Liv Boeree | Vox

How an 18th-century priest gave us the tools to make better decisions

2018-12-11T13:57:31-05:00

I’ve been a hypochondriac for much of my life.

When I was 13, I read an article about a girl my age who had recently lost her hair to alopecia. For the next six months, my teenage self developed an obsessive hair-counting habit every time some collected in my hairbrush.

A few years later, as a freshman at university, a three-day headache led me to call home in tears, convinced I had a brain tumor. (I did not.)

In 2008, my 24 years of neuroticism reached their dizzying peak. I had gone wakeboarding on a warm lake during a trip to Las Vegas, and I woke up a few days later feeling a little under the weather. One three-hour Google spiral later, I was in a full-blown panic.

You see, there is an extremely rare but nevertheless horrifying amoeba called Naegleria fowleri that occasionally appears in warm freshwater lakes in the Southern states, and if said lake water gets into your sinuses through a mistimed splash, the amoeba can climb up your olfactory nerve, reproduce, and quite literally eat your brain. Even though I understood the meaning of the words “extremely rare,” the narrative was just too perfect — neurotic hypochondriac who always worried needlessly about rare terrible diseases succumbs to rare terrible disease.

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Of course, I was wrong again. The only thing eating my brain was my irrational anxiety, and after a few sleepless nights, I felt sheepishly well enough to rejoin the Vegas revelry.

Fast-forward to today, and I’m pleased to say that my hypochondria — and my reasoning skills in general — have significantly improved. A large part of that was my choice of profession; I began playing professional poker shortly after the amoeba episode, and 10 years later, the game has trained my mind to better handle uncertainty.

But the most powerful antidote to my irrationality came from a surprising source: an 18th-century English priest named Reverend Thomas Bayes. His pioneering work in statistics uncovered an immensely powerful mental tool that, if properly used, can drastically improve the way we reason about the world.

Bayes’ theorem, explained

Our modern world is notoriously unpredictable and complex. Should I buy bitcoin? Is that news headline reliable? Is my crush actually into me, or just stringing me along?

Whether it’s our finances or our careers or our love lives, we have to tackle tricky decisions on a daily basis. Additionally, our smartphones bombard us around the clock with a never-ending stream of news and information. Some of that information is reliable, some is noise, and some is intentionally created to mislead. So how do we decide what to believe?

Reverend Bayes made enormous steps toward solving this age-old problem. He was a statistician by training, and his work on the nature of probability and chance laid the groundwork of what is now known as Bayes’ theorem. While its formal definition appears as a rather intimidating mathematical equation, it essentially boils down to this:

In other words, whenever we receive a new piece of evidence, how much should it affect what we currently believe to be true? Does the information support that belief, dispute it, or not affect it at all?

This line of questioning is known as Bayesian reasoning, and chances are you have been using this method of belief-building all your life without realizing it has a formal name.

For example, imagine a co-worker comes to you with a shocking piece of news: He suspects that your boss has been siphoning money from the company. You’ve always respected your boss, and if you had been asked to estimate the likelihood of him being a thief prior to hearing any gossip (the “prior odds”), you would think it extremely unlikely. Meanwhile, your colleague has been known to exaggerate and dramatize situations, especially about people in managerial positions. As such, their word alone carries little evidential weight — and you don’t take their accusation too seriously. Statistically speaking, your “posterior odds” stay pretty much the same.

Now, take the same scenario but instead of verbal information, your colleague produces a paper trail of company money going into a bank account in your boss’s name. In this case, the weight of evidence against him is much stronger, and so the likelihood of “boss = thief” should increase proportionally. The stronger the evidence, the stronger your level of belief. And if the evidence is compelling enough, it should make you change your mind about him entirely.

If this feels obvious and intuitive, it should. The human brain is, to some extent, a natural Bayesian reasoning machine through a process known as predictive processing. The trouble is, almost all our intuitions evolved out of simpler times for savannah-type survival situations. The complexity of more modern-day decisions can sometimes cause our Bayesian reasoning to malfunction, especially when something we really care about is on the line.

The pitfalls of motivated reasoning

What if, instead of respecting your boss, you’re annoyed at him because you feel he’d been unfairly promoted to his current position instead of you? Objectively speaking, your “prior” belief that he is an actual account-skimming thief should be almost as unlikely as in the previous example.

However, because you dislike him for another reason, you now have extra motivation to believe the gossip from your co-worker. This can result in you excessively shifting your “posterior” likelihood despite the lack of hard evidence … and perhaps even doing or saying something unwise.

The phenomenon of being swayed from accurate belief-building by our personal desires or emotions is known as motivated reasoning, and it affects every one of us, no matter how rational we think we are. I’ve lost count of how many times I’ve made an objectively stupid play at the poker table thanks to an excessive emotional attachment to a particular outcome — from chasing lost chips with reckless bluffs after an unlucky run of cards, to foolhardy heroics against opponents who’ve gotten under my skin.

When we identify too strongly with a deeply held belief, idea, or outcome, a plethora of cognitive biases can rear their ugly heads. Take confirmation bias, for example. This is our inclination to eagerly accept any information that confirms our opinion, and undervalue anything that contradicts it. It’s remarkably easy to spot in other people (especially those you don’t agree with politically), but extremely hard to spot in ourselves because the biasing happens unconsciously. But it’s always there.

And this kind of Bayesian error can have very real and tragic consequences: Criminal cases where jurors unconsciously ignore exonerating evidence and send an innocent person to jail because of a bad experience with someone of the defendant’s demographic. The growing inability to hear alternative arguments in good faith from other parts of the political spectrum. Conspiracy theorists swallowing any unconventional belief they can get their hands on until they think the Earth is flat, or movie stars are lizards, or that a random pizza shop is the base for a sex slavery ring because of a comment thread they read on the internet.

So how do we overcome this deeply ingrained part of human nature? How can we become better Bayesians?

Extraordinary claims require extraordinary evidence

For motivated reasoning, the solution is somewhat obvious: self-awareness.

While confirmation bias is usually invisible to us in the moment, its physiological triggers are more detectable. Is there someone who makes your jaw clench and blood boil the moment they’re mentioned? A societal or religious belief you hold so dear that you think anyone is ridiculous to even want to discuss it?

We all have some deeply held belief that immediately puts us on the defensive. Defensiveness doesn’t mean that belief is actually incorrect. But it does mean we’re vulnerable to bad reasoning around it. And if you can learn to identify the emotional warning signs in yourself, you stand a better chance of evaluating the other side’s evidence or arguments more objectively.

With some Bayesian errors, however, the best remedy is hard data. This was certainly the case with my battle against hypochondria. Examining the numerical probabilities of the ailments I feared meant I could digest the risks the same way I would approach a poker game.

Sick of my neuroticism, a friend looked up the approximate odds that someone of my age, sex, and medical history would have contracted the deadly bug after swimming in that particular lake. “Liv, it’s significantly less likely than you making royal flush twice in a row,” he said. “You’ve played thousands of hands and that has never happened to you, or anyone you know. Stop worrying about the fucking amoeba.”

If I wanted to go one step further, I could have plugged those prior odds into Bayes’ formula and multiplied it by the evidential strength of my headachy symptoms. To do this mathematically, I’d consider the counter case: How likely are my symptoms without having the amoeba? (Answer: very likely!) As headaches happen to people all the time, they provide very weak evidence of an amoebic infection, and so the resulting posterior odds remain virtually unchanged.

And this is a crucial lesson. When dealing with statistics, it is so easy to focus on fear-mongering headlines, like “thousands of people died from terrorism last year,” and forget about the other equally relevant part of the equation: the number of people last year who didn’t die from it.

Occasionally, “red pill” or conspiracy enthusiasts fall into a similar statistical trap. On its face, questioning mainstream belief is a good scientific practice — it can uncover injustice and prevent systemic mistakes from repeating in society. But for some, proving the mainstream wrong becomes an all-consuming mission. And this is especially dangerous in the internet era, where a Google search will always spit out something that fits a chosen narrative. Bayes’ rule teaches you that extraordinary claims require extraordinary evidence.

Yet for some people, the less likely an explanation, the more likely they are to believe it. Take flat-Earth believers. Their claim rests on the idea that all the pilots, astronomers, geologists, physicists, and GPS engineers in the world are intentionally coordinating to mislead the public about the shape of the planet. From a prior odds perspective, the likelihood of a plot so enormous and intricate coming together out of all other conceivable possibilities is vanishingly small. But bizarrely, any demonstration of counterevidence, no matter how strong, just seems to cement their worldview further.

Certainly uncertain

If there is one thing Bayes can teach us to be certain of, however, it is that there is no such thing as absolute certainty of belief. Like a spaceship trying to reach the speed of light, a posterior likelihood can only ever approach 100 percent (or 0 percent). It can never exactly reach it.

And so, anytime we say or think, “I’m absolutely 100 percent certain!” — even for something as probable as our globe-shaped Earth — we’re not only being foolish, we’re being factually wrong. By that statement, we’re effectively saying there is no further evidence in the world, no matter how strong, that could change our minds. And that is as ridiculous as claiming, “I know everything about everything that could ever possibly happen in the universe, ever,” because there are always some unknown unknowns we cannot conceive of, no matter how knowledgeable and wise we think we are.

Which is why science never officially “proves” anything — it just seeks evidence to improve or weaken current theories until they approach 0 percent or 100 percent. This should serve as a reminder that we should always remain open to the possibility of changing our minds if strong enough evidence emerges. And most importantly, we must remember to see our deepest beliefs for what they ultimately are: just another prior probability, floating in a sea of uncertainty.

Liv Boeree is a science communicator and TV host specializing in astrophysics, rationality, and poker.

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Why haven’t we found aliens yet?

2018-07-03T10:04:25-04:00

One summer night, when I was a child, my mother and I were scouring the night sky for stars, meteors, and planets.

Suddenly, an object with a light that pulsed steadily from bright to dim caught my eye. It didn’t have the usual red blinkers of an aircraft and was going far too slowly to be a shooting star.

Obviously, it was aliens.

My excitement was short-lived as my mother explained it was a satellite catching the sun as it tumbled along its orbit. I went to bed disappointed: The X-files was on TV twice a week back then, and I very much wanted to believe.

Today that hope is still alive and well, in Hollywood films, the public imagination, and even among scientists. Scientists first began searching for alien signals shortly after the advent of radio technology around the turn of the 20th century, and teams of astronomers across the globe have been taking part in the formal Search for Extraterrestrial Intelligence (SETI) since the 1980s.

Yet the universe continues to appear devoid of life.

Now, a team of researchers at the University of Oxford brings a new perspective to this conundrum. In early June, Anders Sandberg, Eric Drexler, and Toby Ord of the Future of Humanity Institute (FHI) released a paper that may solve the Fermi paradox — the discrepancy between our expected existence of alien signals and the universe’s apparent lack of them — once and for all.

Using fresh statistical methods, the paper re-asks the question “Are we alone?” and draws some groundbreaking conclusions: We Earthlings are not only likely to be the sole intelligence in the Milky Way, but there is about a 50 percent chance we are alone in the entire observable universe.

While the findings are helpful for thinking about the likelihood of aliens, they may be even more important for reframing our approach to the risk of extinction that life on Earth may face in the near future.

Where is everybody?

In 1950, while working at Los Alamos National Laboratory, physicist Enrico Fermi famously exclaimed to his colleagues over lunch: “Where is everybody?”

He had been pondering the surprising lack of evidence of other life outside of our planet. In a universe that had been around for some 14 billion years, and in that time developed more than a billion trillion stars, Fermi reasoned there simply must be other intelligent civilizations out there. So where are they?

We still don’t know, and the Fermi paradox has only strengthened with time. Since the 1950s, humans have walked on the moon, sent a probe beyond our solar system, and even sent an electric sports car into orbit around the sun for fun. If we can go from rudimentary wooden tools to these feats of engineering in under a million years, surely there would have been ample opportunity in our 13.8 billion-year-old universe for other civilizations to have progressed to a similar level — and far beyond — already?

And then, surely there would be some lingering radio signals or visual clues of their expansion reaching our telescopes.

How scientists try to tackle the Fermi paradox, and why this paper is different

Space is a large place, and the task of accurately estimating the likelihood of little green men isn’t exactly easy.

In 1961, astronomer Frank Drake proposed a formula that multiplied seven “parameters” together to estimate N, the number of detectable civilizations we should expect within our galaxy at a given moment in time:

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The Drake equation was only intended as a rough tool to stimulate scientific discussion around the probability of extraterrestrial life. However, in the absence of any reasonable alternatives, it has remained astronomers’ only method of calculating the probability of extraterrestrial intelligence. This is problematic because while some parameters, such as R* — the rate of new star formation per year — are relatively well-known, others remain hugely uncertain.

Take L, the average lifespan of a detectable civilization. If we look at the average length of the past civilizations here on Earth, it wouldn’t be unreasonable to assume a low value. If the Romans, Incas, or Egyptians are anything to go by, it seems hard to make it past a few hundred years. On the flip-side, you could argue that once a civilization becomes technologically advanced enough to achieve interstellar travel, it could conceivably last many billions of years.

This enormous uncertainty leaves the Drake equation ultimately vulnerable to the optimism or pessimism of whoever wields it. And this is reflected in previous scientific papers whose results give values of N ranging anywhere from 10 to many billions.

As astronomer and SETI co-founder Jill Tarter eloquently put it in an interview with National Geographic in 2000: “The Drake Equation is a wonderful way to organize our ignorance.”

Sincere attempts to overcome this vulnerability have previously been made via selecting a handful of conservative, medium, and bullish best estimates for each parameter value and then taking an average across them.

In their new paper, titled “Dissolving the Fermi Paradox,” the FHI researchers dispute this method by demonstrating how this technique typically produces a value of N far higher than it should, creating the illusion of a paradox.

This is because simply selecting a few point estimates and plugging them into the Drake Equation misrepresents the state of our knowledge. As an example, imagine three scientists who have differing opinions on the value of L:

If you take a normal, linear average of all the possible integer values from one to 1000, you would implicitly factor scientist C’s opinion 90 times more than scientist A’s because their range of belief is 90 times larger. If you use a logarithmic scale to represent the above so that each scientist’s range corresponds to one order of magnitude, all three opinions will be represented more equally.

Therefore, the researchers represented the full range of possible values on a logarithmic scale and ran millions of simulations to obtain more statistically reliable estimates for N. They then applied a technique known as a Bayesian update to those results. That means mathematically incorporating the information that we have not discovered extraterrestrial intelligence yet (because the absence of evidence of aliens is evidence itself!).

This two-stage process produced striking results: Based upon the current state of astrobiological knowledge, there’s a 53 to 99.6 percent chance we are the only civilization in this galaxy and a 39 to 85 percent chance we are the only one in the observable universe.

This implies that life as we know it is incomprehensibly rare, and if other intelligences exist, they are probably far beyond the cosmological horizon and therefore forever invisible to us.

But life can’t be that rare, can it?

To be clear, the paper’s authors do not appear to be making any definitive claim about whether or not aliens exist; simply, our current knowledge across the seven parameters suggests a high likelihood of us being alone. As new information becomes available, they would update that likelihood accordingly. For example, if we discover a second instance of abiogenesis — the process of rudimentary life emerging from non-living matter — on a comet or another planet, then this would narrow the uncertainty on the fl parameter significantly.

Nonetheless, their results have certainly caused a stir, especially after SpaceX CEO Elon Musk tweeted them:

This is why we must preserve the light of consciousness by becoming a spacefaring civilization & extending life to other planets https://t.co/UDDP8I1zsS
— Elon Musk (@elonmusk) June 25, 2018

Many reacted to the paper’s findings by calling it anthropocentric and narrow-minded, arguing that any conclusion suggesting we Earthlings are somehow special is simply human arrogance.

This is somewhat understandable because the idea that intelligent life is extremely rare in the universe feels completely counterintuitive. We exist, along with other intelligent life like dolphins and octopi, so we assume what we see must be extrapolatable beyond Earth.

But this alone is not proof that intelligent civilizations are therefore ubiquitous. Whether the true likelihood is as high as one in two, or as inconceivable as one in a trillion trillion trillion, the mere ability to consciously ask ourselves that question depends on the fact that life has already successfully originated.

This phenomenon is known as an observer selection effect — a bias that can occur when thinking about the likelihood of an event because an observer has to be there to observe the event in the first place. As we only have one data point (us), we have no reliable way to predict the true likelihood of intelligent life. The only conclusion we can confidently draw is that it can exist.

So if we are alone, is this good or bad news?

Regardless of which side you take, the idea that we might be alone in the universe raises serious scientific and philosophical questions. Is our rareness something to celebrate or be disappointed by? What would it mean for humans to be the only conscious entities in the universe?

This last question matters hugely. Not only are we depleting our environmental resources at an unsustainable pace, but for the first time in the history of mankind, we’ve reached the technological stage where we hold the entire future of our species in our own hands. Within a few years we built enough nuclear weapons to exterminate every human on earth many times over and made these weapons available to our leaders on a hair-trigger. Each decade has brought us novel technologies with ever-increasing potential for both immense good and immense destruction.

As we rang in the new year, the Bulletin of Atomic Scientists moved the Doomsday Clock to the closest it has ever been to midnight. Meanwhile, estimates from various specialists in existential risk suggest somewhere between a 5 to 19 percent chance of complete human extinction by the end of this century — an unacceptably large probability considering the stakes.

Not only does this dark gamble affect the 7 billion of us alive today; if you factor in the moral weight of the billion billions of future people who would also never get to live out their existences, it becomes clear that we urgently need to get our collective act together.

As Carl Sagan famously said in his 1990 Pale Blue Dot speech: “In all this vastness, there is no hint that help will come from elsewhere to save us from ourselves. The Earth is the only world known so far to harbor life. … the Earth is where we make our stand.”

He’s not wrong, especially in light of this paper’s findings. If humanity really is the only civilization that may ever exist in this universe, then we shoulder a responsibility on a truly astronomical scale.

Liv Boeree is a science communicator and TV host specializing in astrophysics, rationality, and poker.