A recent study asked subjects to give their overall impression of other people based entirely on a photograph of their face. In one group the political ideology of the person in the photograph was disclosed (and was sometimes true and sometime not true), and in another group the political ideology was not disclosed. The question the researchers were asking is whether thinking you know the political ideology of someone in a photo affects your subjective impression of them. Unsurprisingly, it did. Photos that were labeled with the same political ideology (conservative vs liberal) were rated more likable, and this effect was stronger for subjects who have a higher sense of threat from those of the other political ideology.

This question is part of a broader question about the relationship between facial characteristics and personality and our perception of them. We all experience first impressions – we meet someone new and form an overall impression of them. Are they nice, mean, threatening? But if you get to actually know the person you may find that your initial impression had no bearing on reality. The underlying question is interesting. Are there actual facial differences that correlate with any aspect of personality? First, what’s the plausibility of this notion and possible causes, if any?

The most straightforward assumption is that there is a genetic predisposition for some basic behavior, like aggression, and that these same genes (or very nearby genes that are likely to sort together) also determine facial development. This notion is based on a certain amount of biological determinism, which itself is not a popular idea among biologists. The idea is not impossible. There are genetic syndromes that include both personality types and facial features, but these are extreme outliers. For most people the signal to noise ratio is likely too small to be significant.  The research bears this out – attempts at linking facial features with personality or criminality have largely failed, despite their popularity in the late 19th and early 20th centuries.

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I get lots of e-mail, sometimes from people who want to convince me that their pet theory has merit – in explicit hope that I will champion their cause and spread their theory. They are always disappointed. The exchange is always the same, almost eerily so, as if they are all following the same script. I think to an extent they are – they are all absorbing the same narrative from the culture. So here is my generic response to all cranks, past and future.

Dear Crank,

I use that term not as a personal attack, but as an accurate description of your behavior. I want you to understand why that behavior is not serving you well, and what you can do the escape from a cycle of self-destructive, and frankly annoying, behavior. Hey – you e-mailed me, you jumped up in front of me waving your hands in order to get my attention. Well, you got it. And now I am going to do you a massive favor. I am going to give you a tiny slice of the attention you are so clearly desperate for and explain to you why you are a crank.

I understand you have a theory with which you are very impressed, and it includes a lot of math and facts and details. You may even have some scientific education and background. But if you think you have somehow seen through the fog, and have proven that the world’s scientists have all been hopelessly wrong for the last century or so, then you are likely suffering from not only a lack of proper humility, but overwhelming hubris. You may think that you have proven with one devastating argument that evolution is impossible, or global warming is not real, or that you have created free-energy, cured cancer, or changed everything we thought we knew about history (or whatever), but you haven’t.

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A new Pew survey updates their data on American’s trust in scientists. The “good news” is that overall, trust remains high, with 77% saying they trust scientists a great deal or a fair amount, and only 23% not too much or not at all. Actually, when you think about it these numbers are still pretty bad, but they seem good because our expectations are so low. More than one in five people don’t trust scientists. For more perspective, that 77% figure is the same for the military. The highest rated group was medical scientists at 80%. Elected officials were at 28%.

These numbers are also fairly stable over time. Interestingly they did bump up a bit during the pandemic, but then quickly returned to their historical levels. Some argue that these numbers are pretty good and we shouldn’t “freak out about the minority.” I disagree – not that we should freak out, but we do need to take these numbers seriously, and they are not necessarily good news.

One reason I am still concerned about these numbers is that there is a pretty significant partisan divide. Recent years have Democrats at around 90% with Republicans around 63%. More than a third of one major political party does not trust scientists, and they seem to be the political center of the party. This gets even worse if you look at the question of whether or not scientists should play an active role in policy debates. Only 66% of Democrats say yes, and only 29% of Republicans (down from 75 and 43 respectively). This, to me, is very telling. It’s one thing to say you trust scientists, but what does that mean that you also don’t want them to play an active role in policy?

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Humanity has an uncanny ability to turn any new potential boon into con. The promise of stem cell technology quickly spawned fraudulent stem-cell clinics to exploit the desperate. There is snake oil based on lasers, holograms, and radio waves. Any new tech or scientific discovery becomes a marketing scam, going back to electromagnetism and continuing today with “nanotechnology”. There is some indication that artificial intelligence (AI) will be no exception.

I am a big fan of AI technology, and clearly it has reached a turning point where the potential applications are exploding. The basic algorithms haven’t changed, but with faster computers, an internet full of training data, and AI scientists finding more ways to cleverly leverage the technology, we are seeing more and more amazing applications, from self-driving cars to AI art programs. AI is likely to be increasingly embedded in everything we do.

But with great potential comes great hype. Also, for many people, AI is a black box of science and technology they don’t understand. It may as well be magic. And that is a recipe for exploitation. A recent BBC article, for example, highlights to risks of relying on AI in evaluating job applicants. It’s a great example of what is likely to become a far larger problem.

I think the core issue is that for many people, those for whom AI is mostly a black box, there is the risk of attributing false authority to AI and treating it like a magic wand. Companies can therefore offer AI services that are essentially pure pseudoscience, but since it involves AI, people will buy it. In the case of hiring practices, AI is being applied to inherently bogus analysis, which doesn’t change the nature of the analysis, it just gives it a patina of impeachable technology, which makes it more dangerous.

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Science is fun, interesting, and empowering, but it is also hard, especially at advanced levels. Even at a basic level, science forces you to think clearly, precisely, logically, and objectively. It therefore challenges our preconceptions, our biases, our hopes and desires and replaces these things with indifferent reality. Science becomes progressively tricky the more advanced it becomes, requiring an increasing fund of knowledge and mastery over subtle concepts and technical skills in order to be able to take the next step. At the cutting edge of science, nothing short of years of dedicated study is necessary to engage meaningfully with the enterprise of advancing human scientific knowledge. You also have to be able to engage productively with a community of scientists, all picking apart each other’s work.

It’s for these reasons that there is a lot of bad science out there. There are also those who prioritize things other than the pursuit of scientific knowledge, such as money, fame, or advancing an ideology. Many people mean well, but simply get the science wrong. Even successful scientists can make egregious errors, stubbornly stick to false ideas, or let their own ideology get in the way. So what is the average science enthusiast to do? Unless you have a fairly high level of scientific expertise in general and also in a specific field, you cannot hope to engage with the cutting edge of that field. To some extent, you have to trust the experts, but what if the experts disagree, or some of them are just wrong?

There is no easy answer to this, but there are skills and methods other than actual expertise in a specific field that can help a layperson have a pretty good idea which experts to listen to. This requires some scientific literacy, especially about how proper science operates. It also requires a certain amount of critical thinking skills – knowing something about logic, self-deception, and the nature of evidence. Further, we can learn to recognize the different types of pseudoscience and pseudoscientific behaviors, which can act as reliable red-flags to help spot fake science. Recently promoters of the Electric Universe have appeared in the comments to this blog, and this is a good opportunity to review these red flags.

The idea of the electric universe (EU) is that electromagnetism actually does most of the large-scale heavy lifting when it comes to the structure of the cosmos, displacing gravity as the main long-distance force. There are different flavors of EU, with some doing away with gravity completely, and others allowing for some gravity (to help explain phenomena EU can’t) but still relegate it to a minor role. One major example is that EU proponents believe stars are fueled by electromagnetism, and not by gravity-induced fusion. Here are two great videos that give a concise summary of the history of EU belief and why it is complete and utter nonsense. But I will review the major problems with EU and use them as examples of crank pseudoscience.

Crank pseudoscience is a flavor of pseudoscience that operates at a technically sophisticated level, but is missing some of the key elements of actual science that doom proponents to absurdity. But it also contains many of the generic features of pseudoscience. Let’s review, starting with features more typical of crank pseudoscience.

Does not engage meaningfully with the scientific community.

Science is a collaborative effort, especially at the advanced cutting edge level. This is because it is so difficult at this level, you need the self-corrective process of peer-review, rejection of error, criticism of wrong ideas, challenges for evidence and by alternative theories, etc. Without this self-corrective process, fringe groups or individuals tend to drift off from reality into a fantasy land of their own creation, although gilded with the superficial trappings of science. EU proponent Montgomery Childs exemplifies this in an interview (in the second video above) when he tries lamely to justify not bothering to publish any of his findings in scientific journals. Actual experts in plasma physics and cosmology therefore just ignore his fringe work – unless they have data to look at, they don’t have much of a choice. This is a core feature of crank pseudoscience – cranks tend to toil alone or in small fringe echochambers and not engage with proper experts.

Work outside their actual area of expertise (if they have one).

Often we see scientists or engineering getting into crank science when they venture beyond their specific area of expertise. Sometimes this is just hubris – in fact we joke about the Nobel Prize effect, where some Nobel Prize winners go on to support pseudoscience later in their career. There is also an aging-scientist effect where researchers toward the end of their career start looking at their legacy, or lack of one, and want to make a big splash somewhere. Some choose a small fringe pond where their credentials make them a big fish, and start promoting nonsense. The problem, of course, if that being an expert in one area does not equip you to contradict actual experts in a separate field. Electrical engineers are not cosmologists or physicists. It is therefore helpful to see what the most appropriate experts say about a theory, not just anyone with letters after their name. Actual experts reject the EU as completely nonsense (with good reason), and its proponents are all in unrelated fields.

Make grandiose claims while minimizing actual scientific knowledge.

The EU claims to overhaul much of science, which is itself a red flag. It is hard to prove that established science is all wrong, and it’s getting harder as science advances and the foundational concepts of science are increasingly supported by evidence and derivative theories. What cranks often do is grossly exaggerate what is currently unknown in a scientific field, or the meaning of anomalies, and they downplay what is known with confidence. This often become simply lying, making boldly false claims about the state of the science. EU proponents, for example, ignore or deny the evidence for the Big Bang, black holes, stellar fusion, and gravity. The claim that they have overturned pretty much all of astrophysics, stellar astronomy, General Relativity, and more – all on the flimsiest of pretexts. In other words, they reject theories supported by a mountain of evidence, and replace them with theories that have (at best) an ant hill.

They don’t actually explain 0r predict anything.

Another core feature of science is that it makes testable predictions. What this means is that there has to be some way to determine if one theory is more correct than another, because they make different predictions about what we will observe in the universe or the result of experiments. Scientific theories also should have explanatory power (it can explain what we see) – but this is actually necessary but insufficient feature of science. Astrology has explanatory power – if you are willing to just make up BS explanations for stuff. It’s easy, and pattern-seeking humans are good at, finding explanations of stuff. The problem with EU is that it really does neither – predict or explain. In fact, shifting from current cosmological theories to EU would be a massive step backwards. EU cannot explain a ton of established phenomena that are well explained by current theories, such as the evidence for black holes or dark matter, the lifecycle of stars, the existence of neutrinos from stellar fusion, and many more. There are also fundamental problems with EU, such as the known behavior of electromagnetism and charged particles. What EU proponents do, rather, is simply hunt for patterns, and then make very superficial connections between some aspect of EU theory and some astronomical phenomenon.

This is what triggered some of the comments – the regular rings of dust found around WR140, caused by the periodicity of the wind-binary star system. EU proponents said – look, concentric rings. We see those in the plasma dohickey thing. They then count that as a “prediction” when it was actually just retrofitting, and not very well. They falsely call the rings “perfect” when it is the very imperfections in the rings that can be accounted for by the astronomical explanation.

Portray the scientific community as a conspiracy of the small-minded.

If you have a nonsensical fringe theory and don’t publish your findings (except in fringe journals created for that purpose), it’s likely that the broader scientific community with ignore or reject your claims. They should – you have not earned their assent by demonstrating your claims with objective and publicly available evidence. When that happens, cranks universally claim they are the victim of a conspiracy. They don’t self-correct, address legitimate criticisms, recognize the shortcomings of their theories, do better experiments or, in short, engage in legitimate science. They cry foul. They say something to the effect that “mainstream” science is all a conspiracy, and scientist are simply too dumb or too scared to recognize their towering genius. This is the point that self-comparisons to Galileo or Einstein are typically brought out.

EU proponents do this in spades. There is a large, vibrant, world-wide community of astrophysicists, all at different parts of their career, in different countries and institutions, just trying to figure out how the universe works and hopefully make a name for themselves doing so. Yet a few fringe scientists, without the proper expertise, allege they have proven all of them hopelessly wrong, because they are all biased or don’t know what they are doing. And they are stubbornly not convinced by silly superficial evidence its proponents won’t bother to publish. Imagine!

Research into conspiracy beliefs reveals that there are basically two kinds of people who believe in conspiracies. One type is the dedicated conspiracy theorist. For them, the conspiracy is what they are interested in. They never met a conspiracy theory they didn’t like, and they believe pretty much all of them. It’s part of their cognitive makeup. Others, however, are opportunistic conspiracy theorists – they believe one or two conspiracies that align with their ideology or tribe. Rosie O-Donnell is a 9/11 truther probably because it aligns with her politics. (As and aside, I can’t help thinking of her “fire melt steel” quote every time I see someone burn their steel on Forged in Fire.)

We are now facing a new conspiracy that largely follows the opportunistic paradigm, the notion that the 2020 election was stolen from Trump due to massive coordinated voter fraud. Persistently, surveys show that about 70% of Republicans feel that Biden was not legitimately elected. This is still a minority of Americans, about 30% total, but it represents a substantial political movement. The reasons for the popularity of this conspiracy theory are complex and debated, including a general rise in conspiracy claims surrounding elections (on both sides), the closeness of the election, the fact of the “red mirage” that was later wiped away, and of course the fact that Trump himself has been vehemently promoting the “big lie”.

I would note, however, that belief in conspiracies itself is not increasing over time. A recent study shows that conspiracy belief is essentially flat over long periods of time. The stolen election is a blip, an anomaly caused by the factors I listed above. I also note that while doubt in election results has been increasing over the last two decades, the 2020 stolen election belief is of an entirely different order of magnitude. This is not just some whining on the fringe – this is now a core political movement.

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Why do societies collapse? This is an interesting question, and as you might imagine the answer is complex. There are multiple internal and external reasons, but a core features seems to be that a combination of factors were simultaneously at work – a crisis that the society failed to deal with adequately because of dysfunctional institutions and political infrastructure. All societies face challenges, but successful ones solve them, or at least make significant adjustments. There are also multiple ways to define “collapse”, which does not have to involve complete extinction. We can also add political or institutional collapse, where, for example, a thriving democracy collapses into a dictatorship.

There are many people concerned that America is facing a real threat that could collapse our democracy. The question is – do we have the institutional vigor to make the appropriate adjustments to survive these challenges? Sometimes, by the time you recognize a serious threat it’s too late. At other times, the true causes of the threat are not recognized (at least not by a majority) and therefore the solutions are also missed. So the question is, to the extent that American democracy is under threat, what are the true underlying causes?

This is obviously a complex question that I am not going to be able to adequately address in one blog post. I would like to suggest, however, that social media algorithms are at least one factor contributing to the destabilizing of democracy. It would be ironic if one of the greatest democracies in world history were brought down in part by YouTube algorithms. But this is not implausible.

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How people make decisions has been an intense area of study from multiple angles, including various disciplines within psychology and economics. Here is a fascinating article that provides some insight into the state of the science addressing this broad question. It is framed as a meta-question – do we have the right underlying model that properly ties together all the various aspects of human decision-making? It is not a systematic review of this question, and really just addresses one key concept, but I think it helps frame the question.

The title reflects the author’s (Jason Collins) approach – “We don’t have a hundred biases, we have the wrong model.” The article is worth a careful read or two if you are interested in this topic, but here’s my attempt at a summary with some added thoughts. As with many scientific phenomena, we can divide the approach to human decision making into at least two levels, describing what people do and an underlying theory (or model) as to why they behave that way. Collins is coming at this mostly from a behavioral economics point of view, which starts with the “rational actor” model, the notion that people generally make rational decisions in their own self-interest. This model also includes the premise the individual have the computational mental power to arrive at the optimal decision, and the willpower to carry it out. When research shows that people deviate from a pure rational actor model of behavior, those deviations are deemed “biases”. I’ve discussed many such biases in this blog, and hundreds have been identified – risk aversion, sunk cost, omission bias, left-most digit bias, and others. It’s also recognized that people do not have unlimited computational power or willpower.

Collins likens this situation to the Earth-centric model of the universe. Geocentrism was an underlying model of how the universe worked, but did not match observations of the actual universe. So astronomers introduced more and more tweaks and complexities to explain these deviations. Perhaps, Collins argues, we are still in the “geocentrism” era of behavioral psychology and we need a new underlying model that is more elegant, accurate, and has more predictive power – a heliocentrism for human decision-making. He acknowledges that human behavior it too complex and multifaceted to follow a model as simple and elegant as, say, Kepler’s laws of planetary motion, but perhaps we can do better than the rational actor model tweaked with many biases to explain each deviation.

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This is a great idea, and in fact is long overdue. The NIH is awarding various grants to establish educational materials and centers to teach principles of scientific rigor to researchers. This may seem redundant, but it absolutely isn’t.

At present principles of research are taught in basic form during scientific courses, but advanced principles are largely left to individual mentorship. This creates a great deal of variability in how well researchers really understand the principles of scientific rigor. As a result, a lot of research falls short of scientific ideals. This creates a great deal of waste in the system. NIH, as a funding institution, has a great deal of incentive to reduce this waste.

The primary mechanism will be to create teaching modules that then can be made freely available to educational and research institutions. These modules would cover:

biases in research; logical fallacies around causality; how to develop hypotheses; designing literature searches; identifying experimental variables; and reducing confounding variables in research.

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We are still relatively early in the investigation of possible fraud or misconduct relating specifically to amyloid beta (Aβ) in Alzheimer’s disease, so consider this all preliminary. However, independent analysis does allegedly find some highly suspect data in a series of images used in publications by one particular researcher, Sylvain Lesné of the University of Minnesota.  Science magazine has done a good review of what we know at this time. I will quickly review the status of this investigation and what the whole episode means for scientific research in general, and Alzheimer’s research in particular.

For background, Alzheimer’s disease (AD) is a complex neurodegenerative disease and the major cause of dementia, a chronic loss of global cognitive function, especially memory. AD has been extremely frustrating from a scientific and medical point of view. While there is a great deal of research and it has made impressive progress in understanding the pathophysiology of the disease, we remain without a single coherent “smoking gun” cause of the disease. The problem is (as with other neurodegenerative diseases) that there is a lot happening when brain cells age and die. The trick has been to not only identify markers of AD in the brain, but to understand what role those markers play in the disease. Specifically, are they driving the disease, or are they just a consequence of it?

In medicine there are two main ways to test a causal hypothesis for a correlational marker – can we transfer the disease by transferring the marker, and can we cure the disease by treating the marker? That last question is the ultimate goal of medical research, to find a cure, or at least a disease-modifying treatment. If we can prevent, slow down, stop the progression, or even reverse AD by interfering with one aspect of the disease, then that aspect is likely what’s driving it. But also – we have effective treatments, and everyone is happy.

This is where AD research gets very frustrating. Despite having many pathological clues to follow, researchers have been unable to close the loop – to find a disease-modifying treatment based on our basic science knowledge of AD. This leads to a lot of head-scratching and debate – is AD caused many by the build up of toxic proteins, by impaired neuronal function, by inflammation, or something else? One of the prominent theories of AD is that a major contributor to the disease is a build up of toxic protein, specifically amyloid beta (Aβ). But the Aβ theory has not led to a cure, which has led to many Aβ skeptics in the Alzheimer’s research community.

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