Tag Archives: psychology

Book Review: The Case Against Reality

Nima Arkani-Hamed shows up surprisingly rarely in popular science books. A major figure in my former field, Nima is extremely quotable (frequent examples include “spacetime is doomed” and “the universe is not a crappy metal”), but those quotes don’t seem to quite have reached the popular physics mainstream. He’s been interviewed in books by physicists, and has a major role in one popular physics book that I’m aware of. From this scattering of mentions, I was quite surprised to hear of another book where he makes an appearance: not a popular physics book at all, but a popular psychology book: Donald Hoffman’s The Case Against Reality. Naturally, this meant I had to read it.

Then, I saw the first quote on the back cover…or specifically, who was quoted.

Seeing that, I settled in for a frustrating read.

A few pages later, I realized that this, despite his endorsement, is not a Deepak Chopra kind of book. Hoffman is careful in some valuable ways. Specifically, he has a philosopher’s care, bringing up objections and potential holes in his arguments. As a result, the book wasn’t frustrating in the way I expected.

It was even more frustrating, actually. But in an entirely different way.

When a science professor writes a popular book, the result is often a kind of ungainly Frankenstein. The arguments we want to make tend to be better-suited to shorter pieces, like academic papers, editorials, and blog posts. To make these into a book, we have to pad them out. We stir together all the vaguely related work we’ve done, plus all the best-known examples from other peoples’ work, trying (often not all that hard) to make the whole sound like a cohesive story. Read enough examples, and you start to see the joints between the parts.

Hoffman is ostensibly trying to tell a single story. His argument is that the reality we observe, of objects in space and time, is not the true reality. It is a convenient reality, one that has led to our survival, but evolution has not (and as he argues, cannot) let us perceive the truth. Instead, he argues that the true reality is consciousness: a world made up of conscious beings interacting with each other, with space, time, and all the rest emerging as properties of those interactions.

That certainly sounds like it could be one, cohesive argument. In practice, though, it is three, and they don’t fit together as well as he’d hope.

Hoffman is trained as a psychologist. As such, one of the arguments is psychological: that research shows that we mis-perceive the world in service of evolutionary fitness.

Hoffman is a cognitive scientist, and while many cognitive scientists are trained as psychologists, others are trained as philosophers. As such, one of his arguments is philosophical: that the contents of consciousness can never be explained by relations between material objects, and that evolution, and even science, systematically lead us astray.

Finally, Hoffman has evidently been listening to and reading the work of some physicists, like Nima and Carlo Rovelli. As such, one of his arguments is physical: that physicists believe that space and time are illusions and that consciousness may be fundamental, and that the conclusions of the book lead to his own model of the basic physical constituents of the world.

The book alternates between these three arguments, so rather than in chapter order, I thought it would be better to discuss each argument in its own section.

The Psychological Argument

Sometimes, when two academics get into a debate, they disagree about what’s true. Two scientists might argue about whether an experiment was genuine, whether the statistics back up a conclusion, or whether a speculative theory is actually consistent. These are valuable debates, and worth reading about if you want to learn something about the nature of reality.

Sometimes, though, two debating academics agree on what’s true, and just disagree on what’s important. These debates are, at best, relevant to other academics and funders. They are not generally worth reading for anybody else, and are often extremely petty and dumb.

Hoffman’s psychological argument, regrettably, is of the latter kind. He would like to claim it’s the former, and to do so he marshals a host of quotes from respected scientists that claim that human perception is veridical: that what we perceive is real, courtesy of an evolutionary process that would have killed us off if it wasn’t. From that perspective, every psychological example Hoffman gives is a piece of counter-evidence, a situation where evolution doesn’t just fail to show us the true nature of reality, but actively hides reality from us.

The problem is that, if you actually read the people Hoffman quotes, they’re clearly not making the extreme point he claims. These people are psychologists, and all they are arguing is that perception is veridical in a particular, limited way. They argue that we humans are good at estimating distances or positions of objects, or that we can see a wide range of colors. They aren’t making some sort of philosophical point about those distances or positions or colors being how the world “really is”, nor are they claiming that evolution never makes humans mis-perceive.

Instead, they, and thus Hoffman, are arguing about importance. When studying humans, is it more useful to think of us as perceiving the world as it is? Or is it more useful to think of evolution as tricking us? Which happens more often?

The answers to each of those questions have to be “it depends”. Neither answer can be right all the time. At most then, this kind of argument can convince one academic to switch from researching in one way to researching in another, by saying that right now one approach is a better strategy. It can’t tell us anything more.

If the argument Hoffman is trying to get across here doesn’t matter, are there other reasons to read this part?

Popular psychology books tend to re-use a few common examples. There are some good ones, so if you haven’t read such a book you probably should read a couple, just to hear about them. For example, Hoffman tells the story of the split-brain patients, which is definitely worth being aware of.

(Those of you who’ve heard that story may be wondering how the heck Hoffman squares it with his idea of consciousness as fundamental. He actually does have a (weird) way to handle this, so read on.)

The other examples come from Hoffman’s research, and other research in his sub-field. There are stories about what optical illusions tell us about our perception, about how evolution primes us to see different things as attractive, and about how advertisers can work with attention.

These stories would at least be a source of a few more cool facts, but I’m a bit wary. The elephant in the room here is the replication crisis. Paper after paper in psychology has turned out to be a statistical mirage, accidental successes that fail to replicate in later experiments. This can happen without any deceit on the part of the psychologist, it’s just a feature of how statistics are typically done in the field.

Some psychologists make a big deal about the replication crisis: they talk about the statistical methods they use, and what they do to make sure they’re getting a real result. Hoffman talks a bit about tricks to rule out other explanations, but mostly doesn’t focus on this kind of thing.. This doesn’t mean he’s doing anything wrong: it might just be it’s off-topic. But it makes it a bit harder to trust him, compared to other psychologists who do make a big deal about it.

The Philosophical Argument

Hoffman structures his book around two philosophical arguments, one that appears near the beginning and another that, as he presents it, is the core thesis of the book. He calls both of these arguments theorems, a naming choice sure to irritate mathematicians and philosophers alike, but the mathematical content in either is for the most part not the point: in each case, the philosophical setup is where the arguments get most of their strength.

The first of these arguments, called The Scrambling Theorem, is set up largely as background material: not his core argument, but just an entry into the overall point he’s making. I found it helpful as a way to get at his reasoning style, the sorts of things he cares about philosophically and the ones he doesn’t.

The Scrambling Theorem is meant to weigh in on the debate over a thought experiment called the Inverted Spectrum, which in turn weighs on the philosophical concept of qualia. The Inverted Spectrum asks us to imagine someone who sees the spectrum of light inverted compared to how we see it, so that green becomes red and red becomes green, without anything different about their body or brain. Such a person would learn to refer to colors the same ways that we do, still referring to red blood even though they see what we see when we see green grass. Philosophers argue that, because we can imagine this, the “qualia” we see in color, like red or green, are distinct from their practical role: they are images in the mind’s eye that can be compared across minds, but do not correspond to anything we have yet characterized scientifically in the physical world.

As a response, other philosophers argued that you can’t actually invert the spectrum. Colors aren’t really a wheel, we can distinguish, for example, more colors between red and blue than between green and yellow. Just flipping colors around would have detectable differences that would have to have physical implications, you can’t just swap qualia and nothing else.

The Scrambling Theorem is in response to this argument. Hoffman argues that, while you can’t invert the spectrum, you can scramble it. By swapping not only the colors, but the relations between them, you can arrange any arbitrary set of colors however else you’d like. You can declare that green not only corresponds to blood and not grass, but that it has more colors between it and yellow, perhaps by stealing them from the other side of the color wheel. If you’re already allowed to swap colors and their associations around, surely you can do this too, and change order and distances between them.

Believe it or not, I think Hoffman’s argument is correct, at least in its original purpose. You can’t respond to the Inverted Spectrum just by saying that colors are distributed differently on different sides of the color wheel. If you want to argue against the Inverted Spectrum, you need a better argument.

Hoffman’s work happens to suggest that better argument. Because he frames this argument in the language of mathematics, as a “theorem”, Hoffman’s argument is much more general than the summary I gave above. He is arguing that not merely can you scramble colors, but anything you like. If you want to swap electrons and photons, you can: just make your photons interact with everything the way electrons did, and vice versa. As long as you agree that the things you are swapping exist, according to Hoffman, you are free to exchange them and their properties any way you’d like.

This is because, to Hoffman, things that “actually exist” cannot be defined just in terms of their relations. An electron is not merely a thing that repels other electrons and is attracted to protons and so on, it is a thing that “actually exists” out there in the world. (Or, as he will argue, it isn’t really. But that’s because in the end he doesn’t think electrons exist.)

(I’m tempted to argue against this with a mathematical object like group elements. Surely the identity element of a group is defined by its relations? But I think he would argue identity elements of groups don’t actually exist.)

In the end, Hoffman is coming from a particular philosophical perspective, one common in modern philosophers of metaphysics, the study of the nature of reality. From this perspective, certain things exist, and are themselves by necessity. We cannot ask what if a thing were not itself. For example, in this perspective it is nonsense to ask what if Superman was not Clark Kent, because the two names refer to the same actually existing person.

(If, you know, Superman actually existed.)

Despite the name of the book, Hoffman is not actually making a case against reality in general. He very much seems to believe in this type of reality, in the idea that there are certain things out there that are real, independent of any purely mathematical definition of their properties. He thinks they are different things than you think they are, but he definitely thinks there are some such things, and that it’s important and scientifically useful to find them.

Hoffman’s second argument is, as he presents it, the core of the book. It’s the argument that’s supposed to show that the world is almost certainly not how we perceive it, even through scientific instruments and the scientific method. Once again, he calls it a theorem: the Fitness Beats Truth theorem.

The Fitness Beats Truth argument begins with a question: why should we believe what we see? Why do we expect that the things we perceive should be true?

In Hoffman’s mind, the only answer is evolution. If we perceived the world inaccurately, we would die out, replaced by creatures that perceived the world better than we did. You might think we also have evidence from biology, chemistry, and physics: we can examine our eyes, test them against cameras, see how they work and what they can and can’t do. But to Hoffman, all of this evidence may be mistaken, because to learn biology, chemistry, and physics we must first trust that we perceive the world correctly to begin with. Evolution, though, doesn’t rely on any of that. Even if we aren’t really bundles of cells replicating through DNA and RNA, we should still expect something like evolution, some process by which things differ, are selected, and reproduce their traits differently in the next generation. Such things are common enough, and general enough, that one can (handwavily) expect them through pure reason alone.

But, says Hoffman’s psychology experience, evolution tricks us! We do mis-perceive, and systematically, in ways that favor our fitness over reality. And so Hoffman asks, how often should we expect this to happen?

The Fitness Beats Truth argument thinks of fitness as randomly distributed: some parts of reality historically made us more fit, some less. This distribution could match reality exactly, so that for any two things that are actually different, they will make us fit in different ways. But it doesn’t have to. There might easily be things that are really very different from each other, but which are close enough from a fitness perspective that to us they seem exactly the same.

The “theorem” part of the argument is an attempt to quantify this. Hoffman imagines a pixelated world, and asks how likely it is that a random distribution of fitness matches a random distribution of pixels. This gets extremely unlikely for a world of any reasonable size, for pretty obvious reasons. Thus, Hoffman concludes: in a world with evolution, we should almost always expect it to hide something from us. The world, if it has any complexity at all, has an almost negligible probability of being as we perceive it.

On one level, this is all kind of obvious. Evolution does trick us sometimes, just as it tricks other animals. But Hoffman is trying to push this quite far, to say that ultimately our whole picture of reality, not just our eyes and ears and nose but everything we see with microscopes and telescopes and calorimeters and scintillators, all of that might be utterly dramatically wrong. Indeed, we should expect it to be.

In this house, we tend to dismiss the Cartesian Demon. If you have an argument that makes you doubt literally everything, then it seems very unlikely you’ll get anything useful from it. Unlike Descartes’s Demon, Hoffman thinks we won’t be tricked forever. The tricks evolution plays on us mattered in our ancestral environment, but over time we move to stranger and stranger situations. Eventually, our fitness will depend on something new, and we’ll need to learn something new about reality.

This means that ultimately, despite the skeptical cast, Hoffman’s argument fits with the way science already works. We are, very much, trying to put ourselves in new situations and test whether our evolved expectations still serve us well or whether we need to perceive things anew. That is precisely what we in science are always doing, every day. And as we’ll see in the next section, whatever new things we have to learn have no particular reason to be what Hoffman thinks they should be.

But while it doesn’t really matter, I do still want to make one counter-argument to Fitness Beats Truth. Hoffman considers a random distribution of fitness, and asks what the chance is that it matches truth. But fitness isn’t independent of truth, and we know that not just from our perception, but from deeper truths of physics and mathematics. Fitness is correlated with truth, fitness often matches truth, for one key reason: complex things are harder than simple things.

Imagine a creature evolving an eye. They have a reason, based on fitness, to need to know where their prey is moving. If evolution was a magic wand, and chemistry trivial, it would let them see their prey, and nothing else. But evolution is not magic, and chemistry is not trivial. The easiest thing for this creature to see is patches of light and darkness. There are many molecules that detect light, because light is a basic part of the physical world. To detect just prey, you need something much more complicated, molecules and cells and neurons. Fitness imposes a cost, and it means that the first eyes that evolve are spots, detecting just light and darkness.

Hoffman asks us not to assume that we know how eyes work, that we know how chemistry works, because we got that knowledge from our perceptions. But the nature of complexity and simplicity, entropy and thermodynamics and information, these are things we can approach through pure thought, as much as evolution. And those principles tell us that it will always be easier for an organism to perceive the world as it truly is than not, because the world is most likely simple and it is most likely the simplest path to perceive it directly. When benefits get high enough, when fitness gets strong enough, we can of course perceive the wrong thing. But if there is only a small fitness benefit to perceiving something incorrectly, then simplicity will win out. And by asking simpler and simpler questions, we can make real durable scientific progress towards truth.

The Physical Argument

So if I’m not impressed by the psychology or the philosophy, what about the part that motivated me to read the book in the first place, the physics?

Because this is, in a weird and perhaps crackpot way, a physics book. Hoffman has a specific idea, more specific than just that the world we perceive is an evolutionary illusion, more specific than that consciousness cannot be explained by the relations between physical particles. He has a proposal, based on these ideas, one that he thinks might lead to a revolutionary new theory of physics. And he tries to argue that physicists, in their own way, have been inching closer and closer to his proposal’s core ideas.

Hoffman’s idea is that the world is made, not of particles or fields or anything like that, but of conscious agents. You and I are, in this picture, certainly conscious agents, but so are the sources of everything we perceive. When we reach out and feel a table, when we look up and see the Sun, those are the actions of some conscious agent intruding on our perceptions. Unlike panpsychists, who believe that everything in the world is conscious, Hoffman doesn’t believe that the Sun itself is conscious, or is made of conscious things. Rather, he thinks that the Sun is an evolutionary illusion that rearranges our perceptions in a convenient way. The perceptions still come from some conscious thing or set of conscious things, but unlike in panpsychism they don’t live in the center of our solar system, or in any other place (space and time also being evolutionary illusions in this picture). Instead, they could come from something radically different that we haven’t imagined yet.

Earlier, I mentioned split brain patients. For anyone who thinks of conscious beings as fundamental, split brain patients are a challenge. These are people who, as a treatment for epilepsy, had the bridge between the two halves of their brain severed. The result is eerily as if their consciousness was split in two. While they only express one train of thought, that train of thought seems to only correspond to the thoughts of one side of their brain, controlling only half their body. The other side, controlling the other half of their body, appears to have different thoughts, different perceptions, and even different opinions, which are made manifest when instead of speaking they use that side of their body to gesture and communicate. While some argue that these cases are over-interpreted and don’t really show what they’re claimed to, Hoffman doesn’t. He accepts that these split-brain patients genuinely have their consciousness split in two.

Hoffman thinks this isn’t a problem because for him, conscious agents can be made up of other conscious agents. Each of us is conscious, but we are also supposed to be made up of simpler conscious agents. Our perceptions and decisions are not inexplicable, but can be explained in terms of the interactions of the simpler conscious entities that make us up, each one communicating with the others.

Hoffman speculates that everything is ultimately composed of the simplest possible conscious agents. For him, a conscious agent must do two things: perceive, and act. So the simplest possible agent perceives and acts in the simplest possible way. They perceive a single bit of information: 0 or 1, true or false, yes or no. And they take one action, communicating a different bit of information to another conscious agent: again, 0 or 1, true or false, yes or no.

Hoffman thinks that this could be the key to a new theory of physics. Instead of thinking about the world as composed of particles and fields, think about it as composed of these simple conscious agents, each one perceiving and communicating one bit at a time.

Hoffman thinks this, in part, because he sees physics as already going in this direction. He’s heard that “spacetime is doomed”, he’s heard that quantum mechanics is contextual and has no local realism, he’s heard that quantum gravity researchers think the world might be a hologram and space-time has a finite number of bits. This all “rhymes” enough with his proposal that he’s confident physics has his back.

Hoffman is trained in psychology. He seems to know his philosophy, at least enough to engage with the literature there. But he is absolutely not a physicist, and it shows. Time and again it seems like he relies on “pop physics” accounts that superficially match his ideas without really understanding what the physicists are actually talking about.

He keeps up best when it comes to interpretations of quantum mechanics, a field where concepts from philosophy play a meaningful role. He covers the reasons why quantum mechanics keeps philosophers up at night: Bell’s Theorem, which shows that a theory that matches the predictions of quantum mechanics cannot both be “realist”, with measurements uncovering pre-existing facts about the world, and “local”, with things only influencing each other at less than the speed of light, the broader notion of contextuality, where measured results are dependent on which other measurements are made, and the various experiments showing that both of these properties hold in the real world.

These two facts, and their implications, have spawned a whole industry of interpretations of quantum mechanics, where physicists and philosophers decide which side of various dilemmas to take and how to describe the results. Hoffman quotes a few different “non-realist” interpretations: Carlo Rovelli’s Relational Quantum Mechanics, Quantum Bayesianism/QBism, Consistent Histories, and whatever Chris Fields is into. These are all different from one another, which Hoffman is aware of. He just wants to make the case that non-realist interpretations are reasonable, that the physicists collectively are saying “maybe reality doesn’t exist” just like he is.

The problem is that Hoffman’s proposal is not, in the quantum mechanics sense, non-realist. Yes, Hoffman thinks that the things we observe are just an “interface”, that reality is really a network of conscious agents. But in order to have a non-realist interpretation, you need to also have other conscious agents not be real. That’s easily seen from the old “Wigner’s friend” thought experiment, where you put one of your friends in a Schrodinger’s cat-style box. Just as Schrodinger’s cat can be both alive and dead, your friend can both have observed something and not have observed it, or observed something and observed something else. The state of your friend’s mind, just like everything else in a non-realist interpretation, doesn’t have a definite value until you measure it.

Hoffman’s setup doesn’t, and can’t, work that way. His whole philosophical project is to declare that certain things exist and others don’t: the sun doesn’t exist, conscious agents do. In a non-realist interpretation, the sun and other conscious agents can both be useful descriptions, but ultimately nothing “really exists”. Science isn’t a catalogue of what does or doesn’t “really exist”, it’s a tool to make predictions about your observations.

Hoffman gets even more confused when he gets to quantum gravity. He starts out with a common misconception: that the Planck length represents the “pixels” of reality, sort of like the pixels of your computer screen, which he uses to support his “interface” theory of consciousness. This isn’t really the right way to think about it the Planck length, though, and certainly isn’t what the people he’s quoting have in mind. The Planck length is a minimum scale in that space and time stop making sense as one approaches it, but that’s not necessarily because space and time are made up of discrete pixels. Rather, it’s because as you get closer to the Planck length, space and time stop being the most convenient way to describe things. For a relatively simple example of how this can work, see my post here.

From there, he reflects on holography: the discovery that certain theories in physics can be described equally well by what is happening on their boundary as by their interior, the way that a 2D page can hold all the information for an apparently 3D hologram. He talks about the Bekenstein bound, the conjecture that there is a maximum amount of information needed to describe a region of space, proportional not to the volume of the region but to its area. For Hoffman, this feels suspiciously like human vision: if we see just a 2D image of the world, could that image contain all the information needed to construct that world? Could the world really be just what we see?

In a word, no.

On the physics side, the Bekenstein bound is a conjecture, and one that doesn’t always hold. A more precise version that seems to hold more broadly, called the Bousso bound, works by demanding the surface have certain very specific geometric properties in space-time, properties not generally shared by the retinas of our eyes.

But it even fails in Hoffman’s own context, once we remember that there are other types of perception than vision. When we hear, we don’t detect a 2D map, but a 1D set of frequencies, put in “stereo” by our ears. When we feel pain, we can feel it in any part of our body, essentially a 3D picture since it goes inwards as well. Nothing about human perception uniquely singles out a 2D surface.

There is actually something in physics much closer to what Hoffman is imagining, but it trades on a principle Hoffman aspires to get rid of: locality. We’ve known since Einstein that you can’t change the world around you faster than the speed of light. Quantum mechanics doesn’t change that, despite what you may have heard. More than that, simultaneity is relative: two distant events might be at the same time in your reference frame, but for someone else one of them might be first, or the other one might be, there is no one universal answer.

Because of that, if you want to think about things happening one by one, cause following effect, actions causing consequences, then you can’t think of causes or actions as spread out in space. You have to think about what happens at a single point: the location of an imagined observer.

Once you have this concept, you can ask whether describing the world in terms of this single observer works just as well as describing it in terms of a wide open space. And indeed, it actually can do well, at least under certain conditions. But one again, this really isn’t how Hoffman is doing things: he has multiple observers all real at the same time, communicating with each other in a definite order.

In general, a lot of researchers in quantum gravity think spacetime is doomed. They think things are better described in terms of objects with other properties and interactions, with space and time as just convenient approximations for a more complicated reality. They get this both from observing properties of the theories we already have, and from thought experiments showing where those theories cause problems.

Nima, the most catchy of these quotable theorists, is approaching the problem from the direction of scattering amplitudes: the calculations we do to find the probability of observations in particle physics. Each scattering amplitude describes a single observation: what someone far away from a particle collision can measure, independent of any story of what might have “actually happened” to the particles in between. Nima’s goal is to describe these amplitudes purely in terms of those observations, to get rid of the “story” that shows up in the middle as much as possible.

The other theorists have different goals, but have this in common: they treat observables as their guide. They look at the properties that a single observer’s observations can have, and try to take a fresh view, independent of any assumptions about what happens in between.

This key perspective, this key insight, is what Hoffman is missing throughout this book. He has read what many physicists have to say, but he does not understand why they are saying it. His book is titled The Case Against Reality, but he merely trades one reality for another. He stops short of the more radical, more justified case against reality: that “reality”, that thing philosophers argue about and that makes us think we can rule out theories based on pure thought, is itself the wrong approach: that instead of trying to characterize an idealized real world, we are best served by focusing on what we can do.

One thing I didn’t do here is a full critique of Hoffman’s specific proposal, treating it as a proposed theory of physics. That would involve quite a bit more work, on top of what has turned out to be a very long book review. I would need to read not just his popular description, but the actual papers where he makes his case and lays out the relevant subtleties. Since I haven’t done that, I’ll end with a few questions: things that his proposal will need to answer if it aspires to be a useful idea for physics.

  • Are the networks of conscious agents he proposes Turing-complete? In other words, can they represent any calculation a computer can do? If so, they aren’t a useful idea for physics, because you could imagine a network of conscious agents to reproduce any theory you want. The idea wouldn’t narrow things down to get us closer to a useful truth. This was also one of the things that made me uncomfortable with the Wolfram Physics Project.
  • What are the conditions that allow a network of simple conscious agents to make up a bigger conscious agent? Do those conditions depend meaningfully on the network’s agents being conscious, or do they just have to pass messages? If the latter, then Hoffman is tacitly admitting you can make a conscious agent out of non-conscious agents, even if he insists this is philosophically impossible.
  • How do you square this network with relativity and quantum mechanics? Is there a set time, an order in which all the conscious agents communicate with each other? If so, how do you square that with the relativity of simultaneity? Are the agents themselves supposed to be able to be put in quantum states, or is quantum mechanics supposed to emerge from a theory of classical agents?
  • How does evolution fit in here? A bit part of Hoffman’s argument was supported by the universality of the evolutionary algorithm. In order for evolution to matter for your simplest agents, they need to be able to be created or destroyed. But then they have more than two actions: not just 0 and 1, but 0, 1, and cease to exist. So you could have an even simpler agent that has just two bits.

What Are Students? We Just Don’t Know

I’m taking a pedagogy course at the moment, a term-long follow-up to the one-week intro course I took in the spring. The course begins with yet another pedagogical innovation, a “pre-project”. Before the course has really properly started, we get assembled into groups and told to investigate our students. We are supposed to do interviews on a few chosen themes, all with the objective of getting to know our students better. I’m guessing the point is to sharpen our goals, so that when we start learning pedagogy we’ll have a clearer idea of what problems we’d like to solve.

The more I think about this the more I’m looking forward to it. When I TAed in the past, some of the students were always a bit of a mystery. They sat in the back, skipped assignments, and gradually I saw less and less of them. They didn’t go to office hours or the help room, and I always wondered what happened. When in the course did they “turn off”, when did we lose them? They seemed like a kind of pedagogical dark matter, observable only by their presence on the rosters. I’m hoping to detect a little of that dark matter here.

As it’s a group project, we came up with a theme as a group, and questions to support that theme (in particular, we’re focusing on the different experiences between Danes and international students). Since the topic is on my mind in general though, I thought it would be fun to reach out to you guys. Educators in the comments: if you could ask your students one question, what would it be? Students, what is one thing you think your teachers are missing?

Of p and sigma

Ask a doctor or a psychologist if they’re sure about something, and they might say “it has p<0.05”. Ask a physicist, and they’ll say it’s a “5 sigma result”. On the surface, they sound like they’re talking about completely different things. As it turns out, they’re not quite that different.

Whether it’s a p-value or a sigma, what scientists are giving you is shorthand for a probability. The p-value is the probability itself, while sigma tells you how many standard deviations something is away from the mean on a normal distribution. For people not used to statistics this might sound very complicated, but it’s not so tricky in the end. There’s a graph, called a normal distribution, and you can look at how much of it is above a certain point, measured in units called standard deviations, or “sigmas”. That gives you your probability.

Give it a try: how much of this graph is past the 1\sigma line? How about 2\sigma?

What are these numbers a probability of? At first, you might think they’re a probability of the scientist being right: of the medicine working, or the Higgs boson being there.

That would be reasonable, but it’s not how it works. Scientists can’t measure the chance they’re right. All they can do is compare models. When a scientist reports a p-value, what they’re doing is comparing to a kind of default model, called a “null hypothesis”. There are different null hypotheses for different experiments, depending on what the scientists want to test. For the Higgs, scientists looked at pairs of photons detected by the LHC. The null hypothesis was that these photons were created by other parts of the Standard Model, like the strong force, and not by a Higgs boson. For medicine, the null hypothesis might be that people get better on their own after a certain amount of time. That’s hard to estimate, which is why medical experiments use a control group: a similar group without the medicine, to see how much they get better on their own.

Once we have a null hypothesis, we can use it to estimate how likely it is that it produced the result of the experiment. If there was no Higgs, and all those photons just came from other particles, what’s the chance there would still be a giant pile of them at one specific energy? If the medicine didn’t do anything, what’s the chance the control group did that much worse than the treatment group?

Ideally, you want a small probability here. In medicine and psychology, you’re looking for a 5% probability, for p<0.05. In physics, you need 5 sigma to make a discovery, which corresponds to a one in 3.5 million probability. If the probability is low, then you can say that it would be quite unlikely for your result to happen if the null hypothesis was true. If you’ve got a better hypothesis (the Higgs exists, the medicine works), then you should pick that instead.

Note that this probability still uses a model: it’s the probability of the result given that the model is true. It isn’t the probability that the model is true, given the result. That probability is more important to know, but trickier to calculate. To get from one to the other, you need to include more assumptions: about how likely your model was to begin with, given everything else you know about the world. Depending on those assumptions, even the tiniest p-value might not show that your null hypothesis is wrong.

In practice, unfortunately, we usually can’t estimate all of those assumptions in detail. The best we can do is guess their effect, in a very broad way. That usually just means accepting a threshold for p-values, declaring some a discovery and others not. That limitation is part of why medicine and psychology demand p-values of 0.05, while physicists demand 5 sigma results. Medicine and psychology have some assumptions they can rely on: that people function like people, that biology and physics keep working. Physicists don’t have those assumptions, so we have to be extra-strict.

Ultimately, though, we’re all asking the same kind of question. And now you know how to understand it when we do.

Halloween Post: Superstimuli for Physicists

For Halloween, this blog has a tradition of covering “the spooky side” of physics. This year, I’m bringing in a concept from biology to ask a spooky physics “what if?”

In the 1950’s, biologists discovered that birds were susceptible to a worryingly effective trick. By giving them artificial eggs larger and brighter than their actual babies, they found that the birds focused on the new eggs to the exclusion of their own. They couldn’t help trying to hatch the fake eggs, even if they were so large that they would fall off when they tried to sit on them. The effect, since observed in other species, became known as a supernormal stimulus, or superstimulus.

Can this happen to humans? Some think so. They worry about junk food we crave more than actual nutrients, or social media that eclipses our real relationships. Naturally, this idea inspires horror writers, who write about haunting music you can’t stop listening to, or holes in a wall that “fit” so well you’re compelled to climb in.

(And yes, it shows up in porn as well.)

But this is a physics blog, not a biology blog. What kind of superstimulus would work on physicists?

Abstruse goose knows what’s up

Well for one, this sounds a lot like some criticisms of string theory. Instead of a theory that just unifies some forces, why not unify all the forces? Instead of just learning some advanced mathematics, why not learn more, and more? And if you can’t be falsified by any experiment, well, all that would do is spoil the fun, right?

But it’s not just string theory you could apply this logic to. Astrophysicists study not just one world but many. Cosmologists study the birth and death of the entire universe. Particle physicists study the fundamental pieces that make up the fundamental pieces. We all partake in the euphoria of problem-solving, a perpetual rush where each solution leads to yet another question.

Do I actually think that string theory is a superstimulus, that astrophysics or particle physics is a superstimulus? In a word, no. Much as it might look that way from the news coverage, most physicists don’t work on these big, flashy questions. Far from being lured in by irresistible super-scale problems, most physicists work with tabletop experiments and useful materials. For those of us who do look up at the sky or down at the roots of the world, we do it not just because it’s compelling but because it has a good track record: physics wouldn’t exist if Newton hadn’t cared about the orbits of the planets. We study extremes because they advance our understanding of everything else, because they give us steam engines and transistors and change everyone’s lives for the better.

Then again, if I had fallen victim to a superstimulus, I’d say that anyway, right?

*cue spooky music*

The Point of a Model

I’ve been reading more lately, partially for the obvious reasons. Mostly, I’ve been catching up on books everyone else already read.

One such book is Daniel Kahneman’s “Thinking, Fast and Slow”. With all the talk lately about cognitive biases, Kahneman’s account of his research on decision-making was quite familiar ground. The book turned out to more interesting as window into the culture of psychology research. While I had a working picture from psychologist friends in grad school, “Thinking, Fast and Slow” covered the other side, the perspective of a successful professor promoting his field.

Most of this wasn’t too surprising, but one passage struck me:

Several economists and psychologists have proposed models of decision making that are based on the emotions of regret and disappointment. It is fair to say that these models have had less influence than prospect theory, and the reason is instructive. The emotions of regret and disappointment are real, and decision makers surely anticipate these emotions when making their choices. The problem is that regret theories make few striking predictions that would distinguish them from prospect theory, which has the advantage of being simpler. The complexity of prospect theory was more acceptable in the competition with expected utility theory because it did predict observations that expected utility theory could not explain.

Richer and more realistic assumptions do not suffice to make a theory successful. Scientists use theories as a bag of working tools, and they will not take on the burden of a heavier bag unless the new tools are very useful. Prospect theory was accepted by many scholars not because it is “true” but because the concepts that it added to utility theory, notably the reference point and loss aversion, were worth the trouble; they yielded new predictions that turned out to be true. We were lucky.

Thinking Fast and Slow, page 288

Kahneman is contrasting three theories of decision making here: the old proposal that people try to maximize their expected utility (roughly, the benefit they get in future), his more complicated “prospect theory” that takes into account not only what benefits people get but their attachment to what they already have, and other more complicated models based on regret. His theory ended up more popular, both than the older theory and than the newer regret-based models.

Why did his theory win out? Apparently, not because it was the true one: as he says, people almost certainly do feel regret, and make decisions based on it. No, his theory won because it was more useful. It made new, surprising predictions, while being simpler and easier to use than the regret-based models.

This, a theory defeating another without being “more true”, might bug you. By itself, it doesn’t bug me. That’s because, as a physicist, I’m used to the idea that models should not just be true, but useful. If we want to test our theories against reality, we have a large number of “levels” of description to choose from. We can “zoom in” to quarks and gluons, or “zoom out” to look at atoms, or molecules, or polymers. We have to decide how much detail to include, and we have real pragmatic reasons for doing so: some details are just too small to measure!

It’s not clear Kahneman’s community was doing this, though. That is, it doesn’t seem like he’s saying that regret and disappointment are just “too small to be measured”. Instead, he’s saying that they don’t seem to predict much differently from prospect theory, and prospect theory is simpler to use.

Ok, we do that in physics too. We like working with simpler theories, when we have a good excuse. We’re just careful about it. When we can, we derive our simpler theories from more complicated ones, carving out complexity and estimating how much of a difference it would have made. Do this carefully, and we can treat black holes as if they were subatomic particles. When we can’t, we have what we call “phenomenological” models, models built up from observation and not from an underlying theory. We never take such models as the last word, though: a phenomenological model is always viewed as temporary, something to bridge a gap while we try to derive it from more basic physics.

Kahneman doesn’t seem to view prospect theory as temporary. It doesn’t sound like anyone is trying to derive it from regret theory, or to make regret theory easier to use, or to prove it always agrees with regret theory. Maybe they are, and Kahneman simply doesn’t think much of their efforts. Either way, it doesn’t sound like a major goal of the field.

That’s the part that bothered me. In physics, we can’t always hope to derive things from a more fundamental theory, some theories are as fundamental as we know. Psychology isn’t like that: any behavior people display has to be caused by what’s going on in their heads. What Kahneman seems to be saying here is that regret theory may well be closer to what’s going on in people’s heads, but he doesn’t care: it isn’t as useful.

And at that point, I have to ask: useful for what?

As a psychologist, isn’t your goal ultimately to answer that question? To find out “what’s going on in people’s heads”? Isn’t every model you build, every theory you propose, dedicated to that question?

And if not, what exactly is it “useful” for?

For technology? It’s true, “Thinking Fast and Slow” describes several groups Kahneman advised, most memorably the IDF. Is the advantage of prospect theory, then, its “usefulness”, that it leads to better advice for the IDF?

I don’t think that’s what Kahneman means, though. When he says “useful”, he doesn’t mean “useful for advice”. He means it’s good for giving researchers ideas, good for getting people talking. He means “useful for designing experiments”. He means “useful for writing papers”.

And this is when things start to sound worryingly familiar. Because if I’m accusing Kahneman’s community of giving up on finding the fundamental truth, just doing whatever they can to write more papers…well, that’s not an uncommon accusation in physics as well. If the people who spend their lives describing cognitive biases are really getting distracted like that, what chance does, say, string theory have?

I don’t know how seriously to take any of this. But it’s lurking there, in the back of my mind, that nasty, vicious, essential question: what are all of our models for?

Bonus quote, for the commenters to have fun with:

I have yet to meet a successful scientist who lacks the ability to exaggerate the importance of what he or she is doing, and I believe that someone who lacks a delusional sense of significance will wilt in the face of repeated experiences of multiple small failures and rare successes, the fate of most researchers.

Thinking Fast and Slow, page 264

In Life and in Science, Test

Think of a therapist, and you might picture a pipe-smoking Freudian, interrogating you about repressed feelings. These days, you’re more likely to meet a more modern form of therapy, like cognitive behavioral therapy (or CBT for short). CBT focuses on correcting distorted thoughts and maladaptive behaviors: basically, helping you reason through your problems. It’s supposed to be one of the types of therapy that has the most actual scientific evidence behind it.

What impresses me about CBT isn’t just the scientific evidence for it, but the way it tries to teach something like a scientific worldview. If you’re depressed or anxious, a common problem is obsessive thoughts about what others think of you. Maybe you worry that everyone is just putting up with you out of pity, or that you’re hopelessly behind your peers. For many scientists, these are familiar worries.

The standard CBT advice for these worries is as obvious as it is scary: if you worry what others think of you, ask!

This is, at its heart, a very scientific thing to do. If you’re curious about something, and you can test it, just test it! Of course, there are risks to doing this, both in your personal life and in your science, but typical CBT advice applies surprisingly well to both.

If you constantly ask your friends what they think about you, you end up annoying them. Similarly, if you perform the same experiment over and over, you can keep going until you get the result you want. In both cases, the solution is to commit to trusting your initial results: just like scientists pre-registering a study, if you ask your friends what they think you need to trust them and not second-guess what they say. If they say they’re happy with you, trust that. If they criticize, take their criticism seriously and see if you can improve.

Even then, you may be tempted to come up with reasons why you can’t trust what your friends say. You’ll come up with reasons why they might be forced to be polite, while they secretly still hate you. Similarly, as a scientist you can always come up with theories that get around the evidence: no matter what you observe, a complicated enough chain of logic can make it consistent with anything you want. In both cases, the solution is a dose of Occam’s Razor: don’t fixate on an extremely complicated explanation when a simpler one already fits. If your friends say they like you, they probably do.