A Brief Exploration of the Foundational Selection Mechanics of Quantum Reality

This post is an adapted and expanded version of the the talk of the same name that I presented at RefactorCamp 2019.

The material in this post comes largely from two books: David Deutsch’s The Fabric of Reality and Richard Feynman’s QED. The goal of this blog entry is to introduce you to the Basics Mechanics of our shared reality, starting with Quantum Physics. We’ll do this first with a short introduction to quantum mechanics and then talk about two particular aspects of quantum mechanics — observation and time. Finally, we’ll briefly cover what those two aspects tell us about our lived reality.


To accomplish this, my strategy is two fold. First, I need to convince you that the reality we live in is not a singular universe, but rather a multiverse. In this multiverse, everything that can possibly happen, does.

The next part will be to talk about how we end up experiencing this specific version of reality, of all the universes that are possible. What sort of mechanics does the task of universe selection encompass?

Welcome to the Multiverse

David Deutsch gives us a proof for the multiverse in Fabric, that I’d like to revisit for you here. Before we delve too deeply into it, let’s take a moment to briefly reconsider what a ‘proof’ is exactly, at least in the scientific sense

Generally, a scientific proof is done by setting up an experiment, executing the experiment, observing the results and then drawing some conclusions about the world based on those observations.

  • Set up experiment
  • Run experiment
  • Observe results
  • Draw conclusions

In other words, we derive our understanding of the world from observations that we make of it.

Deutsch’s Proof of Multiverse

David Deutsch’s proof of the multiverse relies on a fairly famous quantum experiment — the double slit experiment. In order to explain it properly, however, we first need to come to some conclusions about the ‘true’ nature of light, particularly at very small quantities.

Namely, at it’s smallest, is light a continuous or a discrete entity? For a human, it’s hard to observe light beneath a certain ‘density’ of beams, so to speak. If we were to set up a light and walk away from it, at some point it would go dark, as the amount of light reaching our retinas would be beneath the threshold required to register as light. For humans, then, light appears continuous. Either we can see it, or we can’t.

Deutsch, however, claims that frogs can see light at its absolute smallest amount. When a frog moves farther and farther away from a light, at some point the light begins to flicker. As the frog continues to move farther away, the flicker grows farther and farther apart. This is because light is a discrete, or discontinuous entity. There are individual photons of light emitted by the light source — the frog can still see them, however the rate at which they hit the frog’s eyes decreases as the distance between it and the source increases.

This ‘thought’ experiment (more like me telling you how it happens) is an illustration of the truth that light, at its very smallest, is discrete. These tiny light particles are called photons.

As an aside, it’s this very discreteness that gives ‘quantum physics’ its name. Quantum mechanics is a movement away from classical (pre-quantum) physics, where all values are continuous, to a quantized or discrete understanding of how individual particles move and interact. The movements of these ‘quanta’ are what quantum physics deals with.

Ok, so we’ve established that light, at its smallest, is a discrete unit. If you spread it out thinly enough, you’ll get a single ‘unit’ or photon of light.

Let’s get back to the double slit experiment now. If you’re already familiar with it, please bear with me as I walk through the setup briefly.

The idea is that you have a solid sheet of metal with two slits cut into it, and a screen (really an array of detectors) set up behind the metal sheet.

If I was to shine a flashlight through the slits, what would you expect to see on the screen? The answer is that you’d expect to see two beams of light that pass through the slits.

Two beams of light passing through the slits

Now, if instead of a beam of light from a flashlight, what if we were to send a single photon through the slits? What would we expect to see then?

Common sense tells us that we could expect to see something similar to the flashlight experiment, except instead of a solid beam of light, it’d be a single flash.

This isn’t what happens. Instead, we see a bar-like pattern of light.

Here’s a more detailed photo, that gives you an idea of what it looks like from a single photon at a time view.

The question is why does what we observe not match up with reality?

One explanation that you might hear is ‘well light is wave-like’, we’re just seeing one of the consequences of its wave-like properties.

This is not a good explanation. It is true that light tends to display results that are easily modeled with equations with waves. But in terms of explanation for what we observe, it’s not very useful.

The problem with this is that we know, from our ‘experiment’ with the frog earlier, that light at its smallest is a discrete unit. In the dual slit experiment, we only send one unit of light through the slits at a time (the bar like pattern above and the illustration both show the expected results from repeating the experiment a lot).

What explains the wave-like pattern that we end up seeing? It appears that something is interfering with the movement of the light particle, something that looks a lot like a wave pattern.

Deutsch tells us that the interference is coming from the single photon that we’ve sent through the slits. That the interference is the photon itself. How can that be? There’s only one photon.

The truth is that the photon runs into itself. If you take the photon and you model all of the possible pathways that it could go through the slits and hit the back screen, you would get an output that looks much like the flashlight shining through the slits.

If you take the photon and you model all of the possible pathways that it could go through the slits and hit the back screen, and then run them all at the same time, and take all of the interference, i.e. places that the possible photon paths cross each other, and let them interact or bounce off of each other, you would get an output that looks much like the bar pattern that we actually observe through repeated attempts of the experiment.

Which is to say, that our observations confirm the model where the photon is interfering with (bouncing off of) itself. We can see the result of this interference in the bar pattern.

To reiterate: the movement of a particle through space interacts with all of its potential pathways through space.

Now, let’s call all of those ‘potential pathways’, as a collection, the multiverse. If you split one off, and just pick one of the collection, one possible version of events that can (and does happen), that one version would be a universe.

Each universe is not equally likely, for example it’s less likely that a photon will intersect itself and end up getting bounced way far away from the light source. In fact, you can see that this is a unlikely event in the bar-pattern photo above, given that those parts aren’t lit up as brightly.

Each of the pathways represent a universe option. We end up experiencing one of them. These different universes interfere with each other, and limit or expand what’s possible across all of them. The conclusion that Deutsch draws from this is that other universes exist and they shape what’s possible in this one, the one that we experience.

Physical reality is not a spacetime. It is a much bigger and more diverse entity, the multiverse

David Deutsch, The Fabric of Reality

In the talk that I gave at RefactorCamp, I gave another illustration of how what we see is the sum of all the possibilities, using a light experiment from Richard Feynman’s book QED. Rather than going through it here, I’d rather show you the results that Feynman gives us from the double slit experiment.


Feynman is less interested in explaining what the double slit experiment means, however he makes a really good case for how the possibility must be present in order for the interference to happen.

If the universe we experience is one from a set of what’s possible, we can limit the chance of which ‘universe’ we’ll experience by limiting what’s possible.

You can see this in the double slit experiment by adding a sensor to each of the slits.

The yellow blocks represent sensors.

Instead of a screen, Feynman wants to know how much light that is sent through the slits will end up at a single sensor on the back screen.

Without the slit sensors, we observe anywhere from 0 – 4% of the light reaching a certain spot on the screen.

Percentage of light reaching D, a detector on the screen, with no sensors on the slits (A and B)

If you turn on both of the sensors, then there is a steady amount of light that reaches the detector on the screen — exactly 2%.

Steady observations when the sensors are activated

Why is this? Well, we said earlier that interference happens between the possible paths of the photons moving through the slits, in every possible universe. When there are sensors placed at the slits, however, suddenly there is only one possible way that the photons could have gone through the slits — the one where the sensor was triggered. By adding an observation to the experiment, we’ve removed possibility. We’ve fixed what universe we’ll end up in from a chance to a steady given. There’s only one way for the light to reach the detector, and the results reflect this fact. Consequently, the interference disappears.

What happens, however, if we were to use a faulty sensor? If sometimes it goes off when a photon moves past it, but sometimes it doesn’t. What would you expect to see?

It turns out that the oscillation of observations flattens out, to exactly match the incidence of the faultiness. The faultier your sensors, the closer the wave will be to the sensor-less version of the experiment; the more reliable the sensors, the flatter the line.

Graph from a sort of faulty sensor

This tells us that observation has an effect on what possible universes we might experience. By making observations about the system, we remove the possibility for interference and narrow the result set.

So what? Why does it matter that there’s a bunch of possible ways that the world might go, and that we end up experiencing one of them?

Well, if every possible version of reality happens, it’s interesting to think about our odds of ending up in any one of them. Further is there a way to expand the set of universes that we might end up in? What about limiting them?

We know that everything that is physically possible happens. And that we might experience a subset of this. Are there any things that definitely happen in all universes that we might experience?


Sure there are. We know them as ‘universal constants’. One such example is ‘c’, the speed that light travels through space at. Feynman tells us that light can (and does) travel faster or slower than ‘c’, but for the sake of calculating probabilities of where and when light will end up, it tends to average out to ‘c’ speed.

In fact, this job of ‘what is generally constant between the universes’ is the realm that physics, as a field, deals with.

Observation and Time

I’d like to propose that there are two mechanisms by which universe selection happens: Observation and Time. What do I mean by ‘universe selection’ though? Well, there’s a set of universes that we might end up in. What might expand the set or reduce that set of possibilities?

Which is to say, I’d propose that time and observation are two mechanisms that have the potential to alter the set of possible universes that are reachable from our present universe.


Let’s talk a bit more about this constant ‘c’. What is ‘c’ exactly? It expresses the rate of movement of a photon of light through space. It tells us how much time will pass as light moves through space.

In some sense, then, time is a boundary for how far that light can move. Like how a pawn’s moves are limited on a chess board, time bounds what’s possible in the next moment.

Time is a boundary, it dictates what’s possible.

What does this time limit tell us about universe selection? As it is impossible for light to travel faster than ‘c’, any universe where a human standing on the moon can instantly know about what has happened here on Earth is not a possible universe that we exist in. It’s not in the set of possible universes.

There is a fun intersection here between time and computer science, as a field, that I’d like to illustrate with your help. I’d like you to solve this math problem using a pen and pad of paper.

Ok. What about this one? Three decimal places should be sufficient.

Now for this last one, go ahead an use a calculator.

Great. Thanks for playing along. You should have noticed a vast difference between how long it took you to solve the problem with a calculator versus the ‘easier’ one with paper and pen.


In Fabric, Deutsch introduces the concept of ‘tractability’. A tractable problem is one who’s answer or solution can be found within a timeframe that renders the answer actionable or usable. A tractable problem is one who’s answer is within reach, which in turn expands the set of possible universes to include one in which the answer to a present quandary is known.

Tractability is an important feature of computer science research. Discussions around ‘runtime’ or ‘big O notation’ are conversations of tractability. In classic computation, this is a counting of the number of steps it will take to reach a solution to a problem, often expressed as a function of the number of inputs to a problem.

What you were doing when you used a calculator to solve a division problem is an example of computational tractability. The computer did as many steps, or possibly more, than you would have to reach an answer, however it did them in a fraction of the time that it would have taken you. It made the solution more tractable.

Our ability to arrive at the answer to solutions more quickly expands the set of possible universes. Computers make problems that were previously intractable, tractable. In doing so, they change what universes are possible.


We’ve already seen how observation can serve to bound what’s in the set of possible universes in the earlier example with the double slit experiment with sensors.

There’s another aspect to observation that I’d like to talk about though, and that’s ‘how observable’ the universe is. Namely, can we observe everything?

What is Observation

First, let’s talk a bit about the history and nature of observation. You may have already noticed the word ‘observation’ or ‘measurement’ appear a few times in this essay. We can observe glass bouncing off a pane of glass. We observe what light passes through slits and arrives on a screen. We can construct experiments and measure the speed of light.

In fact, observation is the root of the enlightened era of scientific discovery. What we know of as ‘Science’ is based on our ability to conjecture, construct experiments, and then measure or observe what happens.

At some point, they added ‘run the experiment a few times’, and then do some statistics. Well, we do live in a provably probabilistic universe. It’s good to check that a result from an experiment wasn’t an outlier or a universe possibility that doesn’t occur very often.

As an aside, I do wonder if this possibility set of universes explains why we require science experiments to be repeatable. Without repetition, it’s possible that the conditions that an experiment were run under existed in one possible universe that is, on a whole, not very likely. Requiring repeatability helps us gain confidence that the result is generalizable across the varying set of possible universes.

Anyway. The process of measuring the results worked all well and good until we reached the quantum level. There, physicists ran into an observational roadblock, called Heisenberg’s Uncertainty Principle.

Heisenberg’s Uncertainty Principle

The general idea is that you have a particle that you would like to measure, or observe. Specifically you would like to know the speed that the particle is traveling and it’s current position.

Physicists discovered, however, that this is physically impossible. It is impossible to observe both the location and momentum of any given particle at the same time.

You can know where a particle is, but you will have no idea where it will be next (as the speed is unknowable). Or you can know how fast it is traveling, but you will have no earthly idea where it is!

This is huge. This is unsettling. Imagine being a scientist in this era, when science was the art of observing things. We believed that we could know everything that there was to know about reality, if only we could observe it. So we set out to build better tools for observing all of the things. And we looked at smaller and smaller particles and eventually we got to a point where we can see the smallest things except, we did some math and we discovered that we cannot actually observe all of the things.

This changed science. This changed what we know about the universe.

There are aspects of reality that are physically impossible for us to know, to observe at least simultaneously.


Which brings us to our next point about observability — there are some aspects of reality that are unknowable. This is classification that Deutsch makes as well.

If I were to roll a dice, cover it up, and then ask you which, of the six possible universes, we ended up in, you could guess and have a 1 in 6 probability of accurately deducing the nature of your present universe. It is easy for us to discover which of the six possible universes that we ended up in — we merely have to uncover the dice. This is an example of an aspect of reality that is knowable but not observed.

An unknowable, unobservable aspect of reality would be both the momentum and position of a subatomic particle. This is unknowable information, largely because it is unobservable.

Observability x Tractability

We can take observability and tractability and make ourselves a 2×2.

The upper left quadrant, of tractable and observable things defines the set of universes that we can predict or expand or contract via finding new answers or making new observations.

We can bring more of the set of universes into this quadrant by building new tools that allow us to measure more things or by improving our computational tools that allow us to make difficult problems tractable.


I’d like to wrap up this discussion of possible universes with a short discussion of these ‘sets of possible universes’ and how we, as humans, relate to them.

I gave a very short talk on ZKP through the lens of quantum rhetoric at the Stanford Blockchain Conference earlier this year and afterwards someone wanted to talk to me about jumping off buildings.

Specifically, they wanted to know that since the multiverse was real and really did exist, wouldn’t they survive if they jumped off of a building?

Sure, they would die in most of the universes that resulted from such an act, but they’d just continue to exist in the one where they didn’t die from the fall. Right?


I would officially like to be the one to tell you that the multiverse offers no such guarantee.

To really drive this point home, I’ve made a Venn diagram illustration that shows the guarantees offered by such a situation. In one bubble stands for the set of possible universes where you jump off of a building. The other is the set of universes where you live to see tomorrow.

Notice how the bubbles do not intersect.

I’m not saying that it’s not possible that you’ll survive a fall. I’m saying that the existence of a multiverse is no guarantee that you will. The multiverse is limited to what’s physically possible! You might jump off of a building where it is physically impossible to survive. Sorry.

Ok, so no guarantee that you will survive a building fall in the multiverse.

But what I think is really powerful about this question, is that it illustrates the marvel that is the mind. Our minds can *imagine* a set of possible universes where you don’t die when you jump off of a building. Here’s a Venn diagram of the universe set that I imagine that man had in mind when he asked about surviving a fall.

Isn’t that pretty wonderful? I think it’s pretty profound that humans are capable of imagining things that aren’t possible.

I think it also tells us something about gossip and online communities and our capacity to build VR and games which have their own internal logic and interesting stuff going on. These things are interesting but ultimately, they are not reality.

Just because you can imagine it or believe it does not mean that it necessarily says anything *real* about our reality. Nor does it necessarily make it part of the set of possible universes!

I’d like to leave you with the following.

There are a lot of possibilities of universes to choose from, or that might possibly, physically exist.

A single photon of light itself contains trillions or more different, potential locations. And our physical reality is constantly changing — this is one of the implications of the second law of thermodynamics, with how particles of matter are constantly pushing themselves towards chaos. This constant movement means that the nature of our particular universe that we have ended up in, presently, is a constant question that we can be asking ourselves.

The task of existing in a multiverse, then, is to discover the nature of the particular universe that you and me and all of us ended up in.

More interestingly, who or what decides what universe we end up in? Is it at all changeable?

I’d like to hear back from you what you find out.

A New Look at Heidegger’s Question Concerning Technology

A year ago, I asked for book recommendations. Nicholas Brysiewicz of the Long Now Foundation, responded with this essay. Now it’s my turn to pass the recommendation on, hopefully in a more readable form.

The Lovitt translation of Heidegger’s essay The Question Concerning Technology is good but we can do better. I spent a good chunk of this year re-writing it to be a bit more readable and pithy. Check it out. (PDF and ePub versions below)

There’s a lot in this essay. I wouldn’t go so far as to call it a ‘foundational text’ for quantum rhetoric, but its perspective on insight, the relationship between technology and the arts, greed, and humanity are very much in line with my thinking about the world at large. I found it an incredibly rewarding read.

Rather than write up a critique of it, I’ve added some of my reader’s notes to the PDF version using Hypothesis. Unfortunately, I think you have to install the Chrome extension to see the notes in context.

I hope you enjoy it as much as I did!

Gervais, Reframed

I’ve been doing more reading of Venkat’s (@vgr) writings as of late, mostly driven by a friend, far more well versed in Ribbonfarm than me, who’s references and worldview I’d like to better understand. I got a copy of The Gervais Principle a few weeks ago, and finally got a chance to dig into it this weekend. 

Briefly, the Gervais principle is an analysis for how human interactions play out in organizations. Venkat’s discussion leans heavily on examples from The Office. In fact, I’d argue that it’s one part organizational theory, two parts literary criticism of the television series. If you’d like to read the whole thing (and I highly recommend it) Venkat has made the entire series of essays available on his Ribbonfarm blog.

I’ve been getting a lot of mileage lately out of the, now long running, realization that there’s often multiple plausible interpretations for any set of human interactions. Communication is layered; human intention is rarely straightforward; it’s a widely acknowledged fact that our brains filter out patterns that make sense to it from the vast actuality of stimuli that occurs at any given time.

What we see is a lossy view of the world. This lossiness gives rise to the plausibility of misunderstanding, of differing valid interpretations.

While the best piece of criticism of the GP comes naturally, from Venkat himself (in an analysis of how other theories of organizational behavior mechanics can be fit into the Gervais Principle’s triangle) what I’d like to do in this post is provide an alternative framing for viewing office politics. I’d like to put a different lens on the view of the organization that the Gervais Principle — a beautiful piece of cinematic crit[1].  The savage imagery of bureacratic interactions belies a dark worldview of organizational machinations, one that I’d argue isn’t necessarily true.


Sociopaths, in their own best interests, knowingly promote over-performing losers into middle-management, groom under-performing losers into sociopaths, and leave the average bare-minimum-effort losers to fend for themselves.

The Gervais Principle, source Ribbonfarm

In the way that only brilliant pieces of writing can, Gervais got under my skin. It’s an insightful, compelling, and, in the case of The Office references at any rate, incredibly predictive. It’s also frustrating, flat, and not very instructive. Most damning of all: I find that I don’t personally fit into the framework. Clearly there’s something missing here.

What Gervais Gets Right

The org chart of any company is messy and illogical. It is true that men who talk to upper management as peers, often get treated and rewarded as peers. (and the corollary, men who talk to upper management as sycophants, often get treated as loyalists). Self-interest is a valuable currency in organizational politics; so is blamelessness and the ability to claim ownership of “successful” projects.

A lot of people who don’t run the company or have the social skills to treat upper management as peers spend most of their time at work making friends and building a reputation for themselves in some unrelated field. Favors get traded at every level of the organization; personal brand and likability are hard currency that can be traded on. Middle managers can be loyal, self-satisfied individuals, a caste of like minded individuals who understand their role in protecting the organization and grooming new members for their ranks. Like understands like.

These are all true, and accurate observations about human social structure. They’re true of large organizations especially. 

Life, from a Different Angle

There’s two ways to view evolution. One, the most widely accepted and talked about in our current age, is through the lens of death. That is, evolution is driven by who survives long enough to pass on their genes to the next generation.

The butterflies with large spots on their wings? They’re ones that fool would be attackers into believing they’re animals, not tasty prey.

Ebola virus? Hasn’t wiped out humanity yet because it kills its host too fast to be able to spread to other humans fast enough.

Evolution isn’t a steady winnowing of the most competitive versus the best camo, however. It’s punctuated, it’s messy, it’s faster and more live than terminal survival. There’s bacteria involved and environment and random gene mutations, and, from at least one scientist’s perspective, cross-species love. It’s not about who eats who, but whom seduces whom.

Likewise, there’s another way to look at office politics. Venkat’s Gervais principle asks us to look at them through the lens of a sociopath: pitting the losers against each other, laughing at the clueless’s devotion to a job when they’re clearly the pawns of the situation. Viewing corporate hierarchy through this lens isn’t wrong, in fact. Much like seeing evolution only through the lens of death, it’s useful and instructive and leads to deep insights about the motivations and attitudes of your coworkers. 

However, it’s not particularly useful for driving change or moving within the structure that you’re surrounded by. Most people who subscribe to a death cult think that the only way out is in a coffin. Similarly, if you believe in evolution and only see movement and change as possible via death, you’re missing the deeper, broader implications of the here, of the now.  If evolution has set and fixed who you are — beta, alpha, omega, sociopath, loser, clueless — then you are stuck to act out the script that your genes established.

If you believe that finding and cultivating clueless people to be your fall men is the only way forward in the org chart, you wouldn’t be wrong. You’d also be limiting yourself into the reality where the only organization you know and see are ones that are the playgrounds of self-interested sociopaths. Perhaps this is a worldview you think you’d enjoy, because in your imagining of it, you’d be the sociopath. The Gervais interpretation is seductive because it explains your, the loser’s, hatred for your middle managers’ apparent idiocy. It excuses your slacker mentality. (Let’s be honest, the middle manager type probably isn’t spending many cycles reading into bureaucratic revenge porn).

This is not to say that there aren’t self-interested sociopaths at work who have developed a coded, aristocratic way of sorting peerage, or that some workers’ attitude and relationship with employment is entirely fixated on the transactional and formulaic (it’s just a job).  But there are other ways to understand these dynamics.

A Classification With Moral Precepts

Personally, I find Jane Jacob’s Guardian vs Commercial syndromes to be quite accurate for understanding organizations, as well as uplifting. Her identification of core values of different mindsets provides a blueprint for understanding the core values of people and social groups. (It’s not all rosy though — the monstrous hybrids truly are monstrous, but for a clear and specific corruption of values.)

A quick mapping, for those of you who are unfamiliar with the syndromes. Jane establishes two guiding value systems (Jane calls them ‘moral precepts’) for human organization: guardians and commercial. Guardians shun trading, seek vengeance, treasure honor, respect hierarchy and value loyalty. Commercial types shun force, compete, value honesty, respect contracts, and collaborate. (You can find the whole list of attributes and values on Wikipedia).

You can sort organizational structures themselves into these categories — ‘commercial’: open source software projects, manufacturing firms; ‘guardian’: the army, sales organizations; and ‘monstrous hybrids’: modern police forces, the mafia.

Although I think that most actors inside of a bureaucracy tend toward the guardian mindset, you can loosely map sociopaths and the clueless (definitely the most clueless) as operating from the guardian mindset; losers tend to float more commercial, depending on the broader industry that the organization is framed within.

Importantly, the guardian/commercial split offers something that the Gervais principle does not: a cohesive framing for understanding the value system of the syndromes. Being able to ascribe a value system to a ‘clueless’ person grants them a dignity that the sociopathic ‘clueless’ label would seek to rob them of.  Loyalty and honor above honesty may not be a value system that I subscribe to, but it is one that I can, albeit grudgingly, acknowledge as valid, and learn to at least respect, if not one that I can personally work within.

In Exitus

I love the Gervais Principle. It’s masterful, it’s insightful, it’s opinionated. Its insights are thrifty, efficient, and honest.

I feel that I haven’t quite lived up to my promise to show a lighter way of viewing self interest, rather I bowed out and pointed you instead towards Jane Jacobs’ syndromes; I’m afraid that a value framework and deep appreciation for the game is all I’ve got to offer.

Appendix: Situating Myself, Gervaically 

Let’s see if I can do it using what I learned from another lossy framework — I’m an early Scorpio with a double helping of Aquarius influence in my rising sign and moon. This maps loosely to a passive-aggressive honest sociopath who fails miserably at working towards my own self-interest. I tend to be employed in organizations at the Loser class. As an organizational operative of the Sociopathic bent however, I find that my principle motivator often leans toward revolution. This manifests itself in either organizing revolt*, in face of the obvious injustices meted down by the actually self-interested, or in doomed attempts at drumming up organizational support for exploring new projects or business ventures.

I tend not to last very long or exist very happily when embedded inside large, dysfunctional organizations, as I find office machinations endlessly fascinating, wholly distracting, and completely rage inducing.

*AMA about the time I successfully organized a lower-class faction at Walmart to (almost) sweep the end of summer intern awards.

[1] As an aside, the Gervais Principle is the best writing I’ve ever seen on my favorite usage of television — as a brilliant foil for the structure of our own reality. It reminds me of a short piece on political lessons from a few TV shows I wrote a few years back, with a more political than organizational bent.

Quantum Rhetoric, An Introduction

Ideas are powerful, particularly ideas that help to shape our understanding of what reality is. Stuart Brand once said that the only real news is the revelations that science brings us about reality. What I’d like to do with this blog is to take a host recent science news and tell you a story about that news. I’d like to build a new framing for how we think about reality, one that’s based in real, solid news from the scientific frontier.

This aim is, by nature, philosophical. The news that I present and the framing for it — none of these things are novel. I’m not the first person to write about the multi world interpretation or to explain how spooky action at a distance has been observed. The framework for thinking about it, isn’t something I’ve seen elsewhere. I’ve been calling it quantum rhetoric. Quantum because it’s rooted in what quantum behavior tells us about the nature of reality; rhetoric because it provides a coherent, rich vocabulary for thinking and conversing and understanding each other and our world.

If physics is the study of the laws that describe the behavior of all things, quantum mechanics is the search for equations that generically describe the actions, movement, and relationships of the smallest, most fundamental particles in existence.

An interesting property has recently been discovered about quantum mechanics. That’s that many things we can know about the minute movements of these tiny particles aren’t fixed, but rather probabilistic. Our modeled understanding of an electron’s movement, for example, used to be simply expressed as a set of concentric rings, each ring representing a different “level” of energy. These rings, in a sense, are a lie. Electrons don’t move in set trackways about a photonic center. Their true location about a nuclei is better expressed as an electron cloud – a map of probabilities that depicts where an electron resides at any given moment. The behavior of the electron isn’t tracked — it’s probabilistic.

It turns out that probabilities are a fundamental property of quantum behavior. Feynman shows that light,its particle wave duality that’s never been fully resolved, at least not at a high school physics level of understanding, is largely a probabilistic process as well. The location that a light beam ends up is but the sum of its probabilities.

There’s some fishiness to these probabilities, however. A fishiness that has long perplexed even the most leading of lights in the physical field. Einstein called it “spooky action”. In many ways, this observed fishiness breaks laws — the speed of light limitation for how fast information can travel, probability itself. You can see this fishiness at work in two ways. David Deutsch, in his book The Fabric of Reality, outlines one such experiment.

The dual slit experiment, as it’s called, involves setting up a screen in front of a light source such that light can pass through two slits in the screen. Light particles are then sent through the screen, one particle at a time, kind of like a ball being thrown between slats in a fence. If the ball was covered in paint and there was a white wall behind the fence, when you throw a single ball, what pattern would you expect to see on the white wall?

The naive, normal physics of everyday things rules would suggest that you’d only see a single mark from the ball, or one shaft of light in the case of light particles. The reality, however, is much stranger. What you end up observing is a wave like interference pattern. One particle was sent, but it appears to be interacting with unseeable and immeasurable other particles, leaving not a single shaft of light on the wall, but instead a wavelike pattern, of interfering ripples.

You can solve this “problem” of waves and get the light beams to act in a rational manner in two ways. First, by closing off one of the slits in the fence. Second, by placing a sensor at one or both of the slit openings, such that you can track with absolute certainty which of the two slits the single light particle passes through. In both of these cases, the light pattern on the wall resolves to a single shaft of light. Something about observing the light passing through the slat seems to “fix” the strange interference problem.

Why? How? These are questions that physicists have some theories about, but as of yet have not been able to settle on a single, unifying framework for understanding why light seems to act like a probabilistic wave in one instance, and a normal “ball” in the other.

Further experimentation has only led to more puzzles of the same type. One such example is entangled particles. What we now call quantum entanglement was most famously observed by two particles being bound in extended unknowablity. The classic entanglement experiment goes as follows.

Take two particles that have been blasted apart by a laser. These particles are known to be spinning in opposite directions, yet which particular particle is spinning left and which spins right, is unknowable at the time that they are split. This state, of being in a joint unknowingness, is called quantum entanglement. The particles are entangled in that their final destiny, left or right, is bound to the fate of the other, yet both are in a state of suspended decision.

This may seem like a strange way to talk about the spin of two particles. If these were balls in an urn, one black and one white, it’d be a simple calculation of probability to figure which ball you might get when pulling one out at random. When you reach in, you have a fifty fifty chance to get the white ball. The same goes for the black ball — fifty fifty. Once you’ve drawn the white ball, you know with absolute certainty that the ball you’ve left behind must be black. So which ball will you get when you pull one out? It’s a toss up.

Entangled particles are like this urn, with a black and a white ball, with one exception. Instead of reaching into the urn, let’s say that you bounce one of these unknown particles through a filter. The filter is set up such that only left-spin particles can pass through it. If we took a ball, while blind folded, from the urn and then threw it to a judge who would accept only white balls, we’d expect the ball to be accepted half of the trials. We’d expect the same for particles passing through a “left only” filter. What actually happens is far stranger. Instead of a fifty percent pass rate, we get one hundred percent. If you change the filter, from a left filter to a right one, your pass rate remains at 100%. The particle that passes through the filter is the right spinning particle and the particle not passed through spins left.

That’s the same as saying I’m going to throw balls at a white judge, and then only drawing white balls. Then you say, ok, I will only throw balls at this black judge, and then proceeding to only draw black balls from the vase. The vase still contains two choices, black or white, but you’ve managed to predict with 100% certainty which ball you will draw based on the type of judge that looks at your ball.

How can these particles manage to spin the correct direction, every time? Are the particles communicating? Are you the luckiest physicist in the world? Einstein was perplexed by these results, so much so that he termed the phrase “spooky action at a distance” to describe how these particles managed to spin exactly opposite yet the correct way for the filter every time.

Every time.

These results of entanglement and the infallibility of the filtering mechanism have been replicated at great distances. The spooky action persists. Are the particles communicating? Are they traveling back in time? How is it that a single physicist can be so lucky, so many times in a row?

If the particles are communicating, physics has a problem. That problem is called the speed of light. Einstein himself showed that nothing, especially not information, can travel faster than this speed. The synchronized behavior of the particles is instantaneous, however. There is no delay between measuring an unknown particle with a “left spin” filter (thus making it left spinning) and observing a particle with right spin. If lightspeed still matters, then these particles aren’t communicating.

What else might explain the physicists unfathomable luck?

David Deutsch posits that the explanation for this is simple — that we don’t in fact live in a universe, but rather a multiverse, a multiverse constructed out of all the possibilities that can physically exist. Our multiverse is defined by the probability set. One universe of a black ball drawn, another with a white.

This multi world interpretation, or MWI as it’s colloquially known among the physicist set, explains the spooky action as follows: entangled particles are an urn of two balls, one black one white. There are two different universes that exist, forward in time. One universe in which you pull a black ball. Another in which you pull the white.

You can deterministically decide which universe you’d like to exist in. You do this by picking a filter through which you would like to observe the world — either the black filter or the white filter. Selecting the black filter and then applying it to the urn, or entangled particles, fixes you into the reality where the ball is black.

The dual slit experiment and the filtered entangled particles share one key commonality: the power of observation and its undeniable role in fixing the observed results. This is important. The probability of what ball will be picked has moved from the random chance of the universe to an explicit choice on the behalf of the observer. The observation is the sound of a universe, of two possible, being chosen.

Quantum rhetoric is simply this: the reckoning of existence in a branching multiverse, that becomes fixed into a coherent reality.

Reflecting on Intelligence

My friend John recently published a pretty thoughtful review of Flowers for Algernon. I really liked his multiple interpretations of intelligence and wanted to add one of my own.

It’s been a long time since I last read Flowers, but the story has stuck with me. Briefly, it’s about a low IQ man who goes through a medical experiment which raises his IQ to astronomical levels, only to have it eventually regress to his original baseline.

In my mind, it’s a great story because it starkly questions so much of what we understand about ‘intelligence’ — what does it mean to have a high IQ, or a low one for that matter? Is intelligence itself life-making? Culturally, Americans are pretty obsessed with intelligence qua intelligence, both in the negative fearful sense and awe-struck aspects. We love and fear our geniuses, our cultural panthenon of modern gods is almost entirely devoted to them.

John’s review highlights a good number of different ways of understanding or interpreting the story. I’d like to add another, more personalized interpretation of why “IQ” can be isolating. 

What is IQ?

Let’s start off by saying that I don’t think I really understand what IQ measures. It seems to measure something real and tangible and descriptive about a capability of a mind, but the exact what isn’t something I feel qualified to opine on. Intelligence is something that we Americans use to bludgeon each other with, both in the has too much and doesn’t have enough sense. Given the propensity for abuse, it feels safest to talk from personal experience, as that’s both personally trustworthy (I trust my experiences) and also hard to generalize.

I’d like to conjecture that IQ is roughly a measure of someone’s ability to grasp and draw conclusions about reality based systems. Under this definition, there’s a few things that become important. The first, is your ability to notice and understand the nature of the reality that you exist in. This includes the ability to notice and appreciate deep details. Venkat retweeted a great article a few days back, about how being successful at systems building required this almost maniacal attention to details, how even beautifully simple constructions such as a set of stairs require a niche and complete understanding of the realities of angles and the nature of how wood bends.

It’s been a while since I’ve taken an IQ test, so I went to look one up online to test my theory about the ability to notice and appreciate the depth of detail about reality. I ended up doing this ‘might you be qualified to apply to Mensa’ test that doesn’t actually give you an IQ score. Instead it tells me that I got 28 out of 33 answers correct, or 84%, using an unlimited amount of time — if I had to guess, I probably didn’t spend any longer than 30 minutes on it. The whole thing is minute pattern matching. I never do very well on the number pattern ones but exposure to computer science has made it easier to spot certain patterns; my visual pattern matching skills have definitely improved in the last decade or so.

More interesting, in my mind is that I could probably tell you which of the 5 questions I got wrong. Tests like this don’t give you credit for knowing when you’re wrong or need more information — chalk that up as at least one concrete aspect of ‘intelligence’ that this IQ test is under counting. Being certain about what I know and why is relatively new ground for me, so maybe most people wouldn’t notice it.

But I noticed. And that’s the whole point of these tests. They’re all reasoning from patterns, drawing conclusions based on scant yet important information. It’s literally a rough measurement of what you notice about the reality aka pattern that they’re presenting to you. One nice thing about such encapsulated puzzles is that they’re guaranteed to provide at least enough signal to draw conclusions from — that level of guarantee is a rare thing for real world observations.

Noticing, then, is a large component of what IQ is a measure of. In fact, I think that I can strongly say that the skill this test is judging for is noticing and the consequent ability to draw a conclusion from the set of observations. IQ then, is a measure of what you notice and can predict from those observations.

The Nature of Alienation 

Charlie, in his ascent up the notice-patterning ability scale, finds himself increasingly unable to communicate with the woman character who fills the role of teacher, friend, and lover. At the pinnacle of his observation/pattern-matching performance, he’s as alienated from her as he was at the lower end of the IQ spectrum.

Why would the ability to notice things about reality make it difficult for you to interact with others?

One way of interpreting this is to say that a higher IQ means that what you notice about reality is far different from most people. Your shared context for what there is to see about the world and what that leads you to know about reality are so radically different that you are, in all practical ways, living in a different reality. Alienation, then, is the diverging of contexts such that communication loses a lot of its ability to be compressed. You have to send more signal to get ideas across, as the contexts break down.

In some ways, this is not unlike the struggle that Americans are having with the divergence of news outlets view and presentation on reality. An IQ-observation gap is one based, presumably, on the ability to pick out greater detail or signal from the same set of images. Modern ‘social’ media in the US  is taking the secondary tack of presenting two different images of events — each that lend to a differing interpretation such that the reality you experience as a consumer of political news can be entirely skewed by who you follow. It’s hard to know ‘what to believe’ when multiple images are presented. It’s even harder to communicate between these two realities, because the details that you’ve observed and picked up from the images presented to you are so incredibly disjoint as to have robbed us of the common context needed to have more compressible communication. In this reading, the political alienation across the aisle is real and quantifiable.

In Exitus

Charlie eventually loses both his ability to notice detail, as well his memory[1] of what it was even like. Eventually he falls back into a state where he’d like to know what it’s like to be able to see the details of reality that other, ‘normal IQ’ people see.

Kind of puts that old aphorism “the devil is in the details” in an entirely new light.

[1] Memory definitely plays a part of intelligence, but given the test that I took and the points that followed from those observations, I think this post can stand independent of a discussion on the importance and influence of memory. It’s definitely important and plays a large role, but there’s a nuance to observing details that doesn’t rely on memory.

The Power of Explanation

What I’m hoping to do over the course of several posts is to lay out a foundation for a new way of thinking about ethics and reality, definitively casting a vote in favor of one interpretation of reality. My goal is persuade popular opinion in favor of what is currently considered a niche outlook.

How does one move an idea from the fringes to mainstream, though? Why should you change your mind about how you think about reality? This question of persuasion seems like an important place to start.

In a lot of ways, I am re-tracing the footsteps of David Deutsch, the British physicist who penned a couple of books around the topic of reality. Much of my own thinking on the concept of reality and explanation is largely derivative of his. So let’s start at a similar place, then, with a movement towards understanding the role of explanation, of narrative, as a method of transmitting and cementing paradigmatic thought.

A Survey of Theories about Information

I tweeted at @vgr a few days back about Deutsch’s theory of explanatory power, and he responded with a list of some other theories of information. 

vgr’s informative list of information theories

Admittedly, Venkat doesn’t (yet) have a good grasp of what I mean by Deutsch’s theory of the power of explanation and therefore doesn’t exactly offer up comparable theories or interpretations, but since these are the methods of information theory that he’s using to judge how to change his mind, it feels in scope to at least walk through what these different theories can tell us about information, and how humans process it.

As a way of classifying these, there are two distinct domains about which these theories — Kuhn’s paradigm shifts, Schmidhuber’s compression progress, Occam’s razor, Deutsch’s explanatory power, Kolmogorov information — propose explanations. We can roughly divide them into two groups: the first 1) concerning the measurement and encodeable size of information and another 2) concerning the validity of an explanation. The first, in other words, provides a classification for ideas and thoughts based on how much pure physical matter of bits I need to send you in order to wholly and completely communicate an idea (measurement and density of encodeability); the second deals with what information do I need to present you with and possibly in what order or framework, in order to change your mind about a topic (explanatory validity).

With these two buckets and a bit of explanation as to what the theories entail, we can now categorize these quite effectively.

Let’s start with Kolmogorov. In a way, Kolmogorov wholly defines the first category of theories — the encodeability of an idea. What does it mean, though, to be able to ‘encode’ an idea? The classic, computer science focused explanation usually involves saying something along the lines of “consider a photograph”. You can either represent it as a matrix of color points or in JPG format. The first, or matrix representation, often takes up orders of magnitude more space, in terms of bits, than the ‘condensed’ JPG format. Kolmogrov was concerned with the ultimate ability to take a complex idea such as a photo and represent it in the smallest number of bits. You can then judge information or an idea based on how compactly it can be expressed. The ‘complexity’ of an idea is measured by how few bits you need to transmit over the wire. The lower the number of bits needed to represent it, the lower its stated complexity.

Schmidhuber took this concept of the compressibility of information and developed several examples of how ‘low Kolmogorov complexity’ ideas can still, in reality, be quite complex.

As an aside, my favorite example of these is his Femme Fractale, an equation for a drawing that when executed, creates a set of intersecting lines. Schmidhuber then goes on to explain how insight or creativity can be derived from this relatively simplistic pattern, eventually highlighting one particular pathway that, to him, is evocative of women’s silhouettes. The syntactic expression of the original drawing (top left, below) is as follows: “The frame is a circle; its leftmost point is the center of another circle of the same size. Wherever two circles of equal size touch or intersect are centers of two more circles with equal and half size, respectively. Each line of the drawing is a segment of some circle, its endpoints are where circles touch or intersect”.

Tracing femmes in a low Komolgorov complexity fractal, source http://people.idsia.ch/~juergen/femmefractale.html

Schmidhuber’s compression progress builds upon Kolmogorov’s idea of information compressibility. Schmidhuber’s contribution was the insight that the extent to which an idea can be compressed is dependent upon the existing context which an information storage system has accumulated or that exists between communication partners. For example, when developing an encoding mechanism to use between two parties, the density of the encoding that is possible is based on how accurately you can predict, given a pattern of input or output, what any series of bits expands to represent. In the Femme Fractale example above, you as the decoder can “predict” what a circle looks like, so the English description doesn’t need to encode a definition of a circle. The definition of circle is a part of your shared context.

In an incredibly general sense, compression algorithms, then, are a manner of building and then transmitting data within a shared context. As the shared context becomes more descriptive, the encoding required for an idea decreases.

Schumidhuber proposes that as the amount of information that a system has seen increases, the amount of space or number of bits that an encoder needs in order to transmit or store that new idea decreases. This is ‘compression progress’, or the ability to more greatly compress ideas as you progress deeper into a context.

If you’re not incredibly up to speed on computer science primitives and what it means for an image to be ‘represented as a matrix’, there’s another, less pure yet more revelatory example I can present you with — Dawkin’s term ‘meme’.

As I mentioned earlier, there’s a bit of nuance here with information encoding measurement: all information encoding requires a decoder. How tightly you can pack information is a function of the pre-negotiated symbolism between two parties. An alphabet, for example, encodes information uniformly, sort of, by the construction of words. These words themselves encode meaning, however, such as ‘meme’. Broadcasting the word ‘meme’, in terms of information density, is quite small. It’s four ASCII letters. On a typical late 2010’s transmission line, we can get that idea ‘across’ a wire in approximately 32 bits, without compression (ignoring any transmission control or protocol data).

This 32-bits, however, is only enough to transmit the word itself.  The concept of what I mean by ‘meme’ is assumed to be encoded already within the recipient of the information. There’s already a shared understanding between the message sender and the message recipient.

Is it possible to encode the bigger question, namely ‘what is a meme’ in 32 bits? That, again, depends on the existing, shared context of the two parties wishing to communicate. If I have to explain what a meme is, in English, that will most definitively require greater than 32 bits of information, granted that at the least it requires a sentence or two of explanation. If I need to explain it in German, it’ll take even more bits as I’ll need to do a fair amount of translation in addition.

This progression, of building a shared understanding from an agreed upon  alphabet, to shared words such as English, to paragraph long explanations, to just sending you the short, four-character word meme — this is compression of expression, an encoding of information into progressively smaller and smaller amounts of signal that need to be transmitted as the base context of how and what we’re communicating becomes richer and, in some sense, more predictive.

Both Schmidhuber and Kolmogorov’s theories about information transmission can be loosely classified as theories about measurement and condensibility of information. These theories give us guidelines for how to measure the encodeability of an idea or information, as well as some general guidelines for understanding how we might be able to better compress information.

Let’s look now at Occam’s Razor and Explanatory Power, theories that deal with the explanatory validity of an idea. That is, how do we judge the validity of that idea, in terms of using it as a framing for how to understand our reality.

This question is related to the context question. A “valid framing” is a context that enables a compacted representation of reality. In fact, compactness is what Occam’s Razor expresses, that the most simple explanation is often reality.

Consider the following quote from Ludwig Wittenstein’s Tractatus Logico-Philosophicus:

If a sign is not necessary then it is meaningless. That is the meaning of Occam’s Razor.

Ludwig Wittgenstein, Tractatus Logico-Philosophicus 3.328

An unnecessary sign would be one that does nothing to contribute to the compactness of an idea, or that does not lend to the task of further compressing additional information or observation. Thus, the task of scientific endeavor is to find theories about reality that allow us to maximally compress the way that we represent it. We do this through the construction of the minimally required context.

But what is this context constructed of? How does this context get built? This is where Deutsch’s theory of Explanatory Power fills the gap. Deutsch, in his book The Fabric of Reality, extends Karl Popper’s anti-inductivism to conclude that all scientific theory is the building of a story-like explanation. Deutsch gives several guidelines for how explanatory power can be observed or identified:

  • if more facts or observations are accounted for; (compression)
  • if it changes more “surprising facts” into “a matter of course”; (prediction)
  • if it offers greater predictive power, i.e., if it offers more details about what we should expect to see, and what we should not; (prediction)
  • if it depends less on authorities and more on observations; (?)
  • if it makes fewer assumptions; (compression)
  • if it is more falsifiable, i.e., more testable by observation or experiment; (prediction)
  • if it is hard to vary.

Taken from the Wikipedia entry on Explanatory Power.

This transition, from ‘suprising facts’ to ‘matter of course’ closely mirrors the language used by Schmidhuber to describe the process of building a more compressible context for information.

Let’s look at this concept of compressibility on the example that Deutsch gives in his TED talk about the subject, on why the sun gets colder in the winter. He uses the ancient Greek explanation, that of Demeter getting sad because her daughter Persephone goes down into the underworld to pay a debt for the last part of the year. Deutsch gives a good idea for why, with additional observations, this explanation fails several of his above outlined criteria for a good explanation.

Let’s consider this same story in terms of compressibility. Knowing the story of Demeter and Persephone only gives us the ability to understand this one, specific phenomenon — why the sun weakens in the winter. It’s not very compact, as it doesn’t give us much ability to predict any other observations about the world.

Our current explanation of the Earth rotating on a skewed axis about the Sun, on the other hand, does a lot to predict many things that we can observe about our reality. It predicts seasons. It predicts the changes in day length that you observe at the equator as opposed to the poles. It predicts why the moon’s appearance is different on different parts of the planet. The mere concept of being on a planet that rotates about the Sun on a skewed axis gives us the context to situate and condense other phenomena that we observe about the world. In the terminology of Deutsch, we’d say that this idea of planetary rotation has high explanatory power, but it also goes a long way to contributing to our ability, as humans to compress the knowledge that we know about the world into tighter and more succinct representations. Deutsch is right that we create explanations about the world. Those explanations become the context that we can situate our observations and predictions into.

This just leaves us with Kuhn’s Paradigm‘s shifts, which is largely an observation that Kuhn made about the fact that a shift in the broader contextualization of information happens. In other words, Kuhn points out that when a compression algorithm (be it a human’s understanding or an actual programmatic decision matrix) discovers a new, more predictive way of organizing information, it will shift its interpretation or encoding of prior observations to be re-encoded using this new, more dense understanding.

In Exitus

So, how does one change their mind about a thing? These theories tell us that it is by finding new explanations that lend to more condensible encodings that then allow us to communicate and store our understanding of our reality in richer and more meaningful ways.


This condensed video of Schmidhuber talking it is pretty good; if you’ve got time the whole video might be worth watching. Schmidhuber’s work is largely descriptive of how learning systems learn new things and the representations that they then store of that information into, but he’s also got some really great observations about the mechanism of discovery and curiosity, or why humans are driven to look for more compressible interpretations.