Tuesday, 22 of May of 2012

Category » Scientific Method

How Much Does a Kilogram Weigh?

House of Arbitrariness & Conditionality

We often view measurements as unchangeable. A meter is a meter, a pound a pound. We often forget that at some time someone somewhere declared what those were and that they would be a standard. The point is this: arbitrariness underlies almost all objective standards by which we live.

For example, in the January 29, 2011 edition of The Economist, the article, “The Constant Gardeners”, explores the kilogram. The official standard is a platinum-iridium alloy cast in 1879. However, today, its weight seems to vary from its copies by up to 69 micrograms, about half a grain of sand, an important variance when weighing small things. So, the question is this: How heavy is a kilogram . . . really?

The relevancy to problem solving is similar to that which I wrote in my post, “Arbitrariness: The Cornerstone of Conditions”:

By searching for the underlying arbitrary aspect of any apparently objective situation, we can often find the perspective – when altered – that can cause us to see that situation in a different light.

For example, when someone asks us, “What’s the best way to get from A to B?” we often give the fastest route. The assumption being that the “best way” is “fastest” when “best” could have many different attributes. Over time, the best-fastest link becomes the arbitrary point – when altered – that sheds a different light on what route might be best such as the most scenic one or the most fuel-efficient.

As a more sophisticated example, consider our reliance upon “proven outcomes.” What does that mean especially when you cannot scientifically prove that good leadership begets good results? Thus, when we look at what it took to be proven, we often find that it’s subjective based upon who is determining what “good leadership” and “good results” are.

 


Names and Our Unconscious Biases

Our names unconsciously influence people. We humorously smile at actors who change their names making them more appealing. Yet, some people relate because they wish their parents had given them better names.

Even in a field striving for objectivity such as science, your name can influence the peer review process. In the August 20, 2011 issue of The Economist, the article “A Black and White Answer” reports racial name research by Donna Ginther of The University of Kansas indicating it does. The article also references the 2003 racial name study, Racial Bias in Hiring, by Marianne Bertrand of the University of Chicago and Sendhil Mullainathan at the time of Massachusetts Institute of Technology in which names influenced who received job interviews.

While the article focused on the racial connotation of names, an October 23, 2008 article of The New York Times mentions research about non-racial correlations focused on similar names, initials, sounds and letters. Of course, if we overlay the concept of branding from advertising on these two areas of research and the territory between them, we come back to “what’s in a name?”

From an intuitive perspective, what connotation does each of our names have? What feelings do people get when they hear it? How do we feel when we run across names far different from ours, ones we can’t pronounce? Subconsciously, do they trigger our defense mechanisms? All you need to do is look at popular baby names to know we do not distribute names randomly even if we account for ethnicity.

What we can learn from science in this research is that no matter how objective we think we are it is no match for the unconscious emotions truly driving our decisions.

 


Knowledge is Power, Not!

In Robert Heinlein’s science fiction book, Starship Troopers, the instructor, Mr. Dubois says, “One can lead a child to knowledge but one cannot make him think.” Automatically, a picture forms in my mind of a person who collects a garage full of tools and doesn’t fix anything or who collects a kitchen full of utensils and always orders out. There are many people who treat knowledge the same way; they collect it but never think about it or employ it.

Often I will begin certain seminars by declaring, “You won’t learn anything new, but if you’re like others, you’ll still find it helpful.” We are so preconditioned to view the stuffing of our minds as a benefit, that we have difficulty seeing how this could be true. So, I go on to say, “Most of what I will cover you already know; however, I will present it in a way that will encourage you to think about it differently and take action.”

I contend that rather than go out and collect more knowledge, if we just use even 20% of what we already know but don’t use, we would see substantial changes in our careers and lives. How many people collect business improvement books as though they were collecting stamps?

Intuitively, we know that we must consider the emotional aspect of knowledge. This appears in the form of motivation to think and employ that knowledge. Simply, learning something new shouldn’t be the benchmark of a worthwhile learning effort. Did it encourage us to look at things differently? Did it move us from inertia to action?

Now, that is real power.


Knowledge States

While helping a non-profit, a board member said, “We can only deal with a problem if we know there is one.” Here the state knowledge assumes alters our perspective. In this case, it causes us to ignore the idea of prevention, dealing with problems before they arise. In reality, problems don’t care whether we know or prove they exist. Thus, if knowledge’s form can alter our perspective and prevent us from seeing potential solutions, it is important to have a grasp on the different states of knowledge.

To that end, I’ve created the map to the right. It has five basic states: Unknown, Aware, Know, Prove and Quantify. Each is a subset of the previous one:

Knowledge Map
Knowledge Map
  • Unknown: Not knowing what we don’t know
  • Aware: Knowing what we don’t know, or not being able to express what we do know
  • Know: Knowing without proof but being able to express what we know
  • Prove: Using approaches that adhere closely to the scientific method or the one used in courts of law.
  • Quantify: Being able to count, calculate or formulate.

By looking at knowledge’s states in this manner, we see how much reality we exclude if we only accept what is quantifiable and provable. Imagine in warfare or the game of poker if we took no action unless we could prove it was the right one. Business is not immune to this. Therefore, success is more determined by how we treat what we don’t know or barely know and not by how we treat what we can prove and quantify. Thus, if we lived by the advice of the board member above, we would surely fail without a great amount of fortune.


Scientific Method: An Intuitive Perspective

The scientific method’s usefulness falls far short of people’s belief in it. In other words, hype exceeds reality, and it becomes a panacea for solving problems of any type. The emotions behind this belief are so strong that people are often willing to deny, ignore or discount a reality if they cannot “prove” it. Since emotions and relationships often fall in this unproven domain and play important roles in many events, this belief can retard innovation and problem solving where intuitive approaches are viable solutions.

The inherent weaknesses of the scientific method are produced by its strengths as a disciplined inquiry. In its rigid quest to define observations and hypotheses, to control the experimental process, to quantify results and to present conclusions in a manner that can repeat results with different experimenters; the method excludes aspects of reality that aren’t easily observed, defined, controlled, quantified, presented or repeated. For example, something as obvious as good leadership being good for business cannot be addressed by the scientific method. The same holds true for proving that a good sales person sells more than a bad one or that good morale is better for business than bad morale is.

The proof of the scientific method’s inherent weaknesses is the common observation that what works in the laboratory doesn’t necessarily work in reality. That is why the idea must be reintroduced to reality via developmental and engineering phases. This is reflected in everyday life through disclaimers on product guarantees. For example, a window might be guaranteed but only if the homeowner uses the installer recommended by the window manufacturer. In other words, the best window in the laboratory might not be the best in reality because it’s too difficult to install.