Artificial Intelligence (AI) is unavoidable. It’s now a part of our daily lives as it has been steadily infiltrating the technology we use every day, whether you realize it or not. I remain somewhat in the middle in terms of the hype-to-technological-miracle spectrum. I don’t think, as some fellow skeptics do, that the current batch of AI is all hype and nothing new. Machine learning, neural networks, and large language models have clearly turned a corner. Companies are now willing to spend millions, even hundreds of millions, to train models on vast sets of data. The latest AI apps are powerful. They are genuinely accelerating the pace of research and development, for example, accomplishing in hours or days what previously took weeks or months. But current AI also has clear limitations. It makes mistakes, and can even confidently (it appears to the end-user) proclaim as facts things it just completely fabricated, including entire scientific references. On the creative side (which I use often) it’s still mostly derivative dreck.

I look at AI as an interesting and potentially powerful tool that is flawed and limited. The outcome depends entirely on how it is used, and this is where I think the true risk of rapidly introducing new AI tools into society lies. It’s disruptive in good and bad ways, and if we are not careful it will be mostly in the bad ways. I also think we are facing the silicon valley culture of “move fast and break things” combined with an attitude of “just get out of my way” when it comes to any regulation or quality control. It’s a reasonable corporate strategy to “break things” internally as you are exploring new technology. I really don’t care how many ships Musk blows up if that process leads to a working safe rocket. But they appear to be moving fast and breaking things out there in the world in ways that affect people and society.

How is the use of AI going wrong? One important way is that it makes it easy for people to be lazy. This is something I have long worried about existentially for humanity. I now think of this as the WALL-E syndrome – in a society run by AI and robots (or any such system) that can totally take care of your needs, it’s easy to sit back and do nothing. It’s possible we evolved a certain laziness as an efficiency mechanism – accomplish tasks efficiently, conserve energy and resources.

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Citrus greening (also called Huanglongbing or HLB) is an infectious disease affecting citrus trees in Florida. It is a bacterium, Candidatus Liberibacter asiaticus, and spread by an invasive fly, the Asian citrus psyllid. Since 2004 it has caused a reduction in the Florida citrus industry by 90% and doubled production costs. It is close to completely wiping out the Florida citrus industry. Various methods have been tried to keep it under control, but they have all failed.

There is good news, however. The University of Florida in collaboration with the company Soilcea, has developed a GMO orange that is highly resistant to citrus greening. They expect to have commercial trees available by the Spring of 2027. The limiting factor is that it takes years to grow test trees to see that they remain resistant and produce viable fruit. So far the test trees are doing well.

The company licensed the finding of Nian Wang, a professor at the University of Florida, who found that the bacterium is dependent upon interactions with the host that can be traced to several genes. The company used CRISPR to silence those genes, making it more difficult for the bacterium to infect plants and thereby making the plants resistant to infection. This approach has apparently worked, although again we won’t be sure until the first test trees reach maturity.

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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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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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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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Regulations are a classic example of a proverbial double-edged sword. They are essential to create and maintain a free and fair market, to prevent exploitation, and to promote safety and the public interest. Just look at 19th century America for countless examples of what happens without proper regulations (child labor, cities ablaze, patent medicines, and food was a crap shoot). But, regulations can have a powerful effect and this includes unintended consequences, regulatory overreach, ideological capture, and stifling bureaucracy. This is why optimal regulations should be minimalist, targeted, evidence-based, consensus-driven, and open to revision. This makes regulations also a classic example of Aristotle’s rule of the “golden mean”. Go too far to either extreme (too little or to onerous) and regulations can be a net negative.

The regulations of GMOs are an example, in my opinion, of ideological capture in regulations. The US, actually, has pretty good regulations, requiring study and approval for each new GMO product on the market, but no outright banning. You could argue that they are a bit too onerous to be optimal, ensuring that only large companies can afford to usher a new GMO product to the market, and therefore stifling competition from smaller companies. That’s one of those unintended consequences. Some states, like Hawaii and Vermont, have instituted their own more restrictive regulations, based purely on ideology and not science or evidence. Europe is another story, with highly restrictive regulations on GMOs.

But in recent years scientific advances in genetics have cracked the door open for genetic modification in highly regulated environments. This is similar to what happened with stem cell research in the US. Use of embryonic stem cells were ideologically controversial, and ultimately the development of any new cells lines was banned by Bush in 2001. Scientists then discovered how to convert adult cells into induced pluripotent stem cells, mostly side-stepping these regulations.

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Have you ever been into a video game that you played for hours a day for a while? Did you ever experience elements of game play bleeding over into the real world? If you have, then you have experienced what psychologists call “game transfer phenomenon” or GTP.  This can be subtle, such as unconsciously placing your hand on the AWSD keys on a keyboard, or more extreme such as imagining elements of the game in the real world, such as health bars over people’s heads.

None of this is surprising, actually. Our brains adapt to use. Spend enough time in a certain environment, engaging in a specific activity, experiencing certain things, and these pathways will be reinforced. This is essentially what PTSD is – spend enough time fighting for your life in extremely violent and deadly situations, and the behaviors and associations you learn are hard to turn off. I have experienced only a tiny whisper of this after engaging for extended periods of time in live-action gaming that involves some sort of combat (like paint ball or LARPing) – it may take a few days for you to stop looking for threats and being jumpy.

I have also noticed a bit of transfer (and others have noted this to me as well) in that I find myself reaching to pause or rewind a live radio broadcast because I missed something that was said. I also frequently try to interact with screens that are not touch-screens. I am getting used to having the ability to affect my physical reality at will.

Now there is a new wrinkle to this phenomenon – we have to consider the impact of spending more and more time engaged in virtual experiences. This will only get more profound as virtual reality becomes more and more a part of our daily routine. I am also thinking about the not-to-distant future and beyond, where some people might spend huge chunks of their day in VR. Existing research shows that GTP is more likely to occur with increased time and immersiveness. What happens when our daily lives are a blend of the virtual and the physical? Not only is there VR, there is augmented reality (AR) where we overlay digital information onto our perception of the real world. This idea was explored in a Dr. Who episode in which a society of people were so dependent on AR that they were literally helpless without it, unable to even walk from point A to B.

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Last week I wrote about the de-extinction of the dire wolf by a company, Colossal Biosciences. What they did was pretty amazing – sequence ancient dire wolf DNA and use that as a template to make 20 changes to 14 genes in the gray wolf genome via CRISPR. They focused on the genetic changes they thought would have the biggest morphological effect, so that the resulting pups would look as much as possible like the dire wolves of old.

This achievement, however, is somewhat tainted by overhyping what was actually achieved, by the company and many media outlets. Although the pushback began immediately, and there is plenty of reporting about the fact that these are not exactly dire wolves (as I pointed out myself). I do think we should not fall into the pattern of focusing on the controversy and the negative and missing the fact that this is a genuinely amazing scientific accomplishment. It is easy to become blase about such things. Sometimes it’s hard to know in reporting what the optimal balance is between the positive and the negative, and as skeptics we definitely can tend toward the negative.

I feel the same way, for example, about artificial intelligence. Some of my skeptical colleagues have taken the approach that AI is mostly hype, and focusing on what the recent crop of AI apps are not (they are not sentient, they are not AGI), rather than what they are. In both cases I think it’s important to remember that science and pseudoscience are a continuum, and just because something is being overhyped does not mean it gets tossed in the pseudoscience bucket. That is just another form of bias. Sometimes that amounts to substituting cynicism for more nuanced skepticism.

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