Category Archives: Education

I Say Give Them Time

As my readers know I occasionally take exception to comments made by highly respected intellectuals. I hope that when I do so it is not to engage in a gratuitous attack, but to offer an important counterpoint. In that spirit I must take exception to recent comments made by the highly respected thinker and author Malcolm Gladwell (see here).

The comments I refer to were offered by Mr. Gladwell when he appeared on The Beat with Ari Melber last week. The full text can be heard on the Ari Melber podcast dated July 3rd, 2021.

Mr. Melber introduced the segment by pointing out that we live in a period in which Republicans are attempting to revise history and promote lies. He asked Mr. Gladwell for his thoughts about all of that and whether there were any solutions. It should be noted that this question was asked in the context of promoting Mr. Gladwell as an expert on human thinking and behavior.

Here is a slightly polished transcription of the response by Mr. Gladwell:

I think about the role of time. I wonder whether we’re in too much of a hurry to pass judgment on the people who continue to lie about what happened on Jan 6th, there are many forms that denial takes. One of it is that I honestly don’t believe that anything went wrong there. Another form is that I do believe but I’m not ready to admit it yet. A lot of what looks like a kind of malignant denial in the republican party right now is probably just people who aren’t ready to come clean and renounce a lot of what they were saying for the previous four years. I say give them time.

While this admonition for patience may sound superficially learned and wise, I find it naïve, wrong both theoretically and factually, and damagingly counterproductive. While I certainly don’t expect Mr. Gladwell to cite all his supporting evidence in a short interview segment like this, I don’t believe he has any. I suspect this is simply well-meaning but unrealistic platitude, analogous to “the arc of the moral universe is long, but it bends toward justice.” That’s OK, except that he is putting forth an unsupported platitude as the conclusion of a purported expert in human thinking.

But such an expert on human thinking should understand that neural networks simply do not function in a way that would make “give them time” a reasonable strategy. As long as Republicans continue to hear the same old lies repeated over and over, they are not going to eventually recognize and reject them. Repeated exposure does not reveal lies but rather transforms our brains to accept them more deeply.

Our neural networks are influenced mainly by the quantity and repetition of the training “facts” they are exposed to. They have little capacity to judge the quality of those facts. Any training fact, in this case any idea the neural network is exposed to, is judged as valid by our neural network machinery in proportion to how often it is reinforced. And by the way, I know most of us want to believe that we collectively are not so susceptible to this because we want to believe that we personally are not. But we are.

So, my objection to Gladwell is that he does not truly understand how our neural networks function because if he did he would understand that “I say give them time” is counterproductive advice at this time. Now, yes, it would be good advice if we were confident that Trump voters are being exposed regularly and primarily to truthful information. If that were the case I would agree, yes, give their neural networks more exposure time. However, I don’t believe that there is any reasonable basis to think that giving them more time will serve any purpose except to further reinforce the lies they are continually exposed to from Trump, the Republican Party, and Fox News. We are simply not ready to just be patient and let the truth seep in and percolate.

The more nuanced advice, in my opinion, to the question posed by Ari Melber is that we must discredit and stem the flow of misinformation from these sources and expose Republicans regularly to truly factual information. Once we do that, then, yes, I say just give them time for their neural networks to become comfortable with it. With enough exposure their neural networks will transform whether they want them to or not. But to accept the status quo right now and “give them time” as Mr. Gladwell suggests would be horribly premature and ill-advised.

False Positives and Us

Cognitive scientists often discuss various forms of cognitive bias. Confirmation bias is just one well-known type (see here). Recognizing cognitive biases in all their forms is really important. But that effectively only focuses on symptoms. not the underlying causes or mechanisms of cognitive biases. In order to better overcome them, we also need understand the mechanisms that give rise to them.

As I discuss at length in my book (see here), our brains are essentially pattern recognition machines. Almost everything we do is a form of pattern recognition. And evolution has tuned our pattern recognition neural networks to err strongly on the side of false positives.

Here’s an example I often use to illustrate the importance of false positives. Imagine when we were evolving as animals. There were real tigers in the forest that were a mortal threat to us. Therefore, our neural networks were trained to recognize even the most vague hint of a tiger in the trees as a real tiger. It did not much matter if we imagined a hundred tigers that were only shadows or leaves blowing in the wind. What was critical however, was that we not miss even one real tiger, no matter how cleverly it concealed itself. An extreme bias toward false positives was a gigantic evolutionary necessity.

The result of all of this natural selection is that today we both benefit from and are hampered by powerful neural networks that are tuned to err strongly on the side of false positives. This is particularly acute when it comes to anything that might threaten us or distress us or make us uncomfortable.

This soft-wiring of our neural networks on the side of false positives not only underpins many of our cognitive biases but has huge ramifications in our social and interpersonal interaction.

For example, false positives certainly bias our perception of any *ism that offends or distresses us. If I am sensitive about my hair, I almost certainly detect far more insensitive comments about my hair than are objectively real. This is true of any *ism that impacts us, whether it be sexism, racism, or any other form of bigotry or hostility. And let me be very clear. All these things do exist and do happen, but I’m making the claim that any given individual almost certainly detects many false positives that are not really incidents of it.

This expands on our usual assessment that I am “sensitive” about my hair. Such prosaic sensitivity can be seen as a another symptom of these underlying mechanics. Our understanding of the false positive bias of our neural networks helps us understand how and why this happens and make us better able to accept it in others and defend against it in ourselves.

This is important because our exaggerated perceptions based on false positives have huge repercussions for individuals and for society. They cause us to react negatively in situations where such a response is actually counterproductive. It also exaggerates our feelings of anger and hostility which not only produce unfortunate behaviors and emotions, but those false positives also act as new legitimate “facts” that “train” our pattern recognition brains to recognize even more extreme false positives. Our biased perceptions and our memories of those false perceptions serve to reinforce our biased neural network in a self-reinforcing feedback loop. Soon we see our *ism everywhere, we hear it in every comment, see it in every glance, and respond with depression and anger which make it still worse.

These same mechanisms play a critical role in our one-on-one interpersonal interactions as well. If our friend or spouse says something we find bothersome or offensive, we quickly become attuned to it and start to see it in every nuance of expression and hear it between the lines in every comment. This reinforces our neural network to become even more sensitized toward it, detecting even more false positives. We can soon get to the point where there is nothing you can say, or even not say, to the listener that is not further evidence to support their feelings. We can quickly become surrounded, even paralyzed by all the tigers in the shadows.

Certainly merely being aware of this mechanism of false positive pattern recognition does not eliminate our susceptibility to all cognitive biases, but I think that understanding how our pattern recognition network functions is essential to protecting ourselves against perceptions that are not realistic or healthy. I know that for me, understanding how I am vulnerable to false positives does not immunize me by any means, but it does help me on many occasions to recognize and to push back against my own pattern recognition biases. And this is true even for perceptions or memories that seem incredibly real and compelling. Having some appreciation, and some humility, with regard to how susceptible we are to false positives can have a tremendous impact for the better.

What Pinky and the Brain Can Teach Us

Some of you might remember Pinky and the Brain from the 1990’s or from the revival series released in 2020. But whether you were a fan or not, these genetically enhanced laboratory mice have a lot to teach us all about creative interaction and collaboration.

The Brain was brilliant and preoccupied with conceiving and executing hairbrained schemes “to take over the world.” His dim-witted companion Pinky didn’t care about taking over the world in the slightest but was irrepressibly delighted to join in anything fun.

While most of their schemes flopped hilariously, some succeeded quite well. Regardless of their level of success however, none would have even gotten off the ground were it not for their unlikely collaboration. The Brain on his own would have gotten completely fixated on a scheme without ever seeing obvious flaws or considering alternate options. Pinky, with his right-brain churning away madly could never focus on anything long enough to carry it forward on his own.

Pinky and the Brain are like individual left and right brain hemispheres, divided into separate bodies. And we get to watch and laugh while learning how they work so well together both creatively and logically.

Here’s an example I made up to illustrate of one of their planning sessions..

Pinky I have it! An infallible plan to take over the world!

Egads, really Brain? Oh do tell!!

Look at these schematics Pinky. This device will place jellybeans strategically along the sidewalks to lure people to this park [thrusts pointer toward map]. You know people cannot resist jellybeans. Once the mindless throngs have been lured into the park, I shall announce my candidacy for President and promise jellybeans for everyone.

Narf! Brilliant Brain. I mean no one can resist jellybeans can they? And you can put the red ones on the grass and the green ones on the red carpet so no one can miss them!

Excellent idea Pinky, let me just add that to my calculations…

Oh, but wait Brain… what about the white ones? I mean no one really likes the white ones do they Brain? What are they anyway, coconut? They don’t taste like coconut, narf!

Hmm, excellent point Pinky. I shall have to rethink this entire plan. Let us regroup tomorrow night.

What are we doing tomorrow night Brain?

The same thing we do every night Pinky, try to take over the world!

So, here’s what I’d like to point out about this highly compressed illustration. First, Brain comes up with an idea. Pinky enthusiastically supports the idea and suggests how it can be improved. Brain incorporates the improvement. But then Pinky spots a possible flaw and Brain realizes he must rethink at least a portion of his plan.

In real life, creative thinking must occur this way to be successful. As author Bob Samples pointed out in his book The Metaphoric Mind (see here), effective creative thinking alternates between logical progression and unrestricted lateral thinking. Or as Samples calls it, logic and play. One must move down a logical path sufficiently to develop it, but must also be willing and able to jump out and head in a different direction if that looks more fruitful.

If one remains locked in a single logical train of thinking, there is a huge chance that the thinker becomes blinded to how increasingly ridiculous that train of logic is becoming. Even if every little step is perfectly sound and logical, such paths can end up concluding that benevolent aliens are going to pick us up after we drink poison. Likewise, flighty thinking that cannot settle down to develop an idea sufficiently can never take it anywhere.

This leads many people to think that their role in creative interaction is to play the curmudgeon, the devils advocate, the nay-sayer, the flaw-finder, the pick-aparter. By doing that, they think, they are contributing positively to make ideas better. But unfortunately this does not work if that is all you do. All that such behavior does is to smother every new idea in the crib before it ever has the chance to grow.

Likewise, others believe that if they’re just unfailingly positive, support every idea no matter how objectively flawed, they are helping. They are not. All they are doing is enabling ultimately doomed trains of thought to steam-roll over a cliff.

The best approach is the one modelled by Pinky. He is unfailingly positive and does not poke holes just to show how smart he is or in some misguided view that doing so is the best way to help. He gets genuinely excited and enthusiastically contributes new ideas that make the plan even better as long as he can. But, if he does see a major flaw at some point, he points it out. Despite his investment in the plan, Brain responds appropriately. He bonks Pinky on the head if the objection is silly, makes adjustments if it is substantive, or heads back to the drawing board if it is a fatal flaw.

So when you collaborate with a friend or colleague on a new idea, try to emulate Pinky and the Brain. Help develop ideas as long as you can before poking holes. If holes appear after carrying the idea along a ways, play with divergent new approaches and carry those forward as long as you can. Keep the idea bouncing around like a volleyball. Don’t spike it prematurely into the dirt. If you are all alone for now, use the Pinky and the Brain inside of you. If you do, you’re much more likely to take over the world, maybe even tomorrow night.

A Healthy Model of Equality

Thomas Jefferson prominently enshrined the phrase “all men are created equal” in our Declaration of Independence. This phrase has ever since embodied perhaps the single most important and enduring foundation of the American experiment (see here).

Certainly all people of good-will respect and value this “immortal declaration.” And certainly no one limits their interpretation to the literal meaning of the phrase. For if children quickly and demonstrably became unequal, the idea of equality at creation would lose any practical or useful meaning whatsoever. So we generally accept that “created equal” also implies that we remain equal throughout our lives, independent of what we do or do not accomplish in life.

But this must be much more than a mere rhetorical or theoretical equality. It must extend far beyond a mere begrudging recognition that all people have the right to basic human rights and dignity. It must be a practical working belief that operates at the real functional interpersonal level which allows us to work together in this human project as equal partners.

Indeed, without a sincere and unqualified recognition of the equality of all individuals, our social fabric cannot endure. It is not possible to have a fair and just society if we feel, even deep down, that some are deserving and others are not; that some are superior merely by virtue of their social status or race or gender or even by their level of accomplishment in life. To allow for such fundamental bases of inequality is to travel down the road toward slavery and subjugation and exploitation and ultimately into the abyss of social disfunction.

Yet, moving beyond a mere allowance of certain inalienable rights to a true respect for each individuals capabilities and worth is not easy. In fact that is a huge understatement. For in our everyday life in every social interaction we see that people are simply not equal. It is laughably obvious that in fact we are not equal by wide margins. Some folks are brilliant, others stupid. Some sane, others insane. Some gifted, others inept. Some strong, others puny. Some have lived honorable lives, others lives of ignobility.

The truth is, we cannot help but observe glaringly wide disparities on any measure of worth you care to assess.

So how can we truly hold the ideal of equality alongside the reality of inequality harmoniously in our minds? How can we sincerely believe in equality without lying to ourselves about the reality? And how can we acknowledge the reality without lying to ourselves about our belief in the ideal?

This requires some rationalization. Rationalization is not a bad thing. We all have to find some coherent model for reconciling contradictory ideas. Therefore, we all must find some kind of understanding that allows a recognition of equality to thrive, fully and harmoniously in our individual brains and in our collective psyche, alongside the reality of inequality.

You may already have your own rationalization that works well for you. But here’s how I rationalize it. It’s not perfect, but no model can be. It has long worked pretty well for me.

  1. Excluding physical or chemical debilitation, a human’s total capacity to think is neurologically dependent upon their physical brain capacity.
  2. All human brains are the same size, or close enough as the differences do not matter. Therefore our total brain “power” is essentially the same and all of it is used in some manner.
  3. Brains exhibit a wide spectrum of capabilities. Think of it as an impracticably wide bar chart. Each bar is a narrow trait, like perhaps “math,” or “kindness,” or “neuromuscular control,” but much finer grained than those.
  4. Everyone’s bar chart is a unique. It is a signature of who they are. Everyone has some high bars and some low bars. But the total area under the bars adds up to the same total power.
  5. Some bars are particularly valued by society at any given time, some are measured on an SAT exam and some are not. Some make you a business tycoon, some a starving artist. But although some signatures may be seen as more important to society, or lead to greater success, all are equal and all are valuable to society.

So, in my rationalization all people are truly equal. True, some may be less appreciated or less helpful in a given situation, but all are nevertheless worthy of true respect in my mind for their unique strengths. There is no contradiction whatsoever with the observed differences between individuals. Aspiration and reality are fully reconciled.

This model has helped me to reconcile equality with differences. It has in fact helped me appreciate equality by virtue of our differences. It has helped me to feel proud of my own personal strengths while simultaneously humble about my weaknesses and while still being as worthy and as flawed as anyone overall. It has helped me recognize that being smart or skilled in one area does not make anyone particularly smart or skilled in another. That has helped me apply a healthy level of skepticism to opinions put forth by “smart” people in areas outside their proven expertise and to allow that otherwise uninformed people can offer valuable insights in others. It has helped me understand that traits like “smart” or “sane” are not simple binaries but complex and nuanced and somewhat arbitrary. We are all smart in some things and delusional others (see here). It has also helped me to value undervalued traits and to recognize that disrespecting people for one very low bar of their chart does not mean you disrespect them in totality and that respect overall does not require you to respect every trait.

And further, we should value the undervalued signatures in our society more than we do. It is our failure and our loss if we do not identify and utilize whatever unique strengths each individual has. There are no useless skillsets, only underutilized and underappreciated skillsets.

I think these rationalizations have led me in a healthy direction. Maybe this model will help you come to a more healthy and helpful view of equality as well.

The Greatest Failure of Science

Before I call out the biggest, most egregious failure of science, let me pay science some due credit. Science routinely accomplishes miracles that make Biblical miracles seem laughably mundane and trivial by comparison. Water into wine? Science has turned air into food. Virgin birth? A routine medical procedure. Angels on the head of a pin? Engineers can fit upwards of 250 million transistors in that space. Healing a leper? Bah, medicine has eradicated leprosy. Raising the dead? Clear, zap, next. Create life? Been there, done that. It’s not even newsworthy anymore.

And let’s compare the record of science to the much vaunted omniscience of God himself. Science has figured out the universe in sufficient detail to reduce it to practically one small Standard Equation. It turns out to actually be kind of trivial, some would say. Like God, we can not only listen in on every person on the planet, but no mystery of the universe is hidden to us. We have looked back in time to the first tick of the cosmic clock, down inside atoms to quarks themselves, and up to view objects at very edge of our “incomprehensively” large universe.

Science routinely makes the most “unimaginable” predictions about the universe that are shortly after proven to be true. Everything from Special Relativity to the Higgs Boson to Dark Matter to Gravity Waves and so many other phenomena. Nothing is too rare or too subtle or too complex to escape science for long.

Take the neutrino as just one representative example among so many others. These subatomic particles were hypothesized in 1931 by Wolfgang Pauli. They are so tiny that they cannot be said to have any size at all. They have virtually no mass and are essentially unaffected by anything. Even gravity has only an infinitesimal effect on neutrinos. They move at nearly the speed of light and pass right through the densest matter as if it were not there at all. It seems impossible that humans could ever actually observe anything so tiny and elusive.

Yet, in 1956 scientists at the University of California at Irvine detected neutrinos. Today we routinely observe neutrinos using gigantic detectors like the IceCube Neutrino Observatory at the South Pole. Similarly we now routinely observe what are essentially infinitesimally tiny vibrations in time-space itself using gravity wave detectors like the LIGO Observatory.

The point is, when talking about anything and everything from infinitesimally small neutrinos to massive gravitational waves spread so infinitesimally thin as to encompass galaxies, science can find it. If it exists, no matter how well hidden, not matter how rare, no matter how deeply buried in noise, no matter how negligible it may be… if it exists it will be found.

Which brings us to the greatest failure of science.

Given the astounding (astounding is far too weak a word) success of science in predicting and then detecting the effects of even the most unimaginably weak forces at work in the world around us, it is baffling that it has failed so miserably to detect any evidence of the almighty hand of God at work.

I mean, we know that God is the most powerful force in the universe, that God is constantly at work shaping and acting upon our world. We know that God responds to prayers and intervenes in ways both subtle and miraculous. So how is it that science has never been able to detect His influence? Not even in the smallest possible way?

Even if one adopts that view that God restricts himself rigorously to the role of “prime mover,” how is it that science has found nothing, not one neutrino-scale effect which points back to, let alone requires, divine influence?

It is mind-boggling when you think about it. I can certainly think of no possible explanation for this complete and utter failure of science to find any shred of evidence to support the existence of God when so many of us are certain that He is the most powerful force at work in the universe!

Can you?

Three Major Flaws in your Thinking

BrainwavesEEGToday I’d like to point out three severe and consequential flaws in your thinking. I know, I know, you’re wondering how I could possibly presume that you have major flaws in your thinking. Well, I can safely presume so because these flaws are so innate that it is a statistical certainty that you exhibit them much the time. I suffer from them myself, we all do.

Our first flaw arises from our assumption that human thinking must be internally consistent; that there must necessarily be some logical consistency to our thinking and our actions. This is reinforced by our own perception that whatever our neural networks tell us, no matter how internally inconsistent, nevertheless seems totally logical to us. But the reality is that our human neural networks can accommodate any level of inconsistency. We learn whatever “training facts,” good or bad, that are presented to us sufficiently often. Our brains have no inherent internal consistency checks beyond the approval and rejection patterns they are taught. For example, training in science can improve these check patterns,  whereas training in religion necessarily weakens them. But nothing inherently prevents bad facts and connections from getting introduced into our networks. (Note that the flexibility of our neural networks to accommodate literally anything <was> an evolutionary advantage for us.)

Our second flaw is that we have an amazing ability to rationalize whatever random facts we are sufficiently exposed to so as to make them seem totally logical and consistent to us. We can maintain unquestioning certainty in any proposition A, but at the same time be perfectly comfortable with proposition B, even if B is in total opposition with and incompatible with proposition A. We easily rationalize some explanation to create the illusion of internal consistency and dismiss any inconsistencies. If our network is repeatedly exposed to the belief that aliens are waiting to pick us up after we die, that idea gradually becomes more and more reasonable to us, until eventually we are ready to drink poison. At each point in the deepening of those network pathways, we easily rationalize away any logical or empirical inconsistency. We observe extreme examples of this in clinical cases but such rationalization affects all our thinking. (Note that our ability to rationalize incoherent ideas so as to seem perfectly coherent to us was an evolutionary necessity to deal with the problems produced by flaw #1.) 

The third flaw is that we get fooled by our perception of and need to attribute intent and volition to our thoughts and actions. We imagine that we decide things consciously when the truth is that most everything we think and do is largely the instantaneous unconscious output of our uniquely individual neural network pathways. We don’t so much arrive at a decision as we rationalize a post-facto explanation after we realize what we just thought or did. Our consciousness is like the General who follows the army wherever it goes, and tells himself he is in charge. We feel drawn to a Match date. Afterwards when we are asked what attracted us to that person, so we come up something like her eyes or his laugh. But the truth is that our attraction was so automatic and so complex and so deeply buried, that we really have no idea. Still, we feel compelled to come with some explanation to reassure us that we made a reasoned conscious decision. (Certainly our illusion of control is a fundamental element of what we perceive as our consciousness.)

So these are our three core flaws. First, our brains can learn any set of random facts and cannot help but accept those “facts” as undeniable and obvious truths. Second, we can and do rationalize whatever our neural network tells us, however crazy and nonsensical, so as to make us feel OK enough about ourselves to at least allow us to function in the world. And thirdly, when we ascribe post-facto rationalizations to explain our neural network conclusions, we mistakenly believe that the rationalizations came first. Believing otherwise conflicts unacceptably with our need to feel in control of our thoughts and actions.

I submit that understanding these flaws is incredibly important. Truly incorporating an understanding of these flaws into your analysis of new information shifts the paradigm dramatically. It opens up powerful new insights into understanding people better, promotes more constructive evaluation of their thoughts and actions, and reveals more effective options for working with or influencing them.

On the other hand, failure to consider these inherent flaws misdirects and undermines all of our interpersonal and social interactions. It causes tremendous frustration, misunderstanding, and counterproductive interactions.

I am going to give some more concrete examples of how ignoring these flaws causes problems and how integrating them into your thinking opens up new possibilities. But before I do that, I have to digress a bit and emphasize that we are the worst judge of our own thoughts and conclusions. By definition, whatever our neural network thinks is what seems inescapably logical and true to us. Therefore, our first thought must always be, am I the one whose neural network is flawed here? Sometimes we can recognize this in ourselves, sometimes we might accept it when others point it out, but most of the time it is exceedingly difficult for us to recognize let alone correct our own network programming. When our networks change, it is usually a process of which we are largely unaware, and happens through repeated exposure to different training facts.

But just because we cannot fully trust our own thinking doesn’t mean we should question everything we think. We simply cannot and should not question every idea we have learned. We have learned the Earth is spherical. We shouldn’t feel so insecure as to question that, or be intellectually bullied into entertaining new flat Earth theories to prove our open-mindedness or scientific integrity. Knowing when to maintain ones confidence in our knowledge and when to question it, is of course incredibly challenging.

And this does not mean we are all equally flawed or that we cannot improve. The measure is how well our individual networks comport with objective reality and sound reason. Some of our networks have more fact-based programming than others. Eliminating bad programming is not hopeless. It is possible, even irresistible when it happens. Our neural networks are quite malleable given new training facts good or bad. My neural network once told me that any young bald tattooed male was a neo-Nazi, that any slovenly guy wearing bagging jeans below his butt was a thug, and any metro guy sporting a bushy Khomeini beard was an insecure, over-compensating douchebag. Repeated exposure to facts to the contrary have reprogrammed my neural network on at least two of those.

OK, back on point now. Below are some examples of comments we might say or hear in conversation, along with some analysis and interpretation based on an awareness of our three flaws. I use the variable <topic> to allow you to fill in the blank with practically anything. It can be something unquestionably true, like <climate change is real>, or <god is a fantasy>, or <Trump is a moron>. Alternatively, if you believe obvious nonsense like <climate change is a hoax>, or <god is real>, or <Trump is the greatest President ever>, using those examples can still help just as much to improve your comfort level and relations with the other side.

I don’t understand how Jack can believe <topic>. He is so smart!

We often hear this sort of perplexed sentiment. How can so many smart people believe such stupid things? Well, remember flaw #1. Our brains can be both smart and stupid at the same time, and usually are. There are no smart or stupid brains, there are only factually-trained neural network patterns and speciously trained neural network patterns. Some folks have more quality programming, but that doesn’t prevent bad programming from sneaking in. There should be no surprise to find that otherwise smart people often believe some very stupid things.

Jill must be crazy if she believes <topic>.

Just like no one is completely smart, no one is completely crazy. Jill may have some crazy ideas that exist perfectly well along side a lot of mostly sane ideas. Everyone has some crazy programming and we only consider them insane when the level of crazy passes some socially acceptable threshold.

I believe Ben when he says <topic> is true because he won a Nobel Prize.

A common variant of the previous sentiments. Ben may have won a Nobel Prize, he may teach at Harvard, and may pen opinion pieces for the New York Times, so therefore we should give him the benefit of the doubt when we listen to his opinions. However, we should also be cognizant of the fact that he may still be totally bonkers on any particular idea. Conversely, just because someone is generally bonkers, we should be skeptical of anything they say but still be open to the possibility that they may be reasoning more clearly than most on any particular issue. This is why we consider “argument by authority” to be a form of specious argument.

It makes me so mad that Jerry claims that <topic> is real!

Don’t get too mad. Jerry kinda can’t help it. His neural network training has resulted in a network that clearly tells him that <topic> must obviously be absolutely true. Too much Fox News, religious exposure, or relentless brainwashing will do that to anyone, even you.

How can Bonnie actually claim that she supports <topic> when she denies <topic>???

First, recall flaw #1. Bonnie can believe any number of incompatible things without any problem at all. And further, flaw #2 allows her to rationalize a perfectly compelling reason to excuse any inconsistency.

Clyde believes in <topic> so he’ll never support <topic>.

Not true. Remember our flaws again. Clyde’s neural network can in fact accommodate one topic without changing the other one, and still rationalize them perfectly well. All it takes is exposure to the appropriate “training facts.” In fact, consistent with flaw #3, after his network programming changes, Clyde will maintain that he consciously arrived at that new conclusion through careful study and the application of rigorous logic.

Sonny is conducting a survey to understand why voters support <topic>.

Social scientists in particular should be more cognizant of this one. How often do we go to great efforts to ask people why they believe something or why they did something. But remember flaw #3. Mostly what they will report to you is simply their rationalization based on flaw #2. It may not, and usually doesn’t, have anything to do with their extremely complex neural network programming. That is why “subjective” studies designed to learn how to satisfy people usually fail to produce results that actually do influence them. Sonny should look for more objective measures for insight and predictive value.

Cher should support <topic> because it is factually supported and logically sound!

Appeals to evidence and logic often fail because peoples’ neural network has already been trained to accept other “evidence” and to rationalize away contrary logic. It should be no surprise that they reject your evidence and conclusions and it doesn’t accomplish anything to expect Cher to see it, let alone berate or belittle her when she does not.

And that brings us to the big reveal of this article…

There is a fourth flaw that is far worse than the other three we have discussed so far. And that is the flaw that most of us suffer from when we fail to integrate an deep awareness of flaws 1-3 into our thinking. We may not be able to completely control or eliminate flaws 1-3, but we can correct flaw number 4!

This discussion may have left you feeling helpless to understand, let alone influence, our truth-agnostic neural networks. But it also presents opportunities. These insights suggest two powerful approaches.

The first approach is more long-term. We must gradually retrain flawed neural networks. This can be accomplished through education, marketing, advertising, example-setting, and social awareness campaigns to name a few. None of these efforts need to be direct, nor do they require any buy-in by the target audience. The reality of network training is that it is largely unconscious, involuntary, and automatic. If our neural networks are exposed to sufficient nonsense, they will gradually find that nonsense more and more reasonable. But the encouraging realization is that reprogramming works just as well – or better – for sound propositions. And to be clear, this can happen quite rapidly. Look at how quickly huge numbers of neural networks have moved on a wide range of influence campaigns from the latest fashion or music craze to tobacco reduction to interracial relationships.

The second approach can be instantaneous. Rather than attempt to reprogram neural networks, you force them to jump through an alternate pathway to a different conclusion. This can happen with just a tiny and seemingly unrelated change in the inputs, and the result is analogous to suddenly shifting from the clear perception of a witch-silhouette, to that of a vase. Your network paths have not changed, yet one moment you conclude that you clearly see a witch, and the next it becomes equally obvious that it is actually a vase. For example, when Karl Rove changed the name of legislation, he didn’t try to modify people’s neural network programming, he merely changed an input to trigger a very different output result.

I hope these observations have given you a new lens through which you can observe, interpret, and influence human behavior in uniquely new and more productive ways. If you keep them in mind, you will find that they inform much of what you hear, think, and say.

Champion of Nonsense

RandFrom climate change deniers to religious believers, there is certainly no shortage of intellectuals championing nonsense in the public sphere. But today let’s focus on the Champion of Libertarianism, Senator Rand Paul of Kentucky.

Libertarianism is an extremist version of barely restrained Capitalism. While it may sound reasonable and appealing when presented by a faux-intellectual like Paul, it falls apart completely under the slightest scrutiny, just as it did when Rachel Maddow probed just below the surface of Paul’s position on privatized lunch counters (see here).

For a Libertarian zealot like Paul, Socialism is his most horrifying nightmare. It is therefore unsurprising that in response to increasing public support for Socialist policies, Rand Paul wasted no time in publishing a book denouncing it (The Case Against Socialism).

In making his “case against Socialism” Rand Paul focuses mainly on historical bogeymen by raising the long-dead specters of Stalin and Mao Zedong. In a television interview just the other day, he was asked what Millennials in particular who support Socialism don’t get. Paul replied that they don’t get that Socialism means that the government owns all means of production and that it has been a disaster in every country in which it has been tried. He went on to once again invoke the horrors of Stalin and Mao Zedong.

Here’s what Paul doesn’t get or does not wish to acknowledge. Supporters of Democratic Socialism are not advocating those extreme forms of Socialism. They are not advocating that the government seize all private enterprise. And further, there is no reason to think that such Socialist extremism is inevitable, likely, or even possible in America.

Paul’s entire premise against Socialism is based on an obviously specious argument. It claims that Democratic Socialism is evil because something else called Socialism was evil. It’s the reverse of the logical fallacy used by gun zealots who claim that since revolutionary era guns were protected, modern guns should be protected.

Consider this analogy to understand what Paul is doing here. It is like he is railing against tablets. Tablets, he says, are evil. They waste paper and the spiral binding can cause cuts. We did away with tablets long ago and these Millennials who support them simply do not understand how dangerous they are. But no, they are talking about electronic tablets, not spiral notebooks. And similarly they are talking about Democratic Socialism, as practiced in Norway and Finland, not what was once called Socialism in China or Russia.

If we reflected the same disingenuous form of argument back against Paul, we would say that what Paul doesn’t understand is that Anarchy has been tried and it has always been a disaster. Of course, Paul is not talking about total anarchy when he talks about modern Libertarianism. And likewise no one supporting Democratic Socialism today is talking about the form of socialism attempted by Stalin or Mao Zedong (see here).

Further, when Paul claims that Socialism has always been a disaster, he fails completely to recognize that modern Socialist countries are at on the top of every measure of health and happiness (see here). Nor does he happen to mention that virtually every country that has adopted the more Libertarian economic policies of Milton Friedman has suffered direct human and economic calamity on a massive scale. This was excruciatingly documented in Naomi Klein’s landmark book (The Shock Doctrine).

So no Rand Paul. Sorry, but it is not the supporters of Democratic Socialism that don’t understand history. You are the one who is either delusional in your blind rationalization of Libertarianism, disingenuous in your rabid fear-mongering of Democratic Socialism, or most likely both.

Don’t Believe your Eyes

eyesToday I wanted to talk about perceptions. Not our feelings, but what we actually see, feel, smell, hear, and taste. That is, the “objective” inputs that drive our feelings. Should we really “only believe our eyes?

I think not.

In my book (see here) I talk about how we should be skeptical of our own memories and perceptions. Our memories are not recordings. They are docudrama recreations drawing upon various stock footage to put together a satisfying re-imagining. We remember going to the beach as a child. But in “recalling” details of that experience, we draw upon fragments from various sources to fill it in. The “slant” of that recreation is strongly dependent upon our current attitudes and biases. Our re-imagined, and often very distorted memory then reinforces what we believe to be a “vivid” recollection next time we recall it. Over time our “clear” memory can drift farther and farther from reality like a memory version of the “phone game.”

I contend that our brains work similarly with regard to our senses. We don’t see what we think we see. Our perceptions are filtered through our complex neural networks. It is a matched, filtered, processed, censored, and often highly biased version that we actually see, hear, or feel.

We know that our subconscious both filters out much of the information it receives, and adds in additional information as needed to create a sensible perception. I always favor a neural network model of brain function. As it relates to perception, our neural network receives a set of sensory data. It matches that data against known patterns and picks the closest match. It then presents our consciousness with a picture – not of the original data – but of that best-fit match. It leaves out “extraneous” information and may add in missing information to complete that expected picture. That is, we do not actually see, hear, smell, or taste a thing directly. We see, hear, smell, or taste a satisfying recreation that our network presents to us.

This should not be controversial, because we experience it all the time. Based on sparse information, we “see” fine detail in a low resolution computer icon that objectively is not there. We fail to see the gorilla inserted into the background because it is out of place. We are certain we see a witch or a vase in a silhouette, depending on our bias or our expectations at that moment.

But though this should be evident, we still do not take this imprecision seriously enough in evaluating the objectivity of our own memories or perceptions. We still mostly put near-absolute faith in our memories, and are generally even more certain of our perceptions. We believe that what we perceive is absolutely objective. Clearly, it is not.

In essence, what we believe we objectively recall, see, hear, or touch is not the thing itself, but a massaged recreation of our neural network match. The version we perceive can often be wrong in very important ways. Our perceptions are only as reliable as our neural networks. And some neural networks can be more compromised than others. We can recall or even perceive radically crazy things if our neural network has been trained to do so. I campaign against belief-based thinking of all sort because it seriously compromises these critical neural networks in crazy ways.

Even more unrecognized are the ways that this phenomenon is largely ignored as it impacts scientific research. Scientists often give far too much credence to reports of perceptions, often in extremely subtle ways.

As a simple illustration, consider how we often mock wine connoisseurs who claim to taste differences in wines but cannot pick these out in blinded studies. However, consider the confounding impact of their (and our) neural networks in even this simple case. When experiencing a wine, all the associated data is fed into the drinker’s neural network. It makes a match and then presents that match to the consciousness. Therefore, if the network does not “see” one critical factor, say color, it matches to white, not red, and presents and entirely different taste pattern the the drinker, ignoring some “extraneous” flavors and adding some other “missing” ones.

These same kinds of neural network matching errors can, and I have to assume often do, confound even more rigorous scientific studies. And they are further confounded by the fact that these mismatches are typically temporary. With every new set of data, our neural networks adjust themselves, the weightings change, to yield different results. The effect of a drug or placebo, for example, may change over time. If scientists see this, they typically look exclusively for other physiological causes. But it may be a neural network correction.

That is why I always admonish my readers to stick with inputs that will strengthen your neural networks toward sound objectivity rather than allow them to be weighted toward the rationalization of, and perception of, beliefs and nonsense. But since none of us can ever have perfect networks, or even know how accurate ours performs in any given match, we all need a healthy amount of skepticism, even with regard to our own memories and perceptions.

I further urge scientists to at least consider the impact of neural network pre-processing on your studies, and to develop methodologies to explicitly detect and correct for such biases.

 

But More Importantly…

climate-changeThose of you who follow my blog know that I’m virulently anti-gun. In fact, I’ll take any opportunity to slip my disdain for guns and the deplorable people who own them into any discussion. Which is why you should definitely go back and read this, and this, and even this.

But not now! Because more importantly… climate change.

As much as I loathe, hate, and despise guns, I fear climate change far worse. No matter what your issue, you are extremely foolish if you do not prioritize climate change far ahead of it. Humanity will survive gun violence, wars, poverty, hate, bigotry, diseases, despots, jobs, slavery, even genocides. But we may likely not survive climate change. Every other issue can be fixed, waited out, and overcome in the long term. Climate change is a death warrant for civilization, for mankind, and possibly for all life on Earth. It’s a terminal disease, game over, if not treated with every means we can muster and more.

So how can you ever rationally argue that efforts to curb climate change must wait because your issue, however important, is more urgent and existential? And no, we cannot “do both.” We must still prioritize. If we spend effort on your issue or even my issue then we are not doing enough to avert catastrophic climate change.

Most of my readers have to know that I’m an outspoken atheist activist. However, I cannot prioritize my atheist movement over climate change. Not even remotely. In fact, if atheists are indeed the more rational and sensible humanists that we think we are and claim to be, we should be taking a leading role in battling climate change. Sadly my atheist community as a whole is not showing such wisdom and leadership.

If there is one litmus test in the next Presidential election, it should be climate change. Not abortion, or gender equality, or a Wall, or fealty to Capitalism, or anything else… because more importantly, climate change.

In a recent interview Presidential candidate Pete Buttigieg rattled off ten or so things he would prioritize as President. Not one was climate change. When asked about climate change, he made a dutiful perfunctory comment about it. This should disqualify him utterly. Even if he does make stronger comments about climate change later, I would have no confidence that he is sufficiently sincere.

In fact, at this time, the ONLY candidate we should be strongly considering is Washington State Governor Jay Inslee. He is the only candidate showing the intelligence, leadership, and long-term thinking that we literally cannot live without. Others might make progress on health care, or immigration, or jobs, or LGBTQ rights. But really, will any of that ultimately matter if we fail to mitigate the worst impacts of catastrophic climate change?

Here’s what you should do. Ask your candidates at all levels about what they will do about climate change and make it an unequivocal priority. Be willing to put aside your own issues in order to work together to make progress on climate change. Demand that the social and religious organizations that you affiliate with push for action on climate change.

And finally, in the signature line of your emails, add the line “But more importantly climate change.” This will remind both you and your recipients that while whatever we are discussing is important, it does not begin to compare with climate change.

 

Religion in Public Schools

The teaching of religion in public schools is a topic that stimulates a great deal of honest debate on all sides of the issue. Should religion be taught at all? And if so, what religions? Even well-meaning atheists might feel that religion should be taught, as long as all religions – and atheistic perspectives as well – are taught equally and fairly without bias.

That sounds laudable and enlightened in theory. However, many plans that sound great in theory inevitably turn out to be disastrous when put into practice. Teaching religion in public schools is one such example.

I have personal experience with this. While serving in the Peace Corps in South Africa, I worked for their Department of Education. The South African Constitution requires that all religions be treated equally. In order to comply with the spirit of their Constitution, the Department of Education has adopted a policy that all religions should be taught fairly and equally in the public schools.

Sounds great right? The trouble is that teachers, particularly rural teachers, do not know all religions and do not care to know all religions – let alone teach them fairly. At the point where lofty policies touch the students. all that this accomplishes is to give teachers cover to preach and proselytize their own religious views in the classroom and to misrepresent and disparage all other religions – and atheism is demonized most of all.

The problem of state sanctioned religious instruction is not merely a matter of the recruiting and training and monitoring of teachers. False even-handedness spills over into teaching materials as well. Science texts typically enumerate a long list of native creation myths as legitimate. In at least one science text, after describing the monkey myth, and the milk myth, and many others, it concluded with what was almost an obligatory footnote that said “and some scientists believe that the world was created by natural means and human beings evolved.”

This sort of false balance, not unlike giving equal deference to climate change deniers, is an almost inevitable consequence of a misguided and ill-fated attempt to be fair and inclusive with regard to the teaching of religion.

I came away from my experience in South Africa more convinced than ever that our American system of simply keeping religion out of our public schools is on balance the best, most practical system of fairness. There is no shortage of alternate venues where people can preach and teach religion as much as they wish. Therefore, there is no compelling need being met by including religion in public schools, that warrants the certain risk of abuse and unintended consequences.

Assiduously keeping religion out of our public schools is in fact the more fair, the more enlightened, and the more realistic policy position.