Almost as good as free will

Stanford professor Robert Sapolsky has concluded that free will doesn't exist. I mostly agree.

Neurobiologists like Sapolsky, psychologists, and even computer scientists have realized that the brain has multiple components that independently make decisions in different domains, a point which seems to have eluded philosophers for generations.  Sapolsky's point about our inability to "choose what to choose" takes that dissociation far beyond most philosophers' thinking.

Notably missing from discussions about Sapolsky's ideas are the physicist's perspective.  The brain is a material object subject to the laws of quantum mechanics, which most physicists have realized is fully deterministic, following the Schrodinger and Dirac equations with incomprehensible complexity. In order to preserve free will in quantum theory, some creative physicists have concluded that "electrons have free will".

Yet even without absolute free will, our independence from the environment and other people that allows us to think and act on our own as individuals provides for an autonomous will, which should be good enough for practical and legal purposes.

Unrelated: Happy 2024!

Too much planning to survive can reduce survival

It's a long, strange path that our ancestors have taken to get to our level of cognitive processing.  It's understandable, but not forgivable, that many philosophers don't bother tracking it all the way through from microbial beginning to the latest cultural edifices.

Everyone knows that evolution works by "survival of the fittest".  Which is almost a tautology since "fitness" is defined in terms of number of descendants who survive to reproduce themselves.

Less well understood is how species with complex individual members come about.  It occurs because there is always variation in complexity, and some variants acquire increased fitness by virtue of some aspects of their complexity.  Because "there is always room at the top", there's a general trend towards ecosystems hosting populations with greater complexity.

Then at some point in the evolution of greater and greater complexity, the ability of individuals to make plans can appear.  This can take a long time, but nature can take as much time as it needs; it's not on any particular schedule.

Among the things that planning can do, is make plans to survive.  An organism that can make plans intended to enhance its survival in certain situations (and then execute those plans) will have a greater likelihood of surviving those situations than an organism that just reacts to the immediate aspects of them.

However, the process of planning consumes cognitive resources and attention.  Computational and game-theoretic analyses of the planning process have shown that comprehensive planning involves a search through a space of all possible sequences of actions that grows exponentially in the size of the problem space, or equivalently in the depth of search traversed before a particular plan of action is abandoned in favor of an alternative.  The game of chess is the classic example of planning in a situation whose solution is beyond the capability of any human or computer yet built.

Cognitive resources used by planning might be more effective in enhancing survival if they were applied to reacting quickly and precisely to situations, rather than focusing on planning.  The stereotype of the "absent-minded professor" is an example of this kind of misallocation of resources.

Thus, the most effective kind of planning is resource-bounded, making  heuristic estimates rather than carrying the planning through to a conclusion.  This creates an inverted-U shaped function of the effectiveness of planning in enhancing survival vs the amount of resources applied to planning.  

Maximizing survival involves finding the sweet spot between planning and action.  Finding and maintaining planning activities at this sweet spot requires identifying and controlling the depth and comprehensiveness of planning.  Ability to exercise this kind of control provides its own survival advantages, with its own inverted-U properties.  

Higher order control of planning is one of the cognitive processes involved in consciousness.  Recognizing this provides part of the answer to the questions of the usefulness of consciousness, and to the evolutionary origin of consciousness.

What is it like to be yourself?

Thomas Nagel's famous essay "What is it like to be a bat?" has been impairing people's ability to think about consciousness for some 48 years.  That's a remarkable accomplishment.  It would take a far longer article than we have space for here to survey all the writing it has stimulated, but there is a bit of news to remark about.

Nagel's philosophical goal is to convince you that there are important aspects of consciousness that are beyond the reach of science.  His major method in doing this is to first, convince you that he understands consciousness better than you do.  This is hard, because as a conscious person, you have uncontrovertible knowledge of your own consciousness. But for many readers, and especially trained thinkers like philosophers, he amazingly succeeds.  There are two primary ways that he makes this happen.

First, he commits a basic rhetorical fallacy, closely related to the "appeal to authority" that is in every list of rhetorical blunders.  I've come to call his error "argument by failure of imagination" and it goes like this:

1. I'm a smart person. (This is the appeal to authority. Nagel is a well regarded professional philosopher, and part of the job of a philosopher is to perform smartness.)
2. I've studied this topic thoroughly.  The topic contains a problem X.
3. In my studies, I've covered every imaginable solution to X.
4. I've failed to find a solution. I can't imagine how X might be true.
5. Therefore X is false.

Nagel explicitly concludes "our minds are not constituted to be able to understand the consciousness of bats".

This conclusion is in conflict with the mathematical discovery, in about 1936, independently by Alan Turing, Alonzo Church, and Emil Post, that certain classes of systems that manipulate sentences can perform any possible sequence of manipulation of sentences.  In short, that anyone who can read, write, and follow directions can think any thinkable thought.

This invalidates the jump from step 4 to step 5 in the imaginative fallacy. Just because you haven't found an answer doesn't mean it doesn't exist.  Some problems take a long time to solve, and maybe you just haven't spent enough time on it.  Or maybe you're just a stick-in-the-mud, and need to be more creative.  In my experience, most philosophers aren't nearly as creative as they think they are.

It's a remarkable fact about the diffusion of knowledge that thinkers about consciousness have not incorporated this result into their arguments for scores of years - nearly 90 years by now.

To help you think about the consciousness of other kinds of animals than your own species, Ed Yong has published a new book “An Immense World: How Animal Senses Reveal the Hidden Realms Around Us”.  It's been reviewed in the New Yorker and many other places.

If you are able to reject Nagel's unimaginability argument, Yong's book embodies a method to gradually increase your imaginative capability until you actually achieve the ability to successfully imagine what it's like to be a bat.  Maybe we don't have enough information about the details of the sensory equipment of bats, or the ways that bats' brains process sensory information, but that only means that your understanding of bat consciousness isn't totally accurate, not that there is some fundamental barrier to any understanding whatsoever.

Now, a perceptive philosopher might argue that it's one thing to know all the facts about bat perception and bat consciousness, but it's another thing to know "what it is like to be" a bat.  This snag was embodied by philosopher Frank Jackson in a thought exercise about a vision scientist named Mary, who knows everything there is to know about vision, but is color blind.  Then through a miraculous medical treatment, Mary's disability is cured, and she can now see in full color.  The question is "has Mary learned anything new?"  The conceptual failure by Jackson, and every other discussion that I've read about Mary's situation, is that "knowledge about vision" is not simply a bag of unconnected facts.  If Mary is anything like a real vision scientist, she has constructed a mental model of visual perception systems, and beyond that, she's able to mentally operate that model to provide it with simulated visual stimuli, and watch it produce simulated visual experiences.  When Mary's treatment is complete, and she compares her real experience with the simulated experience that she's been studying all those years, she learns just one thing: "Was I right?" And of course she was.

If you study bats in enough detail, and build a sufficiently accurate mental model of the bat's mind and experiences, you too can operate that model and experience what it is like to be a bat.

If you somehow believe that having a bat's experience inside your own mind is not the same in some important way as being the bat's mind without a host mind, then you have other problems.

1. experiencing what it is like to be a bat (impossible)
2. experiencing what it is like to be a cat (impossible)
3. experiencing what it is like to be an ape (impossible)
4. experiencing what it is like to be someone of the opposite sex (men and women are inescapably, mysteriously different)
5. experiencing what it is like to be someone of the same sex (impossible. Sorry, bro.)
6. experiencing what it is like to be your twin sibling (impossible)
7. experiencing what it is like to be yourself (impossible)

All those self-help admonitions to "just be yourself" would turn out to be impossible tasks.  Thousands of years of writing about the virtue of self-knowledge would turn out to be aspirations that can never be achieved.

Isn't it time to throw Nagel's argument out for good, and learn to understand how empathy really works?

Is obesity research too hard?

The M3 theory of weight regulation, or, no silver bullet for weight loss.

Sometimes ideas that have been floating around in your mind suddenly fall together.  This seems to be one of those cases.  The trigger might have been a recent report by Herman Pontzer and 83 others, who studied 6421 people and found that metabolism peaks at ages 2-5, plateaus during adulthood, and then slowly declines after about age 60.

What makes a model too complex?

M3 stands for "multifactor, multimodal, metabolic".  Weight management is under the control of a multitude of different factors; it's a complex system that can be purturbed in a large number of ways, and the elements of the system are linked by an equally large number of feedback control factors that make predicting the magnitude of the ultimate effect of any single purturbation is very complex.

It's obvious that complex systems like this cannot be communicated in the simple concepts and language that popular journalists are obligated to use if they intend to engage successfully with a large audience. It's less obvious, but still likely, that public health officials, who wish to issue guidance that can be followed by most people, but who attempt to base their guidance on the best scientific knowledge, cannot effectively synthesize that knowledge in consumable form, even if they had an adequate scientific model.

Today's insight is that an adequate scientific model may be impossible to obtain, because the technology currently used to manage scientific knowledge isn't up to the job.  Scientific knowledge advances one publication at a time.  But it's cumulative only in the way that termite mound or beehive is the result of myriads of individual contributions from individual termites or bees.  The mound does not respond to external stimuli on the same time scale as the stimuli themselves.  When new scientific knowledge about a complex model appears, it does not update the model until a new textbook is written that includes the new or revised item.  Figures and equations in textbooks are not executable models, they're representations that allow readers to build executable models in their heads or in computers.  

And it takes executing the model to determine whether any proposed intervention will result in a desired outcome.  If the model is too complex to be operated in your own head or on your own computer, it's not a useful model for managing the system, even though it may be true.  The best that can be done is to measure how accurately the usable models work at each timescale, and to track how they improve as more compute power is applied to them, and whether they're improving over the years.  Tracking improvements in forecasting accuracy is done in meteorology, and practically nowhere else.

The simple model

Every time a discussion of a new "breakthrough" in weight management is announced, someone inevitably pipes up with "it's easy: calories in minus calories out.  It just takes will power, you lazy wimps."  Not only is this insulting, but it's wrong.  Calories are a measure of energy, they don't convert to mass except in high energy particle accelerators.  The weight management fundamentalists should be talking about grams of carbon, not calories.  And they need to talk about rate of carbon in minus rate of carbon out.

The same bathtub analogy that is used for climate warming works for weight management.  Suppose we have a bathtub with a drain that can't be shut off completely, but can be opened up to allow more flow beyond that basic level.  That basic flow represents the body's base metabolism used for simply keeping you alive, and the rest of the flow is what's consumed by other daily activities.  The bathtub also has a faucet whose flow represents the contents of the food that is eaten every day.  We want to regulate the amount of water in the tub, so that it doesn't overflow or get so heavy that it falls through the floor.  

This model is already difficult to manage, since we can easily measure only the weight of the tub and the rate of flow into it.

Calories are a very imperfect measure, since they are an imperfect proxy for carbon. Calories are measured by burning a substance and measuring the amount of heat produced in excess of the amount of heat needed to ignite it.  Since food is made of carbohydrates and proteins that contain both carbon and hydrogen, some of that heat comes from burning the hydrogen, and the amount from carbon that we're interested in must be estimated from a chemical analysis of the food.  And because some of the measured calories come from sources that are not well digested, such as fiber, calorie measurements overestimate the amount of carbon that becomes bodily tissues to contribute to obesity even more.

The M3 model components

If it's too complex for all of science to deal with, it's too complex to describe in detail here.  We can just give a top level outline of its key components.  We can't even list all the linkages between them.  All the components and their linkages form a graph structure, and computer modeling systems that convert graph structure descriptions into executed model runs don't exist, as far as I know.  So anyway, here's a short list:

• Inputs
• Carbs
• glycemic index
  
• protein
• fiber
  
• Input controls
• Appetite - external sensory
• Mouth feel
  
• crispy
• crunchy
• chewy
• temperature
  
• Flavor
  
• salty
• sweet
• savory (umami, MSG)
• smell - hundreds of qualities
• associative learning
• appearance
• smell
  
• Hunger - internal sensory
  
• blood sugar
• stomach fullness
• internal processing
• digestion efficiency
• microbiome spectrum
  
• glucose production
• glucose consumption
• insulin-controlled conversion rate
  
•  tisue targets
• white fat
• brown fat
• muscle
  
• Outputs
• breathing - CO2
• base rate
• exercising rate
• exercise level
  
• excretion
  

A better list would attach to each item and link a citation to the scientific literature that provides evidence for its properties.

 New frontiers in weight control

The silver bullet would be to identify a single item in the list above that is both measurable and controllable, so that you could manage your weight by controlling that item. But this is impossible, because there are always at least two paths between input and output at any stage of control and processing.  Calories are a single measurement, but because the nutrients that provide calories (and their associated carbon) have different rates of utilization (glycemic index) and bioavailability (fiber does not get converted to energy or weight), it's an incredibly unreliable measurement.

Any combination of measurements and controls is even harder to manage and analyze.  What we ideally need is an artificial intelligence system that tracks a bunch of nutritional properties and identifies an optimal combination of them to maximize flavor while maintaining a target weight.  And it needs to be frictionless and transparent at the same time, quietly looking over your shoulder whenever you attempt to eat anything, computing how it will affect your weight management plan, and gently suggesting alternatives.  Alas, this is well beyond the state of the art in AI technology.  Training the machine learning part of such a system would take not 6000 participants, but 600,000 of them or more, each tracking every meal and a host of metabolic indicators.

The latest trend in public health interventions to manage an obese population is dietary sugar, and in particular sugary drinks.  Sugar is a powerful contributor to weight gain since it's both calorie dense and is metabolized very rapidly. It makes a big contribution to the rate of carbon input to a person's mass flow balance.  So regulating sugar input by public health officials might have some impact.

Focusing on the appetite component of the M3 model offers additional possible opportunities for management.  One of appetite's most dangerous properties is that it's insatiable.  It's not for nothing that Lay's Potato Chips once had a slogan "Bet you can't eat just one."  Eating something that's crispy, crunchy and salty doesn't satiate, it increases the desire to eat more.  

How this works is very unclear, and may be beyond the capability of current neurophilosophical thinking to clarify.  Super-appetizing foods have biased, if not overridden, the free will of a large fraction of the human population.  Philosophers arguing over whether free will exists amazingly fail to take facts like this into account. A will that is partially free and can be biased or overridden is incompatible with the content and methods of these arguments. Simply saying that these foods have been engineered to be addictive, as many writers assert, merely assigns blame without explaining the phenomenon.

But if you can't control the desire for salty snacks, you can at least improve the food value of them.  Instead of starchy chips and puffs that are metabolized vary rapidly, you can choose snacks with more protein that is metabolized more slowly, such as pork chicharrones, and ones that contain more fiber that is not metabolized at all.  It's something to look for in the grocery store.

Making progress in philosophy

The online science and culture magazine Aeon recently published an article by philosophy professor Chris Daly on Philosophy's lack of progress, which received a certain amount of broad attention.  I  have some ideas of my own on the topic, so I started composing a reply.  Fortunately Aeon's commenting system contains a design defect that prevented me from posting an immediate reply that I would have regretted later.  Nevertheless, I wanted to get the ideas out somehow or other, so here they are.

Coming back to Daly's article a month later, it seems kind of wishy-washy, and I daresay not up to the best standards of philosophical thought.  Possibly this is due to the heavy editing that Aeon articles receive, in order to keep the flighty attention of their pop-sci audience.  His diagnosis of the problems with philosophy seem mostly accurate, but leave out some important ideas that have been put forth by other philosophers.  It took me only a minute of search on the topic "progress in philosophy" to find articles by David Chalmers and Eric Dietrich that seem much more deeply thought out, and learn that some philosophers have been worrying about the problem for decades, if not centuries.  Daly's article gives no hint that other philosophers have thought about the progress issue at all.

Likewise, his ideas for making progress, while pointing in good directions, seem superficial and tentative, and don't suggest that he has investigated them enough for him to have much confidence that they would actually work.

My diagnosis of the problems with philosophy is similar to that of Daly, Chalmers and Dietrich, but somewhat more harsh, namely that most philosophers don't care if they're wrong. Therefore they are not bothered by the fact that their answers to the big questions don't get better over time.  This is sad.  I ascribe this to two primary factors.  First, that the academic field of philosophy can be considered one of the "humanities", like art, literature, music, religion, and even history.  These studies are fundamentally a sophisticated form of entertainment, and notions of "better" or "worse" are subject to the whims of their audiences and patrons.  

Secondly, they are subject to the "publish or perish" mandate of academia, which drives them into the grip of Sinclair's Law, that it is difficult to get someone to understand something when his paycheck depends on his not understanding it.  It's much easier to get something published when nobody is keeping score, and refutations of your arguments have little or no effect on your stature in the discipline, as long as your arguments are sufficiently scholarly and abstruse to impress journal editors and promotion committees.

Chalmers has a more generous interpretation of the phenomenon, namely that philosophy has no criteria for compelling agreement. Science has experiments, mathematics has proofs; philosophy has only common sense and intuitions.  Common sense evolves, but very slowly.  Me sitting in my Eames armchair with a laptop PC watching videos of robots on Mars has a quite different sense of what's what than a serf in a hovel or a Lord in manor house.

It seems to me that the only way for philosophy to make progress is schism, that is, for the philosophers who are interested in progressing their field to simply get together with other progress-oriented philosophers and go their own way, and leave behind the humanities scholars and the "philosophologists" who feel obligated to give obeisance to the great men of the past in every paper, explaining that their ideas were already known to Kant or Heidegger or Aristotle, who simply did not explain them in modern terms.

Schism shouldn't be unthinkable, it happened in 1988 in my own field of psychology, when the scientifically oriented American Psychological Society split off from the clinically oriented American Psychological Association.

So, here are my two cents suggestions for a new program in Natural Philosophy or Progressive Philosophy.   Founding a new research field is a huge task, even to describe, so this is just an outline.  But I hope it gives a hint of what needs to be done to whoever might be reading it.

Social criteria for a progressive philosophy

1. Identify the most important problem for the community to work on
1. Note that there are annual conferences in both Physics and Astronomy that create priority lists for their entire fields
2. Mathematicians have coordinated enormous efforts like classification of the finite simple groups
2. Accept a method to compel agreement (Chalmers)
1. Consider Adversarial Collaboration as a way to identify criteria for progress.  "What can you do or say that would make me change my mind?"
3. Keep score on progress.  Projects like the Stanford Encyclopedia of Philosophy can act as a vehicle for this.

Conceptual Criteria for a progressive philosophy

1. accept the validity of instrumental knowledge
2. recognize the axioms of evolution: populations, variable reproduction, selection
3. recognize the provability results from the mid-1930s mathematical logic
1. axiom systems can be consistent, inconsistent, or incomplete
2. conclusions can be true, false, or undecidable
1. undecidable algorithms can be finitely decidable
3. universal computability (Turing, Church, Post, et al.) shows that introspective reasoning can not discover the existence of a computational substrate. See item 1
4. nevertheless, universal computability proves that sufficiently powerful and self-consistent systems can encompass any possible rational system with finite axioms and finite data
4. the big problems of philosophy may be too big for any single philosopher to keep track of in their head or communicate effectively (Colin McGinn was right?!)
1. when suitably formalized, shown to be undecidable
2. too big for error-free reasoning, even by skilled, trained philosophers, especially when expressed in ambiguous natural language
3. mathematicians have developed proof assistants like Lean, Coq, and Agda to help with super-big problems. Philosophers could do something similar.  This is very different from handwaving at "AI"
5. Academic philosophers should be concerned with finitely teachable subsets of the possible solutions to philosophical problems
1. The results of item 3 show that "philosophology" is an endless task.  Specifically, refutations of every wrong answer form an infinite set, while the right answers are a finiten set, or at least an enumerable one

Varieties of incompetence

The rollout of the Covid-19 vaccines in the US has been troubled by problems of all kinds, but one of the most frustrating is the apparent contradiction within the medical conventional wisdom about mask wearing after you have received your course of vaccines.  JOE AND TERESA GRAEDON  write a column called The People’s Pharmacy that appears in many small-community newspapers.  Their column that appeared in my paper two days ago explains their thinking.

Q: I read an article that stated even after getting the vaccine you will need to wear a face mask so as not to spread COVID-19. I don’t understand this. Can you explain?

A: Both of the current vaccines have demonstrated that they can prevent serious illness from the coronavirus. In the clinical trials most people who received a vaccine did not get sick.

The vaccine might not keep the virus from entering your body, but it should keep you from developing symptoms. You can’t catch the virus from the vaccine.

Some people who are immunized might become infected without symptoms. We know that asymptomatic spread is quite common, and the trials were not designed to rule it out. That’s why even after getting a vaccine to protect yourself, you should still wear a mask to prevent the spread of the virus to others.

This represents one of my favorite stupidities: the statement that contradicts itself.  The vaccine makes you immune to the disease, but you should wear a mask because you might not be immune.

Of course, the interaction between the SARS-COV-2 virus and peoples' immune systems is very complex and variable -- far too complex to explain in a brief newspaper item.  I don't really know who to blame for this.  The Graedons are simply repeating what every other public medical advisor says, and it's not totally bad advice.  Wearing masks is good.  But the reasons that they give are specious.

Without going into the social psychology of mask wearing in a community where some people have been vaccinated, which is as complex as the biology of the disease itself, this kind of response made me realize that there are additional kinds of incompetence that I needed to add to my catalog of incompetencies.

1. Garden-variety incompetence.  Simply not really knowing what you are doing, and doing it badly.
2. Dunning-Kruger incompetence.  Being so incompetent that you can't tell the difference between competent and incompetent performance. Thinking that you know what you're doing, and that you're doing a good job, when in reality you are totally screwing up.
3. Malicious incompetence.  Intentionally doing a bad job, because you secretly intend to damage what you're working on, but don't want to be blamed for the damage.  Many politicians do this, especially Republicans since Ronald Reagan, who state that the government can't do anything right, and then do everything in their power to make sure that even well-intentioned and skilled officials fail at their jobs. Malicious incompetence often serves as plausible deniability for plain malice.
4. Well-intentioned incompetence.  This is the case that describes the Graedons' misunderstanding.  I can't tell if they really understand that they are hiding the bad reasons for their good advice.  In the case of real experts like Anthony Fauci, Director of the National Institute of Allergy and Infectious Diseases, he knows very well that his explanation of why vaccinated people should wear masks is wrong, but he's misleading people for good reasons.
5. Stress-induced incompetence. Much psychological research in the aftermath of WWII and the Korean War discovered that performance relates to stress in an inverted-U shaped function.  Performance improves with stress up to a certain point, but as the stress level continues to increase, performance decreases.  Many managers and coaches don't recognize this.
6. Financially motivated incompetence.  If you are in a situation where you're paid for the quantity of work rather than the quality of the work, it's profitable to do a poor job, so that you can be paid to keep doing it over until you get it right. Government cost-plus contracting practices, which are useful for technology development and research projects, often lead to this kind of behavior.
7. Strategic incompetence. The chess gambit of sacrificing a piece for a longer term advantage is an example of this. I have to admit that I've done this in my career a couple of times, when I was given a task that I could do well, but found unpleasant, and concerned that my bosses would give me more of the same kind of work if I did a fine job, did it less than energetically.
8. Faux incompetence. Like strategic incompetence and the worst kind of malicious incompetence, faux incompetence is a façade of misbehavior intentionally and competently produced.  I'm writing this while sitting in a room with a modern machine-made oriental rug whose pattern contains perfectly-produced imperfections intended to mimic the defects of handmade rugs.  There are entire segments of the fashion and home decoration industries devoted to the creation of "distressed" effects in new objects to make them look as if they are old and poorly maintained.
9. Judgmental incompetence. Sometimes skilled people, doing the best they can, are called "incompetent".  This is an attribution error, and the people doing the labeling are themselves either incompetent at determining what competence looks like, or are actively malicious.  Judgmental incompetence is often present in adversarial situations like politics or law.  The famous fictional attorney Perry Mason frequently traded accusations with his District Attorney counterpart that their arguments were "incompetent, irrelevant, and immaterial".

Understanding the varieties of incompetence is important because different varieties need different remedies.  Plain incompetence and Dunning-Kruger incompetence can be helped by training and practice, though Dunning-Kruger needs very strong feedback on errors.  Malicious and judgmental incompetence require punishment. Fixing financially motivated incompetence requires a change in incentives. People suffering from stress-induced incompetence can avoid stress-inducing situations entirely, or they can work on "systematic desensitization", where they build confidence in low-stress situations, learning to recognize that the sources of stress are unrelated to the quality of their performance, and thus defusing those stresses.

The benign incompetences, well-intentioned, strategic and faux incompetence, don't really need to be fixed, though we could all do with less cognitive dissonance in our lives.

For mask wearing and social distancing by people who have been vaccinated, given the constraints of a short newspaper column or powerful demand to simplify mask-wearing guidance for an audience of hundreds of millions of people, I can't offer a magic solution.  If the authors could assume an educated, sympathetic audience, a footnote reference to a more nuanced explanation such as the one provided by Sigal Samuel at Vox would solve the problem. But for a large audience with limited time, the more complicated explanation that reflects the complexity of reality can introduce misunderstandings and end up being counterproductive.