There is a common style of journalism, that you are almost certainly very familiar with, in which the report starts with a personal story, then delves into the facts at hand often with reference to the framing story and others like it, and returns at the end to the original personal connection. This format is so common it’s a cliche, and often the desire to connect the actual new information to an emotional story takes over the reporting and undermines the facts.

This format reflects a more general phenomenon – that people are generally more interested in and influenced by a good narrative than by dry facts. Or are we? New research suggests that while the answer is still generally yes, there is some more nuance here (isn’t there always?). The researchers did three studies in which they compared the effects of strong vs weak facts presented either alone or embedded in a story. In the first two studies the information was about a fictitious new phone. The weak fact was that the phone could withstand a fall of 3 feet. The strong fact was that the phone could withstand a fall of 30 feet. What they found in both studies is that the weak fact was more persuasive when presented embedded in a story than along, while the strong fact was less persuasive.

They then did a third study about a fictitious flu medicine, and asked subjects if they would give their e-mail address for further information. People are generally reluctant to give away their e-mail address unless it’s worth it, so this was a good test of how persuasive the information was. When a strong fact about the medicine was given alone, 34% of the participants were willing to provide their e-mail. When embedded in a story, only 18% provided their e-mail.

So, what is responsible for this reversal of the normal effect that stories are generally more persuasive than dry facts? The authors suggest that stories may impair our ability to evaluate factual information. This is not unreasonable, and is suggested by other research as well. To a much greater extent than you might think, cognition is a zero-sum game. When you allocate resources to one task, those resources are taken away from other mental tasks (this basic process is called “interference” by psychologists). Further, adding complexity to brain processing, even if this leads to more sophisticated analysis of information, tends to slow down the whole process. And also, parts of the brain can directly suppress the functioning of other parts of the brain. This inhibitory function is actually a critical part of how the brain works together.

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Remember the “Solar Freakin’ Roadways?” The idea was to pave roads with solar cells that would produce electricity for the grid. The power could also be used for LEDs that could serve as traffic lights and warning signals, and the power could melt snow and ice to boot. I wrote about this in 2014 and at the time I was not impressed with the arguments that were being made.

As many people pointed out – there are huge practical problems with this concept. The main problem is that you would have to engineer the solar cells to withstand traffic and all the abuse that roads take. This would likely degrade their efficiency over time, and also make upkeep very expensive. For the money you would be far better off simply installing solar panels on rooftops, or even suspending them over roads or wherever that might make sense.

I wasn’t entirely negative. I liked the idea in theory, just thought there were serious practical hurdles and we need some real-world testing. I also said this:

“It’s also possible that such panels might find a niche use, but not be cost effective for our entire highway infrastructure. For example, they may find a market for private driveways. I would like not to have to plow or shovel my driveway, and it may reduce my energy bills a bit. Also, a driveway takes a lot less abuse than a highway.

Or perhaps parking lots, bike paths, or playgrounds may find a use. Perhaps they will be better for small back roads than highways, or the other way around, or they will be perfect for cities or sidewalks. Maybe airport runways might justify the cost.”

Well now it’s 5 years later, and we have some real-world testing. The largest test was in France, which two years ago installed a 1 kilometer stretch of solar roadway. Le Monde reports that the experiment was a complete failure. The roadway is deteriorating rapidly. A large section had to be completely demolished. Panels come loose and then are broken or dislodged by traffic. Leaves and other debris cover the surface. Also:

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This is a great example of the unintended consequences that can result from making decisions based on scientific conjecture and preliminary hypotheses. In this case, the hypothesis was never a good one. If you are a pet owner, you may have noticed the recent trend toward grain-free dog or cat food. The justification for this trend is the notion that since dogs are essentially wolves, and wolves are pure carnivores, then we should not be feeding our dogs grains. This is basically the paleo diet for dogs.

It should be noted, however, that many carnivores do need to get some plant matter in their diet. They may get this from the stomachs of the herbivores they eat. Wolves will also occasionally eat berries as a minor supplement to their diet. But sure, wolves don’t generally eat grains. But that is not the problematic premise here.

The problem with the grain-free diet claim is that while modern dogs are closely related to wolves, they are not wild wolves. They evolutionarily split from wild wolves 15-40,000 years ago. Over that time their diet has shifted significantly. They no longer hunt in packs, but live off the scraps of human civilization. And they have adapted.

So the grain-free theory is flawed, and we should not base dietary recommendations on theory alone anyway, but actually gather evidence to test those theories. Perhaps we already have, in an unintended ecological experiment. In 2018 the FDA noticed a spike in reported cases of dilated cardiomyopathy (DCM) in dogs. Previous years had 1-3 reported cases per year, in 2018 there were 320, and 2019 is on track to exceed this. This is still a small number compared to the millions of pet dogs in the US, but is likely massive underreporting. There is also likely some reporting bias here – one article on social media might explain the spike, rather than a true increase. But the FDA had to investigate the increase to see if it were real and what the cause might be.

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I confess I have never heard (or at least don’t remember ever hearing) about Weber’s Law (pronouned vayber) until reading about it with this news item. It is the Law of Just Noticeable Differences. It deals with the minimum difference in a stimulus necessary to notice. While clearly established, and there are many hypotheses to explain the phenomenon, there has never been a way to test which hypothesis is correct. The news items relates to new evidence which may provide a mechanism.

Weber’s law applies to all sensory modalities – sight, sound, taste, smell, and tactile sense. For any sensory stimulus there is a minimum difference that a person can notice. For example, if you are visually comparing the length of two lines trying to determine which one is longer, or if you are holding two weights and trying to determine which one is heavier. There is a minimum difference that is necessary to be able to notice. Experimentally this means there is a relationship between the ratio of the difference and the probability of determining the correct answer.

So if you are trying to determine which light is brighter, an experiment may determine that for lights of 100 and 110 lumens there is a 75% chance of correctly detecting which light is brighter. What Weber’s law states is that one this relationship is determined, it holds true no matter what the absolute value of the stimulus is, as long as the ratio is the same. So for lumens of 200 and 220, or 1000 and 1100, there would still be a 75% probability of being correct. The only thing that matters is the ratio.

As you might expect, there is a lot of nuance to the law, such as subtle variations in the math and differences between vertebrates and insects, etc., which I won’t get into. They are not important for the current discussion, but know that they exist.

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This was highly predictable. Of course there are conspiracies surrounding the apparent recent suicide of Jeffrey Epstein while in prison. That’s just background noise now. There are conspiracies about everything. Apparently the two shootings last weekend were false flag operations, because #conspiracies.

Just as predictably, news about the conspiracy theories, how they spread, and how they are treated by the media is itself news. And yes I get the irony that here I am blogging about it. It’s turtles all the way down. I guess in order to have something interesting to say I have to get one level more meta than everyone else – does that do it? Getting meta about being meta?

By now this phenomenon is old news. The traditional editorial filters are no longer in place. They have largely been replaced by algorithms which determine which news items are “trending.” This becomes a self-reinforcing feedback loop that allows the worst information to spread. Of course, this has always happened. Sensationalism and propaganda spread because they are interesting. They break up the mundane monotony of our lives. They are a real-life soap opera.

Jonathan Swift observed in 1710, “Falsehood flies, and the Truth comes limping after it.” There are also several versions of, “A Lie Can Travel Halfway Around the World While the Truth Is Putting On Its Shoes.” The source of this quote, often mistakingly attributed to Mark Twain, is unclear. The point is – the inherent advantage that false but sensational information has in the human mind over prosaic truth has long been observed. And that, of course, is the ultimate medium, the human mind. The external method of spreading false information is incidental to the core phenomenon, but it can influence the speed with which such information spreads and the credibility it is given.

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There is an industry of misinformation fueling climate change denial. It is often fairly sophisticated, and because it is dealing with a highly complex technical area, it’s easy to create an argument that sounds compelling. This results (as if often evidenced right here in the comments) in people who are confident that they are good skeptics and climate fearmongering is all nonsense. Of course they have to simultaneously believe in a rather absurd conspiracy theory regarding the scientific community, but they make that work somehow too.

Here are a couple of recent examples, both of which involve some subtle cherry picking. The first has to do with electric cars, which are frequently opposed by the denialists, in that they oppose subsidies to help bootstrap the market. This involves the “solution aversion” aspect of climate change denial – deniers are really motivated by the proposed solutions to climate change, which goes against either their politics or other interests. The claim that is often made is that producing electric cars has a higher carbon footprint than gasoline cars, and that if you are charging your car off the grid you are probably getting that electricity from fossil fuels. Therefore – electric cars are worse for the environment.

At the very least, I see climate change deniers delight in how stupid this makes the climate change believers appear.  This is a great example of cherry picking, because the two basic facts are correct but they are not the whole picture. Here, for example, is an article posted by Breitbart claiming that batteries are not green, concluding:

One of the authors, Mats-Ola Larsson at IVL, has made a calculation of how long you have to drive a petrol or diesel before it has released as much carbon dioxide as battery manufacturing has caused.

“The result was 2.7 years for a battery of the same size as the Nissan Leaf and 8.2 years for a battery of the Tesla-size.”

Truly the enduring mystery of why Tesla is now more highly valued than such non-Potemkin U.S. car manufacturers as Ford and General Motors grows more mysterious by the hour.

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The details of the conspiracy theory itself are not the most interesting thing about QAnon. The core of this particular conspiracy is that Trump is secretly very competent, that he is investigating a world-wide sex-trafficking, demonic pedophilia ring run by the Democrats, and that Robert Mueller is secretly working with him and the whole Russia investigation is just a cover for this. Further, JFK Jr. faked his death in order to join Trump’s efforts, and is now the real person behind Q, the insider who is leaking information to the public in order to summon the faithful in this epic struggle.

This is all transparent nonsense, but it is no more nonsensical than the notion that the entire Apollo program was faked, that 9/11 was an inside job, or that the Earth is actually flat.

Some have argued that what is different about QAnon is that the deep state faction secretly running the government is this fantasy are the good guy, when is most conspiracies they are the bad guys. But this, I think, is a superficial narrative point. In grand conspiracies the conspiracy theorists are part of a small “woke” army of light trying to expose an even deeper malevolence, and QAnon fits that mold perfectly.

What’s different about QAnon is that it appears to be an evolution of the conspiracy theory into a new kind of phenomenon, one that combines elements from social media, video games, and live-action role playing. Like all conspiracy theories, QAnon offers an alternate version of reality. But in this case believers are more actively engaged. They are just reading and talking about the conspiracy, they are actively engaging in it. The mysterious person Q (not sure if it is actually one person at this point) will drop hints to followers about what is going on or what is about to happen. The Q conspiracy theorists then have to decode these secret messages. But further, Q will give tasks to its followers. These are usually small tasks, such as posting something on Facebook or Tweeting a message. But they could be bigger. They could involve action in meat-space, and even involve violence.

This is part of a more general phenomenon, called internet role-play. This is just another form of fantasy role-playing using a new medium. In the 1970s and 80s table-top roleplaying became popular, with five or so people sitting around a table rolling dice. Then live-action roleplaying took off, with tens to hundreds of people gathering at a camp site or other venue, dressed as their characters, for a weekend of immersive roleplaying. Now, you can engage in a roleplaying game without leaving your computer chair.

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Recent mass shootings have once again fueled discussion about the role of video game violence (VGV) and aggressive behavior. This is an enduring controversy, which is a real scientific controversy (not just a political one) because the research is highly complex.

Part of that complexity is that there is just one question, does VGV cause aggressive behavior – there are many subquestions, and many ways to measure outcomes. Research can focus on whether or not VGV is correlated with aggressive attitudes, aggressive behavior, or with diminished prosocial attitudes or behavior, or empathy towards the victims of violence, or normalizing aggressive or violent behavior. If there is a correlation, then research needs to tease apart what is cause and what is effect. Researchers also have to decide how to measure all of these things, and to consider demographic variables as well as duration and intensity of exposure and duration of any potential effects. Finally there is the issue of confounding factors, always an issue with psychological research – how do we establish the true lines of cause and effect.

Right now there appears to be two basic schools of thought. Anderson and colleagues champion the view that there is strong evidence for not only a correlation between VGV and aggressive behavior, experimental studies have shown that VGV causes aggressive ideation and behavior, and reduces empathy and prosocial behavior. A 2018 meta-analysis shows that these correlations are indeed strong, and exist across experimental and observational studies. These effects are greatest for males and for whites, less so for Asians, and not significant for Hispanics.

The other school is championed by Ferguson and others, who argue that these results are spurious and due to poor research designs. Specifically he argues that the effects are inflated by including measures of aggression that are too mild, and not ultimately meaningful. There is only an effect if you include things like aggressive language, but not if you restrict the definition of aggressive behavior to actual violence. Further, he argues, that confounding factors are not adequately controlled for, and when you do, the effect disappears.

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Are we eating apples wrong? An ABC news headline reads, “If you aren’t eating the whole apple, you might be eating it the wrong way, a study finds.” This reporting is based on this study, which is a comparison of the bacterial content of different parts of apples, and comparing organically grown to conventionally grown apples. The study found that there was a different bacterial composition between the conventional and organic apples, and that the core and seeds of the apples contained about 10 times the bacteria as the flesh. The authors also conclude:

“Moreover, organic apples conceivably feature favorable health effects for the consumer, the host plant and the environment in contrast to conventional apples, which were found to harbor potential food-borne pathogens.”

All the usual problems I often complain about are present with this conclusion, starting with the fact that it is absolutely not justified by the actual data. First, this is a small preliminary study, of the sort that the media should not even report on. At best this type of study can generate a hypothesis to be tested. The researchers compared a grand total of four apples each from two orchards, one organic and one conventional. Right there you can probably see the problem.

All the apples were of one cultivar, so we cannot generalize the findings to other cultivars. But even worse, only two orchards were compared. Even if you sampled a thousand apples from each orchard, you are still only comparing two orchards.  Elisabeth M Bik, a microbiota researcher, already commented on the study, pointing out that –

For example, the orchards could also have different sun exposures, soil characteristics, age of trees, harvesting techniques and storage conditions, etc. These are all parameters that are not associated with organic vs conventional farming, but that could still have a big impact on the microbiome composition.

Exactly. There are many variables, and absolutely no way for the researchers to isolate the organic farming as the one variable that correlates with the changes they saw. Even worse, and I have no idea why they did this, the organic apples were picked and sampled fresh, while the conventional apples were stored in plastic prior to examination. Why introduce another variable like that? Bacterial populations are certain to change over time after harvesting, and based on storage conditions. So – do I have to say it – this study was not comparing apples to apples while they were comparing apples to apples.

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The BBC reports a case in which an artificial intelligence (AI) system is named as a possible patent holder for a new invention, and interlocking food container. Apparently none of the people involved with the invention meet the criteria for being a patent holder, since they did not come up with the actual innovation.

As a result, two professors from the University of Surrey have teamed up with the Missouri-based inventor of Dabus AI to file patents in the system’s name with the relevant authorities in the UK, Europe and US.

That’s an interesting solution. It does seem that international patent law needs to evolve in order to deal with the product of machine learning creativity. I think this reveals what a true game-changer current AI can be. It’s breaking our existing categories and legal framework.

But I don’t want to talk about patent law, about which I have no expertise – I want to talk about AI, about which I also have no expertise (but I do have a keen interest and pay attention to the news). Over the last few years there have been numerous developments that show how powerful machine learning algorithms are becoming. Specifically, they are able to create solutions that the AI programmers themselves don’t fully understand. The Dabus system itself uses one component to generate new ideas, based on being fed noisy input. But then a second component evaluates those ideas and gives the first component feedback. This idea, having two AI systems play off each other, creates a feedback loop that can rapidly iterate and improve a design or solution. So essentially we have two AIs talking to each other, and humans are largely out of the loop.

AI systems have come up with simulations and other solutions that the scientists using the system do not understand. Sometimes they don’t even know how it was possible for the AI to come up with the solutions it did.

Even more interesting, AI systems have developed their own language that they use to communicate with each other, and no human currently understands that language.

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