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Seeing Like a Finite State Machine

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Reading this tweet by Maciej Ceglowski makes me want to set down a conjecture that I’ve been entertaining for the last couple of years (in part thanks to having read Maciej’s and Kieran’s previous work as well as talking lots to Marion Fourcade).

The conjecture (and it is no more than a plausible conjecture) is simple, but it straightforwardly contradicts the collective wisdom that is emerging in Washington DC, and other places too. This collective wisdom is that China is becoming a kind of all-efficient Technocratic Leviathan thanks to the combination of machine learning and authoritarianism. Authoritarianism has always been plagued with problems of gathering and collating information and of being sufficiently responsive to its citizens’ needs to remain stable. Now, the story goes, a combination of massive data gathering and machine learning will solve the basic authoritarian dilemma. When every transaction that a citizen engages in is recorded by tiny automatons riding on the devices they carry in their hip pockets, when cameras on every corner collect data on who is going where, who is talking to whom, and uses facial recognition technology to distinguish ethnicity and identify enemies of the state, a new and far more powerful form of authoritarianism will emerge. Authoritarianism then, can emerge as a more efficient competitor that can beat democracy at its home game (some fear this; some welcome it).

The theory behind this is one of strength reinforcing strength – the strengths of ubiquitous data gathering and analysis reinforcing the strengths of authoritarian repression to create an unstoppable juggernaut of nearly perfectly efficient oppression. Yet there is another story to be told – of weakness reinforcing weakness. Authoritarian states were always particularly prone to the deficiencies identified in James Scott’s Seeing Like a State – the desire to make citizens and their doings legible to the state, by standardizing and categorizing them, and reorganizing collective life in simplified ways, for example by remaking cities so that they were not organic structures that emerged from the doings of their citizens, but instead grand chessboards with ordered squares and boulevards, reducing all complexities to a square of planed wood. The grand state bureaucracies that were built to carry out these operations were responsible for multitudes of horrors, but also for the crumbling of the Stalinist state into a Brezhnevian desuetude, where everyone pretended to be carrying on as normal because everyone else was carrying on too. The deficiencies of state action, and its need to reduce the world into something simpler that it could comprehend and act upon created a kind of feedback loop, in which imperfections of vision and action repeatedly reinforced each other.

So what might a similar analysis say about the marriage of authoritarianism and machine learning? Something like the following, I think. There are two notable problems with machine learning. One – that while it can do many extraordinary things, it is not nearly as universally effective as the mythology suggests. The other is that it can serve as a magnifier for already existing biases in the data. The patterns that it identifies may be the product of the problematic data that goes in, which is (to the extent that it is accurate) often the product of biased social processes. When this data is then used to make decisions that may plausibly reinforce those processes (by singling e.g. particular groups that are regarded as problematic out for particular police attention, leading them to be more liable to be arrested and so on), the bias may feed upon itself.

This is a substantial problem in democratic societies, but it is a problem where there are at least some counteracting tendencies. The great advantage of democracy is its openness to contrary opinions and divergent perspectives. This opens up democracy to a specific set of destabilizing attacks but it also means that there are countervailing tendencies to self-reinforcing biases. When there are groups that are victimized by such biases, they may mobilize against it (although they will find it harder to mobilize against algorithms than overt discrimination). When there are obvious inefficiencies or social, political or economic problems that result from biases, then there will be ways for people to point out these inefficiencies or problems.

These correction tendencies will be weaker in authoritarian societies; in extreme versions of authoritarianism, they may barely even exist. Groups that are discriminated against will have no obvious recourse. Major mistakes may go uncorrected: they may be nearly invisible to a state whose data is polluted both by the means employed to observe and classify it, and the policies implemented on the basis of this data. A plausible feedback loop would see bias leading to error leading to further bias, and no ready ways to correct it. This of course, will be likely to be reinforced by the ordinary politics of authoritarianism, and the typical reluctance to correct leaders, even when their policies are leading to disaster. The flawed ideology of the leader (We must all study Comrade Xi thought to discover the truth!) and of the algorithm (machine learning is magic!) may reinforce each other in highly unfortunate ways.

In short, there is a very plausible set of mechanisms under which machine learning and related techniques may turn out to be a disaster for authoritarianism, reinforcing its weaknesses rather than its strengths, by increasing its tendency to bad decision making, and reducing further the possibility of negative feedback that could help correct against errors. This disaster would unfold in two ways. The first will involve enormous human costs: self-reinforcing bias will likely increase discrimination against out-groups, of the sort that we are seeing against the Uighur today. The second will involve more ordinary self-ramifying errors, that may lead to widespread planning disasters, which will differ from those described in Scott’s account of High Modernism in that they are not as immediately visible, but that may also be more pernicious, and more damaging to the political health and viability of the regime for just that reason.

So in short, this conjecture would suggest that  the conjunction of AI and authoritarianism (has someone coined the term ‘aithoritarianism’ yet? I’d really prefer not to take the blame), will have more or less the opposite effects of what people expect. It will not be Singapore writ large, and perhaps more brutal. Instead, it will be both more radically monstrous and more radically unstable.

Like all monotheoretic accounts, you should treat this post with some skepticism – political reality is always more complex and muddier than any abstraction. There are surely other effects (another, particularly interesting one for big countries such as China, is to relax the assumption that the state is a monolith, and to think about the intersection between machine learning and warring bureaucratic factions within the center, and between the center and periphery).Yet I think that it is plausible that it at least maps one significant set of causal relationships, that may push (in combination with, or against, other structural forces) towards very different outcomes than the conventional wisdom imagines. Comments, elaborations, qualifications and disagreements welcome.

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13 days ago
The first rule of authoritarian regimes is that they need to project strength. Therefore it is foolish for those on the outside to take their claims of strength at face value. This also makes them much less resilient. They will be completely stable until they fracture. There is never any real secret sauce. There is only the decades or centuries long bluff that works until it is suddenly called.
13 days ago
I worked for a company that used voice printing tech to tag scammers who called into contact centers (typically to engage in financial fraud, e.g. getting new credit/debit cards sent to a new address). It worked in near real-time and was very accurate with a fairly small pool of known scammers (these guys are at it all day and will make dozens of calls each day). It would even catch the same person trying to disguise their voice, such as when a man tried to sound like a woman or vice versa. Unfortunately, we also had a reporting mechanism that was used to flag new calls. It turns out that there are a LOT of scammers out there. Over time, the voice print database of known scammers grew...and grew. At first this seems like an amazing thing! We have biometric data matching all the scammers! The problem is that with so many scammers out there and in our database, non-scammers are bound to end up producing hits and our accuracy dropped. Phone call audio is not particularly high-fidelity, so that didn't help things either. With that said, phone audio quality has been rapidly improving and this may be a more viable project in the future or even today. I wouldn't know, however, since I'm no longer in the space.
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Gen Breakfast

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Follow @lamebook on instagram for more content!

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22 days ago
Watching this movie now, I mostly sympathize with the thankless job of that poor vice-principal who had to deal with these five malcontents on his day off.
16 days ago
I had a similar experience rewatching Empire Records and what terrible employees Joe had to deal with
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Twitter hates me. The Des Moines Register fired me. Here’s what really happened.

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During the seven months I worked as a trending-news reporter for the Des Moines Register, it was my job to write about viral news in Iowa and to frame my stories in ways that would increase their viral potential.

My last story for the paper, a profile of local celebrity Carson King, was my most widely read—because it provoked a national controversy. The series of events it triggered also cost me my job. 

The controversy, as it took shape in the media and on social platforms, had all the trappings to become its own viral story—it had a hero who prevails, a villain who’s taken down, and a satisfying ironic twist. The reality, of course, was much more complicated. What happened to me has opened my eyes to how viral stories so easily twist the truth into something unrecognizable, and how ill-equipped news organizations are to respond. 

Prior to the profile’s publication, I had been celebrating my professional accomplishments. I’d recently written several popular stories, among them a feel-good news piece about King, a twenty-four-year-old Iowan who’d become famous after channeling a chance ESPN appearance into a wildly successful fundraiser for a children’s hospital. I followed the story closely as the week went on and it attracted regional, then national, attention.

When King announced that his fundraiser had crossed the million-dollar mark, I decided to write a longer profile of him. I drove out to his home in a suburb of Des Moines. I had been talking with King via Facebook Messenger, but this was my first time meeting him in person. He was humble, and struck me as a genuinely kind and well-meaning person.

ICYMI: BuzzFeed receives scoop from controversial source

As I began writing, an editor requested that I run a background check on King. This is standard practice at the Register, as it is for many newspapers, when reporting on public figures. I looked at King’s court records as well as his public social media, and found a few racist jokes he’d tweeted in high school. In context, I could see that these had been references to sketches by the comedian Daniel Tosh. I told my editor about the tweets and was asked to reach out to King for comment. 

I believe this was the right thing to do. Performing background checks on public figures is part of a journalist’s responsibility. If I had found the tweets, others would, too. I approached King with an understanding that what you tweet in high school is not necessarily representative of your beliefs as an adult, and he duly apologized.

I included a brief mention of the offensive tweets and King’s apology toward the end of my profile. It was a small moment placed in context at the end of a positive story. The tweets were part of a narrative of growth, maturity, and compassion—not an accusatory, “gotcha” moment. 

When I asked King about his tweets, I tried to communicate that I was not trying to bring him harm. It’s clear to me now, though, that he was worried about personal blowback. As is common in the world of celebrity PR, he moved to get ahead of the details that would be revealed in the profile.

The evening before the profile was scheduled to be published, King held a press conference to confess to the existence of his tweets and to make a public apology. In a statement given to local television news stations, he noted that a Register reporter had brought the tweets to his attention. I was not provided with this statement or informed that he was speaking to the press.

In his statement, King included a more recent tweet of his that denounced racism. I recognized this tweet when I read it later—I had sent it to him on Facebook Messenger, to show him that I believed the crude tweets I’d found were not fully representative of his beliefs.

I don’t believe that King set out to implicate me, but because he preempted my forthcoming profile, people believed that I intended to impugn his character. Immediately after he released his statement, angry messages began to come in to the Register’s Facebook page. The messages demanded that the identity of the journalist who had found King’s tweets be revealed, and threatened the reporter’s life and the lives of Register staff. The Register decided to publish my profile that night, and King tweeted that he bore the paper no ill will, but it was too late. The narrative that a Register reporter was trying to discredit Carson King had already been set in motion.

In the hours after King’s statement, people on Twitter found material that they used to discredit me, instead. They shared offensive tweets that I’d posted when I was younger, including statements that were meant sarcastically but that employed homophobic and misogynistic language and could be read as such if taken at face value. I also tweeted, verbatim, a Kanye West lyric that used the N-word. 

Tweeting these things was a mistake, and I apologize for them. I would not tweet the same things now. Like many people as they mature, I’ve come to understand that such language can cause real harm, and I’ve learned to better represent my values. 

At the request of an editor at the Register, I tweeted an apology: I had not “held myself to the same standard the Register held others.” But I immediately regretted the statement. They were words I did not believe—I was never in the business of holding others to any kind of a moral standard. As I told King, I don’t think it is fair to use someone’s old tweets to make blanket assaults on their character. 

ICYMI: NPR kills journalist’s piece over her accent

I haven’t spoken to King since our last interview, but the day after publication I received a message from his older brother Josh. “I had to deal with a 24-year-old young man last night that was bawling hysterically because of what happened,” he wrote on Facebook Messenger. “He truly is a good kid and he has defended everyone involved in this whole situation.” 

Over the next several days, I was the subject of a maelstrom of misunderstanding, anger, and hatred. My phone was nearly unusable for forty-eight hours due to constant calls from unknown numbers. The days were fogged with an ambient cloud of vitriol coming from strangers, from local people I knew but had little contact with, and from people I hadn’t spoken to in years. I did receive many kind messages—but this was also unsettling. The more I heard from people who’d grown distant in my life, the more widespread I realized the story had become. 

My Twitter and email were inundated with anger. I received death threats by text message and by Facebook Messenger. My family and loved ones, and other Register reporters, received threats and angry messages as well. Threats were received at the office, and the paper was forced to hire extra security.

The death threats were frightening. But even more hurtful were the attacks on my character and humanity. These were propelled both by ordinary readers seemingly ignorant of the facts and, more insidiously, by reactionary journalists and the outlets that published them, specifically right-wing demagogue Mike Cernovich, Breitbart, and Barstool Sports. Local television stations as well as national platforms such as CNN and the Washington Post helped to spread the false but palatable narrative established by these outlets—that I had sought to vilify King for his tweets. A statement given by the Register attempted to explain the situation but failed to correct the assumptions. Throughout, I was instructed not to comment or respond to requests from the press. 

After two days of media furor, representatives from Gannett, the Register’s parent company, called me at the home of a friend, where I was staying out of fear for my safety. Gannett, they told me, had determined that my tweets had compromised my credibility as a reporter. The company gave me two options: quit the paper, or be fired with no severance. On the phone, in my friend’s bedroom, I chose to be fired. I then returned to the living room, where two police officers stood waiting. With the assistance of my partner, I walked the officers through the messages I’d received from strangers. Some threatened to kill me; others asked me to kill myself.

This marked the conclusion of my time as the trending-news reporter for the Des Moines Register

THE DAYS BETWEEN King’s press conference and my firing were some of the worst of my life. I was made into a villain and a fool, a man who tried to “cancel” Carson King and in so doing got himself “canceled.” People resented what they perceived as a reporter’s making King a target of political correctness. King represented the foundations of Iowan identity and, more generally, Americanism. He was the young, white son of a police officer. He had an unassuming selflessness, he was a fan of college football, and he drank Busch Light. 

The existence of King’s racist tweets complicated this simple portrait. But instead of attempting to understand the nuances of a man’s character within the complexities of the world, readers reacted by punishing the writer who made those complications visible. 

There was never any attempt to “cancel” Carson King. In fact, his status as a folk hero has only grown. By the end of his fundraiser, he had brought in over $3 million. Though Anheuser-Busch withdrew its association with King and its donation of a year’s worth of beer, a man in Iowa donated it to King in the brewer’s stead. On September 28, Iowa’s governor established an official Carson King Day, proclaiming that “individuals like Carson King demonstrate how ‘Iowa Nice’ isn’t just a slogan, but our way of life.”

ICYMI: The story BuzzFeed, Daily Beast, NYTimes and more didn’t want to publish 

Meanwhile, I lost my job—work that I was good at and proud of. My family has deep roots in Iowa, and I grew up reading the Register. The writer Jesse Singal gleefully pointed out on Twitter the irony of the fact that I had shared Osita Nwanevu’s New Republic article on the fallacy of “cancel culture” before I was fired. But I still don’t believe in the boogeyman of cancel culture. I was not “canceled”; Gannett chose to fire me. That’s an important distinction.

I’m far from the first person to be doxxed or to endure an online mob. It’s a more common occurrence, and turns more quickly violent for women or writers of color. With the support of my partner and my friends and family, I was able to avoid collapsing beneath the weight of the great hatred directed toward me. Some of my former colleagues at the Register have reached out to communicate their support—off the record, of course—and that has strengthened my conviction that I reported the story as well as I could.

The specter of “cancel culture” is a concept most often invoked to protect those in power, often straight white men such as myself, from facing consequences for their actions, but I want no part in it. I’m not going to start a YouTube channel railing against the perceived dangers of PC culture. I believe I lost my job unfairly. At the same time, I firmly believe that people, especially those in power, should be held accountable for what they say and do.

GANNETT HAS SET a dangerous precedent: allowing editorial decisions to be made by public demand. Most of the reporters in the Register newsroom are, like me, in their twenties. They serve as cheap labor, filling the positions of older reporters who were laid off. They are there because they believe in the necessary work of local journalism, as I did and still do. They deserve better than this, as do their subscribers.

After King’s statement that Tuesday evening, I was not allowed to return to the Register office. In the roughly forty-eight hours that elapsed from that time to my firing, I had limited contact with my direct supervisors and a single conversation with Gannett HR, where I gave them a statement similar to what I’ve written here. The managerial process that resulted in my firing was completely opaque to me. 

I wish Gannett would have taken into further consideration how I’d represented myself as an employee. But rather than trust the character I’d established in the newsroom and work with me to help address the anger, misunderstanding, and misinformation in the community, they vindicated bad-faith attacks and allowed disingenuous arguments to influence their decisions.

There was no union at the Register. Had I been a union member, I believe I would have been able to more effectively advocate for myself. The day I was fired, the Department of Justice approved a massive merger between Gannett and Gatehouse, forming the largest media corporation in the nation. The Gannett/Gatehouse merger will result in a historic monopoly over local news media and will likely prompt widespread layoffs. Earlier this month, the Arizona Republic, a Gannett-owned paper tired of enduring staff purges and fearful of what’s to come, voted to unionize despite heavy-handed attempts by Gannett to suppress their movement. I hope this signals better things to come.

Neither the Register nor Gannett was prepared for what virality truly meant, or for what the kind of story they had asked me to report truly looked like. They wanted the clicks. But they did not anticipate how powerful the narrative would be once wrested from their control and turned on them and their reporters. In the end, I believe I was scapegoated by a corporation trying to preserve its bottom line.

Nearly as quickly as the Carson King story made me into a villain, it is leaving me behind. A Register story about the end of King’s fundraiser published October 2—less than a week after I was fired—makes no mention of me, King’s tweets, or the torrential news cycle that followed. The story includes an interview with King, but he makes no comment on those events.

ICYMI: A reporter attended a school board meeting for 3 hours, longer than other journalists present. That ended up being a very good decision.

Aaron Calvin is a writer living in Iowa.
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36 days ago
If you are part of an online mob, you are the problem and not the solution.
32 days ago
Outrage culture. Twitter. It all needs to be burned with fire.
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The Risk of Dying Doing What We Love

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Many of us participate in activities and sports that are at least somewhat dangerous.  However, most of us also do not have a full appreciation of how risky these activities really are, especially compared to other things that we could be doing instead.

We just love our favorite pastime and facing up to its risks can be stressful because we also want to be safe while having fun. Psychologists call this type of stress “cognitive dissonance”, and we intuitively look for ways to remove the discomfort of our conflicting emotions, often by downplaying the risks to ourselves and to others. 

E.g., when I became a glider pilot some 35 years ago, my instructors used to proclaim that “the most dangerous aspect of the sport is the drive to the airport”.  This was a widely held belief at the time even though it could not have been further from the truth. And while the slogan was famously debunked by the prominent German pilot Bruno Gantenbrink in his speech “Safety comes first“, our instinct to downplay the risks to ourselves (and to others) has of course remained.

Given our natural inclination to deceive ourselves, it is not surprising that good data about the factual risks of many activities can be difficult to come by.  And even if data are reported, they are often accompanied by statements that soften, blur, or contradict the facts, frequently through the use of misleading comparisons.

Here is just one such example from scuba diving in which the author asserts that scuba diving is safer than driving a car. She does this by comparing the statistic that 1 in 5,555 people were killed in a car accident in 2008 with the statistic that only 1 out of 212,000 dives ended deadly.  Did you catch the fundamental flaw?  The comparison would be ok only if each driver would drive just once a year.  In reality, each driver makes on average 2 trips per day, i.e. 730 car trips per year, which means that the 5,555 drivers drove in aggregate about 4 million times (5555*730).  I.e., 1 in 4,000,000 drives ended deadly vs 1 in 212,000 dives. By this – still not perfect, but definitely more comparable – measure diving isn’t safer than driving but instead about 19x more dangerous! No matter the sport or activity, you’ll quickly find similar examples of apples to oranges comparisons and a conscious or subconscious attempt to downplay the risks.

When I looked for data on risky sports and activities, I also found the other extreme: a Google search will return plenty of articles listing “the most dangerous sports in the world,” almost all of which try to make most sports sound insanely dangerous. However, more often than not these articles are just click-bait to generate ad revenue and lack any serious effort to get to the facts.  Even the most well-intentioned ones that actually quote their sources tend to suffer from one of two major problems: either they lack a common denominator and therefore compare stats that are just not comparable; or they use a denominator that isn’t all that meaningful such as the general population while ignoring the differences in participation rates among different sports.

I wanted to know the honest truth and so I set out to do the research myself.  The most important decision that I had to make at the outset was to select the most appropriate basis of comparison and hence, what denominator to use.  I concluded that the most meaningful datapoint to me is the risk of dying (and the risk of getting injured) per hour of participating in a particular activity.  There are two reasons I picked this risk per participation hour as the most sensible base of comparison: First, it allows me to compare different choices for my spare time, e.g., the risk of spending an afternoon riding a mountain bike vs the risk of spending the same afternoon flying a sailplane. Second, it gives me a sense of how serious the risk really is and therefore how carefully I should prepare to mitigate it.

The graphic that we’ll get to below shows what I came up with.  To facilitate the readability of the comparison, I benchmarked all activities against traveling on commercial airlines, which happens to be one of the safest things you can do when you leave your home:  only once in 10 million passenger hours (i.e., once in 1,141 years) will a passenger die when traveling on a commercial airline.  In other words, the chance of a person dying within their next 1,000 participation hours is only 0.01%.

Other activities that I participate in regularly such as driving, cycling, skiing (on and off piste), or marathon running aren’t nearly as safe as traveling on an airliner but they are still quite safe.

Unfortunately, my favorite sport, flying sailplanes, aka soaring, is one of the more dangerous activities.  There are no reliable participation data available for the US but I found quite solid information for Germany and France where soaring is much more practiced than in the US.  In both countries the sport has a fatality rate of 1 in 50,000 participation hours; i.e., the risk of dying within the next 1,000 hours of participation is 2%, about twice as high as the risk involved in riding motorcycles.  It also means that an active pilot, who flies about 100 hours per season, has a 1 in 50 chance of dying in the sport within the next decade, and it makes soaring about 200 times more dangerous as traveling on a commercial jet. Other air sports tend to have similar risks:  flying powered airplanes is just a little bit safer whereas hang-gliding and paragliding are somewhat more dangerous.

Some of the data surprised me.  E.g., I found driving, skiing, and cycling to be safer that I expected, whereas climbing the Tetons and especially Mt Everest is actually much more dangerous than I anticipated.  Not surprising to me was the insanely high risk involved in Base Jumping, which is shown to be 480,000 times more dangerous than commercial aviation, with an expected death per 21 hours of participation, and practically no chance at all to survive the next 1,000 hours of flying through the air.  If you’re a Base Jumper you are likely to complain that my methodology of counting only the short duration of the jump (and, e.g., not the time you spend climbing up the mountain) puts your sport into an unfair light.  To that I say feel free to count differently if you want to convince yourself that jumping is safer than it really is.  As I pointed out above, you certainly won’t be alone in your desire to deceive yourself.

Unfortunately, all the information in the chart below only refers to the risk of death and does not account for the risk of injuries.  The reason is simply the fact that data about injuries are extremely unreliable since the great majority of sport injuries are never reported and/or accounted as such.  (The omission of injury information also means that activities that tend to have a relatively high injury to death ratio (e.g. skiing, equestrian eventing, marathon running, riding motorcycles, hang gliding, paragliding, downhill mountain biking) might look relatively safer than they really are, and activities that have a relatively low injury to death ratio (e.g. general aviation, soaring, skydiving) might appear relatively more dangerous than they really are.)

Without further ado, here is the chart:

Another way to look at the same data is to compare them to the normal risk of dying (of any cause) at different life stages.  Life insurance companies keep track of these risks as they seek to adjust their premiums based on the age of the insured.  It should be intuitive that an 18 year old person has a much lower risk of dying within their next 1,000 life-hours than a 90 year old.

Below is a chart that shows how this normal risk of death increases as you get older. E.g, the odds that an average 18-year-old American male will die within their next 1,000 life-hours is about 0.01%.  This happens to be exactly the same odds as traveling on a commercial airliner, once again illustrating how save commercial air travel has become. A 90-year-old male, by comparison, has a 1.9% chance of dying within their next 1,000 life hours.  You can see how the slope of the curve remains fairly flat until the age of 50, and how it really steepens around 75. If someone manages to survive until the age of 119, their odds of dying within the next 1,000 life-hours will have risen to 10.2%.

(The source of this information is the US Social Security Administration.  Note that they report the risk of dying within the next year, which I converted to the risk within the next 1,000 life hours, i.e. 41.7 days.  Note also that the risk level tends to be slightly lower for females since their life expectancy is higher, but for our purposes the gender differences are negligible.)

So how do the risks of the various activities compare relative to the normal day-to-day risk of dying at different ages?

To illustrate this, I placed the activity icons onto the same chart (see below).  Once again, you see that commercial air travel is the safest of these activities. Driving, skiing, cycling, back-country skiing, and marathon running are all along the relatively flat part of the curve.  The risk of dying per hour when swimming in open waters or while participating in equestrian eventing is about 0.3%, equivalent to the risk that an average 71 year-old person faces in their day-to-day life.

As you move right and up along the curve, the risk level increases much more noticeably. Scuba diving is about as dangerous as being 80 years old, and motorcycling corresponds to the normal risk of being 85.  Several air sports come next: general aviation, flying sailplanes, hang gliding, and paragliding.  Each of these is about as risky as the normal lives of people aged 88 to 95.  Downhill mountain biking also falls into this category.

As you continue further up the slope you can see two outliers: skydiving is about as dangerous as the normal life of a 107 year-old and climbing the Tetons is about as dangerous as being 119 yeas of age.

Three activities from the initial graphic above are still missing: Formula 1 racing, Climbing Mt. Everest, and Base Jumping.  The dangers of these three sports are so great they are literally off the chart because the Social Security Administration does not compute death risk statistics for anyone older than 119.  (You probably don’t know anyone of that age either.)  Since Formula 1 racing is about 2x as dangerous as Climbing the Tetons and Climbing Everest is another 2x as dangerous, you can roughly imagine how high up the risk curve you have to go.  With Base Jumping even that becomes impossible: it is more than 100x more dangerous than climbing Mt. Everest!

Why put all this information together?  I believe we should all be fully aware of the risks that we take, and that we should let our awareness of these risks be an incentive to take the appropriate preparations and precautions to reduce these risks as much as possible.  Most of the fatal accidents in sports are at least in part the result of human error and could have been avoided. If we close our eyes to the risks (as we are naturally inclined to do in order to remove this pesky thing called cognitive dissonance), we are also unlikely to do what it takes to keep the risks contained.

Commercial aviation is a great example that risk mitigation really works. After the invention of powered flight in 1903, flying was certainly one of the most dangerous things humans could possibly do. Gradually and over time, this risk has been reduced to such an extent that commercial air travel is now one of the safest things we participate in.

The concrete risks and the strategies for risk mitigation are obviously quite specific to each of the different activities and discussing them is beyond the scope of this article.  But risk mitigation strategies do exist for all activities and deploying them deliberately and consistently can be very effective (for some activities probably more so than for others).  If you do something that is objectively dangerous (and now you know that it is), learning about these strategies and taking them seriously can truly help you stay alive.

Have fun and be safe!

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39 days ago
Running marathons is more dangerous than I would have expected. Most of the rest checks out against my intuitions.
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The Best Carry-On Luggage

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We’ve tested 47 bags over the past five years and are convinced that the Travelpro Platinum Elite is the best carry-on luggage for most travelers. It packs five days’ worth of clothes into standard US carry-on dimensions and has premium build-quality touches you’d expect from a $500 bag at about half the price. It’s a bag that you can rely on for life, even if it’s damaged by airlines—a rarity at any price.

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46 days ago
If there is one thing I've learned it is that wheeled bags are almost never worthwhile. It is much better to have a bag that is convertible to a backpack so you can get your hands free. I can't imagine ever trading my Tom Bihn luggage for any other kind.
46 days ago
I've got a 40L travel backpack loaded up as we speak. Exit the airport into a city with busted sidewalks and ask yourself if you prefer wheels or shoulder straps :P
46 days ago
Exactly. Even on relatively smooth surfaces a single bump on a two-wheel bag can make it pop out of your hand and splat. Or tip over a four wheel bag.
46 days ago
I'm a big Tom Bihn fan. With the right bag, you don't need wheels. I've also had their Empire Builder in daily use for 12 years and it's got another 20 in it based on current wear.
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What I Think Republicans Don't Understand About Republicans

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Not gonna link because it's Hugh Hewitt but:
If Republicans don’t stand by Trump, they risk losing their base forever
is the subhed.

One thing *I* know about the Republican base which I think too many people don't is that takes them about a week from circulating pictures of Trump-As-Jesus-Christ to literally not remembering his name. We went through this with Bush. We went through this with Palin.

Because it never was about Bush or Palin or Trump. And to a great degree Bush himself was never about Bush, it was about that lovely wonderful post-9/11 era, the greatest time for Republicans ever. They were merely vessels for making Republicans feel like they were Owning the Libs and Fox News handles that pretty well for them daily even without a figurehead.
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47 days ago
Yes. This is accurate. And it is true for both parties. The candidates and individuals take on the mantle of their party for a time and move on but the party remains. The 'base' never leaves and will then follow the next person. Even Presidents that are regarded as universally lousy like Carter and Nixon were not truly abandoned by their 'base' until after they were out of office. And at that point the 'base' just moved on to a new leader.
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