In the movie Blade Runner 2049 (an excellent film I highly recommend), Ryan Gosling’s character, K, has an AI “wife”, Joi, played by Ana de Armas. K is clearly in love with Joi, who is nothing but software and holograms. In one poignant scene, K is viewing a giant ad for AI companions and sees another version of Joi saying a line that his Joi said to him. The look on his face says everything – an unavoidable recognition of something he does not want to confront, that he is just being manipulated by an AI algorithm and an attractive hologram into having feelings for software. K himself is also a replicant, an artificial but fully biological human. Both Blade Runner movies explore what it means to be human and sentient.

In the last few years AI (do I still need to routinely note that AI stands for “artificial intelligence”?) applications have seemed to cross a line where they convincingly pass the classic Turing test. AI chatbots are increasingly difficult to distinguish from actual humans. Overall, people are only slightly better than chance at distinguishing human from AI generated text. This is also a moving target, with AIs advancing fairly quickly. So the question is – are we at a point where AI chatbot-based apps are good enough that AIs can serve as therapists? This is a complicated question with a few layers.

The first layer is whether or not people will form a therapeutic relationship with the AI, in essence reacting to them as if they are a human therapist. The point of the Blade Runner reference was just to highlight what I think the clear answer is – yes. Psychologists have long demonstrated that people will form emotional attachments to inanimate objects. We also imbue agency onto anything that acts like an agent, even simple cartoons. We project human emotions and motivations onto animals, especially our pets. People can also form emotional connections to other actual people purely online, even exclusively through text. This is just a fact of neuroscience – our brains do not need a physical biological human in order to form personal attachments. Simply acting or even just looking like an agent is sufficient.

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I was away on vacation the last week, hence no posts, but am now back to my usual schedule. In fact, I hope to be a little more consistent starting this summer because (if you follow me on the SGU you already know this) I am retiring from my day job at Yale at the end of the month. This will allow me to work full time as a science communicator and skeptic. I have some new projects in the works, and will announce anything here for those who are interested.

On to today’s post – I recently received an e-mail from Janyce Boynton, a former facilitator who now works to expose the pseudoscience of facilitated communication (FC). I have been writing about this for many years. Like many pseudosciences, they rarely completely disappear, but tend to wax and wane with each new generation, often morphing into different forms while keeping the nonsense at their core. FC has had a resurgence recently due to a popular podcast, The Telepathy Tapes (which I wrote about over at SBM). Janyce had this to say:

I’ll be continuing to post critiques about the Telepathy Tapes–especially since some of their followers are now claiming that my student was telepathic. Their “logic” (and I use that term loosely) is that during the picture message passing test, she read my mind, knew what picture I saw, and typed that instead of typing out the word to the picture she saw.

I shouldn’t be surprised by their rationalizations. The mental gymnastics these people go through!

They’re also claiming that people don’t have to look at the letter board because of synesthesia. According to them, the letters light up and the clients can see the “aura” of each color. Ridiculous. I haven’t been able to find any research that backs up this claim. Nor have I found an expert in synesthesia who is willing to answer my questions about this condition, but I’m assuming that, if synesthesia is a real condition, it doesn’t work the way the Telepathy Tapes folks are claiming it does.

For quick background, FC was created in the 1980s as a method for communicating to people, mostly children, who have severe cognitive impairment and are either non-verbal or minimally verbal. The hypothesis FC is based on is that at least some of these children may have more cognitive ability than is apparent but rather have impaired communication as an isolated deficit. This general idea is legitimate, and in neurology we caution all the time about not assuming the inability to demonstrate an ability is due purely to a cognitive deficit, rather than a physical deficit. To take a simple example, don’t assume someone is not responding to your voice because they have impaired consciousness when they could be deaf. We use various methods to try to control for this as much as possible.

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About 30-40% of the produce we grow ends up wasted. This is a massive inefficiency in the food system. It occurs at every level, from the farm to the end user, and for a variety of reasons. This translates to enough food worldwide to feed 1.6 billion people. We also have to consider the energy that goes into growing, transporting, and disposing of this wasted food. Not all uneaten food winds up in landfills. About 30% of the food fed to animals is food waste. Some food waste ends up in compost which is used as fertilizer. This still is inefficient, but at least it is recycled.

There is a huge opportunity for increased efficiency here, one that can save money, reduce energy demand, reduce the carbon footprint of our food infrastructure, and reduce the land necessary to meet our nutritional needs. Increased efficiency will be critical as our populations grows (it is estimated to likely peak at about 10 billion people). But there is no one cause of food waste, and therefore there is no one solution. It will take a concerted effort in many areas to minimize food waste, and make the best use of the food that does not get eaten by people.

One method is to slow food spoilage. The longer food lasts after it has been harvested, the less likely it is to be wasted due to spoilage. Delaying spoilage also makes it easier to get food from the farm to the consumer, because there is more time for transport. And delayed spoilage, if sufficient, may reduce dependence on the cold chain – an expensive and energy dense process by which food must be maintained in refrigerated conditions for its entire life from the farm until used by the consumer.

A recent study explores one method for delaying spoilage – injecting small amounts of melatonin into plants through silk microneedles. The melatonin regulates the plants stress response and slows spoilage. In this study they looked at pak choy. The treated plants had a shelf-life (time in which it can be sold) from 4 days to 8 without refrigeration, and with refrigeration shelf life was extended from 15 days to 25. This was a lab proof-of-concept, and so the process would need to be industrialized and made cost-effective enough to be viable. It also would not necessarily be needed in every situation, but could be used in areas with a cold chain is very difficult or expensive, or transportation is slow. This could therefore not only reduce waste, but improve food availability in challenging areas.

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Let’s talk about climate change and life on Earth. Not anthropogenic climate change – but long term natural changes in the Earth’s environment due to stellar evolution. Eventually, as our sun burns through its fuel, it will go through changes. It will begin to grow, becoming a red giant that will engulf and incinerate the Earth. But long before Earth is a cinder, it will become uninhabitable, a dry hot wasteland. When and how will this happen, and is there anything we or future occupants of Earth can do about it?

Our sun is a main sequence yellow star. The “main sequence” refers to the Hertzsprung-Russell diagram (HR diagram), which maps all stars based on mass, luminosity, temperature, and color. Most stars fall within a band called the main sequence, which is where stars will fall when they are burning hydrogen into helium as their source of energy. More massive stars are brighter and have a color more towards the blue end of the spectrum. They also have a shorter lifespan, because they burn through their fuel faster than lighter stars. Blue stars can burn through their fuel in mere millions of years. Yellow stars, like our own, can last 10 billion years, while red dwarfs can last for hundreds of billions of year or longer.

Which stars are the best for life? We categorize main sequence stars as blue, white, yellow, orange, and red (this is a continuum, but that is how we humans categorize the colors we see). Interestingly, there are no green stars, which has more to do with human color perception than anything else. Stars at an otherwise “green” temperature have enough blue and red mixed in to appear white to our color perception. The hotter the star the farther away a planet would have to be to be in its habitable zone, and that zone can be quite wide. But hotter stars are short-lived. Colder stars last for a long time but have a small and close-in habitable zone, so close they may be tidally locked to their star. Red dwarfs are also relatively unstable and put out a lot of solar wind which is unfriendly to atmospheres.

So the ideal color for a star, if you want to evolve some life, is probably in the middle – yellow, right where we are. However, some astronomers argue that the optimal temperature may be orange, which can last for 15-45 or more billion years, but with a comfortably distant habitable zone. If we are looking for life in our galaxy than orange stars are probably the way to go.

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What the true impact of artificial intelligence (AI) is and soon will be remains a point of contention. Even among scientifically literate skeptics people tend to fall into decidedly different narratives. Also, when being interviewed I can almost guarantee now that I will be asked what I think about the impact of AI – will it help, will it hurt, is it real, is it a sham? The reason I think there is so much disagreement is because all of these things are true at the same time. Different attitudes toward AI are partly due to confirmation bias. Once you have an AI narrative, you can easily find support for that narrative. But also I think part of the reason is that what you see depends on where you look.

The “AI is mostly hype” narrative derives partly from the fact that the current AI applications are not necessarily fundamentally different than AI applications in the last few decades. The big difference, of course, is the large language models, which are built on a transformer technology. This allows for training on massive sets of unstructured data (like the internet), and to simulate human speech in a very realistic manner. But they are still narrow AI, without any true understanding of concepts. This is why they “hallucinate” and lie – they are generating probable patterns, not actually thinking about the world.

So you can make the argument that recent AI is nothing fundamentally new, the output is highly flawed, still brittle in many ways, and mostly just flashy toys and ways to steal the creative output of people (who are generating the actual content). Or, you can look at the same data and conclude that AI has made incredible strides and we are just seeing its true potential. Applications like this one, that transforms old stills into brief movies, give us a glimpse of a “black mirror” near future where amazing digital creations will become our everyday experience.

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My last post was about floating nuclear power plants. By coincidence I then ran across a news item about floating solar installations. This is also a potentially useful idea, and is already being implemented and increasing. It is estimated that in 2022 total installed floating solar was at 13 gigawatts capacity (growing from only 3 GW in 2020). The growth rate is estimated to be 34% per year.

“Floatovoltaics”, as they are apparently called, are grid-scale solar installations on floating platforms. They are typically installed on artificial bodies of water, such as reservoirs and irrigations ponds. Such installations can have two main advantages. They can reduce evaporation which helps preserve the reservoirs. They also are a source of clean energy without having to use cropland or other land.

Land use can be a major limiting factor of solar power, depending on how it is installed. Here is an interesting comparison of the various energy sources and their land use. The greatest land use per energy produced is hydroelectric (33 m^2 / MWh). The best is nuclear, at 0.3 (that’s two orders of magnitude better). Rooftop solar is among the best at 1.2, while solar photovoltaic installed on land is among the worst at 19. This is exactly why I am a big advocate of rooftop solar, even though this is more expensive up front than grid-scale installations. Right now in the US rooftop solar produces about 1.5% of electricity, but the total potential capacity is about 45%. More realistically (excluding the least optimal locations), shooting for 20-30% of energy production from rooftop solar is a reasonable goal. If this is paired with home battery backup, this makes solar power even better.

Floating solar installations have the potential of having the best of both worlds – less land use than land-based solar, and better economics and rooftop solar. If the installation is serving double-duty as an evaporation-prevention strategy, this is even better. This also can potentially dovetail nicely with closed loop pumped hydro. This is a promising grid-level energy storage solution, in that it can store massive amounts of energy for long periods of time, enough to shift energy production to demand seasonally. The main source of energy loss with pumped hydro is evaporation, which can be mitigated by anti-evaporation strategies, which could include floating solar. Potentially you could have a large floating solar installation on top of a reservoir used for closed-loop pumped hydro, which stores the energy produced by the solar installation.

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This is an intriguing idea, and one that I can see becoming critical over the next few decades, or never manifesting – developing a fleet of floating nuclear power plants. One company, Core Power, is working on this technology and plans to have commercially deployable plants by 2035. Company press releases touting their own technology and innovation is hardly an objective and reliable source, but that doesn’t mean the idea does not have merit. So let’s explore the pros and cons.

The first nuclear-powered ship, the USS Nautilus, was deployed in 1955. So in that sense we have had ship-based nuclear reactors operating continuously (collectively, not individually) for the last 70 years. Right now there are about 160 nuclear powered ships in operation, mostly submarines and aircraft carriers. They generally produce several hundred megawatts of electricity, compared to around 1600 for a typical large nuclear reactor. They are, however, in the range of small modular reactors which have been proposed as the next generation of land-based nuclear power. The US has operated nuclear powered ships without incident – a remarkable safety record. There have been a couple of incidents with Soviet ships, but arguably that was a Soviet problem, not an issue with the technology. In any case, that is a very long record of safe and effective operation.

Core Power wants to take this concept and adapt is for commercial energy production. They are designing nuclear power barges – large ships that are designed only to produce nuclear power, so all of their space can be dedicated to this purpose, and they can produce as much electricity as a standard nuclear power plant. They plan on using a Gen IV salt-cooled reactor design, which is inherently safer than older designs and does not require high pressure for operation and cooling.

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The recent discussions about autism have been fascinating, partly because there is a robust neurodiversity community who have very deep, personal, and thoughtful opinions about the whole thing. One of the issues that has come up after we discussed this on the SGU was that of self-diagnosis. Some people in the community are essentially self-diagnosed as being on the autism spectrum. Cara and I both reflexively said this was not a good thing, and then moved on. But some in the community who are self-diagnosed took exception to our dismissiveness. I didn’t even realize this was a point of contention.

Two issues came up, the reasons they feel they need self-diagnosis, and the accuracy of self diagnosis. The main reason given to support self-diagnoses was the lack of adequate professional services available. It can be difficult to find a qualified practitioner. It can take a long time to get an appointment. Insurance does not cover “mental health” services very well, and so often getting a professional diagnosis would simply be too expensive for many to afford. So self-diagnosis is their only practical option.

I get this, and I have been complaining about the lack of mental health services for a long time. The solution here is to increase the services available and insurance coverage, not to rely on self-diagnosis. But this will not happen overnight, and may not happen anytime soon, so they have a point. But this doesn’t change the unavoidable reality that diagnoses based upon neurological and psychological signs and symptoms are extremely difficult, and self-diagnosis in any medical area is also fraught with challenges. Let me start by discussing the issues with self-diagnosis generally (not specifically with autism).

I wrote recently about the phenomenon of diagnosis itself. (I do recommend you read that article first, if you haven’t already.) A medical/psychological diagnosis is a complex multifaceted phenomenon. It exists in a specific context and for a specific purpose. Diagnoses can be purely descriptive, based on clinical signs and symptoms, or based on various kinds of biological markers – blood tests, anatomical scans, biopsy findings, functional tests, or genetics. Also, clinical entities are often not discrete, but are fuzzy around the edges, manifest differently in different populations and individuals, and overlap with other diagnoses. Some diagnoses are just placeholders for things we don’t understand. There are also generic categorization issues, like lumping vs splitting (do we use big umbrella diagnoses or split every small difference up into its own diagnosis?).

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As a scientific concept – does race exist? Is it a useful construct, or is it more misleading than useful? I wrote about this question in 2016, and my thinking has evolved a bit since then. My bottom line conclusion has not changed – the answer is, it depends. There is no fully objective answer because this is ultimately a matter of categorization which involves arbitrary choices, such as how to weight different features, how much difference is meaningful, and where to draw lines. People can also agree on all the relevant facts, but disagree simply on emphasis. (If all of this is sounding familiar it’s because the same issues exist surrounding biological sex.)

Here are some relevant facts. Humans – Homo sapiens – are a single species. While we are an outbred species with a lot of genetic diversity, we have passed through several fairly recent genetic bottlenecks (most recently around 900k years ago) and the genetic disparity (amount of difference) among humans is relatively small (about 0.1%). It is also true that genetic variation is not evenly distributed among human populations but tend to cluster geographically. However, genetic variation within these clusters is greater than genetic variation between these clusters. Further, obvious morphological differences between identifiable groups tend to be superficial and not a good reflection of underlying genetic diversity. But at the same time, genetic background can be meaningful – predicting the risk of developing certain diseases or responding to certain medications, for example. Genetic variation is also not evenly distributed. Most genetic variations within humans is among Africans, because all non-Africans are derived from a recent genetic bottleneck population about 50-70k years ago.

How should we summarize all of these non-controversial and generally agreed upon facts? You can emphasize the clustering and say that something akin to race exists and is meaningful, or you can emphasize the genetic  similarity of all humans and lack of discrete groups to say that race is not a meaningful or helpful concept. So, as a purely scientific question we have to recognize that there is no completely objective answer here. There are just different perspectives. However, that does not mean that every perspective is equally strong or that our choice of emphasis cannot be determined by other factors, such as their utility in specific contexts.

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In my previous post I wrote about how we think about and talk about autism spectrum disorder (ASD), and how RFK Jr misunderstands and exploits this complexity to weave his anti-vaccine crank narrative. There is also another challenge in the conversation about autism, which exists for many diagnoses – how do we talk about it in a way that is scientifically accurate, useful, and yet not needlessly stigmatizing or negative? A recent NYT op-ed by a parent of a child with profound autism had this to say:

“Many advocacy groups focus so much on acceptance, inclusion and celebrating neurodiversity that it can feel as if they are avoiding uncomfortable truths about children like mine. Parents are encouraged not to use words like “severe,” “profound” or even “Level 3” to describe our child’s autism; we’re told those terms are stigmatizing and we should instead speak of “high support needs.” A Harvard-affiliated research center halted a panel on autism awareness in 2022 after students claimed that the panel’s language about treating autism was “toxic.” A student petition circulated on Change.org said that autism ‘is not an illness or disease and, most importantly, it is not inherently negative.'”

I’m afraid there is no clean answer here, there are just tradeoffs. Let’s look at this question (essentially, how do we label ASD) from two basic perspectives – scientific and cultural. You may think that a purely scientific approach would be easier and result in a clear answer, but that is not the case. While science strives to be objective, the universe is really complex, and our attempts at making it understandable and manageable through categorization involve subjective choices and tradeoffs. As a physician I have had to become comfortable with this reality. Diagnoses are often squirrelly things.

When the profession creates or modifies a diagnosis, this is really a type of categorization. There are different criteria that we could potentially use to define a diagnostic label or category. We could use clinical criteria – what are the signs, symptoms, demographics, and natural history of the diagnosis in question? This is often where diagnoses begin their lives, as a pure description of what is being seen in the clinic. Clinical entities almost always present as a range of characteristics, because people are different and even specific diseases will manifest differently. The question then becomes – are we looking at one disease, multiple diseases, variations on a theme, or completely different processes that just overlap in the signs and symptoms they cause. This leads to the infamous “lumper vs splitter” debate – do we tend to lump similar entities together in big categories or split everything up into very specific entities, based on even tiny differences?

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