Why it's impossible to be rational about anything: measuring decision-making factors' potential for rational analysis

One of the problems with making decisions rationally is that it's conceptually impossible. Behavioral economist Dan Ariely highlights this by examining the decision-making process of someone faced with two coffee shops across the street from each other, one featuring handcrafted roasts and the other a standard chain where the coffee is $1.75 cheaper:

What you should do (if you wanted to be rational about it) is consider all of the things that you could buy with that $1.75, now as well as in the future, and decide to buy the expensive coffee only if the difference between the two coffees is more valuable than all of those other possibilities. But of course this computation would take hours, it is incredibly complex, and who even knows all the possible options to consider? [The Psychology of Money and Habits]

If you spend some time thinking on the factors that influence the direction of any decision, what you find is that every factor somewhere on a scale from high potential for rational analysis to low potential for rational analysis. Consider, for example, that a puppy's markings have a very low potential for rational analysis when deciding between one of two puppies to take home.

The problem is that even factors like price that fall relatively high compared to puppy spots are still far from being accurate tools for rational decision making. In this case it's because we can't help but make decisions based on context, relying on a memory that's spotty at best to judge the relative value of any monetary amount at any given time (see: How relativity affects every decision we make: an experiment in making $20K worth more than $20K). This is just one rule of human decision-making among a host of others.

Even if one were to accurately measure the various potentials for rational analysis of every factor at hand (impossible), one would then have to accurately compare factors within the overwhelming matrix of results (also impossible).

Our entire complex of heuristics and cognitive shortcuts exists entirely because being rational is simply far too difficult (see: this list of all the ways you could be completely wrong about everything).

patterns, analysis, and metrics

I absolutely love finding patterns and causes; while distinct entities, they are what make analysis interesting, and what everyone who "hates research" tends to overlook. This set of tea canisters, for example. I spent a good amount of time thinking through the patterns that make up the spatial positions throughout the wall, qualitfying and quantifying them the best I could. It was almost better than the tea itself.

The patterns and canisters point to the most fascinating part about data analysis: nothing is random; there is only cause and effect. Everything is human, from the arrangement of physical objects to the arrangement of our perceptions, beliefs, and preferences. As an example, try finding the underlying causes of the nature of data collected on Daytum. Daily intake of food and drink is a good start.

The while pattern-finding is fascinating, the hardest part of data analysis is never the analysis itself. It's always determining the metrics. Far more often than not, the metrics we choose often assume the cause, as opposed to reaching to get a critical understanding of the group in question. Consider the idea of determining the reason people like a particular soda by measuring the amount of soda a group of people drink over time. Or by qualifying the reasons they reportedly like soda. The problem is that the measurement assumesthat the reason people drink a particular soda is because of its characteristics. Certainly this is a rational approach but since when have our desires ever been rational?

You could measure when they drink the soda. After what experiences? When did they first start? You'd be getting on the right track, but almost always we devise metrics by subconsciously asking ourselves, "if X is the reason people drink this soda, how do I measure X?" Begging the question at its finest.

It's a daunting task, but it's only when we gather all the information - not just the information we think is important - that the real interesting patterns start to emerge. How else would we know that road closures actually lead to fewer traffic jams? (much more important: why)

Sounds suspiciously like "observe everything." The general theme here: human behavior is of course far too counterintuitive for simple, top-of-mind metrics. 

So why all this 3rd-grade level ROI out there?

the progression of humanity, science, and euhermerism

The video I posted yesterday was created by a wise man who goes by the name QualiaSoup; he and his brother TheraminTrees have been getting some attention over the last few months on Buzzfeed, Neatorama et al thanks to their solid demonstrations of logic and rationality.

It reminded me that I'm quite a strong believer that as humanity progresses, we are only accumulating more and more information about ourselves and our world, and that this is only a natural and good thing. Something of a simple statement, but it has implications on the way we perceive the world and the nature of belief and reality itself. And I don't think it's something quite everyone holds to be true right away, as evidenced by opponents of scientific progress (stem cell research), civil rights (gay marriage) or anything of the sort.

I think there's this idea out there that humanity could somehow be "doing it wrong." This seems to be the basic argument behind "social decay" or "losing our morals" or anything of that nature: everything was much better _____ years ago. As a quick side note, this is one of the reasons I'm so fascinated by nostalgia. It's logical fallacy/fooling ourselves in pure form; a true testament to the integrity of the quote I've used on http://www.projectnostalgia.com: "Nostalgia is like a grammar lesson. You find the present tense and the past perfect."

But as the history and reality of the world has shown time and time again, there is only one direction we're going in: more information, and more rights for more people.

What got me thinking on it was a new term I ran into today while listening to the How Stuff Works podcast describing the conditions in Cameroon and other similar climates that allow for huge clouds of CO2 to erupt suddenly from lakes, killing up to thousands of nearby villagers on any given occurrence. For ages these seemingly unexplainable events were thought by villagers to be evil spirits exacting vengeance, or any number of other supernatural phenomena; it's only in the last couple of decades that researchers actually started investigating and understanding what's really going on.

The term is euhemerism, describing the rational/scientific understanding of previously mythical/supernatural phenomena. Euhemerus, circa late 4th century B.C., believed that much of Greek mythology could be interpreted as natural events subsequently given supernatural characteristics. And I think humanity will continue to explain the world around us in similar fashion, indefinitely.

Lots of more thoughts on this, and a similar dynamic with respect to social norms/how we "should" be doing things. Still need to get to that "implications on the nature of belief and reality" part. Soon.

In the meantime, another great video: