Individual perception of reality is a collection of models. Models are created when facts are interpreted. Everyone sees reality a little differently because no one has all of the facts, and everyone interprets the facts a little differently. If the models are good, then the perception of reality will be accurate. If the models are faulty, they lead people astray.
Models are everywhere. They are formed when two people greet each other and when astronauts are launched into space. Models are used to shape human understanding. All of science, history, religion, social studies, and mathematics come from models. When models are identified, they can be critiqued. Critiquing models cannot guarantee accurate models, but inaccurate models are more likely to be rejected. Before a model can be critiqued, one must understand its four basic parts.
A model consists of four components: assumptions, data, analysis, and conclusions. Assumptions are the things we accept as truth. Data are the things we can see, touch, hear, taste, and smell. The process of thinking about assumptions and data is called analysis. Conclusions are the answers the model generates. Conclusions make up our reality.
Sometimes these components are carefully identified and documented. At other times, we make assumptions, collect data, perform analysis, and form conclusions unconsciously and in the blink of an eye. When models are created or used carelessly or unconsciously, we have no assurance that our perception of reality is anywhere close to the truth. Critical thinking is the process of carefully identifying, documenting, critiquing assumptions, data, analysis, and conclusions. Critical thinking helps us to make sure our models represent the truth as closely as possible.
Assumptions are the things we accept as truth. Assumptions may come from previous models. They may be things we were taught, things we discovered, or our personal beliefs. Assumptions may be things we do not know to be accurate but declare to simplify a model. If the model makes correct predictions, that will lend validity to the assumptions.
Data are the things we can see, touch, hear, taste, and smell. Data also includes measurements, historical records, and personal witnesses. Data is good if it accurately depicts facts. Unfortunately, not all data is good. Instruments may be inaccurate or misinterpreted. Witnesses may be dishonest or mistaken. And records may be incomplete or inaccurate. If the data is not good, then the models that use that data will be incorrect. We must often make assumptions about the quality of the data.
The analysis is the process of thinking about the assumptions and data. For any analysis to be good, it must consist of good logic. Math formulas and accurate identification of causes and effects are reliable indications of good logic and sound analysis. Formulas that have been misapplied or solved incorrectly will result in an incorrect analysis. Poorly or incorrectly defined causes and effects will also lead to faulty analysis. A complex analysis also requires assumptions regarding the quality of the logic.
Logical fallacies are often evident in poor analysis. There is an entire study of logical fallacy, which is highly recommended. The topic is very well covered elsewhere and will not be discussed here. However, one logical fallacy must be mentioned. The False Cause Fallacy is evident when a false cause is identified. That means a benign event or condition is identified as the cause of an outcome, while the real cause is not correctly identified.
This fallacy must be noted because of the popular use of statistics as evidence. Statistics are very effective at establishing correlation. However, correlation means that two events or conditions are more likely to occur together. It does not mean that one condition caused the other. This particular fallacy is insidious because statistical data appears to be reliable, but it is very easily manipulated to establish predetermined correlations that imply incorrect causation.
Conclusions are the results of the analysis and either rejected or accepted. If the assumptions, data, or analysis are questionable, the conclusions should be rejected. However, if the assumptions, data, and analysis are all acceptable, the conclusions may be accepted. Accepting or rejecting the conclusions is the same as accepting or rejecting the model.
It is important to note that a model may produce incorrect conclusions and still make accurate predictions. The flat earth model accurately predicted the rising and setting of the sun. The model was still wrong. Additional data and analysis eventually produced a model of the earth as a round body orbiting the sun. That model was more accurate to the truth.
It is also important to emphasize that every aspect of the model contains assumptions. One must make assumptions about the quality of the data, the quality of the logic, and the validity of the conclusions. Every assumption should be clearly defined and documented.
We may challenge assumptions. When we do, we challenge every model that relies on those assumptions. Additional models may be used to validate challenged assumptions. However, the assumptions that support the additional models are subject to review and may themselves be challenged. This process continues until a set of assumptions is accepted without challenge.
Creating models is a part of the scientific method. The process begins with a question or a desire to understand reality. The next step of the scientific method is to do research which involves identifying assumptions and collecting data. Performing the analysis and making the conclusions are both necessary for the third step in the scientific process, forming a hypothesis. One may choose to accept or reject a model after developing the conclusions or hypothesis. However, the fourth step of the scientific method requires the hypothesis or model to be tested. Then after analysis of the test data, the model will be validated or disproven. The scientific method is a powerful tool to ensure that models align with reality as closely as possible. The scientific method is also covered abundantly elsewhere. And the study of the scientific method is also highly encouraged.
There is no shortage of models. Everything from advertisements to sermons and media to meditation involves a model created to guide how reality is perceived. Each person must decide whether the models they encounter are accurate to reality, just plain garbage, or something in between. Identifying a faulty model requires the careful critique of each element of the model. The assumptions that underpin every aspect of the model are the most important aspects to critique.
Sentient Clay 