Monday, June 19, 2017

Prerequisites for Universal Basic Income

When I hear people talk about UBI, they often paint a picture of a future in which most labor has been automated, from agriculture to shipping to construction to manufacturing. A handful of people can produce everything needed to support the entire population. That handful of people are rewarded handsomely, and the rest of the population lives out their days in leisure, supported by UBI.

Generally speaking, I like that picture. It leaves out important questions, like what the majority of the population does with their time, but that’s a question for another day. It certainly seems silly to have an economy in which most people work jobs they hate, when you could have an economy in which most people don’t need to work at all unless they want to.

On the other hand, that picture depends on very high productivity, driven by very high automation of labor. In the middle ages, it would not have been possible to build this sort of UBI-society, because the vast majority of the population needed to work just to produce enough food to feed everyone. If most people need to work just to keep everyone alive, then no amount of clever distribution is going to create a society of leisure.

But where’s the line? Somewhere between the middle ages and the future, UBI should be possible… but how can we tell whether we’ve passed that line yet? And what happens if we try to institute UBI before crossing that line?

Key Pieces
I sat down at one point and worked out the math for UBI in a very simple model economy. The answer was, in retrospect, pretty intuitive. The key questions are (1) how many people need to work, and (2) what motivates those people to work? Conceptually, the logic goes like this:
  1. Enough people need to work to produce and distribute all the necessary goods needed by the population as a whole. This includes food, housing, medical, military/police, etc.
  2. Extra goods, above and beyond those consumed by the general populace, must be produced in order to incentivize the workers to work. Additional workers are needed to produce these incentive goods. Enough must be produced for both the workers producing necessary goods, and the additional workers who are producing the incentive goods.
The key piece here is that, under UBI, nobody is forced to work - everyone has the option of simply not working, and everyone can live a comfortable life without working. But at the same time, we need some people to work - the economy isn’t 100% automated, and worker productivity isn’t infinite. So we need a positive incentive to convince people to work - people who work must be able to afford some goods which are not available to the populace as a whole, and those goods must be attractive enough to motivate working rather than not working, and the incentive goods must attract enough people to produce both necessary and incentive goods.

Note that the UBI amount is a key variable here. Is the UBI amount set to include internet and cell service? Travel? A car? Every additional good provided to the population as a whole requires more people to work in order to produce that good. On the other hand, every good provided to the population as a whole is one less good to serve as incentive. There has to be things which workers can afford, but non-workers cannot - otherwise there’s no incentive to work. As UBI amount goes up, more workers are needed but fewer people will work. Economically, the more goods covered by the UBI amount, the higher productivity and more automation required in order for that UBI amount to be possible.

Failure Modes
To make these requirements more intuitive, I’ll outline what happens when UBI fails, i.e. when UBI is implemented without meeting the economic prerequisites.

Scenario: One Time Inflation
In this scenario, UBI is set to some fixed dollar amount, sufficient to live comfortably at pre-UBI prices. As soon as UBI is put into effect, most of the population quits their job. Prices skyrocket across the board, reflecting shortages in every good. Wages also skyrocket, with companies desperate to fill positions.

Very quickly, prices on consumer goods increase enough that the UBI amount no longer covers living costs. The population reluctantly returns to work, and the economy basically ends up where it started. Inflation has rendered the UBI amount too small to have a significant impact.

Scenario: Runaway Inflation
In this scenario, UBI is indexed to inflation. As before, everybody quits, prices shoot up, etc. But this time, every few months, the UBI amount jumps up to reflect price growth.

This won’t make a substantive difference. Everybody knows the UBI will increase, so prices stay ahead of it. As before, the economy ends up roughly where it started, except inflation is so high we have to ask Zimbabwe to return our wheelbarrow.

Scenario: Price Controls
In the worst case, price controls are instituted. Now people quit their jobs, don’t go back, and things get very ugly. The economy does not produce enough goods for everyone, and prices cannot adjust, leading to shortages. Food riots are likely.

Political Failure Mode
There’s one more important failure mode, separate from the economic failure modes above. In this case, the economy is capable of supporting UBI, but there’s no politically stable equilibrium.

As before, UBI is set to some fixed amount, sufficient to live comfortably at pre-UBI prices. Lots of people quit their jobs, prices go up, but it’s not a full failure. Enough people still work, and the UBI amount is still enough to live off.

But now a huge chunk of the population has lots of time on their hands and not much to do. Maybe they want to travel, but the UBI amount isn’t enough to travel much. Maybe they want to take classes in music or a language, but the UBI amount won’t cover that either. Maybe they just want to eat out more often.

One way or another, a huge chunk of the population is left with lots of time on their hands, and they’re all going to want more money for something. They may not want more money badly enough to work, or they may not be able to work, but they’ll still vote. So every politician with a hope of winning is going to promise to raise the UBI amount.

It shouldn’t take much imagination to see that, in a country like e.g. the US, the UBI amount is going to increase and keep increasing. Sooner or later, it will cross the threshold, and the economic failure modes discussed above will kick in. Politics will raise the UBI amount, inflation will kick in to effectively lower it, back and forth, back and forth.  That’s a stable equilibrium, and not a terrible one, inflation aside. But it’s only a matter of time before some clever politician tries to outsmart inflation, and the food riots kick in.

I see two solutions where politics won’t likely ruin UBI.

The first is less-ambitious UBI, intended more to replace welfare than to overhaul the economy. In this case, people able to work are generally expected to keep working, and the UBI amount is intentionally limited to a living wage, not intended for comfortable living. The key here is that living off UBI would have to be tight enough that pretty much everyone would prefer to work if they can. This would still need to meet the economic prerequisites, but with most of the population still working, hopefully the political issues wouldn’t be a limiting factor.


The other solution is when automation is so complete that hardly any people are needed. If only a thousand people need to work to support the entire population, then we could plausibly get a thousand people to just volunteer, without needing extra goods to incentivize them. We’re certainly nowhere near that point today - even just looking at food distribution, we’d never get enough volunteers to drive all the big rigs needed. But it’s not out of the question for the future.

Monday, June 12, 2017

Be More Evil

Spoiler warning: significant spoilers for Avengers: Age of Ultron.

The Road to Hell
Everyone thinks of themselves as a hero of the story.

Gandhi thought of himself as a good person. So did Lenin. So has every president of the United States, from Jackson to Lincoln to FDR. Your parents see themselves as good. Your annoying neighbors see themselves as good. Everyone sees themselves as good.

This is a problem.

People tend to model their identity - and their life - after stories. Alas, the tropes which make fun stories are not representative of the real world. People grow up with stories of heroes fighting villains, heroes fighting monsters, heroes fighting alien invaders. In the stories, nine times out of ten the problems are caused by antagonists. So of course, people turn to the real world, and they see problems, and they look for antagonists. They blame society’s problems on the rich, the politicians, the religious, the sinful, etc.

We’re a world full of heroes in search of villains.

What if what we really need is more villains?

Remember that scene in Avengers: Ultron, where Tony and Cap argue about how best to defend the world from invasions by alien armies? Tony argues that Earth has no viable defense against an invasion, and Cap argues that the Avengers can handle it.

Really? Six people? How are six people going to stop an invading army?

“Together”, replies Cap, against a backdrop of dramatic music.

Yeah. Great plan ya got there, Cap. All that togetherness makes for a real solid planetary defense strategy.


But it’s not Cap being a moron that’s notable here. Heroes act that stupid more often than not. What’s really surprising is that one of the good guys - Tony - is not a complete moron. Normally, it would be a villain’s job to point out that six people and some togetherness do not constitute a military defense strategy.

But it’s not a total departure from literary norms - Tony’s unusual common sense is portrayed as a character flaw. Tony overcoming that character flaw is one of the main lines of character development in the film, as well as the following Iron Man III film.

Apparently the only way a superhero is allowed to display real intelligence is as a character flaw.

What’s really alarming about all this, is that these are the stories which people use to model their own identities… and everyone thinks of themselves as a hero. We have a world full of people trying to be Captain America, people who want to save the world by (usually metaphorically) punching villains in the face. If the punching doesn’t work, then maybe we need some more togetherness?

They say politics is the mind-killer, but it’s broader than that. Morality is the mind killer. Everyone is trying to be the hero, and the vast majority of the heroes we see are morons. It’s no surprise that the moment morality comes up, everyone scrambles to grab the idiot ball.

Trolley Problems
In addition to behaving like morons in general, heroes have a contractual obligation to make very poor decisions in certain situations.

Going back to Ultron, there’s a trolley problem near the end of the film. The villain is levitating a mid-size city. Once it gets high enough, the villain plans to drop it, generating a big enough boom to wipe out Europe (or something like that). Tony suggests nuking the whole thing while it’s still near the ground. Cap says “No! There’s civilians in that city, we need to evacuate them!”. Of course, there’s no real doubt for the viewer - everyone knows they’re going to evacuate the city first. When a hero faces a trolley problem, they save the baby and then punch the trolley in the face.

Heroes, in general, are very bad at tradeoffs. Mosquito nets can save a life for something like $5000, but what hero would leave a baby on a train track in order to save a briefcase full of money? It’s hardly surprising that most altruism is so ineffective, when everybody’s trying to mimic heroes who have no idea how to handle tradeoffs.

Planning Ahead
The nature of fiction dictates that protagonists mostly be reactive, rather than proactive.

When the hero sets out to foil the villain’s dastardly plan, they don’t know the plan yet. The plan is a mystery, gradually revealed over the course of the story. It makes for a good story.

The converse would be a hero making a plan. Imagine: the first half of the story consists of the hero running various scenarios and putting backup plans in place for each of them. Finally, the plan actually kicks off, and the second half of the story consists of watching the plan work more or less as outlined earlier.

You know what we call that? A heist story. Funny coincidence, the genre where the protagonists plan things is also the genre where the protagonists are villains.

Heist stories aside, hero plans do not usually make for a good story. At most, they are small in scope, limited to laying a trap for the villain. Villains have plans, heroes try to break them; that’s how the story works.

When people try to act heroic, their first thought is not “you know what we need? A plan!”. Maybe they’ll throw together a small plan to stop their perceived villain, but nobody sits down to write a detailed, quantitative plan to eliminate poverty.

And if someone did write a detailed, quantitative plan to eliminate poverty, they would probably be a villain.

Join the Dark Side
Time for the pitch.

Join the dark side! You’ll immediately receive:
  • 15 IQ points!
  • Special Ability: Make Tradeoffs! (Includes: Resistance to Dutch Book Attacks!)
  • Special Ability: Plan Ahead more than Five Minutes!
… and many other bonuses.

You don’t need to take over the world. You don’t need a secret lair. You just need to ask yourself - what would a villain do? When faced with a problem, you just need to consider the Evil approach.

Even if your goal is world peace, or eliminating poverty. Villainy does not judge you on your aims, only on your methods. Ruthless efficiency, the pursuit of your objective above all else, doing what works - that is what the Dark Side is all about.

So the next time you want to do something about poverty, don’t volunteer at the soup kitchen or march to “spread awareness” or write a scathing facebook post about Bad People. That won’t fix poverty. Instead, do what a villain would do. Sit down and research the problem. Learn the underlying causes. Run the numbers. Make a detailed, quantitative plan. Find a devious way to make people help, whether they want to end poverty or not. If you need resources, acquire them. Make the necessary tradeoffs. And above all, be smart - it’s not about punching Bad People in the face, it’s not about togetherness or love, it’s about achieving the goal.


Ruthlessly.

Wednesday, June 7, 2017

Be More Amoral

Morality Projection
“If everyone cared and nobody cried
If everyone loved and nobody lied
If everyone shared and swallowed their pride
Then we'd see the day when nobody died”
- I have officially sunk to quoting Nickelback

Intuitively, humans tend to think that bad things happen because of bad people. If only everyone were caring and loving and humble and shared with each other, then cancer would be magically cured. Apparently technical issues ranging from cytokine signals to senescence-autophagy choice to drug specificity can all easily be resolved by sufficient loving and sharing.

Of course, it sounds completely stupid when you put it like that, but Nickelback just takes the usual stupidity and stretches it into hyperbole. Ever notice how people think marching in the street will somehow make it easier to cure cancer?

I call this sort of thinking morality projection. People think of the world in terms of Good and Bad: doing Good things will cause everybody to be happier and healthier and generally better off, while doing Bad things will cause everybody to be sadder and die sooner and be generally worse off. Conversely, if people are unhappy, it must be because of Bad People doing Bad things, or at least not enough Good People doing Good things.

This post is about how to avoid morality projection in your own thinking.

Taboo Morality
A few years ago, I decided to taboo all moralizing terms in my own head, just as an experiment for a week. If I caught myself thinking “X is good”, then I had to cross out that thought and replace it with “I would like X” or “X would result in Y, which I would like” or “X would result in Y, which lots of people would like”. Similarly with “X is bad”, or right/wrong, or “should”. Especially “should” - that one was particularly insidious. The goal was not simply to replace morally-flavored words, but to reduce moral concepts down to peoples’ preferences wherever they appeared.

I was shocked by the extent of morality projection in my own head. I was expecting political thoughts to be the main offender, but there was so much more - choices of food, clothing, social interaction, work habits, sleep schedule, financial habits... moralization was hiding everywhere. Everywhere were long-since-absorbed social lessons on the “right” thing to eat or to wear, “good” habits, all the little things one “should” do. All these lessons, absorbed when I was too young to question them, were suddenly thrust back into my awareness and re-examined.

Of course, I also started to notice morality projection in others - and I started to notice myself projecting on others as well. I caught myself thinking of others as “bad” when they engaged in “bad” habits, or ate the “wrong” foods, or didn’t act as they “should”. Even after recognizing the flaws in many of society’s lessons, it’s still hard to adjust your standards of others accordingly.

Halfway through the week, I knew this experiment had to become permanent. Turns out, a large chunk of the little things society teaches us are either pointless, situational, or just plain counterproductive.

I’m not going to write out a long list here, because people will just argue with it. When you’ve been trained from childhood to view some foods as good and others as bad, some habits as good and others as bad, and so forth, challenges to that worldview just trigger cached responses. I bet most of the people reading this got fired up when I criticized marching for cancer, for instance.

So I’ll just say this: try it. Just try it for a week. Taboo all the little “good” and “bad” and “should” thoughts, ask yourself whether each little thing actually achieves something you want.

Here are some examples to start off:
  • “X is a good idea” -> “X would make it easier to achieve goal Y”
  • “X is bad” -> “X would make lots of people unhappy”
  • “I should do X” -> “X would make it easier to achieve goal Y”
  • “I should do X” -> “X would make it easier to achieve lots of my goals”
  • “I should do X” -> “If I don’t do X, lots of people will be angry at me”
  • “They should do X” -> “If they do X, it will make it easier to achieve goal Y”
  • “They should do X” -> “X needs to be done in order to achieve Y, and it will be easiest for them”
  • “X is healthy” -> “X has high vitamin content”
  • “X is polite” -> “X avoids confrontation”
  • “X would be a nice thing to do” -> “X would make someone feel happy, which is something I want”
In general, replace anything that conveys a positive feeling without a specific physical interpretation. Words like “good”, “should”, “healthy”, “polite”, “nice”, etc all feel positive, but don’t mean anything specific. Phrases like “I want” or “they want” are fine, emotions are fine, anything with a specific physical meaning is fine.

One final note. Some clever person is bound to say “Why don’t we just define ‘good’ as whatever makes people happier/live longer/generally better off?” That is a perfectly decent definition of “good”, but it doesn’t necessarily have anything to do with any of the things we usually consider “good” or otherwise virtuous. So you’re welcome to define good that way, but you’ll still need to go through and check that all the things we usually think of as “good” meet the new definition… and that’s going to be a lot harder with an overloaded word floating around.

Wednesday, May 31, 2017

Economics of College Cost

This post builds on two prior posts. However, this post can be read standalone, especially if you're more interested in the conclusions than in the data. Quick recap:
  • The question is why the cost of college has risen much faster than inflation for almost 40 years, with relatively little increase in quality.
  • There’s really two questions in there. First, there’s an accounting question: where is all the extra money going? Second, there’s an economics question: knowing where the extra money is going, why is it going there?
  • The first post addressed the accounting part, mainly using data on 4-year private nonprofit colleges from the Digest of Education Statistics, running from 1999-2013.
  • A large mismatch between sticker-price tuition and tuition revenue confirms what private college students know: sticker price isn’t what’s actually charged. Real tuition charges have grown at about half the rate of sticker price, although that’s still after adjusting for inflation.
  • All the extra tuition money has gone to paying faculty and staff. The growth in per-student expenditure is mostly driven by decreasing student/faculty (and probably student/staff) ratio. Faculty salary has also increased a bit faster than inflation.
  • Based on some quick statistics on Berkeley’s old course catalogues, the extra faculty per student are fueling a cambrian explosion in academic courses.
So we have a pretty good idea of where all the extra money is going: students today face a much wider buffet of course options, which requires more faculty per student. That’s the “what?” part. This post tackles the “why?” part, moving our view from trees to forest.

Our main driving question is this: why doesn’t somebody just set up a college that teaches roughly the same courses as back in the 70’s, with roughly the same student/faculty ratio, and charge half as much as the rest of today’s colleges?

There’s a few pieces to the puzzle.

Signalling
We’ll start with the low-hanging fruit. College education is the textbook example of signalling - the game theory text at the foot of my bed spends the first half of the signalling chapter just on that. The standard education signalling game won’t provide all the pieces we need, but it will provide the main framework for reasoning about the problem.

Here’s the usual setup: we have two players, an employer and a prospective worker. For simplicity, there are two types of workers: high value workers (more intelligent, more diligent, follow directions, whatever) and low value workers (opposite of all that). All else equal, the employer would rather hire a high value worker than a low value worker, but it’s hard to tell them apart in interviews. It’s not like the employer can just ask “hey, are you smart and diligent?” because everybody will just say yes.

What the high value workers really want is some way to signal to the employer that they’re high value. That’s where college comes in: obtaining a degree is a lot easier for people who are more intelligent, more diligent, follow directions, etc. So the high value workers go get a degree, and now the employer can tell high value workers apart from low value workers by asking whether they have a degree. Since the employer wants high value workers more, they get offered more money.

Of course, this is the dramatically over-simplified version. Pick up a game theory textbook if you want to build up a more realistic model.

Framework
The signalling model of education quickly leads into a general framework.

From an economic standpoint, the primary function of post-secondary education is filtration. Ever wondered why so many people pay so much money for a college education, when the vast majority of the material they learn is never used in the workplace? Well, there’s your answer: the things learned aren’t relevant. The main economic purpose of higher education is not to acquire knowledge, but to signal intelligence/diligence/direction-following/etc.

This is hardly novel; it’s the default assumption among the small portion of education researchers who actually bother with statistics. Researchers tend to focus more on high school than college, but the same idea applies: education isn’t about learning, it’s about filtering.

There’s an endless stream of idiots in education research saying things like “hey look, top-scoring schools all have lots of trees!”. Then the people who bother with statistics say “yes, but if you account for top-scoring schools having higher-scoring students coming in, then the trees don’t have any significant effect.”. Then the idiots ignore them, and go on a big political campaign to spend hundreds of millions of dollars planting more trees at low-scoring schools. Ten years later, lots of low-scoring schools have more trees, and their scores haven’t improved at all.

Anyway, I digress. If you want more details, here’s an entire blog to check out. For our purposes, the takeaway is this: in and of itself, education has very little effect on the sorts of things employers care about. The vast majority of what people learn in college goes unused at work. The economic role of education is not to acquire knowledge, but to filter higher-value workers from lower-value workers.

Furthermore, the difference between “better” and “worse” schools is mainly filtration. Harvard teaches roughly the same material as any state school, but employers pay a premium for Harvard grads because Harvard is pickier in its admissions. This will turn out to be a key piece of the puzzle.

Decoupling
Back to our main problem: why doesn’t someone start a college which teaches roughly the same subjects as the late 1970’s, at half the cost of other colleges today?

One obvious guess is “well, maybe all those new subjects teach new skills which are needed in our ever-diversifying economy”. The signalling framework disagrees, and offers two sanity checks: employers don’t care exactly what you studied, and most of what was covered won’t be used anyway.

But this raises a question. Clearly, academic courses and content have little to do with employer needs. So what does drive courses and content? Why are students so interested in a wild variety of courses that they’re willing to pay double for it?

What do colleges want?
Now for the last key piece: what do colleges want? We’re talking mainly about private nonprofits here, so it’s not like they’re out to make money. College administrators give lip service to all sorts of ideals, but what objectives actually drive their spending?

Well, we mentioned earlier that from an employer’s point of view, the difference between Harvard and a state school is that Harvard graduates higher-quality students on average, mainly by bringing in higher-quality students in the first place. So… what if that’s the main goal driving college behavior? What if colleges are mainly competing to attract and retain the best students?

Intuitively, that makes a lot of sense.

How do colleges attract and retain the best students? Generous scholarships for top students are one obvious approach. The difference between sticker price and actual tuition paid for college isn’t the main focus of this post, but competition for top students explains it neatly.

But what about the cambrian explosion of courses? My guess is that top students are much more likely than average to have specific academic interests. A college which can provide courses tailored to a student’s particular interests will have a major advantage over a college with a few generic courses.

A college adds a handful of courses in a hot new field, and they attract some excited top students. Other colleges catch on, and begin to offer courses in the hot new thing themselves. The cycle repeats. It’s an arms race to attract the best and brightest by offering courses in the hottest new fields.

Summary
Finally, we have a coherent picture. From an economic standpoint, college is about signalling, as we’d expect. Individual colleges are economically incentivized to recruit the best and brightest students they can. Thus the key insight: college is optimized, not for the average students, but for the top students.

And then it makes all sorts of sense.

What do the top students want? Courses tailored to their interests, and a free ride. What do the top students get? Courses tailored to their interests, and a free ride. The economic weirdness of college cost growth - the cambrian explosion in courses, the divergence between actual cost and sticker price - is a result of competition for top students.

Zooming out, why is attracting top students the main de-facto goal of most colleges? The signalling model provides an economic answer. The higher the quality of the students a college attracts, the more employers will eventually pay for those students, and the more the college’s degree is worth.

In short: colleges are economically incentivized to optimize for top students, not average students.

Epilogue
The real point of this whole exercise is not to better understand college cost growth. The real point is that, since we didn’t understand college cost growth, there was probably some key principle missing. By looking at college costs, we hope to dredge up that missing principle, and then generalize it to other domains.

So let’s formulate the key principle more generally.

Suppose there’s some class of signalling goods whose main role is to signal X. Maybe X is wealth, maybe X is virtue, maybe X is intelligence, maybe X is hipness, maybe X is membership in some group. The general principle is: under competition, goods used to signal X will be optimized for people with the highest X, not for their average consumer.

Why? Well, it’s fashion 101. If the cool people do it, everyone else will follow. If the cool people don’t do it, nobody else will either. So, the successful products will be those which optimize for the cool people.

As applied to college, the logic goes like this: colleges which optimize for top students will get the top students. If a college tries to break out and optimize for average students, then they won’t get any top students. Employers will realize this, and will not be very interested in their graduates. Since employers won’t be interested in their graduates, even average students won’t want to attend.

Tuesday, May 23, 2017

User Adoption Energetics

I’m pretty sure this idea isn’t new, but I can’t find another source talking about it directly. I think I got it from a Yudkowsky essay talking about venture investing.

There’s a strong analogy between the rate of a chemical reaction, and the rate at which new users adopt an app.


Chemistry
In chemistry, there’s a standard picture of the energy in a reaction:
Here’s the idea in english. Imagine the chemicals in the reaction as a bunch of balls sitting on the flat part of the curve pictured, right above “reactants”. The big hill, called the energy barrier, keeps them in place. If the big hill were removed, the balls would all roll down to the right, where it says “products”. In physical terms, when a ball crosses the hill and rolls down the other side, it represents a few reactant molecules turning into product molecules.


But the balls don’t just sit there. In real life, there’s heat! It’s like we’re shaking the balls around. Shake hard enough, and they’ll start to bounce up over the hill; the reactants will turn into products. The harder we shake (i.e. the more heat we add), the faster balls will bounce over the hill, and the faster the reactants will turn into products.


But shaking doesn’t just turn reactants into products. Shake enough and, every once in a while, a ball from the product side will bounce back to the reactant side. This is a reverse reaction - products turning back into reactants. If the reactants are much higher in energy than the products, then balls will bounce forward much more than backward. But if the two sides are about even - if reactants and products have about the same energy - then the balls will bounce backward just as often as forward.


Product and UI
We can use exactly the same model for user adoption of a product, e.g. an app.


Now, the balls represent potential users. People on the “reactants” side are not yet users; people on the “products” side have fully adopted the product. In between, there’s a hump - the energy barrier which a potential new user must cross.


Generally, we want to get everyone to adopt our product. In order to make that happen, we need two things.


First, we want to make the energy barrier as low as possible. In other words, make it easy for new users to adopt the product. Things like a steep learning curve or long onboarding flow or upfront cost make the energy barrier higher. A lot of UI design, especially for onboarding, is focused on making that barrier lower.


But the energy barrier is only half the equation. We also need the “products” to have much lower energy than the “reactants”. In other words, our users need to get lots of value out of the product once they’ve adopted it. If the users are about equally happy between using the product or not, or if they’re happier without the product, then they’ll just bounce back to the other side. We’ll see high “churn”, with lots of users leaving.

In chemistry, a strong reaction requires two pieces: low activation energy and a big energy drop. A successful product requires the same two pieces: low activation energy (easy acquisition/onboarding) a big energy drop (value for the user). If either one of those is missing, then the product will not see much use.