Placing “self-replicating” and any kind of “bots” in the same sentence immediately raises red flags, conjuring the image of reducing the surface of the world to gray goo. But that is not a concern here, for reasons that will become clear. There is a lot to unpack here, so let’s start with what xenobots are. They are biological machines, little “robots” assembled from living cells. In this case the source cells are embryonic pluripotent stem cells taken from the frog species Xenopus laevis. Researchers at the Allen Discovery Center at Tufts University have been experimenting with assembling these cells into functional biological machines, and have now added self-replication to their list of abilities.

Further, these xenobots replicate in a unique way, by what is known as kinematic self-replication. This is the first instance of this type of replication at the cell or organism level. The researchers point out that life has many ways of replicating itself: “fission, budding, fragmentation, spore formation, vegetative propagation, parthenogenesis, sexual reproduction, hermaphroditism, and viral propagation.” However, all these forms of self-replication have one thing in common – they happen through growth within or on the organism itself. By contrast, kinematic self-replication occurs entirely outside the organism itself, through the assemblage of external source material.

This process has been known at the molecular level, where molecules (like proteins) can guide the assemblage of identical molecules using external resources. However, this process is entirely unknown at the cellular level or above.

In the case of xenobots, the researchers placed them in an environment with lots of individual stem cells. The xenobots spontaneously gathered these stem cells into copies of themselves. However, these copies were not able to replicate themselves, so the process ended after one or a very limited number of generations. In a new study, the researchers set out to design an optimal xenobot that could sustain many generations of self-replication. They did not do this the old-fashioned way, through extensive trial and error. Rather, they used an AI simulation, which calculated for literally months, testing billions of possible configurations. It came up with a simple shape – a sphere with a mouth, looking incredibly like a Pac-Man. These xenobots are comprised of about 3,000 cells. The researchers assembled their xenobot Pac-Men and when placed in an environment with available stem cells they spontaneously herded them into spheres and then into copies of themselves. These copies were also able to make more copies of themselves, and so-on for many generations.

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There are different ways of looking at history. The traditional way, the one most of us were likely taught in school, is mostly as a sequence of events focusing on the state level – world leaders, their political battles, and their wars with each other. This focus, however, can be shifted in many ways. It can be shifted horizontally to focus on different aspects of history, such as cultural or scientific. It can also zoom in or out to different levels of detail. I find especially fascinating those takes on history that zoom all the way out, take the biggest perspective possible and look for general trends.

A recent study does just that, looking at societal factors that drive the development of military technology in pre-industrial societies, covering a span of 10,000 years. They chose military technology for two main reasons. The first is simply convenience – military technology is particularly well preserved in historical records. The second is that military technology is a good marker for overall technology in most societies, and tends to drive other technologies. This remains true today, as cutting edge military technology (think GPS) often trickles down to the civilian world.

As an interesting aside, the researchers relied on Seshat: Global History Databank. This is a massive databank of 200,000 entries on 500 societies over 10,000 years. This kind of data is necessary to do this level of research efficiently, and is a good demonstration of this more general trend in scientific research – in increasing areas of research, it’s all about big data.

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Syukuro Manabe, Klaus Hasselmann, and Giorgio Parisi share this year’s Nobel Prize in Physics for their work increasing our understanding of how complex systems work. This is a powerful tool for understanding the world, which reminds me of previous advances in our understanding of how gases behave.

Gases are a phase of matter in which high energy particles are bouncing around at random. It would be impossible to predict the pathway of any individual gas molecule. However, collectively all of this random complexity follows very predictable laws. Similarly, weather is a very complex system. We can predict weather that is about to happen, but beyond a few days it becomes increasingly difficult. The system is simply too chaotic. However, climate (long term weather trends) follows theoretically predictable patterns. The trick is to see the hidden patterns in the chaos, and that is the work that these three physicists did.

Manabe and Hasselmann share half the prize for their work on climate models:

Syukuro Manabe demonstrated how increased levels of carbon dioxide in the atmosphere lead to increased temperatures at the surface of the Earth. In the 1960s, he led the development of physical models of the Earth’s climate and was the first person to explore the interaction between radiation balance and the vertical transport of air masses. His work laid the foundation for the development of current climate models.

About ten years later, Klaus Hasselmann created a model that links together weather and climate, thus answering the question of why climate models can be reliable despite weather being changeable and chaotic. He also developed methods for identifying specific signals, fingerprints, that both natural phenomena and human activities imprint in the climate. His methods have been used to prove that the increased temperature in the atmosphere is due to human emissions of carbon dioxide.

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It is not uncommon, if you do not like any particular finding of scientific research, to attack the institutions of science or even the very notion of science itself. These kinds of attacks are now common in the anti-vaccine pushback against common sense public health measures, and often from a religious or ideological perspective. It’s not surprising that the false claim that science is just philosophy has reared its head in such writings. The attack on science also tends to have at least two components. The first is a straw man about how scientists are pretending that science is a monolithic perfect and objective entity. This is then followed by the claim that, rather, science is just opinion, another form of subjective philosophy. This position is entirely wrong on both counts.

Here is one example, embedded in a long article loaded with misinformation about vaccines and the COVID pandemic. There is way too much misdirection in this article to tackle in one response, and I only want to focus on the philosophical claims. These are now common within certain religious circles, mostly innovated, at least recently, in the fight against the teaching of evolution. They have already lost this fight, philosophically, scientifically, and (perhaps most importantly) legally, but of course that does not mean they will abandon a bad argument just because its wrong.

First the straw man:

The second consequence of “following science” is that it reinforces one of modernity’s most enduring myths: that “science” is a consistent, compact, institutionally-guaranteed body of knowledge without interest or agenda. What this myth conceals is the actual operation of the sciences—multiple, messy, contingent, and tentative as they necessarily are.

The myth is itself a myth. It exists almost nowhere except in the minds of science deniers and those with an anti-science agenda. Elsewhere the author admits:

As a lay person, unqualified to judge the technical issues, I have concluded only that there might be a legitimate question here, and one that must, necessarily, remain open until time and experience can settle it.

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The ultimate goal of scientific skepticism is to skillfully use a process that has the maximal probability of accepting claims that are actually true and rejecting those that are false, while suspending judgment when an answer is not available. This is an open-ended process and is never complete, although some conclusions are so solid that questioning them further requires an extremely high bar of evidence. There are many components to scientific skepticism, broadly contained within scientific literacy, critical thinking skills, and media savvy. Traditional science communication focuses on scientific literacy (the so-called knowledge deficit model), but in the last few decades there has been copious research showing that this approach is not only not sufficient when dealing with many false beliefs, it may even be counterproductive.

A new study offer more evidence to support this view, highlighting the need to combine scientific literacy with critical thinking in order to combat misinformation and false claims. The study focuses on the effect of trust in science as an independent variable, and combined with the ability to critically evaluate scientific evidence. In a series of four experiments they looked at acceptance of false claims regarding either a fictional virus, or false claims about GMOs and tumors:

Depending on experimental condition, however, the claims contained references to either (a) scientific concepts and scientists who claimed to have conducted research on the virus or GMOs (scientific content), or (b) lay descriptions of the same issues from activist sources (no scientific content).

They wanted to see the effect of citing scientists and research on the acceptance of the false claims. As predicted, referring to science or scientists increased acceptance. They found that subjects who scored higher in terms of trust in science were more likely to believe false claims when scientists were cited – so trust in science made them more vulnerable to pseudoscience. For those with low trust in science, the presence or absence of scientific content had no effect on their belief in the false claims. These results replicated in the first three studies, using the fictional virus and the GMO claims.

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We are approaching two years into this pandemic and we still haven’t proved the origins of the SARS-CoV-2 virus. However, this is not unusual at all, and in itself is not suspicious. It took 13 years to identify the origin of SARS, and we have never identified the origins of some Ebola outbreaks. But what do we know about the origins of SARS-CoV-2? The question has become highly political, which is unfortunate. Let’s review what the actual evidence has to say.

If we go back to the beginning of the pandemic, the early scientific investigation of the virus found that it was 96% identical to a bat coronavirus in the region. Zoonotic spillover is common, and the virus originated in a part of the world with wet markets and close contact with wild animal populations. Direct examination of the virus also did not show any telltale signs of deliberate manipulation. There has been some scientific debate on this topic, but in the end there is general agreement among scientists that there is no smoking gun of genetic manipulation. For these reasons it was concluded early that the most probable origin of COVID was from animals, either directly from bat to human or through an intermediary.

This conclusion was based on examination of the virus itself and the the reservoirs of similar viruses in the region. This was, and by many still is, considered the most likely origin. Researchers have searched for the precise animal origin, and so far have not found it, but that is not in itself unusual or suspicious.

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In the early days of my skeptical activism I and my colleagues often took on some of the classics of pseudoscience, such as UFOs, dowsing, astrology, and ghost-hunting. As a New England-based group we also focused on local pseudoscience, which means ghosts and ghost-hunting. By coincidence we had perhaps the most famous ghost hunters in the world living just a couple towns over from us, Ed and Lorraine Warren. They were made famous by the Amityville Horror case, and more recently by The Conjuring series of movies.

Even 23 years ago, when we encountered the Warrens, they were famous. They made the college circuit with their talks and slide-shows, held ghost-hunting classes, and spawned dozens of breakaway groups over the years. They were clearly the big fish in our little pond, and so we didn’t know what quite to expect when they agreed to allow us to interview and then investigate them. I want to stress this was a collaborative endeavor throughout, although they certainly weren’t happy with our final conclusions.

On our initial visit Ed gave us a tour of his basement museum, which he claimed was the most haunted place in the world. It included that Raggedy Ann doll that is now the focus of The Conjuring movies, which was kept behind a glass case with a stern warning not to open. I was amused that the collection of haunted items includes a D&D handbook, the Unearthed Arcana. We also asked Ed to show us his best piece of evidence after years of hunting ghosts, and without any hesitation he said it was his video of the White Lady of Union Cemetery. This video has now been digitized and uploaded to Youtube, so you can see for yourself what Ed considered his best evidence.

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Misinformation is a booming industry, and that is often exactly what it is. Sometimes it may emerge organically, out of sincere error or misunderstanding. But increasingly misinformation is being weaponized to achieve specific goals. That goal might be to protect the interests of a corporation or industry, to promote a candidate or particular policy position, to engage in a broader culture-war, promote an ideology, or just sell a brand or product. Recently it has become more apparent to me that often there is a common strategy to weaponizing misinformation. It’s likely always been there, but is getting more blatant.

The “misinformation trifecta” combines three synergistic strategies. The first is spreading the misinformation itself, factual claims that are wrong, misleading, fabricated, cherry-picked, or simply indifferent to the truth. This is the “payload”, if you will. For example, claiming that GMOs are harmful to one’s health is simply wrong. There is no evidence to support this, and in fact there is copious evidence that GMO crops are as safe and healthful and their non-GMO counterparts. This bit of information is used to promote a certain ideology (based on the appeal to nature fallacy) and a competitive brand, organic farming. It is often packaged with lots of other bits of misinformation, all woven together into a certain narrative.

Narratives are powerful because they tend to take on a life of their own. They organize misinformation into a story, and people have an easier time understanding, remembering, and relating to stories rather than isolated facts. Narratives also provide a lens through which we view reality. Once you have sold someone on a narrative, they then curate their own misinformation to further support the narrative.

If misinformation itself were the only issue, then the solution would be straightforward. This is the “knowledge deficit” model, where misinformation is corrected with better, more accurate or complete information. Past efforts at public education and countering misinformation have focused on this knowledge deficit approach. This has a limited (but non-zero) effect. It is highly variable depending on the particular topic, but mostly it is inadequate to counter misinformation.

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In science it is not only OK to be wrong, it is an unavoidable and perpetual state – depending, of course, on how you define “wrong”. We lack a complete understanding of the universe, and all of our theories are at best approximations of reality. From this perspective no theory is completely correct, and therefore to some extent is at least somewhat wrong. The idea of progress in science it to become less wrong, knowing that perfect knowledge is not technically possible.

Progress in science is therefore mostly about identifying what facts and ideas we hold that are wrong, exactly how they are wrong, and how we can gather new data or observations that will test those ideas, allow us to refine them, and become one step less wrong.

Some philosophers express this idea as – there is no metaphysical truth in science. What science has is models that predict how the universe will behave. The more accurate and far reaching those predictions, the better the model is. When these models start to break down, because new observations conflict with their predictions, then we have to revise the model to account for the new observations. In this way we make more and more complex, and/or deep models that can make better and better predictions.

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There is definitely something to be said for the neurodiversity perspective – when it comes to brain function there is a wide range of what can be considered healthy. Not all differences should be looked at through the lens of pathology or dysfunction. Some brains may be more typical than others, but that does not mean objectively “normal”, better, or healthier. Like any valid concept it can be taken too far. There are conditions that can reasonably considered to be brain disorders causing objective dysfunction. But the scope of healthy variation is likely far broader than many people assume.

Part of this concept is that brain organization and function includes many trade-0ffs. To some extent this is a simple matter of finite brain resources that are allocated to specific abilities, increase one and by necessity another has to diminish. Also different functions can be at cross-purposes. Extraverts may excel in social situations, but introverts are better able to focus their attention inward to accomplish certain tasks.

In light of this, how should we view the phenomenon of aphantasia, a relative inability to summon a mental image? Like most neurological functions, the ability to have an internal mental image varies along a spectrum. At one end of the extreme are those with a hyperability to recall detailed mental images. At the other are those who may completely lack this ability. Most people are lumped somewhere in the middle. The phenomenon of aphantasia was first described in the 1880s, then mostly forgotten for about a century, and now there is renewed interest partly due to our increased ability to image brain function.

A new study does just that, looking at people across that phantasia spectrum to see how their brain’s differ. Using fMRI they scanned the brains of those with aphantasia, hyperphantasia, and average ability. They found that in neurotypical subject there was a robust connection between the visual cortex (which becomes active when imagining an image) and the frontal cortex, involved in attention and decision-making. That makes sense – this connection allows us to direct our attention inwardly to our visual cortex, to activate specific stored images there. Subjects with aphantasia had a relative lack of these connections. While this is a simple model, it makes perfect sense.

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