Big Questions, Little Questions, and Stolen Elections
Updated: Apr 22, 2022
It's going on week three after the 2020 election, and still the incumbent president has not conceded the race. The putative reason for the stalling is a complaint that the election was unfair or fraudulent or stolen by the dark forces of the opposing political party. (The real reason likely has to do with self-interest and economics. But that's another post.)
To date, millions of people on the right have grasped hold of this story that the 2020 election was fraudulent. Some of them march in the streets. Some of them donate to war chests dedicated to recounts (the bill for Wisconsin alone is almost $4M). And all of them (or so it seems) complain about the stolen election on social media.
Was there significant voter fraud in 2020?
To answer that question, we first need to know what sort of question it is. One chapter in my book on fake news is about big and little questions. Here's the basic idea. All questions can be sorted into two discrete piles: big questions and little ones. Little questions are those that we can reliably answer using our natural and automatic perception and thinking. Both features are required: our answers to these questions must be generally reliable (even if not perfect) and answers must come naturally or easily. For example, I know that my computer is on, that it's sunny outside right now, and that I had breakfast this morning. I can reliably answer all those questions on my own.
Big questions are those we can't answer reliably using our natural and automatic perception and thinking. We need artificial help of some sort. For example, my natural and automatic thinking won't be enough to reliably tell me whether the economy will grow in the 3rd quarter of 2025, how many babies are born in India every minute, or what I had for breakfast one year ago today. Answering big questions like these requires outside help in the form of expertise, technology, written records, or special tools.
So get back to our question. Is the question of voter fraud in the 2020 election a big question or a little one? No doubt about it, it's a big question. You can't just sit back and think about mail-in ballots or long queues for voting booths or the rise in partisanship or the hatred of those in the other party for your candidate to confirm or deny that there was significant voter fraud in 2020. You need artificial help.
To answer this question, like many other big questions, we rely on experts who have special training or have devised special tools that we lack. (How experts do so is another chapter in the book.) So while we can't answer the question about fraud ourselves, we can rely on experts to do so for us.
This means we can't tell for ourselves whether the 2020 election was stolen, and thus we need to rely on experts to help us out. And therein lies the problem with right-wing complaints about the 2020 election. The experts and systems that called the 2020 election are the SAME experts and systems that called the 2016 election. Yet supporters of the president ACCEPT the results of the first but not the second.
So there are really two problems here. First, many people seem to think that they know or can just tell that the 2020 election was fraudulent. In that case, they are making an epistemic mistake because they have not recognized the question as a big question. Second, many people trust election experts in inconsistent ways. They trust the exit-polling, network calls, and local voting officials in 2016 but distrust the same apparatus in 2020. To do that without compelling evidence of a difference between the two cases is intellectually dishonest.
Here's how these points gets translated into action. If you meet someone who claims that the 2020 election was fraudulent, ask them how they know. Don't accept any answers like "it's just obvious" or "I can just tell." It's not a little question, so those sorts of answers are off limits. Only an appeal to credible experts could settle the matter one way or the other.
Follow-up with a second question: did you trust the results in 2016 when President Trump was elected? If they say no, well, at least they are consistent. If they say yes, then ask them why they trusted the system and the experts in 2016 when they won but distrusted the same system and experts in 2016 when they lost.