Arguing About Unicorns
Impartiality is a joke.
Okay, maybe not a joke, but at the very least, a unicorn. It can be pretty to imagine, even magical to some, but searching for it is a waste of time.
Now, I’m not saying that one can’t be objective in their evaluation of a situation, but that even simply evaluating a set of facts introduces bias. Author and editor-in-chief of The Daily Wire, Ben Shapiro, offers 3 hypotheses about journalism:
1. All journalists are biased, even if they won’t admit it.
2. The facts of a story are either factual or they are not.
3. The bias of the journalist may impact how the facts are presented, but they do not automatically discredit the facts presented.
For argument’s sake, I’d suggest all of these claims apply not just to journalists, but also to anyone presenting an argument.
I’d consider number 2 to be pretty obvious… When claiming a statement as fact, one would hope the assertion was, indeed, a fact. But why do researchers, or perhaps more importantly the casual reader, need to care about bias? Surely most adults will have learned how to be objective and impartial, right?
Since humans have free will, they must therefore form opinions to come to decisions. This happens naturally, and in some cases on an exclusively subconscious level. These unavoidable and immensely important judgements ultimately coalesce into a personal bias. Still, considering how inherent this process is to humanity, why do some journalists, or even the public at large, put such weight on seeming impartial?
Often, students are taught how to present facts in a paper. One’s first essays will often be highly structured (remember the 5 paragraph essay guidelines?) and focus on bridging a connection between bullet points and something slightly more readable. These early papers often succeed in establishing a respect for reporting ‘just the facts’ but leave little room for the developing mind to understand how a viewpoint is acquired. This can lead to situations where there are a lot of good facts, but the lines connecting them in a discussion are tenuous at best.
Since everyone naturally forms a bias for or against certain data or stimuli, why is there a stigma against it? When Hillary Clinton said “I think implicit bias is a problem for everyone,” why didn’t the nation rise up and say “well duh” if everyone is so obviously biased? Ultimately, this behavior stems from a misunderstanding of the purpose of arguments.
Persuasive writing allows the author to present their own ideas as a (hopefully) logical argument juxtaposed with facts that support said argument. The public rightly casts a suspicious eye on articles that lack any obvious sources. Nonetheless, arguments can be taken as fact simply by the fact that there are some citations, ignoring whether these sources are biased themselves or have been cherry-picked when the plethora of data suggest something contrary to the narrative being argued.
Part of this misunderstanding is the fault of the early papers. Quantity is often mandated, while quality is excused due to the age or inexperience of new writers. While some eventually pick up on the need for quality sources and thoroughly researching all the viewpoints, it is hardly intuitive changing from report-minded writing to argument-minded writing.
Considered statement 3 from Shapiro, it’s principles can be used to craft a solution to this dilemma, not just for journalism, but for everyone. Not only would arguments and news articles open with an acknowledgement of how the author leans on the pertinent issues, but also a mention of how each source’s bias may tend to fall.
The modern world allows everyone to participate in the media, whether that be through YouTube, Instagram, conventional media or a blog. Everyone has not only a duty to investigate what they believe, but also what they pass along. It need not take long, but a brief moment of consideration can help refocus the mind.
There will always be news, there will always be bias, but we don’t have to always wonder there these two constants intersect. Stand by your beliefs, stand by partiality, stand by bias, and whatever you do, don’t chase a unicorn.
James Clague is a junior studying computing.