The Cost of Being Right

Hi everyone, and welcome back to The Long Run. Hope it was a nice Labor Day weekend and short workweek. I spoke too soon — it’s hot again, and summer is in fact not over yet. Just give it a few weeks…

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Everybody likes to be right.

We’ve all found ourselves in senseless arguments where each of us will not back down, where we just have to prove that what we think is correct. We fight tooth & nail, even if it means creating a bigger problem or sacrificing a relationship, simply to prove that we knew the truth all along.

And this is completely natural. In fact, we actually get a flood of adrenaline and dopamine to our brains when we argue and we’re right — being right is like a drug that impacts our judgment.

In our day-to-day lives, it could be something objective, such as arguing about how many wins UNC’s football team had last year. It could also be something subjective (even if the person insists that it’s objective), like what the best pizza restaurant in New York City is.

And then of course there are the “subjectively-objective” statements that someone might make, like “it’s not okay to put used egg shells back in a carton of eggs and then return the carton to the refrigerator.” (I was guilty of this statement myself, and despite my firmly held belief and scientific data to support my side, my opponent in this debate would not back down.)

Despite how much you want to be right (and even know you’re right), it’s not worth harming a friendship or relationship over such trivial matters.

So back to the point of this article – why is it that we are so dead set on being right all the time?

In fact, maybe it’s not important to be right. Maybe what’s important is knowing how likely we are to be right.

How likely are we to be right?

When we judge the accuracy of decisions, it’s so easy to look in hindsight and say “that was dumb” or “that was a smart choice,” because in hindsight we know how they turned out.

The clearest examples of this idea are prediction markets – like betting on sports games or picking a specific stock to trade. We take the information we have, use our knowledge to form an opinion, and we put money behind our conviction in that decision.

These events are entirely objective. Whether we are right or wrong, we know one way or the other once the event is complete, and we may end up looking like a genius or a fool.

However, when we judge past decisions of others, we often forget a key point – that no decision is “static”. New information is always being added in real-time.

Should Pete Carroll have passed the ball on 2nd & goal against the Patriots in the 2015 Super Bowl? Probably not, but we only know that in hindsight because the pass was intercepted and the Seahawks lost the game.

But had it ended differently, had they scored and won the game to give them back-to-back super bowl wins, we’d be calling Pete Carroll a genius. I’m no football expert, but given the information he had at that time, passing may have been the statistically right thing to do, given that everyone in the stadium was expecting them to run the ball.

Nevertheless, since we knew how it turned out (poorly), arguments ensued, and Carroll’s competency was severely questioned.

As a more common example, let’s say you and your friend live in New York, and you’re making plans for the weekend.

You ask your friend, “Should we go to the Met museum, or should we hang in Central Park?

Your friend: “We went to a different museum last weekend and the weather is supposed to be great outside, so let’s go to the park.”

Later that day, the subway breaks down and you’re stuck for hours.

Should you have gone to the Met?

No, because based on the information you had, you made the right call. You looked at the pros and cons and weighed your options, but unfortunately new information arose after you had already decided. You had no way of knowing the subway would break down.

Knowing our worst case scenario – how much do we have to lose?

People often say that, if you can be right just 51% of the time, you can become rich.

Let’s imagine a game where there’s a roulette wheel where 52% of the outcomes are red, and 48% are black. The payout is exactly double if you win and zero if you lose. Should you play this game?

Yes – you should place super small bets on red every time and play as many times as you can, and eventually, the law of large numbers will dictate that you will win more often than you don’t, and you’ll ultimately end up with far more money than you started with, when played out enough times.

Now let’s imagine a similar game, and this time the wheel is 90% red and 10% black. BUT, the only catch is that, with this game, you have to go all-in every time. Is this a game you should play?

Well, probabilistically speaking, your chances are really good, but if you lose all of your money too soon, you’ll never have a chance to make it back, because you’ll be bankrupt.

So beyond being right, and beyond knowing how likely you are to be right, it’s also important to know how likely you are to be so wrong that it ruins you.

This was the type of game decision-makers were playing during COVID lockdowns early in the pandemic. They had limited information, and new information was being added every day.

Given the information they had, being right (i.e. Should we have lockdowns or not?) was not as important as how likely we were to be so wrong that it ruins us (i.e. What is the worst case if we are wrong in either direction?).

The likelihood of being right was probably more important than actually being right, given the potential worst case scenarios (i.e. widespread death and despair) of what we didn’t know.

In sum, we can’t judge decisions based solely on their outcomes. When we do, it inevitably leads to frustration, arguments, and agonizing over “what could have been.”

In career decisions, ask any successful older person and they will likely tell you that there are far too many unknowns to accurately know how your career will end up, so the best you can do is use the information you have to make a decision, and account for the likelihood that being “wrong” will be catastrophic. Chances are, if you’re reading this, your “worst case scenario” is a lot better than you think.

A similar note goes for relationships. I’ve been on enough bad dates to tell you that all you can do is make the best decision given the information you have and then reassess afterwards when you do have more information about the person.

It’s not only important to be right. It’s also important to know how likely you are to be right. The importance of your likelihood of being right matters more or less with different decisions, depending on the worst case impact of being wrong.

In the pandemic lockdown example, being wrong could potentially be globally catastrophic to the human race (in the worst case scenario).

But in more trivial matters (like going on a bad date), we have a lot more liberty to not care so much about the likelihood that we’re right – after all, the worst case scenario is usually just that it’s not a fit, we learn, and we move on.

In general, knowing one’s likelihood to be right leads to a more proper assessment of confidence with decisions – avoiding the negatives that come with being overconfident or underconfident.

Understanding why we’re arguing to begin with

Which brings us back to the question that got us here to begin with – does it even matter if we are right?

The desire to be right is fundamentally bad for our society if it pits us against each other over small issues and distracts from the things that really matter.

Or as Stephen Levine puts it:

There’s a difference between trying to win an argument and trying to understand another person’s perspective.

With social media, issues have become increasingly binary and polarizing. And usually, no one actually wins these arguments. It seems like everyone is just shouting in an attempt to “dunk on” someone else, proving that they are right and conveying high status.

But rather than treating arguments as competitions, what if we just tried to understand each other’s point of view?

As he mentions in his book Greenlights, when Matthew McConaughey was visiting Mali, he found himself as an observer to a heated argument between the two local guides.

When he decided to step in and share his own opinion on the matter, the guide responded, “It is not about right or wrong. It is, ‘Do you understand?!’”

In this kerfuffle, he learned a valuable lesson:

Too often we argue over small misunderstandings that grow into larger ones. Personally, I’ve definitely had instances where I got angry at someone but never took the time to hear their full side of the story.

Hanlon’s razor sums it up well:

Without understanding the purpose of the argument we’re engaging in, we create bigger issues, grudges, and enemies that didn’t need to exist in the first place.

When we make enemies of people who aren’t enemies, even when we win, we’ve still lost.

There’s being right, there’s knowing how likely we are to be right, and there’s knowing our worst case scenario of being wrong.

But maybe, above all, there’s knowing the point of the argument, conflict, or decision we’re engaging in to begin with.

While there is a truth, we’re living in a world where the truth is not always universally agreed upon. And sometimes, the cost of proving we’re right outweighs the marginal boosts to our egos. Could it be possible that actual truth is discovered through deeper, more civilized understanding of each other and the world around us?

Seeking to understand, not to be right.

-Owen

Fresh Finds

The Best Pizza in America Region by Region (Washington Post)

Article | 20 minutes

This was some excellent Labor Day Weekend reading content. Now that I live in New York, I have to take Pizza seriously, and this article gave a nice overview of the best pizza in major cities around the US, this history of how different regional styles of pizza came to be, and a ton of interesting factoids that you can bring up at your next party (like how Detroit-style pizza was supposedly created by an Italian guy who worked for Ford Motor company and made Sicilian pizza in a thick industrial pan that was meant to catch oil drippings in the factory).

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