Co-founder of St. Louis Tea Party Coalition and Nationwide Chicago Tea Party
Persuasive design expert
Latest book: Turning On Trump: An Evolution (2016)
Author of The Conservative Manifest (1993), Zen Conservatism (2009), Weaving the Roots (2011), and Fight to Evolve (2016)
I believe every person deserves the dignity of meaningful work as the only path to human flourishing.
You probably would like to know how to spot a very stable genius. It’s a skill that can come in handy. (Free Bonus: I’ll point you to the funniest thing I ever read in my life. Just because I like you. But first . . .)
Well, today, Donald J. Trump gave us a lesson in genius detection.
With the MSM chanting “mentally unfit” and “stupid,” our very stable genius president took to his favorite persuasion tool, Twitter. Here is his genius 3-part tweet:
Now that Russian collusion, after one year of intense study, has proven to be a total hoax on the American public, the Democrats and their lapdogs, the Fake News Mainstream Media, are taking out the old Ronald Reagan playbook and screaming mental stability and intelligence…..
….Actually, throughout my life, my two greatest assets have been mental stability and being, like, really smart. Crooked Hillary Clinton also played these cards very hard and, as everyone knows, went down in flames. I went from VERY successful businessman, to top T.V. Star…..
To sum up, you can spot a genius by the way they trigger their enemies’ sarcasm and sanctimony to spread the idea they want spread. Donald Trump got CNN and Clay Aiken (and millions of other unhinged leftists) to repeat “very stable genius Trump” tens of millions of time in just a few hours. CNN might even launch a TV show called “Stable Genius” that discusses nothing but Trump. That’s genius.
A comedian wrote a spoof of Fire and Fury. It’s so funny I hurt myself laughing and almost dialed 9-1-1 because I was having trouble breathing. I was laughing that hard. You will, too. Be careful where you are when you read this in a moment.
But the funniest thing: most leftists and Trump-haters thought this was an actual passage from the book! They retweeted like madmen and shared it with their friends. Only to find out . . . it was a spoof! In fact, the author had to change his Twitter handle to “the gorilla channel thing is a joke.” Cognitive dissonance at its best!
Read this genius spoof of the Wolff’s mostly-fake book that caused so much concern:
Latest: Sheriff sets up emergency shelter for displaced residents:
Due to the size and cope of this investigation an emergency shelter has been set up @ East Ridge Rec Center, located at 9568 University Blvd. in Highlands Ranch. If anyone has been displaced from their homes due to this event please feel free to head there.
Earlier: Domestic disturbance led to shots fired, via Douglas County Sheriff:
UPDATE 0513 this morning deputies responded to he Copper Canyon Apartments for a Domestic Disturbance. During the Investigation, shots were fired and multiple deputies were injured. No status on the deputies and no status on civilian injuries. Please avoid this area.
Do you think Democrats will retake the House, the Senate, or both in the 2018 election?
Now that you’ve answered, let’s consider the limits of data science in 2018.
The best data scientists in the world agreed with nearly absolute certainty. These scientists determined, beyond a reasonable doubt, that Hillary Clinton would be the 45th President of the United States. That was in 2016.
Those scientists were wrong.
Many of those same scientists applied their advanced degrees and supercomputers to the next problem: how would a Trump presidency affect the US economy. Joined by several Nobel-winning economists, the data scientists came to one conclusion with absolute certainty: Trump will sink the US economy, and smart people should sell 100% of their stock immediately following Trump’s win.
Those scientists and economists were all wrong.
It’s easy to blame partisanship and bias for these huge errors by the best data scientists and economists in the world. And it’s likely that bias played a role in their embarrassing failures to predict the future. But bias wasn’t the only problem. Nor was it the primary error.
The primary error in data science is its confidence in data.
Now, I’m a huge proponent of data science. I work with big companies who under-invest in analyzing their own data and in studying publicly available data. Data analysis and lightweight artificial intelligence and machine learning can greatly improve business results. I’ve helped smart companies achieve amazing growth through a combination of data science and human behavioral science. It’s what I do for a living.
But I also know the limits of data science. And those limits are far more humbling than many data scientists admit. The biggest limit comes from unknowns. Scientists call these “confounding variables.” While eventually knowable, in our present limits of knowledge, the effect of an unknown, confounding variable cannot be measured or accounted for. I’ll give you an example.
Say I want to test a hypothesis. My hypothesis is that trees begin to change colors as a result of temperature changes in the fall. I also want to factor out some variables I know could affect the trees: humidity, cloud cover, rainfall, and heat stress. Then I run my test over 3 years.
In the end, I discover a perfect correlation between temperature change and leaf color change.
Only later do I learn that I missed one other variable: sunlight hours. In the fall in subtropical zones, the hours of daylight decrease and the hours of darkness grow. In October, trees in my part of North America receive several hours less sunlight than they did in June.
Upon further investigation, I learn that scientists had long ago determined that hours of sunlight, not temperature, cause trees to hibernate in the winter. Their transition from active growth to dormancy causes their leaves to change color. An oak tree in coastal California where fall temperatures are often warmer than in mid-summer turns colors just as it does in St. Louis. Here’s the science, according to the United States National Arboretum:
In late summer or early autumn, the days begin to get shorter, and nights are longer. Like most plants, deciduous trees and shrubs are rather sensitive to length of the dark period each day. When nights reach a threshold value and are long enough, the cells near the juncture of the leaf and the stem divide rapidly, but they do not expand. This abscission layer is a corky layer of cells that slowly begins to block transport of materials such as carbohydrates from the leaf to the branch. It also blocks the flow of minerals from the roots into the leaves. Because the starting time of the whole process is dependent on night length, fall colors appear at about the same time each year in a given location, whether temperatures are cooler or warmer than normal.
It took science a long time to figure that out. While a pretty simple problem that’s easily tested in both the laboratory and in the wild, trees are subject to many variables: wind, moisture, cloud cover, heat stress, terrain, parasites, deer, beavers, etc. But people have been studying trees for many, many years. And trees are less complex than the human brain.
Now, let’s go back to the problem of modern data science. Data scientists are mostly concerned with how people will behave at some point in the future. These scientists don’t care why leaves change colors in the fall. They care about how people (consumers) will respond to the leaves changing.
People are more complicated than trees, at least when it comes to their behavior. The factors that influence human behavior have also been studied for centuries. But our understanding of the factors that influence our behaviors is limited. And even the variables we know about are so varied and numerous that predicting how one variable affects all the others is as much art as science. (For example, shoppers who receive a free sample of luxury chocolate candy at a kiosk in a mall are more likely to make a purchase from a luxury retailer in the mall than the same shoppers in a mall that doesn’t give away free luxury candy.)
Which brings us back to the 2018 election.
It’s very possible that Democrats will take over the House and the Senate. It’s also possible that Republicans could increase their majorities in both houses. It’s also possible that something in between will happen. I don’t know. Neither do you. And neither do the greatest data scientists alive.
That’s the point. When you hear predictions, don’t be fooled by the math and science used to bolster those predictions. The scientists who did the work, usually in good faith, don’t know the variable they don’t know. Nor do they know the likelihood of a new variable creeping into the equation. Nor can they factor the influence of those infinite unknown variables. Take all predictions about elections with a grain of salt, and be especially circumspect if the prediction comes with a lot of easy-to-understand charts and graphs. And, if you have a strong belief in science, you are actually more susceptible to believing in charts and graphs.
The appearance of being scientific can increase persuasiveness. Even trivial cues can create such an appearance of a scientific basis. In our studies, including simple elements, such as graphs (Studies 1–2) or a chemical formula (Study 3), increased belief in a medication’s efficacy. This appears to be due to the association of such elements with science, rather than increased comprehensibility, use of visuals, or recall.
And people who believe in science are most gullible:
Belief in science moderates the persuasive effect of graphs, such that people who have a greater belief in science are more affected by the presence of graphs (Study 2). Overall, the studies contribute to past research by demonstrating that even trivial elements can increase public persuasion despite their not truly indicating scientific expertise or objective support.
When you see scientific-looking studies predicting with 98% confidence how the 2018 election will turn out, remember this study and this blog. In fact, check out this chart which shows you are more likely than others to share this blog post on Twitter or Facebook. You’re also slightly more likely than others to remember this blog post when the actual results of the election are announced in November.
The US Department of State released 2,800 emails involving Hillary aid Huma Abedin that were found on Anthony Weiner’s hard drive last year, Judicial Watch reports. You can read all the emails here: FOIA Abedin Emails
This is a major victory. After years of hard work in federal court, Judicial Watch has forced the State Department to finally allow Americans to see these public documents. It will be in keeping with our past experience that Abedin’s emails on Weiner’s laptop will include classified and other sensitive materials. That these government docs were on Anthony Weiner’s laptop dramatically illustrates the need for the Justice Department to finally do a serious investigation of Hillary Clinton’s and Huma Abedin’s obvious violations of law.
Scott Adams first identified Donald Trump’s greatest strength. What do you think that might be?
It’s not his money or his business experience. Those are strengths, sure, but they’re not THE strength.
Scott Adams believes Trump’s campaign was a movie script. Here’s what Adams wrote way, way back when Trump’s candidacy was still just a PR stunt because he had zero chance of winning even a single primary:
A movie script is almost always arranged in what the professionals call a three-act form. In this model, the protagonist always has some sort of life-changing event (such as suddenly becoming the frontrunner for president) in act one.
In act two, we see the protagonist living out the results of that change. In the Trump movie, we see a smiling candidate amassing popularity and defying the experts. Just like act two in any good movie. This is the calm before the storm.
At the end of the second act, nearly all movies follow the model where some unsolvable problem rears its head. The audience must feel that the protagonist can’t escape this problem. We know the movie is fiction, but we still feel the emotions of the actors. We love the feeling of the third act because it reminds us of our own unsolvable problems. The main difference is that the movie hero finds a way to solve the unsolvable. That solution is what makes it a movie. The audience needs to feel the third act tension followed by an unexpected solution in order to get the chemical rush of movie enjoyment.
If you follow Scott Adams, you already know that Trump intentionally sets traps for himself. He creates “unsolvable problems” that everyone knows will be his downfall. From his immigration statements to his war with Megyn Kelly to jailing women who have illegal abortions to pussygate, Trump turns every small win into a future disaster with the things he says.
So I buy some of Scott Adams’s story. Trump does provide viewers a great action-adventure storyline. Every win sows the seeds for the next unsolvable problem. People feel compelled to tune in to the next episode to see how The Donald escapes this mess. Like the old Batman series. Or Silicon Valley. Or . . . here’s where I think Scott Adams is wrong.
Movies usually resolve themselves pretty neatly. Except for Star Wars, which ended with Darth Vader escaping to set up his next attack on Luke, Han, and the Princess. But most movies don’t explicitly sow the seeds of future problems in the resolution of the current story. That’s more like television.
Great TV heroes need a nearly as-great villain. Or, in the case of Batman, many near-equal villains. Trump has many near-equal villains: Robert Mueller, James Comey, CNN, New York Times, Washington Post, etc. There’s also the really scary villains like Iran and Kim Jung Un. When those villains start to drift away, Trump has an uncanny knack for pulling them back in. Ratings depend on a series of insurmountable problems. We want to see how our hero escapes each one of them. And we demand that every plot line has its resolution.
In other words, Donald Trump has turned world history into a television series. And we’re already at the end of season three.
Season One: The series begins as Trump descends the huge escalator in Trump Tower and declares his candidacy by saying Mexico isn’t sending us their best people, but their rapists and drug dealers. Pundits and experts write his candidacy off as a publicity stunt. But our hero seems to be serious. Trump defies conventional wisdom by eschewing a ground game and focusing on huge rallies with tens of thousands of people. And despite all of his supposed missteps and inflammatory rhetoric, Season One ends with Trump miles ahead of his closest competitor for the GOP nomination, but the entire conservative intelligentsia turns against Trump, setting an insurmountable problem for Season Two.
Season Two: Season Two of Trump begins with the run-up to the first Republican caucuses and primaries. At this point, Republicans are either fully behind Trump or fully against him. The leading conservative magazine devotes an entire issue to hating Trump. And Trump loses the first event to Ted Cruz in Iowa. But Trump rallies, sweeping a number of primaries leading up the decisive Super Tuesday blowout. He even holds a bizarre press conference that’s really an infomercial for many of the Trump businesses. It’s the strangest thing anyone has ever seen in American politics. At least in the TV era.
The first half of Season Two ends as Trump wins the nomination and continues his unconventional ways. He fires two campaign managers. He gives a blistering “America First” acceptance speech. He does everything wrong but Trump stills comes out on top.
In the climax to Season Two, Trump upsets the favored (by 98%) candidate to become the president-elect. His enemies, left and right, band together to form a Resistance movement. And the Russian Collusion narrative sets up our hero for the ultimate downfall in Season Three. Ask any anti-Trumper or NeverTrumper on December 29, 2016, and they’ll tell you Trump won’t survive the first 100 days in the Oval Office. Everyone expects the Deep State to take Trump down. Stay tuned for Season Three.
Season Three: Trump’s third season opens with a controversial inauguration. Trump disputes press estimates of the crowd size at his inauguration. Then Trump fires the FBI director, his attorney general recuses himself from the Russian investigation, and an underling appoints a sinister special counsel named Robert Mueller. Mueller is the smoking guy from X Files brought to life. Mueller is like The Penguin or Mr. Freeze. (Comey is The Riddler.) The anti-Trump press declares his presidency a failure after two attempts to overturn Obamacare fail in Congress.
But Trump looks amazingly deft at foreign policy. He wins favor with China’s leader. Israel loves him. His support base grows more resilient. His opponents lose popular support when they turn to mass violence over the summer.
Season Three ends with our hero’s biggest win since the election. Trump drives home the largest tax reform since Reagan and biggest single tax cut in US history. But the Russian narrative continues unabated, setting up Season Four. Pundits and experts say Republicans will lose the House and Senate to Democrats in the upcoming off-year elections.
Season Four: Here are just some of the open plot lines going into season four:
Will Robert Mueller find evidence of Russian collusion?
Will the Justice Department’s inspector-general indict Robert Mueller, James Comey, Andy McCabe, Peter Strzock, or Bruce Ohr?
Will Trump’s wall get Congressional okay?
Will North Korea nuke San Francisco triggering World War III?
Will Iran go to war with Saudi Arabia triggering World War III?
Will Trump get his big, beautiful infrastructure bill through Congress?
Will Democrats take control of the House and Senate and immediately begin impeachment proceedings?
Or will Trump find a way to get out of these jams before Season Four ends?
We don’t know how season four of Trump: The President will unfold. But we have to watch it. It’s the greatest show on earth.