A Hypothesis is a Liability

Two Truths and a Take, Season 2 Episode 38

Hello everyone! My apologies for the lack of original content last and this week - it’s a busy time over at Shopify and my brain is tapped out. I have some good stuff for the newsletter coming up soon, though.

Today, I want to share something I read a few days ago that is profoundly important and reminds me of an important lesson I learned back in grad school. It’s an editorial in Genome Biology, an open-access scientific journal, called “A hypothesis is a liability.”

The authors, Itai Yanai and Martin Lercher, have written the clearest explanation I’ve ever read on the difference between “day thinking”, where you have a specific hypothesis you want to test and determine if it’s true, and “night thinking”, where you are exploring with an open mind for what’s important and non-obvious, and might be just there in plain sight. It’s an important lesson on the power of being able to say, “I don’t know what I’m looking for, or what I’m trying to accomplish - I’m just exploring.” And, conversely, the immense but unarticulated cost of not being able to say so.

So today, please enjoy this important lesson - I’ve copied it verbatim here, although you can read the original article by Yanai & Lercher on the open-access journal page here or as a PDF here.


“ ‘When someone seeks,’ said Siddhartha, ‘then it easily happens that his eyes see only the thing that he seeks, and he is able to find nothing, to take in nothing. [...] Seeking means: having a goal. But finding means: being free, being open, having no goal.’ ” Hermann Hesse

There is a hidden cost to having a hypothesis. It arises from the relationship between night science and day science, the two very distinct modes of activity in which scientific ideas are generated and tested, respectively [12]. With a hypothesis in hand, the impressive strengths of day science are unleashed, guiding us in designing tests, estimating parameters, and throwing out the hypothesis if it fails the tests. But when we analyze the results of an experiment, our mental focus on a specific hypothesis can prevent us from exploring other aspects of the data, effectively blinding us to new ideas. A hypothesis then becomes a liability for any night science explorations. The corresponding limitations on our creativity, self-imposed in hypothesis-driven research, are of particular concern in the context of modern biological datasets, which are often vast and likely to contain hints at multiple distinct and potentially exciting discoveries. Night science has its own liability though, generating many spurious relationships and false hypotheses. Fortunately, these are exposed by the light of day science, emphasizing the complementarity of the two modes, where each overcomes the other’s shortcomings.

The Gorilla Experiment

Many of us recall the famous selective attention experiment, where subjects watch a clip of students passing a basketball to each other [34]. If you have not seen it, we recommend watching it before continuing to read [5].

As you watch the two teams in action, your task is to count the number of passes made by the team in white. About halfway through, a person dressed up as a gorilla enters the foreground. The gorilla pauses in the center, pounding its chest with its fists, before exiting to the opposite side of the frame. Surprisingly, half of us completely miss the gorilla, as we are focused on counting passes, even though hardly anyone overlooks it when simply watching the clip without the assignment.

We wondered if a similar process occurs when we analyze a dataset. Would the mental focus on a specific hypothesis prevent us from making a discovery? To test this, we made up a dataset and asked students to analyze it [6]. We described the dataset as containing the body mass index (BMI) of 1786 people, together with the number of steps each of them took on a particular day, in two files: one for men, one for women (Fig. 1a). The students were placed into two groups. The students in the first group were asked to consider three specific hypotheses: (i) that there is a statistically significant difference in the average number of steps taken by men and women, (ii) that there is a negative correlation between the number of steps and the BMI for women, and (iii) that this correlation is positive for men. They were also asked if there was anything else they could conclude from the dataset. In the second, “hypothesis-free,” group, students were simply asked: What do you conclude from the dataset?

The most notable “discovery” in the dataset was that if you simply plotted the number of steps versus the BMI, you would see an image of a gorilla waving at you (Fig. 1b). While we teach our students the benefits of visualization, answering the specific hypothesis-driven questions did not require plotting the data. We found that very often, the students driven by specific hypotheses skipped this simple step towards a broader exploration of the data. In fact, overall, students without a specific hypothesis were almost five times more likely to discover the gorilla when analyzing this dataset (odds ratio = 4.8, P = 0.034, N = 33, Fisher’s exact test; Fig. 1c). At least in this setting, the hypothesis indeed turned out to be a significant liability.

Not all who wander are lost

We typically acquire data with the expressed goal of testing a specific hypothesis. But as we have seen with the gorilla experiment, we are likely to miss other interesting phenomena as soon as we are in a mental mode of hypothesis testing. To account for this, we must consciously adopt a different mindset—one of exploration, where we look at the data from as many angles as possible. In this mode, we take on a sort of playfulness with the data, comparing everything to everything else. We become explorers, building a map of the data as we start out in one direction, switching directions at crossroads and stumbling into unanticipated regions.

Essentially, night science is an attitude that encourages us to explore and speculate. We ask: What could be hiding here? How would we lure it out? Night science may occur when we are most relaxed, such as when Friedrich Kekulé dreamingly looked into the fireplace in his study on an evening in 1862, until his mind formed the image of a molecular serpent biting its own tail—an image that he immediately converted into the hypothesis for the ring structure of benzene [7]. However, more often than not, night science may require the most acute state of mental activity: we not only need to make connections where previously there were none, we must do this while contrasting any observed pattern on an elaborate mental background that represents the expected. To see the discovery in our gorilla experiment, all that was needed was some notion of primate appearances. But when you roam the limits of the scientific knowns, you need a deep understanding of a field to even recognize a pattern or to recognize it as surprising. Different scientists looking at a given dataset will do this against a backdrop of subtly different knowledge and expectations, potentially highlighting different patterns. Looking is not the same as seeing, after all, and this may be why some of us may stumble upon discoveries in data that others have already analyzed.

Patternicity, or “just a correlation”?

“Correlation is not causation”—an aphorism that perhaps all scientists have heard at least once in their careers—warns of putting too much weight on mere covariation of two variables. Undoubtedly, a correlation between two features is not sufficient to infer a causal relationship. But some form of covariation is implied by a causal relationship, and hence, finding a previously hidden correlation may be the first glimpse of something new. We may then think of data exploration as the generator of correlations and patterns that can later be tested for causality.

One of the major facilitators of human intelligence is our minds’ ability to easily find patterns and connections—a tendency called patternicity by Michael Shermer [8]. Patternicity helps us in generating new night science ideas; it is the seed of many discoveries. On the flipside, patternicity makes us vulnerable to being fooled by randomness [9], when we mistakenly infer relationships between genuinely independent things (called apophenia). Clearly, spurious results will be generated during unguided explorations, and this generation of false starts is night science’s own liability.

Day science tempers this liability. In a sense then, correlations are the domain of night science, while causation is solidified by day science. Day science is the adult in the room, rigorously testing hypotheses. But despite its power, the day science mode is not amenable to generating the ideas in the first place. Only the night science realm, with its lack of specific hypotheses that blind us in day science, allows us to think freely in an exploratory fashion. Science relies on this back and forth between day and night, each overcoming the other’s shortcomings; we can let ourselves explore so freely in night science because we trust ourselves to check the generated hypotheses later, in day science.

Fishing Expeditions

In many scientific circles, one of the most condemning judgments about a project is to label it as “a fishing expedition”: an exploration of data that lacks even the pretense of a hypothesis. But as we argued above, such hypothesis-focused criticism misses a crucial point. Discoveries are not only unexpected, they are also undiscoverable without data. Provided that a dataset is carefully designed to be rich in information relevant to a specific field, initially hypothesis-free night science explorations are a systematic way to generate hypotheses, a way that is not only powerful, but, in our opinion, also beautiful.

Many discoveries that we read about came out of projects that were originally devised as fishing expeditions or that turned into such after the original hypothesis had to be abandoned. But we rarely hear about this historical aspect, because a tale about a logically made hypothesis and then tested in rigorous day science makes for a much better story and because these are the kind of stories that editors and reviewers like to read. We know this from hearsay about many works of valued colleagues, but we know it best from our own publications. For example, Tin Pang assembled a dataset connecting genotypes and phenotypes across the evolution of the E. coli clade, looking for further support for our hypothesis of bacterial evolution through stepwise niche expansion [10]. But analyzing the data, we found something much more interesting [11]: none of the more than 3000 detectable metabolic innovations in the history of E. coli required more than a single horizontal gene transfer! Another project, led by then-graduate student Michal Levin, involved the collection of a gene expression dataset of embryogenesis in 5 species of worms, assembled based on the idea that it might reveal gene regulatory networks. Analyzing the dataset instead led us to find a distinctive developmental stage, which we inferred to be the nematode phylotypic stage [12].

Keep Exploring and Carry On

One thing we have learned from decades of exploratory data analysis: do not give up on a dataset. If it does not support your original hypothesis, it likely contains hints at alternative, possibly even more interesting phenomena. And if the data supports your original hypothesis, still keep exploring beyond. If the dataset has been designed and assembled well, there are likely additional discoveries to be made. These cannot be expected to emerge after just a first look. They will take time to unfold. It is not well appreciated, but the truth is that one never really finishes to analyze a dataset. You just decide to stop and move on at some point, leaving some things undiscovered. Because night science demands a highly creative state, it is not surprising that this process mirrors the situation in the arts as described by the poet Paul Valéry in 1933: “un ouvrage n’est jamais achevé . . . mais abandonné” (“a work is never finished, only abandoned”).

In line with the premise of this article, we of course had to explore our own gorilla experiment dataset beyond our original hypothesis—that hypotheses may prevent discoveries. We indeed found hints at something else: hypotheses may also lead you to give up on your data prematurely. The students who had a hypothesis to test were more than twice as likely to not even attempt the exercise or to give up after the first initial steps. While this difference is not statistically significant (odds ratio = 2.15, P = 0.21, N = 44, Fisher’s exact test), it suggests further day science experiments. Maybe we will keep our students motivated in science by providing more opportunities for data exploration and discovery.

In sum, keep your mind open when working with data. Think about the particular dimensionality of your dataset and study the variation across these. Consider what the variation along these dimensions may reflect, and try to connect that to aspects beyond the dataset. By asking what other dimensions could be integrated to explain the observed variation, you are positioning yourself for a discovery. Let your fantasies run wild to generate classes of hypotheses that would leave traces in the data. There could be gorillas hiding in there.

If you want to share this with anyone, please share the original paper from the authors here.

Have a great week,

Alex

Election Day 2020: Rene Girard, Part 2

Two Truths and a Take, Season 2 Episode 37

What a week it’s been. Here’s something I wrote on Tuesday afternoon, before it all officially kicked off.


A couple years ago when I started this newsletter, the inaugural post was an introduction to René Girard. I’ve been meaning to rewrite it for quite some time. Today - Election Day, 2020 - seemed like a pretty good time to do that. 

In my opinion, Girard’s worldview on mimetic desire, differentiation, and scapegoating is still the best way to understand Trump and the MAGA movement. So I went back and substantially rewrote the original Girard essay. I think this one’s a lot tighter and better, and clarifies some of the misconceptions people had over the last one. Even if you read the last one, I hope this one is valuable to you too.

Wanting is about Being

Last July, I became a parent. Our daughter is now one going on one and a half years old, and it’s been fascinating to watch her become a little person and develop an identity and sense of self. 

Kids are learning machines. The whole world is new to them, and they have to go make sense of it. And kids learn very quickly that the most important thing to pay attention to and learn about is other people. It’s really sweet, but also a little nerve-wracking, when kids start explicitly imitating you. It starts early, when they’re not even a year old. Kids want what what you have, and want to do what you’re doing. 

This hard-wired desire to imitate is deeper than any given object, or any given behaviour they’re trying to copy. We’re relentlessly amused when our kid takes pretend sips of our coffee mug in the morning and then fake smacks her lips and goes “aaaaaah”, or when we laugh about something that happened in our adult lives, she fake-laughs along with us. (It’s really clear she’s fake-laughing in order to fit in; she’s not a very good liar yet. It’s adorable.) It’s funny, but also quite serious: it’s not about the coffee, or about the joke. She wants to be like us

We have some insight into why this is, neurologically. There’s a mechanism in our brains called mirror neurons that fire when you do or get something that successfully imitates someone else. The more you care about that other person, the harder these circuits will engage. Those neural pathways carve out habits that shape who we become as people; even when our role models aren’t directly around, the behavioural predispositions we’ve acquired from them persist. 

When we grow up, not much changes. Desire isn’t about having, or doing. It’s about being. It’s never really the objects or experiences we’re pursuing; it’s about the role models off of whom we’ve learned that behaviour, and acquired that desire. Girard calls these people the “mediators” or the “models” of our desire. We want whatever they have, and to do whatever they do. It’s never really about the object. 

One way we continually give this away is through our language and word choices. There’s a reason why Terry Malloy in On the Waterfront doesn’t lament “I coulda contended!”; the line is “I coulda been a contender”. VC thought leaders in Silicon Valley don’t want to think contrarily; the want to be contrarian

Advertisers understand this principle: you’re not trying to convince somebody that they want Bud Light or a Ford F150; you’re telling them they ought to desire membership to an aspirational peer set, and the way to become a part of that group is to drink Bud Light and drive an F150. Growing up, I remember thinking it was funny that Abercrombie advertised their clothes with models that weren’t actually wearing any of them. It makes sense; the clothes obviously aren’t the point. 

If you’re trying hard to be cool, you’re not cool

One of the biggest transitions for a kid is when they start going to school and hanging out with other kids, and their peers become role models. Kids learn quickly whether they’re in or out - and they can rewrite their personality and their desires in order to conform to their new aspirational peer set. Like in Mean Girls, when Lindsay Lohan falls under the influence of “the plastics” (the cool girls) and Regina George becomes her role model, her brain goes into overtime rewriting her personality, and what she likes and wants. 

Adults aren’t any different; they just hide it better. Marcel Proust’s masterpiece A La Recherche du Temps Perdu is all about this phenomenon: how our memory of objects and experiences is powerfully and retroactively shaped by the opinions of people who we aspire to imitate. In the book, Proust’s character is on a literal and metaphorical search to rediscover his initial impressions of experiences as he actually perceived them, before those memories became coloured by the mediating influence of others. 

The driving force behind all of this imitation isn’t just the joy and pleasure of successful imitation, it’s also the guilt and shame you experience when you fail your role models, by liking the wrong things or behaving the wrong way. You feel like a loser, or like a bad kid. The problem is, sometimes joining the cool kids involves sacrifices of their own; like doing things explicitly forbidden by your parents, your original role models. You can’t satisfy everyone. 

One of the classic teenage emotions is that feeling of being trapped by all of these different kinds of pressure. That’s why it can feel so good to just throw yourself headfirst into some peer-driven impulse, or alternately to forget the cool kids and do your own thing for a day. For a moment feel this weight get lifted from your shoulders, as you throw off the weight of all your other role models. But that relief is temporary; in all likelihood, you’ll feel differently the next day. 

Guilt accumulates. As it grows, it can turn into anger, and we direct that anger into a variety of different places. We direct it outwards, towards whatever obstacles we see as being in our way. We direct it inwards towards ourselves, for failing to live up to our (often impossibly contradicting!) Role Model aspirations. Eventually, our anger finds its way towards our Role Models themselves. 

That anger comes from an impossible contradiction: the harder we strive to be like them, the more it reinforces that we aren’t. The harder you try, or are seen trying, the more obvious it is that you’re a pretender; an aspirer. Our effort is self-defeating; imitation definitionally is failure. We get caught into a cycle: we resent them for how hard we’re trying and how our effort is self-defeating, which then reinforces the original desire: “you’ll never be like them.” We have a name for this vicious cycle: envy. (Charlie Munger once wisely quipped: “Envy is the stupidest of all the deadly sins, cause it’s the only one you can’t have any fun at.”)

We don’t fight because we’re different; we fight because we’re the same 

So far all of this should seem like common sense. So we’re ready to apply the first key Girardian insight: not all role models are alike. Specifically, role models who are your peers affect you very differently than role models who aren’t. 

Girard establishes an important definition: Internal versus External role models, which he calls “mediators". Internal mediators are your peers. You see them every day, you want to be like them, and you continually compare yourself to them. External mediators, in contrast, are far away from you and are not your peers. Think of role models who are strongly differentiated from you: a popular hero, a king or a president; it could be a role model in your community who you admire from far away; it could be your priest, or even God. What matters is that you are definitively not peers with them. You cannot compare yourself to them because they are fundamentally different from you. 

With internal mediators, imitation definitionally is failure. If you’re trying real hard to imitate your cool peers, then you are definitionally not cool. (If your other peers see you trying, even more so.) The harder you try, the more you fail. But with external mediators, that’s not true. They don’t present that same unescapable contradiction, because they fundamentally aren’t your peers. So there’s no resentment; there’s no envy. It’s a much healthier relationship. 

External mediators inspire you from far away, whereas internal mediators torment you from up close. They pull you in two directions simultaneously: “Be like me, because that is what you want; but also don’t be like me, because the harder you try, the more you expose and embarrass yourself.” This kind of conflict is called a Double Bind: when a role model both compels and punishes you for just trying your best. 

Kids and young teenagers struggle with this double bind out in the open; by the time you reach adulthood, you’ve learned a few strategies. When our role models are distant, we continually praise them and invite comparisons whenever possible. But when our model is close - if they’re our peer, or coworker, neighbour, or even family member - we do the opposite. We try to hide the fact that they’re the model for our admiration and jealousy, while we go about copying them nonetheless. 

As our mimicry intensifies, we progressively go to greater lengths in order to disguise our feelings, and what initially was a feeling of admiration will mutate into envy. We begin to do all sorts of things that seem out of character – attack our model for various reasons; talk behind their back, and try to sabotage them socially. (I had a boss once who compulsively took positions, both personally and professionally, that were the exact opposite of one of his peers that was seen in the community as more successful than he was.) 

One of the classic mistakes I see people make when they think they understand Girard is they run with the phase, “We don’t fight because we’re different; we fight because we’re the same” and interpret that to mean we want the same objects. Again, it is not about the objects of desire. They are transient; they don’t matter. It is about the other person, and the frustrating contradiction of the Double Bind. When you‘re far apart, there is no double bind. We’re just inspired from far away. But the more similar you are, the more you’re setting yourselves up for rivalry.

The fight was so fierce because the stakes were so small

Envy and mimetic frustration are tragic when they go in one direction, but they can morph into dark comedy if your role model peers actually feel the same way about you - which, more often than not, is actually the case. Admiration is often mutual. Or, at least, it starts out that way. 

Simplistic human conflict, like fighting over a mutually desired prize, behaves the way you see in kids’ books or movies: the more important the prize you’re fighting for, the harder you’re going to fight. But a lot of human conflict is the opposite: the smaller the stakes, and the more trivial the differences you’re fighting over, the more bitter and personal the fight gets. 

When you're fighting over something big, the object of the fighting sufficiently justifies the conflict. So you can spend your time thinking and obsessing over it; and when the conflict resolves, it can actually resolve. But when you're fighting over something small, it's not really about the object. It's about your mimetic relationship with your opponent, and the double bind of tension you fall into: the compulsion going after this mimetic achievement, but also the embarrassment of what it reveals about you.

The smaller the stakes involved, the more embarrassing it is for you. Tiny stakes make it really obvious that you’re fighting for your ego, not for the actual stakes. So instead, we construct a narrative and assign a ton of importance to the object we’re fighting over, in order to legitimize the conflict and mask how petty it all is. The smaller the object, the more spiteful your narrative will have to be.

This can turn into a vicious cycle, if both parties feel a similar kind of insecurity, and both feel compelled to stuff more and more significance into this tiny stupid conflict about nothing. The farther you are down the journey of assigning fake importance to a tiny made up conflict, the harder it is to let go. 

These kinds of conflicts are really hard to resolve, because they aren’t over anything. We call them “Shakespearian” conflicts, because he had such a thorough understanding of how they work; Shakespearian conflicts escalate to absurd heights and in strange directions because they’re truly pointless. Girard’s book Theatre of Envy is a great entry point - he takes you through all of these Shakespeare plays you already know, and narrate what’s going on in mimetic terms. 

As Henry Kissinger once put it, describing his time in academia: “The battles were so fierce because the stakes were so small.” The initial stakes being fought over – some trivial object, like desirable desk space in an office or a lawn care dispute among neighbours – are like the tiny grain of sand at the centre of a pearl. Which particular grain of sand seeds the pearl isn’t important. If the conditions for pearl formation are there, sand will be found. 

Ultimately, these kinds of conflicts threaten to spiral out of control. Since they’re not over anything, there’s no possible resolution or compromise that can be made. These fights are strictly symmetric in character; Girard calls them mimetic violence. Historically, mimetic violence between two individuals would often boil over and conclude the only way possible: in a duel to the death. Duels are the inevitable conclusion when neither party will back down, and no compromise is possible because there is no object being fought over that could legitimately coax either party into a truce. An even more dangerous form of mimetic violence is blood feuds: “You killed someone in my family? I’ll kill someone in your family” becomes such a catastrophically dangerous form of tit for tat violence that it could mortally threaten the survival of entire communities. 

Scapegoating

Here’s where Girard takes a turn into some of the material for which he’s most known. He asks us to consider what it’s like to live in a premodern society, without the same kind of justice system we have today. In Girard’s view, mimetic violence was the most dangerous threat to your community if you were living earlier in history: it stems directly from human nature, it naturally magnifies in character (as the sides of each conflict get steadily larger and angrier), and it’s difficult to stop once it gets going. Unlike inter-tribal conflicts, where we fight over actual stakes and can deter conflict by arming ourselves, intra-tribal conflicts have no such recourse: there’s no way to pre-emptively defend against them, because the enemy is you. 

Once mimetic conflict has been seeded and starts to escalate, what are our options to stop it if there is no external, formal justice system? If de-escalation isn’t an option, you have another option: find a scapegoat. Scapegoating is when the community on both sides of the mimetic conflict collectively decides to find an outlet for all the violence. If they can come up with a surrogate victim who can be blamed as “responsible” for the conflict, then they have a rare opportunity to escape the violence. They can end the fighting in one decisive stoke by stating, before everyone, that “the true source of this fighting has been found, and we will kill him.” The community comes together by murdering the scapegoat victim, and symbolically resolve the conflict. 

Who is the victim, and why does the conflict end? First of all, tragically, the victim should ideally be someone neutral to the conflict; therefore someone who is innocent of any real culpability. They have to be neutral, because if the victim were assignable to one side or the other in anybody’s mind, then the violence would simply be interpreted as another salvo in the back-and-forth conflict, which would demand a response just like all the others. 

Second, by assigning responsibility for the conflict to the victim and then killing them, we do two important things. First, we channel all of the violence in the conflict into one person, who is now killed and cannot return violence. Second, we’ve now created credible grounds for violence to cease: “We found the cause of the conflict! And we have stamped it out.” Everyone can now get what they want, which is a peaceful exit while saving face. Except the poor victim, of course, but they can’t respond because they’re dead.

We still do this today, just with character assassination instead. When all else fails, we turn to blame as a conflict resolution mechanism. Finding somebody to blame for all of our problems, and then channeling all of that frustration and resentment into that person, feels really good. When you unload all of this pent up guilt and frustration and violence, it feels like a tremendous release - like a weight getting lifted from your shoulders. 

The problem is, unloading on a scapegoat does not actually resolve any of the underlying mimetic competition. The release is temporary. Without any further levels of sophistication, the initial resentment and conflict will work its way back up again. 

God Save the King

Another important way we defend against mimetic violence is hierarchy. Mimetic violence is fundamentally a product of peer relationships; so if people aren’t peers, and role model relationships pass through an understood hierarchy rather than across a flat playing field, then you should see less mimetic conflict. You’re a lot more jealous of your neighbour than you are of the king. 

We can think of hierarchies as trading one kind of justice for another kind of justice: hierarchies may not fit well with our modern ideals of fairness or equality, but they are generally successful at establishing differentiation that suppresses mimetic violence. They work especially well if they are “natural”, rather than meritorious. With royalty, for example, the source of the King’s power and differentiation cannot be earned in a typical sense – if it were, then the King would be your peer, albeit a more successful one than you. Kings are not CEOs. The power structure of the hierarchy needs to come from something else – either from the divine, from dynasty, or otherwise from the faraway. 

Kings reinforce their power is through taboos. The King is only the King if everyone believes they’re the King. So one way they reinforce that is by deliberately breaking very specific, sacred rules that no one else is allowed to break, unless you’re the king, in which case you can do it. And then every time you do, it just reinforces, over and over again; they’re the King, not you.

Silicon Valley startups have learned this lesson. CEOs, who are promoted into their titles and earn their power by working their way up to it, are in many ways less effective than founders, who rule their companies as if by divine right. Founders are differentiated from their employees to an absolute degree: the title of ‘founder’ can never be earned or seized the way CEO can, and can be wielded as an invitation to break almost any kind of rule - so long as you maintain the blessing of the priesthood (the VCs) who bestow you that divine power.

Religion is the ultimate source of hierarchy. There is no role model more powerful, more virtuous, or more far away than God. God is not your peer. Nor are the priests, nor is the king (whose power is granted through the clergy). All of these non-peer relationships establish distance and differentiation. Here we reach the real meat of Girard’s body of work, which concerns the roles and purposes of religion. To Girard, early human religion evolved as a necessary, inevitable and successful defence against jealousy and mimetic rivalry within communities. His book Violence and the Sacred is all about this evolution.

One particularly gruesome but widely prevalent way that early religious institutions suppressed mimetic violence was through human sacrifice. Human sacrifice as a religious rite came in many different forms across prehistoric religions, but they all seem to have a basic structure in common. The rites begin by acknowledging undifferentiation and “sameness” within the community as the source of problems. Then, it channels those problems ritualistically into a sacrificial victim, who is scapegoated as the cause and answer for their problems, but then paradoxically praised and hailed - almost like a temporary God - as the sacrificial path to reconciliation. Upon killing the victim, the community celebrates the return of “differentiation”. 

These practices might seem barbaric, but we go through the exact same motions today in communities like Silicon Valley. When once-promising startups succumb to competition, on the day they formally shut down we perform an elaborate series of rites that formally “sacrifice” the company and ritualistically fend off “undifferentiated competition” as a common enemy. The founder, formerly God-King, because God-King-Sacrifice; we praise them with a nearly-religious level of devotion, while symbolically burying their company. We ritualistically strip the startup of every differentiating feature (leaving behind only “This company, who raised 80 million dollars), as if we were ritualistically killing competition itself. To conclude, the community solemnly pronounces, to complete the ritual: Silicon Valley is a place where we celebrate failure. 

Things hidden since the foundation of the world

The problem with ritual sacrifice and with scapegoating in general, again, is that it doesn’t actually resolve the conflict. It may bring peace, but only temporarily. The source of the conflict is still there; it’s just been placated for a little while. But it’ll come back. 

The Christian Bible covers this subject pretty extensively. From the very beginning, Adam and Eve are cast out of the Garden of Eden – for doing what, exactly? For eating fruit from the Tree of Knowledge, which is the one thing they’re not supposed to touch. Knowledge of what, though? It’s often written as “knowledge of good and evil”, although Evil is left to further interpretation. But the answer is revealed in the very first thing that Adam and Eve do upon eating the fruit: they realize that they are naked, feel embarrassed, and cover themselves. 

Knowledge of “Good and Evil” is really knowledge of Self and Other. The moment that they discover their nakedness is the moment they discover an opinion they care about other than God’s, and they realize they have peers to impress. The Original Sin established at the beginning of the Old Testament is the seed of our subsequent bad behaviour: pride, shame, envy, and the other components of mimetic conflict. What happens next? Upon being expelled from Eden, the first thing that happens is the rivalry between the sons Cain and Abel, where Cain initially admires his brother, but eventually becomes resentful of him and is ultimately driven to murder. 

Remember, Girard would remind you, that at the time these texts were written and transcribed mimetic conflict was most likely a top-of-mind concern. In the time of the Old Testament we were still in a world where early beliefs, with their practices around scapegoating and human sacrifice, were pretty common. By the time of the New Testament, the Romans had codified together a sophisticated justice system, and a more “modern” world was being built where primitive fears around mimetic violence were mostly buried and covered up by society. But that doesn’t mean those same instincts and urges weren’t there. 

As the Bible puts it in so many ways, the Devil acts through making us conscious of the Other, and making us feel the frustration, guilt and anger of peer pressure. A modern civilization like Rome, at the time of the writing of the New Testament, had evolved a sophisticated justice system and social structure that masked these original impulses and violent trends. But they’re still there; just buried - and because they’re out of sight, we understand them less well than we used to

Girard’s interpretation of the New Testament is laid out in his most challenging book, Things Hidden Since the Foundation of the World. The title references a passage where Jesus tells us, “I am here to reveal things hidden since the foundation of the world”; in other words, something we used to understand but have now forgotten. We’re told, in Girard’s narrative: at the beginning of human history, we understood that the nature of evil lies in knowledge of the Other. The Devil acts on us through our peers; the only way to overcome evil is through God (the one, true external mediator), and through Jesus sacrificing himself as one, last scapegoat to finally, permanently, put an end to Original Sin.

The great human temptation is to think we can conquer evil ourselves, without God’s help. But we cannot. If we try, we only end up redirecting that evil and violence through blame and scapegoating - which cannot destroy evil, only hide it temporarily. As society gets more and more sophisticated, we get better at denying the presence of evil, and pretending it isn’t there, while it continually grows stronger.

In Revelations, the final chapter of the New Testament, we get a warning: “In the future, an Antichrist will come who brings a promise: we can all be role models for one another, and we can all live in harmony together.” The Antichrist promises us that the answer for how to be and what to want can be found in one another. Revelations is a warning to reject this: the more we turn to each other for answers rather than to God, the more we are inviting evil, and setting ourselves up for a future where everyone is each other’s peer, everyone becomes a model, and everyone becomes a scapegoat. 

Sound familiar?

Let America Discriminate Again

Four years ago, Trump was elected as possibly the first truly Girardian president. 

He is an incredible study in contradictions; but probably none of them have perplexed people as much as his administration’s single-minded pursuit of a remarkably Catholic agenda. There is an obsession in his administration about differentiation. It is the most compelling common thread between anti-political correctness, nationalist anti-immigration policy, the restoration of archaic gender roles, an interventionist approach to free enterprise, the strange obsession with naming things and with neoclassical aesthetics, a total abdication of responsibility from some consequences, and total enforcement of others. It is reactionary, to be sure. But to what exactly? 

The common thread of the Trump appeal is that it is a complete and total counter-reaction to undifferentiation. Trumpism rejects the last couple decades of policy and rhetoric that have advanced, more or less, the agenda that “everybody is equal and the government is going to actively make sure that everyone is treated the same.” Trumpism is a rejection of the ideal that we are and ought to be undifferentiated.

This is a very Girardian mindset. It is also a rather Catholic mindset, in an odd but important way: everything about the movement enshrines this idea that differentiation is important, not for any specific reason; just absolutely. Trump is absolutely differentiated from everyone else, both in his metaphorical un-cancellability and in the literal wall he’s built around the White House. He is the perfect satirical caricature of an External Mediator. He flaunts every sacred taboo; his toilet is made of gold. Meanwhile in his policy, “Equal protection” is absolutely rejected. The notion that “everyone is each other’s peer”, again, absolutely rejected. (Notably, the two people that will shape his presidency most for years after he’s gone are Bill Barr, his attorney general, and Amy Coney Barrett; both are Catholic.) 

Make America Great Again, interpreted rather straightforwardly, really meant "Let America Discriminate Again.” It means, “Bring differentiation back to America. Bring America back to a time and place where we didn’t have this top-down enforcement of ‘everyone is the same’”. I think if you asked a lot of people if what they genuinely meant by MAGA is “Make America more explicitly discriminatory again”, they’d say some version of: "Undifferentiation is dangerous.”

That message is really compelling, if for no other reason than it offers a release from the crushing set of peer expectations we experience in Progressive America. We live in a world full of problems, complexity, and intertwined guilt. It is truly hard for anyone to actually live up to the peer ideals we aspire to today. We’re supposed to feel guilty about global warming, and aspire to meet a peer standard of carbon-neutrality. We’re supposed to feel guilty about social justice, and aspire to meet a peer standard of active allyship. 

All of these causes and expectations are for real, important problems in the world. But people are weak, we get exhausted, our good intentions are compulsively twisted into Blue Check Mark performances, and that exhaustion makes us turn on each other for the smallest things. It’s no wonder that the Trump opposition seems so fractured, and so tired all the time. The stakes inside the movement are so small - all things considered - but that’s why the infighting is so fierce.

The MAGA crowd, in contrast, is pretty much united. The heart of Trump’s appeal is that he offers a release. When you hear something like "Trump is our salvation" spoken un-ironically, it speaks to that release. The Trump 2020 slogan might as well be, “Give up, let it go. Be free.” To quite a few of us, that’s just desperately what we want. 

He’s an outlet for all of our stored up anger and frustration, at ourselves and at everyone around us, wrapped up as an invitation to have fun, almost like a practical joke. Trump offers a rhetorical, even satirical, playground where you can shout nonsense slogans like “Obama is the Antichrist!”, but then back it up with an administration who might actually believe that the last president, who fought very specifically for that idea that we could inspire each other as peers to overcome evil as a community, might, you know, be saying something oddly close to what Revelations talked about.

If you don't understand what Trumpism is, like what it really is, it's going to stick around.

Anyway, we’ll see what happens tonight. Fingers crossed, everybody. 


I’m sure the last thing you want to read is more actually serious stuff right now, so instead, here is something better:

An oral history of Marge Vs. the Monorail, the episode that changed The Simpsons | Sean Cole, Vice

Have a great week,

Alex

Tune in today at 2 PM EST / 11 PST

Two Truths and a Take, Season 2, Streaming Party 1

Hi everyone,

No newsletter this week (sorry), but in exchange you can tune into something even better: a group get-together streaming party this afternoon with me, Eugene Wei, Julie Young and Julian Lehr, hosted by Mario Gabriele of The Generalist (which you should subscribe to if you haven’t already).

I have no idea what this is going to be like, except that it’s going to be an enormous amount of fun. As of a few days ago there were 500 people signed up, and you should too. It’s from 2-3 PM Eastern / 11-noon PST and with the extra hour tonight you have no excuse not to attend; spend that extra hour on this.

Register

In the meantime, if you didn’t catch it a few weeks back you can read a very fun interview with me, Eugene and Julie here.

The kids are alright: an interview with Eugene Wei and Julie Young (Gift Culture, Part 4) | alexdanco.com

See you there!

Alex

Six lessons from six months at Shopify

Two Truths and a Take, Season 2 Episode 36

I’m now six months into Shopify.

So far it’s going basically on schedule: as I was told, “Your first couple months you’re going to have zero idea what’s going on. Then around month three you’ll come up for air and think, ok, I got this; and then you’ll try to start doing stuff. Then you’ll really struggle, because you won’t be in that happy new float-around-and-learn-people’s-names mode, you’ll be in oh-shit-can-I-really-do-this mode. It’s actually a little scary. But then around month five or six, you start to actually figure some things out for real. And then it starts to feel fun.”

So far it’s gone pretty much exactly to plan. But it’s starting to get fun. So this week I’m sharing six things I’ve learned in my first six months; some of them about working for a big company in general, and some about Shopify specifically. I hope they’re helpful. 


  1. Job number one

In my first week at Shopify, I had a bunch of meet-and-greet conversations with people around the org and one of them really stuck with me. It was a conversation with a GM for somewhere else in the company, and I asked him, hey, what advice do you have for me in my first year? Here’s what he told me:

“In your first 6 months here, here is your number one job. Familiarize yourself with the dozen senior people at Shopify who have the final call on really important decisions, from Tobi and Harley on down. You need to familiarize yourself with their operating philosophy around business and around how Shopify works. Go consume every written memo and every podcast episode (we have a great internal podcast called Context) they’ve ever done, get inside their heads, learn their perspectives and their preferences, and learn what gets them to say Yes to things

“Here’s why this is your most important job. In your first six months, you’re gonna be useless anyways. You’re going to be drowning in new information and context and it’ll take you a few months to learn how to swim. But then once you do, you need to become effective. And in order to be effective, you need to know how to get those people to say Yes to things, and how they would think through a decision down to a detailed level. If you can do that, then you can get basically anything you want done. If you can’t do that, then you’re never going to get anything done. Therefore, this is your most important job right now.”

I remember thinking at the time, wow, that sounds like really important advice, I should listen. And I did put in some effort; not nearly enough, in retrospect, but more than zero. Now, six months in, I’m not nearly at a point where I would consider myself “effective” yet - I still have a long way to go in that department. But that advice is paying huge dividends already; not only with my own initiatives but actually more so with helping other groups with theirs. 

When you’re in a company full of smart people, like Shopify, it can often be quite tricky to resolve disagreements and impasses with, say, product decisions - because the conflicting opinions all have a lot of merit. So I’ve found it very helpful to be able to bring to the table: “Here is how I think ____ would look at this problem, from their perspective and their philosophy. It’s a pretty different POV from how we’ve been talking about it so far, so hopefully that added perspective helps us get unstuck, since they’re ultimately the person who has to say Yes here.”  

Moreover, it’s not like we only care about their opinions because they are decision-makers; this isn't really advice about relationship-building. It's advice about how to think better. Great leaders are right, a lot. They know things. So having their operating philosophy available on-demand, or even a rough approximation of it, can be really useful in moving the ball forward and getting teams aligned around the best possible decision.

  1. Conway’s Law

Conway’s Law, if you don’t know it, is usually summed up in the famous phrase: “You ship your org chart.” The original wording from Melvin Conway goes: “Any organization that designs a system (defined broadly) will produce a design whose structure is a copy of the organization’s communication system.” (Eric S. Raymond helpfully elaborated: “If you have four groups working on a compiler, you’ll get a 4-pass compiler.”)

I’ve known about this concept for a while, I’ve probably repeated it to try and sound smart in conversations, but I never really understood it until joining a large organization.  

Think about any complex product you like - it could be your phone, your car, a public transit system; whatever. That product is composed of many different parts, and sub parts, all the way down to tiny little atomic units that feel like indivisible “chunks” of product. Conway’s law is an observation about the contours of those chunks of product. 

Each individual chunk of product was probably built and shipped by one specific team, who worked together closely and understood each other well. Within that team (think of Amazon’s famous “two pizza teams”), everyone knows each other, and communication flows easily. So the final product that gets shipped by that team will feel like a unified, cohesive, harmonious chunk. You won’t be able to tell that one employee worked on one half and another employee on the other half; it feels like one piece.

But the boundary between that product and an adjacent product - let’s say, between a car door versus the car handle - will be between two internal teams that don’t communicate as easily with one another. Those communication barriers, even when they’re small, shape the contours of the final product that gets shipped. If two teams work side-by-side and speak daily, then the contours between their adjacent products might feel small. But if they rarely speak, or have different product or design principles, or are “far apart” for whatever reason, then the boundaries between the products will feel disjointed and bolted together. 

In an ideal world, everybody would communicate perfectly with everyone. But that's just not practically possible. In a large organization, there are necessarily going to be teams you don't talk to as much. So your organizational design, which imposes a kind of topographic map for communication, matters a lot: it'll shape what products get built, and how, before the product even starts getting brainstormed.

That’s one half of “you ship your org chart”: boundaries between chunks of product mirror communication boundaries inside the org. But there’s a second part, too: not all product teams are able to advocate equally. There are power differences between groups. So the final structure of a product won’t just reflect the boundaries of the teams; it’ll reflect the relative influence those teams in getting their products shipped. Power is, in of itself, a form of communication: in large systems, the meaning of a communication is the behaviour that results. If the system said it happened, then it happened. That system behaviour manifests in the form of the product as it’s made: teams ship what they’re empowered to ship, but their output often finds itself looking a lot like the same hierarchy that went in. 

  1. Partnerships

One particularly inspiring project I’ve been working on over the last month is our newly announced partnership with Operation HOPE to help start 1,000,000 new Black-owned businesses over the next decade. It’s a really great project to help get off the ground, and now the hard work is starting to get it to real success over the long term. 

Working on this project was the first time I’ve ever really interacted with an outside organization from inside Shopify. And it gave me some insight into something I was told a long time ago: “if you’re a startup, try not to waste your time talking to big companies unless you’re doing it deliberately. They have an absolutely endless capacity to consume your time with meetings.” I’m not sure I really understood why at the time. 

But it’s clear to me now how this happens. And not because our current partnership is going badly by any means - we’re still in the early stages of getting a lasting framework in place that will help the partnership succeed over ten years, but we’re making progress and I’m feeling optimistic with how things are going. But even so, I can see firsthand how complexities and potential liabilities, once you introduce them into an environment like the inside of a company, can rapidly metastasize and create more of themselves. 

The art of getting these partnerships right is really solution architecture: making sure from the very beginning that someone who understands every piece involved can get them lined up right, and interacting the right way, from the very outset of the project. If you don’t get that person immediately, what happens is that people who don’t understand every piece (like me, currently, I’m afraid) start “solutioneering” to make forward progress quickly. 

This creates more problems, which often kicks things back to the partner company to straighten out: what are your requirements again? How do you need that workflow to go? And since they won’t understand your architecture problem you’re dealing with internally, they’ll just give you straightforward answers about what they want - without really understanding the degrees of freedom available to fix the problem.

Unless you really fix things quickly, the interface between your two companies (and the mechanics on both sides) just compound with problems on both sides, and never get really fixed - just patched over and over. All the while, this creates meeting after meeting as new groups get pulled in, but never really solving the real problem, which was an initially misunderstood problem or misapplied architecture. (Fortunately, this isn’t happening yet - as far as I can tell - with our project with Operation HOPE so far! But I’ve felt some degree of painful self-awareness as, in an effort to be helpful and move the ball forward, some of my “help” may just be creating net more meetings for everybody. It’s something I’m trying to keep in mind, anyway.) 

  1. Canada & the impact of being in a secondary market

Five years ago when I was starting at Social Capital, I remember an ongoing debate over what tech company would grow into the next $100 billion market cap firm, and retroactively define what that “era” of tech was all about in hindsight. So obviously Uber and Airbnb came up a lot (“this era of tech is about the networking of assets”), Snap (“This era of tech is about images and video taking over as the new default internet format”), we obviously hoped for Slack (“This era of tech is about the future of knowledge work”). 

No one really mentioned payments or commerce. PayPal or Stripe never came up in those discussions, that I can recall. And certainly no one ever mentioned Shopify. (Except one person. He’s doing really well now.) 

Until recently, no one really knew about Shopify. We were just quietly up there in Canada, helping merchants make websites, as far as anyone in Silicon Valley could tell. Not a lot of Tech Twitter, not a lot of hype. Until one day, everyone knew who we were, everyone suddenly figured out that we’re an entrepreneurship company, not a website company, and “Shopify for X” became a Demo Day trope. 

There have been several profound consequences of Shopify being a Canadian company, tucked out of the way in Ottawa (and then Montreal, Toronto, Waterloo…) and not in the Silicon Valley limelight. The most important consequences have to do with people. 

The first impact is on employee retention. Shopify never competed in the never-ending war for Silicon Valley product and engineering talent, where average employee tenure at some companies is under two years (!) and employees work for a portfolio of high-growth companies over their best years, not just commit to one. Instead, the common complaint about Shopify up here in Canada is that all the good tech talent comes to work here, and then never leaves. There’s a virtuous feedback cycle at work: since Shopify can count on you staying for longer than your average tech company can, they can invest more into you when you start. Reciprocally, having everyone get more up-front investment and more context and tenure means that you can make a lot tactical choices in how you work that people really like, and makes them stick around. 

The second impact is on what employees do when they’re here, especially product people. In Silicon Valley, if you are a product person, you are probably friends with lots of other product people at other companies and especially with other founders. You are going to feel pressure to live up to, and impress, your peer set. And the ultimate peer set you’re being judged against are successful founders. They are the top of the food chain. 

This peer pressure is a mixed blessing. It’s good in the sense that it promotes more people to start startups. People see founders with status, and ego, and success, and want that too. But it’s bad in that it creates a lot of ego, and big egos aren’t what you want on a team that’s going to stick around for the long run. Shopify doesn’t really have that problem; not because we’re somehow more virtuous or ego-free or anything, but just because the peer set up here in Canada is different. Again, it’s a mixed blessing. We don’t have as many startups or as many wild crazy bets. But it’s great for Shopify, because not only do people stick around, they stick around as team players. That’s valuable. 

  1. The surface area of software is enormous

This is a quick learning but it’s a powerful one: there is so much software. I know this seems like a silly lesson, and that this is something I’ve already had plenty of exposure to. Software markets are huge, we chronically underestimate how big they are, et cetera. But it’s one thing to see all these SaaS businesses and productivity tools as isolated businesses or in market maps; it’s quite another to see all of them inside your Okta portal and realize, oh wow, we use all of these. A lot. 

I forget who said this - someone smart on Twitter - but your mental idea of the software business changes when you realize that the primary customer of software is becoming other software. Shopify runs a pretty tight ship, and even we use so many different tools and work products if you look across different teams and job functions. And that’s just the SaaS products - it all sits on top of an immense body of open source code, of which Shopify is a proud contributor. And we’re just one company. Anyway, it’s all so big, and it’s getting bigger at a rate many people who should know better still don’t appreciate.

  1. Compressed Learning

The last lesson I’ll share here it that Shopify takes learning very seriously. Learning isn’t just something that happens at its own pace: some environments for learning work better than others, because they let you practice certain transferrable skill over and over and over again. I’ll leave you with a quote from Tobi (lightly edited) in a podcast interview with Patrick O’Shaughnessy earlier this year

“I’m a card-carrying member of the “video games are actually good” club. I’ve learned so many things in my life through video games. The only reason I learned programming is because I wanted to make changes to the video games I was playing. And obviously not all games are created equal; I tend to point out a few I think are extremely valuable. Factorio is one of those. It’s the one game that anyone at Shopify can expense. Because it’s just bound to be good for Shopify if people play Factorio for a little while. We’re building supply chains for our customers; logistics networks; and Factorio makes a game out of that kind of thinking. And you know what, it’s actually not surprising, cause that kind of thinking is super fun.

It’s fun to say, hey here’s a factory, and that factory needs inputs, and those inputs come out of the ground, and they needs to be producing at the rate it needs to be consumed. I invariably find that this is a very exciting world. I find that video games are getting a little bit more mature; I mean, sure, I enjoy a good game of Call of Duty every once in a while, but we understand why those our popular; building a supply chain is a little less obvious. But then you play this particular game, and it’ll suck you in. And your brain will have pathways that will light up in many, many more situations than you can imagine. 

The tl;dr of why I think video games are good is because of transfer learning. There’s a good book called The Talent Code that talks about this. There was a famous story about people analyzing why Brazilians became so much better at soccer than anyone else. And there were many reasons - it’s a system that’s reinforced by all these things - but people hadn’t found the key reinforcing mechanism that made this true.

It turns out, in Brazil there was a culture of playing a pickup game, a version of soccer that was played in a much smaller space and with fewer players. And the players did all the things you need to be good at soccer, but they did them significantly more often, because there was more ball contact per person. Just because that’s a different game than soccer doesn’t mean people won’t learn soccer skills. They had way more ball contact than someone who went through the British system, by the time they entered the Premier league, for instance. 

What are other situations where you can - in a compressed way - practice these skills that you need in the business world? I make strategic decisions, for my job at the company. For most of these strategic decisions, I hope I do well, but I only find out a couple years later. The way I’m doing them is I try to get as much context as I can, and resolve this big multi-stakeholder situation, plus technical abilities, plus future timelines, plus the way the internet will go… How often do I do this in a year? A couple times, maybe once a month? I don’t think so. Major opportunities to bet the company and allocate resources don’t come around that often. 

But if I sit down for an evening of poker, I make these decisions every hand. And then you look at a game like Starcraft, which I think is very good, or Factorio, and in a very compressed, fun environment, follow a certain activity over and over and over again which otherwise comes around only rarely. And doing that will change your mind, and your brain, and help you be prepared for situations you could never predict."

I won’t elaborate into this too much more, so as not to reveal anything I shouldn’t, but applying these principles that Tobi walks through here lead pretty directly to some shockingly effective practices. 

Permalink to this post is here: Six Lessons from Six Months at Shopify | alexdanco.com

Have a great week,

Alex

Covid Kills Inertia: Homeownership Edition

Two Truths and a Take, Season 2 Episode 35

You may have contemplated, or been asked at some point: “How will homeownership and residential real estate change after Covid?” In my experience, most of these discussions become far-fetched hypotheticals about remote work, the role of cities, and other fairly myopic perspectives from the Zoom-Bourgeoisie. 

But there is one specific way where I could see Covid having a pretty significant impact on the way that housing works in specific cities, and on how homeownership works there for regular people.

Homeownership is a peculiar asset class. Most of the time, when we think about assets and why they’re valuable, we think of them in terms of what they enable. When you buy equity shares in a business, commercial real estate, treasury bonds, or other assets, the asset typically derives its value from what it makes possible. More can happen in a world where the asset exists than in a world where it doesn’t. Value is created, the asset captures some of it, and that’s what you’re buying.

But residential real estate is different. When you buy a house on a residential plot, a large part of the value of that house is in what’s not possible, and in what it excludes. Part of the value of your home lies in the zoning laws and building codes that prevent your neighbour from tearing down their house and putting up a bar, or a retail store, or a condo. The value of a good school district isn’t just that your kids get to go to that school; it’s also that other kids don’t. (That’s uncomfortable to say out loud!) The price of residential real estate reflects everything it’s not; and can’t easily become. 

This is why there truly is not a “free market” for housing in the same way there can be for goods and services. The asset you’re buying and selling is entirely a product of the law and regulatory environment that dictates how the asset can be used, how it can’t be used, and how it can be bought and sold.

As a homeowner, you’ve bought a bundle. You get a home, leverage, tax breaks, and most importantly to this discussion, you get friction. You can frame that friction in a positive or a negative light: proponents will argue that you need these rules in place to protect residents from displacement, preserve local social capital, and protect the intangible but undeniable value of neighbourhoods that have accumulated character over time. Opponents see this behaviour as “pulling up the ladder behind you”: once you get into a neighbourhood, residents typically act and vote in ways that support their neighbourhood staying exactly the way it is: opposing more density, multifamily buildings, and especially subsidized housing.

Not all housing works like this, mind you. When you buy a downtown condo, you do not have a whole lot of influence over what happens around you. If you own a rural plot of land, there may not be many rules over what your neighbours can do with theirs. The exclusionary value of residential real estate is most concentrated in where that exclusion is most consequential: 1) single-family zoned neighbourhoods; 2) in fast-growing  or highly unequal cities, where 3) development laws and zoning codes in place are expected to persist

That last part is important: it’s not enough for that exclusion to exist; people need reason to believe that it will continue to exist in the future. In most cities, it’s a pretty safe bet to count on that kind of persistence, because it’s the emergent product of a system of local influence that has evolved over time and accumulated a lot of inertia. 

The simple way to think about that system is as a three-way power relationship between developers, politicians and homeowners: the developers want to do stuff, and homeowners want them to not do that stuff. Politicians influence the compromise through immediate decisions and long-term policies: they want economic growth from development, but they also want votes from the homeowners. Every municipality is a little different in how this triangle relationship has evolved; but once it’s in place, it’s pretty hard to change.

In a world with few building restrictions, you'd expect to see positive feedback relationships around growth: investment spurs more investment. However, in a world where local residents have influential power, you reliably see an offsetting negative feedback force from local opposition: more development (developers trying to change what’s there) creates more resistance from residents as they organize and focus on blocking that change. In most North American cities, those feedback loops are a reliable form of inertia. 

But not everywhere. Toronto is an instructive example for what happens when those inertial forces are disrupted or circumvented. Unlike virtually every other North American city, local elected leaders and planners are not the final arbiter of what gets approved for development. We have an institution called the Ontario Municipal Board, which exists at the level of the province, and has near-total power to override local planning decisions. 

Initially, the OMB was imagined a “development-neutral” entity, not strictly pro- or anti- growth, but meant as an appeals tribunal for specific development decisions. The OMB’s job is to consider all hard evidence brought forward to the hearing, and then make the appropriate decision around whether that development is in the best interest to proceed. In practice, this makes OMB planning decisions easily influenced by developers (who can spend money on planning, expert opinions, and other supporting “evidence”), and hard to influence by homeowners, whose main currency - their votes - isn’t worth much here. 

(Illustration and Copy from this Toronto Star article)

What this means in practice is that, although the OMB does not have the power to actively change local zoning rules, the minute that city zoning decisions get made, developers now have a straightforward path to propose, approve and build the maximum-sized project now permitted. It’s a fairly ham-fisted way of promoting growth, since this tends to overwhelm the subtleties and locally-crafted plans for specific areas, and anger local community members. It also effectively severs the negative feedback loop where homeowners had power to block or mediate individually proposed local developments. 

Instead, homeowners here can only really fight development at a larger scope, like rezoning decisions. But those decisions are years-in-the-making, top-down decisions with momentum behind them than individual development proposals. It’s a lot harder for individual neighbourhood groups to block a rezoning decision than a specific new condo proposal. Consequentially, although Toronto certainly has its share of bone-headed individual development decisions or zoning choices, and we have a well-deserved reputation as a city who continually devours itself, we are nonetheless doing an okay job at the hard and necessary thing we need to do, which is to get the big planning and rezoning decisions done, and build a ton of dense new housing. Still not enough, mind you, but we’re sure trying. 

So what does this have to do with Covid? It’s an instructive example because the OMB severed the local feedback loop usually in place between homeowners and local politicians, moving mediation to different levels of government (the province) and different stages of community engagement (larger-scale zoning decisions, rather than individual developments). And one pattern we’re seeing a lot with Covid - not just with city governments, but anywhere - is that Covid has shaken the inertia out of everything. And a lot of old feedback loops keeping things in place (e.g. the relationship between corporate IT departments, vendors, and consulting firms), which have been held in place under the weight of their own inertia, got shaken out really quickly this year, as people have moved to take advantage of the crisis and advance their goals. 

The Toronto example may be instructive for other cities in the wake of Covid, as cities scramble to put in place new policies that both mitigate - and in some cases, exploit - the unusual situation created by the pandemic. The one common effect that Covid had everywhere is it reset all the inertia. Budgets have changed, priorities have changed, and a lot of city-building projects have gotten fast-tracked as planners and politicians try to seize the moment and advance their priorities. 

One of the laws of systems is that they’re really hard to change once they’re established; but one way they do change is that emergency patches to the system, meant to be temporary, become permanent. I would not at all be surprised if some emergency “patches” we’ve made to city governance, or will make in the coming year, introduce temporary short circuits to the development process - just like the OMB did in Toronto - which find end up becoming permanent. 

When we look forward a few years and ask, “what will be the longest-lasting effect of Covid on homeownership and real estate”, most of the predictions and takes you hear involve people and their preferences: like “People will leave cities when they can work remotely.” But if you ask me, I’ll bet you that the most consequential impact of Covid on homeownership will be the temporary short-circuits and policy circumventions that cities and local governments set up to enact their pandemic agendas. 

In the short term, like the next 3-5 years, this change will probably manifest itself in specific developments, rezoning decisions, and civic projects that could never have advanced before - even more likely if we get a round of fiscal stimulus after the election in November. But in the longer term, Covid’s real legacy for homeownership and residential development may be the temporary patches, circumventing local feedback loops, that become permanent. When they stick around and become permanent, they could really change the balance of power between people, politicians and developers in different local markets - maybe with some unintended effects, like what happened here. 

Permalink to this post is here: Covid kills inertia, homeownership edition | alexdanco.com


Something neat to highlight this week: the VC firm NFX asked their founders what were the most influential or interesting essays on startups and tech over the past year, and one of the essays they selected was my newsletter issue from back in January, Social Capital in Silicon Valley. They then commissioned audio versions, which you can find here if you’d like to listen to it that way:

Social Capital in Silicon Valley: the NFX Founder’s List | Alex Danco

A few more reading links for the week:

Audio’s opportunity and who will capture it | Matthew Ball

Buy now, pay later | Marc Rubenstein

A big Shopify launch: our new wholesale marketplace, Handshake, officially launched earlier this month. For merchants who want a really simple and easy way to buy wholesale that’s interacted directly with your Shopify account, or alternately who want to sell in bulk to other merchants, check out Handshake and please spread the word. 

And finally, this week’s Tweet of the Week, which made me laugh the hardest: (you’ll have to click through and watch the whole video to get the real effect; it’s pretty great)

Have a great week,

Alex


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