2020 was one hell of a year. For many it was a very, very difficult year. The beginning of 2021 has already seen political scenes we may never witness again.
Throughout all of this turmoil we have seen mountains, upon mountains, of information. Social media becoming prominent source of information, sometimes good, sometimes not so good (as I write this Twitter has banned a Donald Trump).
From believers, non-believers, pro-vaccine, anti-vaccine, conspiracy theorists etc etc, it can become a minefield for anyone seeking facts. It can be overwhelming and somewhat confusing to separate the facts from the bullsh*t.
The aim of this blog is to explain what the difference in terms and terminology used between opinions, facts, biases.
A fact:
A fact is a truth, or statement of truth, that can be supported or verified by evidence. It is a truth about events that is not someones interpretation or opinion.
An opinion:
A statement is a point of view that is based on beliefs, values, emotions or personal perspective. Of course, everyone has an opinion and are fully entitled to it. However, a person’s opinion can be supported or dismissed when the facts are presented (generally through critical thinking).
Bullsh*t:
Its key to know the difference between fact, opinion and bullsh*t. There is so much of it out there it can be harmful, dangerous and spread very, very quickly. However, bullsh*t is different from a lie, which is just that a lie. As defined by Bergstrom and West (2020).
Bullshit involves language, statistical figures, data graphics, and other forms of presentation intended to persuade by impressing and overwhelming a reader or listener, with a blatant disregard for truth and logical coherence.
I’d also highly recommend the authors free course “Calling Bullshit: Data Reasoning in a digital world.
The scientific method and scientific inquiry:
Broadly speaking, scientists will generate a hypothesis based on the relationship between variables. A hypothesis is essentially a proposed explanation of a phenomenon. For example: there may be a relationship (correlation) between X & Y. But does X cause Y? Or why does X cause a change in Y?
Thus, scientists will take an educated guess (research hypothesis) about the relationships of the variables within their research study.
However, a null hypothesis maybe formed and accepted when the research does not accept or refute the research hypothesis.
Types of Bias
A bias, is simply the tendency of a human to have a positive tendency or inclination for something/someone, or perhaps a negative tendency or inclination against something/someone.
The concept of cognitive bias was first introduced by researchers Amos Tversky and Daniel Kahneman in 1972. Cognitive Biases are limitations in objective thinking by seeing things through personal experiences and perceptions.
Below are some examples:
Groupthink bias: the tendency to put value on consensus, thus not thinking independently. A group will favour harmony, cohesiveness and agreement, as opposed to a lack of harmony and/or conflict.
Confirmation bias: The tendency to support new ideas or accept things that are consistent and congruent with their already held thoughts, beliefs, and opinions.
Overconfidence bias: This bias appears when someone is inherently biased towards their own perspectives and opinions. They may hold the belief that they are the only expert that ever exists and everyone else is dumb. A small bit of knowledge can be a very dangerous thing.
Dunning-Kruger Effect: This is when people who believe that they are smarter and more capable than they really are. For example, they are too stupid to realise how stupid they are.
The halo effect: when a the initial perspective of an individual (such as a first impression) tends to cloud the judgement of the individual as a whole. Therefore, it becomes difficult to re-think that perspective of an individual based on new or opposing information.
The horn effect: The opposite of the halo effect. The horn effect is when someone demonstrates a negative attitude or set of behaviours towards another based on their appearance or character.
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