Explainology: The Science of Explanation and Its Impact on Action
By Dr Charles Margerison, Psychologist – Amazing People Institute
Introduction: The Nature of Explanations and the Learning Process
Explanations are integral to human understanding, shaping our actions and decision-making. They are how we make sense of the world, interpret events and justify our choices. The history of the verb ‘explain’ is illuminating. Derived from the Latin explānāre, it originally meant “to make level, flatten out or spread out.” By the 15th century, it acquired the figurative sense of “making plain or clear” in the mind. This history highlights the human desire to render complexity intelligible.
Since Explainology contains the suffix -ology, which denotes a subject of study or learning, the discipline offers a framework for systematically learning to discern between valid and invalid explanations. Students can use this science to master the art of distinguishing fact from fiction by examining fundamental dichotomies:
- Logical explanations are characterised by coherent reasoning, while illogical explanations contain contradictory or non-sequitur reasoning.
- Proven explanations are empirically verified, whereas unproven explanations are speculative or lacking evidence.
- Acceptable explanations meet ethical and scientific standards, while unacceptable explanations are biased, misleading or harmful.
- Evidence-based explanations are supported by data, while assumption-based explanations rely on unsupported beliefs.
Explanations vary significantly across contexts (science, law, medicine, personal identity) and are always influenced by our beliefs, evidence and underlying assumptions, which fundamentally shape our perception of reality. They guide not only what we believe but also how we act.
What is Explainology? Deciphering Assumptions, Perception and Reality
Explainology is defined as the study of attributing meaning and cause to events and human behaviour. It serves as the bridge between knowledge and action. This process is more than just providing reasons; it involves interpreting facts or phenomena through a lens shaped by our values and cognitive frameworks.
Explainology examines how cultural and social factors create explanations, and how the interplay between assumptions (presupposed truths), perceptions (subjective interpretations) and realities (objective facts) dictates the soundness of a conclusion. Unexamined assumptions dramatically skew perception, leading to explanations disconnected from reality, whereas robust Explainology works to align perception with reality. Explanations can be evidence-based truths or mere rationalisations and excuses used to justify actions or beliefs.
Explanations Across Fields
· In Medicine: Explanations must be evidence-based for effective treatment. Diagnoses evolve with new evidence; for example, outdated practices like leeching were once accepted but lacked scientific grounding. Modern medical explanations rely on scientific research and testing.
· In Law: Legal explanations interpret statutes, justify actions or provide defences. They represent a justification that combines facts with an interpretation of those facts within the legal framework.
· In Science: Scientific explanations are rooted in evidence, theory and observation. They involve proposing hypotheses that can be tested and falsified. For instance, the understanding of gravity moved from a basic concept of attraction to Einstein’s complex theory of general relativity.
· In Personal Identity: Personal explanations of success or happiness shape how individuals perceive their lives. Societal norms, personal experiences and cultural definitions often influence these frameworks.
The Critical Role of Probability
A key tenet of explanation theory, highlighted by Karl Popper, is the concept of probability: no explanation is ever 100% certain. All scientific explanations are provisional and subject to falsification—they can be disproven by new evidence.
The probability of an explanation being correct is contingent on the available evidence. A robust explanation might only account for a small percentage (e.g., 10%) of variables, yet this may be the single primary causal factor. Conversely, an explanation that covers a high percentage of visible factors (e.g., 60%) can be entirely misleading if it fails to pinpoint the fundamental cause. The objective is not maximum coverage but the highest conditional probability of identifying the true causal mechanism. This inherent uncertainty necessitates continuous critical thinking and evaluation.
The Evolution of Explanations
Past Explanations
Historically, explanations were often driven by superstition. The geocentric model (Earth at the centre) was the accepted explanation for the cosmos, supported by prevailing beliefs until alternative explanations, grounded in empirical observation by figures like Copernicus and Galileo, were validated. Similarly, mental illness was once explained by supernatural beliefs, leading to harmful treatments like trepanning or exorcisms based on unproven rationales.
Present and Future Explanations
Today, explanations in science and medicine are predominantly evidence-based and subject to peer review. However, political explanations of concepts like freedom or justice remain highly variable, based on ideological perspectives.
Looking forward, explanations will increasingly integrate predictive models. Advances in artificial intelligence and big data will shift explanations toward probabilities and predictive outcomes based on statistical analyses, moving decision-making from reactive to proactive.
The Dangers of False Explanations
The rise of conspiracy theories illustrates the hazards of unfounded explanations. These theories often gain traction because they offer simplified, emotionally satisfying explanations for complex events, but they are invariably based on unverified assumptions and misinterpretations of facts, leading to misinformation and harmful behaviour.
A powerful real-world danger is found in fields like aviation, where relying on a false explanation—such as attributing a crash to pilot error when the actual cause is a systematic failure or flawed design—prevents corrective action and risks future disasters. Identifying the correct explanation is vital for safety.
Summary: The Importance of Explainology
Explanations are fundamental to our understanding and guide our actions. Explainology provides the key concepts on how explanations are constructed, influence behaviour and evolve. For informed decision-making and positive outcomes, evidence-based explanations are crucial in all fields.
In an age of complexity and information overload, understanding how to critically assess and refine explanations—recognising the impact of perception, the inherent probabilistic nature and the risk of unexamined assumptions—is essential for students and citizens alike.
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