I don't have quite the same critical perspective as the blogger, but I think there's a certain misguided attitude underlying the phenomena observed by Shor.

Yesterday or the day before I was listening to the radio and someone with a physics background was talking about something (I think quantum entanglement) and started asserting that physics has basically figured out almost everything. This is probably a somewhat unfair paraphrase, but not too unfair.

What irritated me about it was the assumption that, if most of your predictions are correct, your model is almost entirely correct, and just needs to be tweaked a bit. This is certainly true some of the time, but sometimes those little empirical cracks are what brings down a major paradigm, and leads to another one, one that has the same predictions as in 99% of the cases, but in the other 1% has totally different predictions with very different implications.

This carries over to grant funding, etc. in that the prevailing community often assumes that what they're doing is fine, and all that's left are these little empirical tweaks. That's certainly helpful some of the time, but it seems to dominate too much. Academics needs to leave more room for people to fail at high rates with good ideas, to increase those small percent of times they succeed wildly.

Haha, no. We wish.

Epicycles worked very well and were highly accurate, because, as Fourier analysis later showed, any smooth curve can be approximated to arbitrary accuracy with a sufficient number of epicycles. However, they fell out of favour with the discovery that planetary motions were largely elliptical from a heliocentric frame of reference, which led to the discovery that gravity obeying a simple inverse square law could better explain all planetary motions.

https://en.wikipedia.org/wiki/Deferent_and_epicycle

A theory can explain observations even perfectly well and still be wrong- because the frame of reference is wrong. The worse thing is that you can't figure that out until you've figured out what the correct frame of reference is, and looked at your obsrevations in a new light.

Well strictly speaking, it wasn't wrong. It explained the observations perfectly well. What a heliocentric description brought was a simpler description that illuminated the principles behind it, in a way that enabled us to discover the inverse-square law of gravity, link that to Gauss's theorem for gravitation, explain it even from a more fundamental geometric perspective with general relativity, etc.

Revolutions happen when a new mental model - or frame of reference, or whatever you want to call it - can generate new kinds of math.

The old model is certainly wrong in the sense that it's not a good picture of how reality actually works.

If you really want to, you can still use epicycles for certain kinds of problem, just as you can use Newtonian physics for basic mechanics.

But this is engineering, not physics. These theories are useless for frontier research. They're absolutely wrong in the sense that their lack of completeness means they cannot be used to generate theory[n+1].

How do you distinguish "an entirely imaginary math artifact" from the "principles" that "reality works on"?

(Hint: planetary orbits are not ellipses once you take GR effects into account.)

Not if you define "wrong" as "inaccurate predictions". You can approximate ellipses with circles and epicycles to any desired degree of accuracy by putting in more epicycles. So you can match the predictions of ellipses to any desired accuracy with epicycles.

Also, as I noted, the actual orbits of the planets are not perfect ellipses once GR effects are taken into account. Have you proven mathematically that it is impossible to construct an epicycle model that makes more accurate predictions than perfect ellipses, based on the actual data (which confirms the GR predictions to within current observational accuracy)?

Super interesting. I'm a physics major (graduated) who didn't take GR, so I didn't know this. Want to learn GR now but very likely won't haha.

"It was not until Galileo Galilei observed ... the phases of Venus in September 1610 that the heliocentric model began to receive broad support among astronomers."

According to General Relativity, there's no such thing as a "wrong" frame.

Running through this exercise with some honesty can give one a greater understanding of why our physics is framed the way it is, and why it is that while all sorts of reference frames are valid, "inertial" reference frames are still important on their own merits.

Is there a deeper meaning to "Consider the speed of light in the Andromeda galaxy" that I missed? The speed of light is known to be constant in every reference frame.

You can reformulate all of physics into your Earthly non-inertial reference frame. You can formulate all of physics into a reference frame in which you personally are always stationary! Nothing stops you from doing it, and the physics will work, as much as they ever do (i.e., we know something's wrong with our theories). To the extent that the result is a hideous monstrosity, well, such is my point. Pondering the nature of that hideous monstrosity is something I think worth doing, at least for a bit. Not to the extent of actually writing the equations, though. It brings clarity to why inertial reference frames are so important that we almost consider "inertial reference frame" to be a single atomic word, because non-inertial reference frames are in general not very useful. (In specific they can be.)

But now I understand why Einstein wrote in his last book, after much thinking, that this perspective is wrong. He called it "unthinkable" for a good reason. The model I'm using also has relativity, but with an absolute frame. It also behaves differently in extreme situations like the surface of super massive black holes and and near field of a proton. In fact, I have much more relativity but not everywhere and it's paradox free :)

What if I say there are frames of reference that are irrelevant to discovering the process that generates the observations?

Edit: Um, guys? I genuinely don't know what general relativity says and I didn't get the comment above. It'd be nice if someone explained.

The location, and speed with which you are travelling is what general relativity calls a "frame of reference", and none of them are "correct" or "incorrect", they're just predictors for what observations will be possible from that frame.

then the weirdest part is that one of the consequences is that planetery bodies are large enough for that “speed of light must remain constant” rule to matter in a particular way as to generate a warping of spacetime around them, the geometry of this warp perfectly explaining gravity. or put another way, we stick to the earth because time runs slightly faster at our heads than at our feet.

This youtube video explains it really well:

https://www.youtube.com/watch?v=Xc4xYacTu-E

>> The location, and speed with which you are travelling is what general relativity calls a "frame of reference", and none of them are "correct" or "incorrect", they're just predictors for what observations will be possible from that frame.

OK, I see- "frame of reference" is a technical term, in General Relativity, that refers to your position in space, and determines what you can observe. Instead, I meant "frame of reference" as a more general "point of view" or "frame of mind" - a set of assumptions that give context to any observations and that inform interpretations of them.

Even going by the technical sense of a frame of reference, though, there are frames of reference that will not permit the cocrrect identification of a process that generates a set of observations- or at the very least, they will tend to favour incorrect interpretations of the observations.

I think that is in keeping with what your comment says about a frame of reference in General Relativity allowing a range of physical observations.

Going from observation, that the speed of light is constant, regardless of how fast the light emitter is travelling relative to you, he made that the unbreakable assumption, and made the shape of spacetime flexible to always satisfy a constant speed of light. This theory was then confirmed when the light of a distant star was observed to bend when travelling through the strong gravitational field of our sun during a total solar eclipse.

Therefore the physics described by General Relativity have greater predictive power.

Quantum physics, can also predict everything in general relativity, but doing so is a lot more complicated than using general relativity. However, Quantum Physics can explain things that happen on small scales that General Relativity cannot. Quantum Physics has greater predictive power, but it's more convoluted. Like Epicycles. Einstein didn't like quantum physics and spent a great deal of time trying to debunk it, but, well, he couldn't.

This is all to point out that one should not confuse predictive power with complexity. Ockham's Razor is a rule of thumb that prefers "simpler" explanations for things. But the predictive power of the two competing theories must be equal for that to apply.

My original comment is grounded in an assumption that predictive power is not enough to identify a theory as correct, and neither is simplicity. There's nothing to stop any number of theories to have the same predictive power and the same kind of complexity. Sometimes, it's just very difficult to choose one, above the others.

Did I come across as confusing predictive power with complexity?

EDIT: it's interesting you bring Occam's razor up. It's part of what I'm studying, in the context of identifying relevant information in (machine) learning. There are mathematical results (in the framework of PAC-learning) that say that, basically, the more complex your training data, the more likely you are to overfit to irrelevant details. At that point, you have a model that explains observations perfectly well, but is useless to explain unseen observations (the really unseen ones- not those pretending to be unseen for the puprose of cross-validation).

...iiish. The result is that large hypothesis spaces tend to produce higher error. But, the size of the hypothesis space in statistical machine learning depends on the complexity of the data, as in the number of features. Anyway, I'm fudging it some. I'm still reading up on that stuff.

Unfortunately, the two theories, while both being extremely successful and accurate in their predictions, are incompatible with one another. Quantum Field Theory has successfully combined Quantum Mechanics with Special Relativity, but that is all.

Which is to say: they break under conditions very unlike the every-day universe, which is important but also indicative that they are not that broken.

The incompatibility is important though, because if there's any more card tricks we can do with physics so we can do interesting things, somewhere in that bit of incompatibility is where we must find it.

maybe some day we’ll find the grand unifying theory of the universe.

Also, "frame of reference" has a specific meaning in relativity but it also has a more general meaning regarding the framework within someone understands something. It's pretty clear from the context (imo) that this latter is what was meant in this comment.

"I'm not that kind of geek" is a bit of an in-joke so my bad for using it where the context is missing, but I thought it would work even so. The missing context is that a colleague used to tease me for my deplorable lack of a science background, although we did hit it off in terms of our fantasy and science fiction tastes. So, I was not the science kind of geek, although I was the science fiction and fantasy kind of geek.

Like I don't understand either Australia or Argentina.. but I know that they are not the same!

For one, it seems to assume the algorithm involved is somehow inferentially perfect, which is curious. A lot of this literature is circular, in that it assumes credit from citation patterns, which are flawed, which then taints the whole thing. For another thing, it seems to assume researchers aren't manipulating the perceptual processes being referenced in the article, which is obviously isn't true (that is, that they're not engaging in dishonest hijacking of the credit system).

People with [psycho]somatic symptom disorders, with medically unexplained symptoms, are more likely to report negative side effects in response to placebo, for example.

When I've read about it, the research is often focused on perceived negative symptoms rather than lack of therapeutic effect, but that's just my impression and I suspect both happen.

In fact, one of the problems with the Myers-Briggs is that it is continuously brought up in these discussions, even when experts in the area of behavioral individual differences dismiss it because it is lacking in evidence (and it has never really been dominant, or at least not for decades). There's all sorts of model-testing that lends support to some models (e.g., the Big Five, which is mentioned in the essay) and not the M-B, in terms of its internal empirical characteristics and predictive properties. And they do involve falsifiable predictions of multiple sorts.

The problem is that people complain about nonsense such as the M-B being nothing more than a money-making consulting scam, but then don't take that assertion seriously, in the sense that they assume the consultants are scientists.

It's as if con artists were selling perpetual motion machines, and HR departments started buying them, and then we started complaining about physics being non falsifiable, rather than about HR departments and business administration not understanding physics. It's all strawman arguments.

As an exercise, for example, I recommend someone searching for modern basic research using Myers-Briggs uncritically in mainstream psychology journals. You probably won't find it except for as some kind of deceptive ruse in an experimental protocol.

As for measuring behavior, any measurement throws away information. That's the tension: weight, BMI, blood pressure, temperature (under what pressure?), etc. The problem isn't in the measurement, it's in how that measurement is used and interpreted, and how much information is thrown away.

So, nothing is wrong with getting a measure of emotional-behavioral state. The problem is overgeneralizing from that, across time or situations, overestimating its predictive information, failing to consider uncertainties or biases of measurement, and so forth. BMI is an imperfect summary of someone's physical health, but it does have utility. The danger isn't in BMI per se, it's in assuming it won't change, assuming things about the reasons for a given BMI, ignoring how any given BMI was calculated, and so forth.

I do agree with the person you're responding to that astrology would likely still be considered somewhat scientific if it didn't rely on things that we know to be false. For instance astrology mixes Mercury starting to go backwards as a key player in its predictions. The problem being there that Mercury doesn't go backwards. It was/is an optical illusion based on an inaccurate understanding of our solar system. But outside of getting some things fundamentally wrong astrology is the same as any other unfalsifiable model. Being wrong doesn't matter, and you can just constantly add onto it and claim you're 'refining' it.

Maybe even that geocentric model though is the same story. Part of the reason the geocentric model of our universe lasted so long was because, with the technology at the time, it wasn't completely falsifiable. Mercury needs to go backwards to make this model work? Other planets need to go into crazy floral sharped curvy patterns to make it work? Well okay then I Mercury goes backwards and planets go in floral shaped curvy patterns. If you wanted to suggest a different model, such as a heliocentric one, that'd involve throwing away literally centuries of work and entirely discrediting astrology (which was at one time a pursuit as scholarly as any other) as a science. People blame the church for the geocentric model, but there was much more to it than just that.

I don't think that can be said for characteristics of someone's personality. It's hard to even define them, much less measure them.

The prior state idea seems more accurate, but even that (at least in its extreme state) doesn't seem to me to encapsulate the idea of free will because it disallows the idea of a decision being undetermined and free to decide.

I personally think the notion of free will is fallacious because it's poorly defined, or even undefinable. I admit I could be totally wrong about that, but I think lack of predictability leads to an illusion of free will. It's the same illusion as the god illusion, injecting agency as an explanatory mechanism when there is none, either through chaotic processes, true randomness, or epistemological weaknesses.

That doesn't compute. A decision doesn't do deciding. A decider decides decisions. Any phenomena of "will" necessarily implies contingency on a prior. To ask for non-contingency is to ask for freedom _from_ will.

I certainly think randomness comes into play for sure, but conceptually my personal prior state might include a source of randomness. It could be just one factor, and I might make choices based on my memories and preferences to allow greater or lesser input from that randomness, or I might lack the mental tools to prevent that randomness from manifesting in my actions. At an extreme that might be a form of pathology and then we can talk about the limits of personal responsibility in various circumstances. The idea that my state leads to my decisions still holds though.

I think at some point notions of intervention or change become critical. So, for example, I think implicit in the idea of free will is the idea that an individual can freely choose to change their decision in some repeatability sense, and this change cannot necessarily happen in any other way, such as from outside influence.

Just to make it clear, let's say there's two choices or choice types, A and B. A is "bad" and B is "good," in whatever sense (utilitarian, moral, whatever).

Key to the notion of free will it seems is that one could change, of their own volition, their choice, from A->B or B->A. In practice we can't rewind time or transport to possible worlds in a counterfactual sense, but we do talk about decisions as interchangeable and repeatable. E.g., someone can choose whether or not to take a drug at one point, and then, at a later point, choose again whether or not to take the drug. In one metaphysical sense, those decisions are not the same because circumstances have changed, but we treat them as the same.

I think the idea of free will is that someone could change their decision, to an extent that another person could not. That is, I cannot make you change your choice, only you can.

This is fine at some level, but what if someone wants to change their mind but cannot? E.g., a drug addict or someone trying to lose weight? What about something simpler, like decision under a lapse in attention? How do we define volition or lack thereof?

Or, maybe more importantly, let's say the external individual in question is omniscient. If an omniscient external individual cannot alter your behavior, why would you hold that individual responsible in a free will sense? That is, let's say someone truly wants to change, but an omniscient being could not even help and change them. Why should the non-omniscient individual seeking change be held responsible?

This is all stream-of-consciousness, but I think at some point the notion of free will starts to lead to counterintuitive problems and/or becomes very poorly definable. At some level I suspect it implies not only autonomy but complete agency, which is suspect.

In No Country for Old Men a guy flips a coin to decide if he will kill someone. He chose to flip the coin though - delegating a choice to randomness does not abrogate us of responsibility. By doing so he created the framework in which the outcome arrises, whatever that outcome is. He made it possible, even likely and bears responsibility for that by selecting the set of possible outcomes and the degree of randomness. Also he does this many times, so it wasn't a "random choice to randomly choose", it's a consistent repeated pattern of behaviour that directly emerges from his personal ongoing mental state.

I don't go around randomly killing people and that's a consistent pattern that emerges from my persistent ongoing (if evolving) mental state and it _is_ a free choice. The fact that it's pre-determined is fine, because it means it comes from me.

To some extent yes, our choices and scope of action is constrained by our essential nature, some of which is determined before we are even born. However this doesn't absolve us of all accountability. It simply sets up a framework within which we can discuss what accountability is and how we want to manage it.

This is a difficult issue and I don't have all the answers about accountability, I see my take on it as my starting point for the discussion about it not the end. I believe in rehabilitative rather than retributive justice because of this. Also see my reply to fjuerfilis.

I think that morality, love and justice emerge from human nature. I think that I, my self and my consciousness are emergent properties and I'm fine with that. I think that the purpose of human life is chosen for us by the rules of biology, natural selection, game theory and a host of other factors that, seemingly miraculously, lead me to the conclusion that the philosophical Good Life is desirable and largely attainable.

> If you have a prior state that is in part systematic, and part random, is the randomness per se free will?

Let's please replace random with uncertain. If _part_ of an entangled system is uncertain the _whole_ system is uncertain [1].

> Does that encapsulate the notion of free will?

    free will [2] 
    the power of acting without the constraint of necessity or fate; 
    the ability to act at one's own discretion.

> That is, I cannot make you change your choice, only you can.

Your free will attempts at influencing me to make a certain choice would seem to entangle my state with your's and perhaps change the probability I will make one choice over another.

> If an omniscient external individual cannot alter your behavior,

'omniscient external individual' is a quite an assumption here.

> Why should the non-omniscient individual seeking change be held responsible?

Free will is the _only_ way to hold the individual responsible.

> but I think at some point the notion of free will starts to lead to counterintuitive problems and/or becomes very poorly definable. At some level I suspect it implies not only autonomy but complete agency, which is suspect.

(I may be misunderstanding you here) Free will over a decision must ultimately collapse to a choice made. At that point it is determined reality and no amount of free will can undo it.

You either took the Red pill or the Blue pill. If the decision is never observed the choice was never made ergo it didn't happen, it is not real.

In the spirit of Spinoza [3] I actually find bestowing free will upon particles very intuitive. We then have free will because it is an attribute of our fundamental components. If particles have no free will and are pre-determined we have no free will and are pre-determined. If we have free will then particles must have free will.

Full disclosure, I am an armchair philosopher with an interest in the cross-section with physics.

[1] https://en.wikipedia.org/wiki/Schr%C3%B6dinger%27s_cat [2] https://www.google.com/search?q=define%3A+free+will [3] https://en.wikipedia.org/wiki/Ethics_(Spinoza)

I know I'm in the minority, but I object to the idea of responsibility actually, and prefer to think of change in a kind of "neurobehavioral engineering" or transformative justice sense. That might seem pathological or even psychopathic (which is ironic because I'm anything but); I just mean that I think responsibility (like randomness maybe, at least with reference to free will) is sort of a red herring. It's one of the reasons I'm interested in free will issues, because I think the notion of responsibility (outside of a very strict causal sense, as in "this geological formation is responsible for this waterfall") is misguided, and also shifts focus away from change efforts, toward retribution. To me, punishing an individual for a crime out of retribution makes as much sense as punishing a car for breaking down; I'd prefer to see the individual "fixed" in the same way I'd prefer to see my car fixed. The primary obstacle to the former from my perspective is lack of knowledge, which will diminish rapidly with time whether we as a society want it or not. I think one of the biggest challenges we will face as a society in the next 200 years (assuming we don't disappear or devolve into a dark age) is how to integrate advances in neuroscience and psychology into our sense of justice and responsibility. E.g., if you could change a person completely for the better, is withholding that change unethical? What's the point of retributional justice then? Aren't you just shooting yourself in the foot, societally speaking?

This is all tangential to the paper, but I think issues of free will become critical when you are faced with the possibility of total change in an individual.

My belief in determinism as a driver of free will is predicated entirely on the principle that without that there is no responsibility. Taking out determinism breaks the connection between my self, my persistent state, and my decisions. My choices have to come from me in a deterministic way, or they are not mine. I want to be responsible for my choices.

This is of course a mechanistic interpretation in the sense you describe, so it also leads me away from a retributive justice stance towards a rehabilitative stance even though I strongly believe in responsibility.

If a decision is undetermined, i.e. not determined, how can it be called a decision?

People seem to get fixed on ranked choice voting versus plurality voting (the current system), and what we really need is a movement to change the voting method to something more accurate.

But it's puzzling to me why the discussion seems to highlight ranking rather than approval voting. The only argument I've really heard against it is that people would get confused and not realize they can vote for more than one person. But it seems to me in that case you've just re-implemented plurality voting, and people would figure it out well enough. Just put out a big public ad campaign. People would learn.

Oakland switched their mayoral election to IRV (maybe ten years ago?) and it was so misunderstood that even one of the candidates recommended that his supporters vote for him in every IRV rank position! (Or perhaps he just didn't want to recommend his supporters even think about the other candidates names?)

1. My experience with the frontiers of open access science in my field have been concerning, in that it seems to feed even more off of the social media hype-TED-talk branch of academics that I see as just as much a problem. That is, with traditional closed publishing, you have lack of access to the public and lack of transparency which seems unacceptable, but with very open access platform things can turn into a petty social media popularity contest. Yes, you get your stuff out, but the dynamics can be very different and feel more like a glorified flamewar ala reddit or old-style USENET groups.

Related to this, I think the way peer review plays out in different fields is very different. So, arXiv stuff might seem normal in comp sci, math, stats, but if you ever want to see uptake of that in an applied field, it had better have a rubber stamp of peer review or no one will touch it.

2. Unfortunately, at many universities, at least in the US and the UK, the pressure and nonsense has moved (increased?) from publishing from prestigious journals into grants. That is, the power structures underlying this all are indirect costs (in the US) subsidizing universities. The problems with this are problems in the way grant monies are allocated and awarded, the kind of "slush fund" quality of the indirect costs that afford universities profits, and the vast inequities across disciplines and topic areas in terms of what requires funding and what is popular at any given time (some research, for example, just requires less money to conduct; this should be a good thing for research funding, but is a bad thing from the university perspective because there's less indirect money to siphon off of).

The reason why I bring this up here is because I think the publishing problem and grant problem are kind of linked, but in a way that makes the open access issue kind of missing the target in terms of where the big problems with academics currently are. I worry, for example, that if you move to a model where everyone just publishes whatever anywhere, it turns academics into a giant flamewar, decreases the value of good research per se even more relative to grant receipts (because it's all fuzzy anyway and everyone can post anything to arXiv), etc.

I definitely think academic publishing needs to become totally open. But my current sense is that there isn't a good infrastructure to replace it in many fields, especially the biomedical fields, and pathologies in those areas will just sort of rip what's left of its integrity apart.

To answer your question: in some cases, transferring probabilistic reasoning about discrete states to continuous states, or vice versa, is sort of trivial. But sometimes it becomes somewhat controversial, and often this is because it's unclear how the scale of information maps onto the scale of data, to put it murkily. When it's discrete, you know your observations have specific possible values, which in itself is a chunk of information. But when it's continuous, you have an infinite range of values, and what constitutes "indifference" can be unclear.

Think of a scale (like a kitchen or bathroom scale), for example. The scale will have a certain accuracy within a certain range, and as you go further outside that range, the accuracy will decrease further and further. So, to make an analogy with the water-and-wine paradox, let's say I tell you "here's this container of walnuts, that could be anywhere from 0 to 100kg. What's the probability its mass as measured on this scale is in a certain range?" What would be adhering to the principle of indifference? You could argue it would be a uniform distribution over the numbers from 0 to 100, but you could also say it's somehow uniformly distributed over the distinguishable units of the scale, which will not be uniform from 0 to 100 because the meaningfulness of the scale's numbers will be compressed in its most accurate range, and stretched in its less accurate range, and there will also be issues with machine precision, etc. If you were counting walnuts though, you've kind of implicitly fixed the scale to the nonnegative integers, and assumed your ability to count doesn't get fuzzy at some point. So you assume uniformity on one scale is uniformity on another.

E.g., if you think of Jeffreys prior as being one scaling of indifference, even with a Bernoulli variable, indifference isn't necessarily scaled as a uniform: https://en.wikipedia.org/wiki/Jeffreys_prior.

I think this paradox involves (along with maybe being underspecified or poorly posed) somewhat related information-scale mapping issues, about how you define uniformity and what your "possibility space is" to be sort of Jaynesian about it.

Even if they bring it up to 85% accuracy with 50% base rate, by the time you are dealing with base rates that are more realistic, you're going to run into way more problems than just 1 out of every 7 people.

I don't expect either R or Python to go away either time soon, nor would I want them to, but I would like to see people moving to things like Julia and Nim, which have the same level of expressivity, but are much more performant. I have difficulty imagining many people saying "I love programming in R and Python, but don't like Julia or Nim."

I like Python but at least with stats/numerics there isn't a big reason to move away from R except for specific libraries (especially DL stuff) or front-end integration with web-land (and even then things like Jupyter mitigate against that).

In theory, there are Python and Julia equivalents to RStudio (JupyterLab, Spyder, PyCharm, Juno, whatever) but RStudio is just so, so, so good. A truly great piece of software.

And of course if you have a data pipeline type workflow, and it fits into the Hadleyverse paradigm and isn't too performance intensive, there's nothing better.

It's still in development (mutate and select have PRs) but it's almost there.

https://github.com/queryverse/Query.jl