Causal Illusion and the Emperor's New Clothes

I stumbled across this article on the psychology of being wrong.

This one adds to my emerging thinking that one of the principle difficulties we face in conducting unbiased research is that we're swimming against a biological imperative. Humans are just not wired to operate in an unbiased way. We are, in fact, wired to fool ourselves and presumably at a deeply instinctive level.

With a lot of evidence that erroneous beliefs aren’t easily overturned, and when they’re tinged with emotion, forget about it. Explaining the science and helping people understand it are only the first steps. If you want someone to accept information that contradicts what they already know, you have to find a story they can buy into. That requires bridging the narrative they’ve already constructed to a new one that is both true and allows them to remain the kind of person they believe themselves to be.

The comment above is framed as if a scientist is trying to persuade a lay skeptic. But as scientists, these are conversations we need to also have with each other and particularly with ourselves. We have to find a way to cut through what seems to be a deeply rooted psychology that functions to convince ourselves that the decisions we make are right, even when we are dead wrong.

Actually, we had found that way.

But somewhere along the lines over the last couple of decades we stopped using statistical procedures for the reason they were designed, which is simply to keep our thinking and the conclusions we draw from our experiments as unbiased as possible.

The practice switched from conducting unbiased statistical tests of hypotheses to running the calculations as affirmations of the significance of our ideas. That's a major philosophic distinction. Statistics morphed into a cloak that we wrapped around our brilliant self-deceptions. The situation we grew into is not unlike the Emperor's new clothes. We fool only ourselves when our intention is to test how right we are.

Yes, we've made tremendous progress and fantastic discoveries over the last 20 years. But the landscape is riddled with irreproducible results.

Bitter irony, the reason I was poking around on the 538 site and stumbled into this was to analyze the wreckage of my NCAA tournament picks, which all seemed so brilliant prior to the event. I'm in an auction-based game, where half the pot goes to the most points. You earn points equivalent to your team's seed each time they win. I did a probability-driven play selecting a stable of 8-9-10 seeds. This worked brilliantly in round 1 (50 pts!), but I emerge from round 2 with only a single pony in the race. I figured I needed at least two 2nd round upsets for a shot at the money.

Go Syracuse! You are all I have left.

The Anatomy of Deceit

Like many great scientists before him, Dan Ariely was inspired to answer questions surrounding what he called “deceitful behavior” from a real life experience he had in the burn ward of a hospital. From his laboratory experiments on pain and reward at MIT and CMU, he concluded a few key points, which will serve as a framework for my reaction to the accompanying articles. These key points are as followed (paraphrased from Mr. Ariely’s own words):

1. Many people engage in deceitful behavior, but only do so a little bit at a time.
2. When people are reminded of their own morality, deceitful behavior goes down.
3. If someone is out-performing the rest of the group and part of the in-group, deceitful behavior increases.
4. When there is distance from a tangible end-point, deceitful behavior increases.
5. People have a hard time doing difficult tasks to prove they are engaging in deceitful behavior. 

Some of these points, when contrasted against the accompanying articles, brought up interesting questions for me on how and why dishonest science happens. For instance, according to the article written by Julia Belluz on supposed “miracle” drugs, there appears to be both the in- and out-groups who perform some level of deceitful behavior. That is, it is not only the doctors who use exuberant language to describe the results of certain cancer drugs, but also the journalists who are responsible for reporting on them.

                                                         

Can one then make the argument that journalists, like medical practitioners, occupy the same in-group? Or is it that the in-group and out-group have a symbiotic relationship where the in-group (doctors) can influence the out-group (journalists) and vice versa? In addition, Belluz cites immunotherapies, “the vanguard of cancer research,” as being the most frequently hyped cancer therapies. This addresses Ariely’s 4^th conclusion above: that is, a cure for cancer is far off in the distance, but scientific publications exist as an immediate means of professional currency. However, it exposes an interesting question for me: would cancer researchers not working in cancer’s “hottest field” feel the need to engage in describing their therapies with such hyperbolic rhetoric?

My gut tells me the answer to this question is no, especially considering the implications of curing cancer. I believe no matter where you end up, these overreaching descriptions of therapeutic results serve as a way to move the field forward, albeit not in a very honest way. This grandiose language exposes dishonest behavior by putting a proverbial red flag to heed attention to potential results. In Jared Horvath’s article, he suggests that these mistruths are simply a consequence of science, and that reproducibility, whether it can be achieved or not, must be fully disclosed. Furthermore, the inability to reproduce serves as a helpful caveat to moving the body of research forward. In many ways, Hovarth seeks to engage more researchers in Ariely’s 5^th conclusion: he hopes that researchers will undertake the difficult tasks of proving their deceitful behavior for the common good of science. This, I believe, is the future of scientific research -- engaging with our human errors.