In Part 1, I discussed the difficulty with finding the Truth. It is a quest complicated by the amount of information that we are inundated with on a daily basis. It is further complicated in that much of the information we find is either erroneous or outright lies. The average person has never studied information theory in school and is ill equipped to sort through the morass of Data, Evidence and Facts that are presented to them. I admitted in Part 1 that I do not have the entire solution to this problem. Namely, how do we find the Truth? In Part 2, 3 and 4, I want to describe the three elements of Truth seeking: Facts, Data and Evidence and then in the final Part 5 show how they relate to the problem of finding the Truth. We will start by looking at what a Fact is.
Facts:
The common definition of a Fact is something that can be verified. But the concept of verification is a very difficult idea to pin down. What do we mean by verify? Do we mean that we can find other people who agree with the “Fact?” For instance, most people today would agree that the world is round or at least elliptical. However, there was a long period in history, when common knowledge held that the world was flat. Thus, common knowledge is not always a good means of verifying a Fact. Nevertheless, we often rely on common knowledge as a means of Fact verification. Most so called Facts are simply things that have become commonly agreed on. For instance, that Columbus discovered America in 1492. We are taught this in history but we are not taught that many people would not agree with this Fact. Common knowledge is a very dangerous form of verification.
It is very easy to accept a Fact as Truth if we forget or ignore the limitations of such verification. In many court trials, jurors have considered it as a Fact if they have verification by an eyewitness to the sequence of events or people who were present at a particular crime. History has shown however, that eye witnesses are very unreliable (see How reliable is eyewitness testimony?). Today we rely more and more on video cameras for verification of certain events. Even their use has not proven to be the panacea that many have hoped for.
Another means of Fact verification is measurement. What if we can measure the Fact? Surely, the ability to measure something should be conclusive proof that a Fact is accurate or true. Unfortunately, this is not the case. For instance, it is now stated as a Fact that Mt. Everest is 29,029′ in elevation (Wiki). We can accept this measurement as a Fact but there are two problems with doing so. First, the height of every mountain in the world is constantly changing. Weather, erosion and other forces of nature will over time lower some mountains and raise other mountains. Second, any measurement system is dependent on the accuracy and reliability of the measurement instrument and the process used in the measuring of the particular variable. A sloppy process of measurement can lead to false or unreliable results. The OJ trial was a good example of where the jurors refused to believe the Facts obtained from the LA crime labs.
“The prosecution had expert witnesses that testified that the Evidence was often mishandled. Photos were taken of critical Evidence without scales in them to aid in measurement taking; items were photographed without being labeled and logged, making it difficult, if not impossible, to link the photos to any specific area of the scene. Separate pieces of Evidence were bagged together instead of separately causing cross-contamination; and wet items were packaged before allowing them to dry, causing critical changes in Evidence.” http://www.crimemuseum.org/crime-library/forensic-investigation-of-the-oj-simpson-trial/
Take your common bathroom scale. If you weigh yourself regularly you will notice that you can get different readings on successive times of getting on the scale. I am not talking about different days but even taking these readings at the same exact time. Get on your scale, get off again and then get right on again and you will very likely get slightly different readings. Our ability to measure things has become more and more accurate. Nevertheless, every measurement system is either subject to errors of validity or reliability.
A validity error is when we are not measuring the right thing. IQ tests have been repeatedly criticized for not really measuring the intelligence of a human being or for being biased by many cultural Factors. Thus opponents of IQ tests argue that they are not valid measures of intelligence. A reliability error is when our measures are not consistent. The scale example given above illustrates the problem with reliability. Most people use a scale to weight themselves and most scales have problems with reliability. However, if you tried to equate your weight with your health, you would be assuming that the scale could also measure health and this would be a problem with validity. Scales cannot measure health although health might be correlated to some degree with appropriate height and weight.
A correlation is a measure of how much things vary with each other. Thus, the amount of grass growth is generally highly correlated with rainfall. The more rain we get, the more the grass grows. The amount of money one makes is somewhat but not highly correlated with IQ. Earnings tend to be more highly correlated with amount of education but this is only true up to a point. The concept of correlation is a very important concept in measurement. We are often fooled by thinking that things are correlated when they are not. This can lead to poor decision making. Here are some examples of positive correlations:
- The more time you spend running on a treadmill, the more calories you will burn.
- Taller people have larger shoe sizes and shorter people have smaller shoe sizes.
- The more hours you spend in direct sunlight, the more severe your sunburn.
- As the temperature goes up, ice cream sales also go up.
- The more gasoline you put in your car, the farther it can go.
- As a child grows, so does his clothing size.
examples.yourdictionary.com/positive-correlation-examples.html#JFuQhtBXA6whRayS.99
When a 100 percent or 1-1 correlation does not exist, you can always find exceptions to any rule or Fact. A false correlation is created when people assume two things to be true and related when they are not. For instance, Trumps claim that a good businessperson will make a good president has no basis in Fact or historical Evidence. False correlations lead to many problems including delusions, myths, fanatical beliefs and not just poor but disastrous decision making. Following, I will provide some examples of false correlation:
- The more one exercises, the more weight one will lose
- Reading will make a person more intelligent
- Paying people more will increase productivity
- A happy worker is a productive worker
- The longer one is married, the happier they are
- Lowering taxes will create jobs and improve the economy
Understanding the concept of correlation is critical to measurement and hence critical to Fact finding. If we assume that measuring anything is the best way to verify a Fact, we must be critical and open minded about the limitations of the measurement system that we decide to use.
Before we move on to looking at the concept of Data, we will look at two more problems with the concept of Facts. These are distortion and bias. Distortion relates to twisting the meaning of something. This can happen by taking something that someone has said out of context. For instance, I might be talking at a conference and say something in sarcasm such as “Yeah, I will definitely vote for Trump.” My words could be repeated verbatim and it would sound like I was endorsing Trump. It is difficult to detect sarcasm. To most people reading or hearing my words second hand, it will sound like I am a strong Trump supporter. Slick politicians and advertisers will often distort a Fact to make it sound like the Fact is supporting their position.
Bias is another major problem with Fact checking or Fact verification. Sites like PolitiFact have lulled people into thinking that Facts can be checked with great accuracy. Not only is this assertion mostly false but there is another problem. Bias will inevitably creep into the process of Fact checking when some Facts are checked and others are not. Another example will illustrate this problem. Let us take a debate between Hillary and Trump as our example. During the course of a 90 minute debate there might be as many as 200 assertions that could be Fact checked. PolitiFact will not check all of them. Which ones will they check? The Facts that might make Hillary look like a liar or the Facts that might make Trump look like a liar? By judiciously choosing the Facts that I decide to check, I can bias the results for either Trump or Hillary. Just having the most Facts on one’s side does not insure that one also has Truth on their side.
Next week in Part three, we will look at Data and the how this concept informs our search for the Truth.
Time for Questions:
Can you tell me how you know a true Fact from a false Fact? How do you decide what to believe? How much credibility do you put in the news that you hear? How do you choose the news that you want to hear? How do you decide who is telling the Truth?
Life is just beginning.
“I am a firm believer in the people. If given the Truth, they can be depended upon to meet any national crisis. The great point is to bring them the real Facts.” — Abraham Lincoln
Aging Capriciously 