these in each dwelling unit makes no sense.  Then, we decide how much each person-dwelling there pays.  And, while we are doing all this, we build these communities using DC technology … not AC as we do now.  After all, solar panels generate DC, lights are best done with DC, and power reliability for the dwelling units becomes trivial.

Once we return to essential questions, such as how we heat and cool our homes, we should consider more innovative redefinitions of comfort and safety.

On an easier topic, eat more food produced locally vs. transporting it from the other side of the world.  Purchase food products made in your community vs. made abroad and brought here on ships and planes.  Walk or share a ride to the store vs. driving your own 3,000+-pound vehicle. These are small steps we can all take that, and when combined, make a difference on our planet. 

I was reading my church’s Sunday bulletin and noticed the announcement of a support group for parents with neurodivergent children or relatives.  I wasn’t sure what that meant, so of course I looked it up and found this on the Cleveland Clinic’s website: https://my.clevelandclinic.org/health/symptoms/23154-neurodivergent

“Neurodivergent is a non-medical term describing people whose brains develop or work differently for some reason. This means the person has different strengths and struggles from people whose brains develop or work more typically. While some people who are neurodivergent have medical conditions, it also happens to people where a medical condition or diagnosis hasn’t been identified.”

Some of the conditions that are most common among those who describe themselves as neurodivergent include:

• Autism spectrum disorder (once called Asperger’s syndrome).
• Attention-deficit hyperactivity disorder (ADHD).
• DiGeorge syndrome.
• Down syndrome.
• Dyscalculia (difficulty with math).
• Dysgraphia (difficulty with writing).
• Dyslexia (difficulty with reading).
• Dyspraxia (difficulty with coordination).
• Intellectual disabilities.
• Mental health conditions like bipolar disorder, obsessive-compulsive disorder and more.
• Prader-Willi syndrome.
• Sensory processing disorders.
• Social anxiety (a specific type of anxiety disorder).
• Tourette syndrome.
• Williams syndrome

Well, now I understand how to describe the idiots in today’s world claiming to solve the world’s problems.  They are simply neurodivergent.  We used to call these disabilities or personality disorders.  Please think carefully about that.  We are implying there is no personal accountability.

Now, don’t get me wrong … I am fully aware that we should avoid the term idiot since it sounds so judgmental but give me a break.  When somebody says that biological boys who “identify” as girls can participate in their sports, I draw a line.  Having raised four daughters, the idea that a biological boy is in a girl’s locker room makes my skin crawl.

Sure … medical conditions such as autism, down syndrome, and even cases of obsessive-compulsive behavior can have virtually no personal accountability.  They are not choices in life, nor are they the result of inadequate education or upbringing.  We must learn to welcome and support individuals with these attributes.  I am also painfully aware how we used to wrongly poke fun at them.  Fair enough … guilty as charged, but let’s move on.

It is also interesting to note that some of the most famous brilliant people suffered from these conditions including Temple Grandin, Sir Anthony Hopkins, Simone Biles, and Greta Thunberg.  The list also includes Marie Curie, Albert Einstein, Van Gogh, Nikola Tesla, and F. Scott Fitzgerald.  So, who am I to judge how history books will define some, or even me?

Given our modern proclivity to come up with labels for these conditions, and following the pattern of difficulties with math, reading, and writing to make these less critical of the obvious failings in our education system, I would like to add these neurodivergent classes:

• Dyslogia (difficult with critical thinking) – oooops … already taken!
• Dysensia (difficulty with common sense).
• Dyshistoria (difficulty with learning anything from history).

Please note that these three were possibly classified with the label “intellectual disabilities” in the prior list.  Yes, we must learn to love one another … but simply using labels to excuse society’s failure to educate, apprentice and mentor people to be productive members of society is just one more example of our modern temptation to simply define situations rather than correct them.  Then, when we do, we either resort to medications or promise a cure politically … how silly.

Oh, I could have used the “ism”, “ist” and “phobia” suffixes as lists of the same tendencies.   How about logiphobia, sensiphobia, and hostoriphobia?  We are now being told by labelists that everything we deem wrong in society is just another point of view … there are no rights and wrongs.  These are simply western society’s bias toward dualistic perspectives.  We need the eastern mystical worldview.

Want to understand the recent fuss over pronouns?  Can you now see these are simply labels to legitimize personal obsession with non-normative identities.  The worst case in my opinion are “furies” who have been known to insist classrooms have litter boxes.  No, I am not making this up!

My wife is right … nobody gets the complete package.  We are all simply puzzles with missing pieces.  The book Chop Wood Carry Water says: comparison is the thief of joy.  The goal of comparison is only to point out realistic areas for improvement. 

Unfortunately, as my prior blogs have proven, you just can’t fix dystupidia.  There … I didn’t use the word stupid.