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We can’t launch our trash into the sun. But why?
If you’ve spent any time on the Earth in the last 50 years or so, you might have noticed a lot of trash laying around…with less and less space to, you know, put it. Meanwhile, we’re sending all sorts of satellites and rockets beyond our atmosphere every day.
That’s why you asked us: Why can’t we launch our junk into space, too? Or better yet: STRAIGHT INTO THE SUN!
For the moment, let’s set aside the big problems with creating too much trash in the first place, and focus on the blocker: We simply can’t afford to shoot our junk into that flamin’ hot Cheeto in the sky.
Plus, shouldn’t we worry about finding a solution down here on our planet? Yes.
On our latest video episode of Ask Us Anything, we explain why we can’t launch our garbage into the sun or onto the moon.
If you’d like to see more Popular Science videos, subscribe on YouTube. We’ll be bringing you explainers and explorations of our weird world.
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Computer run on human brain cells learned to play ‘Doom’
A biocomputer powered by lab-grown human brain cells has leveled up from Pong to Doom. While nowhere ready to handle the video game shooter’s most challenging levels, researchers at Cortical Labs in Australia believe their neuronal chip is well on its way to powering a new generation of hybrid organic technologies.
“This was a major milestone, because it demonstrated adaptive, real-time goal directed learning,” Brett Kagan, Cortical Labs Chief Scientific and Chief Operations Officer, said in a recent video announcement.
It’s taken years to cross the Doom benchmark. In 2021, Cortical Labs debuted DishBrain—an early biocomputer utilizing around 800,000 human nerve cells. These neurons were connected to a small processing chip capable of interpreting and directing electrical activity similar to a standard silicon-powered device.
To showcase DishBrain’s potential, engineers successfully trained their biocomputer to play Pong. The classic, 2D game is often a test case for computational neuroscientists because it requires their system to navigate a dynamic information landscape in real time.
It took Cortical Labs more than 18 months using its original hardware and software to accomplish their Pong goal. DishBrain was eventually supplanted by CL1, which the company bills as the “world’s first code deployable biological computer.”
But for a biocomputer to be actually useful, it’s going to need to do much more than move a pixelated paddle up and down on a screen. Enter Doom. For decades, major tech companies and DIY hobbyists have demonstrated ways to run the video game on all types of devices including calculators, tractors, and even ATM machines. “Can it play Doom?” is such a ubiquitous request in the tech world that it wasn’t a question of “if” Cortical Labs would try it on neuronal chips, but “when.”
The major challenge for CL1 to understand Doom is that it needed to “see” what a human player sees when playing the game on a computer. Without any optical input, this meant that engineers needed to figure out a way to convert visual information into electrical stimulation patterns that are recognizable to the neurons.
The solution wasn’t only achievable,it was completed in about a week by Sean Cole, an independent developer with little experience in biological computing. The key to this is the CL1’s new interface, which allows anyone to program it using Python.
Don’t expect the biocomputer to win any Doom tournaments, however. It plays the game better than a system that simply fires randomly at enemies, but it still loses a lot of the time. That said, Cortical Labs says it reached its current performance level faster than silicon-based machine learning systems, and will likely get better as its algorithms improve.
Beyond gunning through pixelated enemies, future generations of biocomputers may one day power robotic arms or help run complex digital programs. It’s got a long way to go, but surpassing rites of passage like playing Doom bodes well for the technology.
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Mystery stone is actually ancient Roman board game
Like many other cultures, the ancient Romans loved their board games. Some of history’s most well-documented examples of tabletop pastimes date back to the empire. Ludus Latrunculorum, aka latrones, was a strategy face-off between two players on a grid board similar to chess or checkers. Another favorite, Ludus Duodecim Scriptorum, saw players compete on a backgammon-like setup that also involved dice.
A complete catalog of Roman games may never be known, but an international research team is confident they have a new addition to the list. As detailed in a recently published study in the journal Antiquity, their explanation also finally solves a mystery that’s puzzled archaeologists for over 40 years.
The saga began in 1984 while researchers excavated the ancient settlement of Coriovallum. Located in the Netherlands not far from the present-day German border, the town was founded during the reign of Augustus (27 BCE–14 CE) and is one of the region’s only outposts that is specifically named in primary sources. Coriovallum was also strategically placed at the nexus of two principle roadways for the Roman Empire. This guaranteed a sustained level of economic prosperity for centuries, as evidenced in its impressive architecture and ornate burial plots.
During their excavation work, archaeologists discovered an oval stone measuring roughly 8.3 by 5.7 inches in diameter and etched with various intersecting lines. Further examinations revealed the material to be a type of white Jurassic limestone sourced from ancient quarries in Norroy in northeastern France.
“Norroy limestone was a popular choice for large architectural elements in the Roman northern provinces because of its white color, smooth surface, and relative softness, making it an easily sculpted substitute for marble,” explained the study’s authors.
Experts debated the stone’s purpose for years. It was too small to be intended as a building component, and its shape wasn’t suited for roadwork. Although its lines conceivably could represent some form of architectural sketch, the theory was unlikely due to a lack of similar examples from the time period. But while some researchers consistently contended the stone was a board game’s playing surface, it didn’t resemble any known examples from the era.
Recent analysis now appears to support the longstanding board game theory. 3D imaging revealed some of the diagonal and horizontal lines are deeper than others—indicative that people routinely moved tiny pieces along these routes more often than others.
“We can see wear along the lines on the stone, exactly where you would slide a piece,” Leiden University archaeologist and ancient game specialist Walter Crist said in a statement.
But if it was a board game, then what were the rules? The question may seem impossible to answer without access to a playing guide, but Crist’s team doesn’t think this is necessarily the case. After enlisting help from machine learning programmers at Maastricht University in the Netherlands, researchers designed an artificial intelligence system trained on rules from around 100 ancient games documented from the same region as the stone’s origin. The resultant AI program (dubbed Ludii as a play on ludi, Latin for “games”) calculated a number of optional playing styles for the mystery pastime researchers named Ludus Coriovalli.
“[Ludii] produced dozens of possible rule sets. It then played the game against itself and identified a few variants that are enjoyable for humans to play,” said Maastricht University AI designer Dennis Soemers.
From there, researchers doublechecked the potential rule sets against the documented wear on the stone to confirm the most likely move patterns in the game. In the end, Crist, Soemers, and their colleagues theorize Ludus Coriovalli was a “deceptively simple but thrilling strategy game” with the objective to pursue and trap your opponent’s pieces in as few moves as possible.
Although the study’s conclusions offer arguably the most plausible explanation behind the limestone artifact, researchers stopped short of declaring themselves the winners. Without additional primary source references, the exact rules of Ludus Coriovalli may never be fully known.
“If you present Ludii with a line pattern like the one on the stone, it will always find game rules. Therefore, we cannot be sure that the Romans played it in precisely that way,” Soemers cautioned.
Like any great board game, it’s always important to consider all the options and avoid getting too cocky.
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7,000-year-old deer antler headdress uncovered in Germany
To an untrained eye, it might just look like the remains of some ferocious predator’s feast. But this particular antler is thousands of years old, and could be a remnant of interactions between the last of Europe’s hunter-gatherers and the continent’s early farmers.
Neolithic farmers belonging to what archaeologists refer to as the “Linear Pottery culture” began to expand across Europe around 5500 BCE. During this migration, they pushed Mesolithic hunter-gatherers in central Germany, among other places, further north.
“There is a long period in which farmers and hunter-gatherers coexist,” Oliver Dietrich, co-author of a recent study published in Praehistorische Zeitschrift and press officer at the State Office for Heritage Management and Archaeology Saxony-Anhalt – State Museum of Prehistory, tells Popular Science. “Neolithic and Mesolithic thus are not mutually exclusive time periods, but describe two life styles, which are partly contemporary.”
Archaeologists know very little about the contact between these two peoples. Cue Germany’s Eilsleben-Vosswelle settlement, a prehistoric farming community that existed on the frontier, with hunter-gatherers in the north and farmers in the south. It was likely fortified, and may have seen significant interactions with proximal hunter-gatherer groups.
“The material culture discovered at Eilsleben reflects this frontier situation, as it shows many influences from the world of hunter-gatherers,” Dietrich continues. “[Among] them is the antler industry, i.e. tools and other implements made from antler in a Mesolithic/hunter-gatherer style. The roe deer antler is a prime example,” he adds, referencing a previously discovered 7,000-year old antler from Eilsleben.
Dietrich and his colleagues investigated the artifact for signs of human modification. They found that the rectangle-shaped skull fragment, cut marks (suggesting skinning), and notches at the base fit the bill. The artifact was probably worn as part of a mask or headdress, and the notches would have secured it in place. The headdress also dates back to 5291–5034 BCE.
Roe deer antler worked into a headdress from Eilsleben. Image: Juraj Lipták/State Office for Heritage Management and Archaeology Saxony-Anhalt.“Similar headgear is not known from early farmer contexts, but there are good analogies from hunter-gatherer contexts. The best comparison for the Eilsleben antler is from the shaman´s grave of Bad Dürrenberg,” says Dietrich.
The Bad Dürrenberg shaman was a 30 to 40-year-old woman who died around 9,000 years ago. She was laid to rest alongside an approximately 6-month-old child in an intricate tomb in present-day central Germany. Researchers identified her as a shaman, or spiritual leader, thanks in part to animal teeth pendants and a deer antler that researchers believe to be a headdress.
Despite the fact that the shaman´s grave of Bad Dürrenberg is older than the Eilsleben antler, the shaman’s antler “provides a frame of interpretation for the find,” Dietrich explains. The Eilsleben antler could represent contact between hunter-gatherer ritual specialists and farmers, according to the researchers.
Some transitions associated with the Neolithic lifestyle weren’t healthy, per a statement by the State Office for Heritage Management and Archaeology Saxony-Anhalt – State Museum of Prehistory. Within this context, it’s possible that early farmers would have requested help from a healer connected to the spirit world who was certainly an expert on local flora’s healing properties.
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Horse whinnies are weirder than they sound
A horse’s whinny is an iconic sound, arguably on par with a cow’s moo and a sheep’s baa and a donkey’s hee-haw. Most people can immediately recognize a horse’s signature sound, so it might come as a surprise to learn that researchers have no idea how the animals actually produce some of the whinny sounds. That is, until now.
“Although humans have been co-existing – and co-evolving – with horses for 4000 years, we still understand their communication imperfectly,” Elodie Floriane Mandel-Briefer, a biologist at Copenhagen University interested in vocal communication and cognition in birds and mammals, tells Popular Science. “The whinny in particular is strange: it has a low-frequency component that fits the large body size of horses, but a very high-frequency component as well that is way too high for such a large animal.”
About 10 years ago, Mandel-Briefer and colleagues discovered the existence of the two pitches, which overlap to create a vocal phenomenon called biphonation. The low-frequency component is produced when air from the lungs causes vibrations of the vocal folds. This is also how humans, along with the majority of mammals, make sounds.
However, normal vocal fold vibrations can’t explain the high-frequency part of whinnies, given how big horses are. So how are these animals making such high noises? Mandel-Briefer and co-authors investigated this biomechanical puzzle in an interdisciplinary study recently published in the journal Current Biology. They ultimately discovered that a laryngeal whistle is behind the whinnies’ high-frequency sound. Part of their work involved two of the authors blowing air through horse larynges secured from a horse meat supplier.
“Initially they only got the low component, but with some playing around they were able to obtain the high frequency component as well. That showed that both components are produced by the larynx itself (not, as in human whistling, with the lips),” Mandel-Briefer explains. “To prove that the high component is a laryngeal whistle, they then blew two different gases through: air and helium. Because it has different physical properties, helium—compared to air—shifts whistle frequencies up, while frequencies emitted by tissue vibration (like the low component) do not change.”
A horse at Le Borre equestrian center in Montecreto, Italy. Horses have a whistle in their larynx behind their whinnies. Image: Margherita Bassi/Popular Science.The frequency change confirmed that a laryngeal whistle explains the mechanical production of the high-frequency whinny component. More broadly, the team found that horses create biphonation by simultaneous vocal fold vibration and laryngeal whistling. As far as they know, horses are the only animals that use these two mechanics at the same time. The team proposes that their biphonation probably evolved to communicate multiple messages to each other at once.
In a 2015 study, Mandel-Briefer and colleagues also demonstrated that frequency and emotion are connected. The high-frequency whinny component indicates that a horse’s emotion is pleasant or unpleasant. The low-frequency components represent the feeling’s intensity. Horses could also use two components to convey messages across varying stretches of space. The high component is louder and can travel farther.
While Przewalski’s horses, which are close relatives of domesticated horses, also create whinnies with biphonation, more distant relatives such as zebras and donkeys don’t seem to have the high frequency part. Horses might possess distinctive vocal adaptations enabling them to create a more plentiful and intricate call spectrum than fellow mammals.
The paper “highlights the remarkable adaptive flexibility of the mammalian laryngeal vocal production system,” Mandel-Briefer concludes. “Understanding the communication system of any species is of fundamental scientific interest to help us understand their cognition, emotions and welfare, and this helps us understand horses better.”
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Macro Cultural Debt
The personal lives of Olympic medalists seem overwhelmingly devoted to practicing their sport; a dreary life. In contrast, prestigious firms today have norms that discourage such complete career devotion:
Employers have little patience with candidates who didn’t pick the most prestigious possible college or job, but were swayed by other considerations. Such as topics of interest, limited money, or the needs of a spouse or family. A “serious” person always picks max prestige. Always.
Yet for extracurriculars, you are not supposed to connect those to your career plans, as “nerds” do. You must instead do something with no practical value, but that is prestigious. Like varsity athletes in lacrosse or crew, sports that are too expensive for ordinary folks to pursue. Excess interest in ideas marks you as a “boring” “tool”. (More)
We can see this as elites using norms to coordinate to prevent their lives being totally filled with career competition. Yes, they also compete in non-career activities, but at least they get a change of pace. Common norms among elites through history can be seen as similarly trying to limit how people could achieve high status. To limit which sorts of people could compete, which activities they would do, and how much of their time would be spent on those.
This is how I now think about this key modern change:
Early in the Industrial Revolution, many noted the great productivity that resulted from very regimented and organized workplaces like shipyards and factories. They then expected and feared that such regimentation would spread to all the rest of their lives, including their food, clothes, homes, friends, lovers, and parenting. Novels like Pictures of a Socialist Future and We warned of this coming totalitarianism.
But what happened instead is that we have spent most of our increased wealth on not regimenting our non-work lives. Instead of such things being arranged and regimented efficiently by big orgs, as in our work lives, we instead each make pretty autonomous and artisanal choices. For example, instead of wearing standard uniforms, living in dorms with shared bathrooms, and eating at cafeterias, we each vary and duplicate all this at great expense. (More)
Though we allowed big competitive orgs to achieve high levels of efficiency and innovation in many key areas, we have so far coordinated to discourage people from using such orgs to achieve max competitive advantage in their non-work lives.
How could this have worked? Imagine you sold a big fraction of your future income to a for-profit “style agent” org, to which you gave the power to substantially influence where you live, what car you drive, what clothes you wear, how you do your hair and face, and what are your hobbies. They would do this in consultation with you, to best complement your abilities and ambitions, but also to max your career income, so they can max their cut of it.
Such firms would plausibly produce max income people, except that such folks’ status would fall too far when others learned that their lives had been managed this way. As we made strong norms ridiculing such regimented and managed lives. So while modern rates of cultural evolution have greatly increased in areas where we’ve allowed strong selection, we’ve prevented such strong selection in other areas.
The modern world thus has a big split, variously described as STEM vs humanities, quantitative vs qualitative, competition vs cooperation, profane vs sacred, and work vs. leisure. I’ll call them “system” vs “soul”. In the system areas, people and orgs frequently choose according to a low dimensional set of concrete metrics, driving big competitive orgs that used modern systems of concepts, analysis, and organization to make those “numbers go up”. Like how phone companies compete to make their phones cheap, light, long-lasting, wide-ranged, big-screened, and high computing.
In the remaining soul areas, in contrast, choices are made mostly by individuals pressured to use vibes to express their individuality, creativity, and authenticity. Like in friendship, love, parenting, art, entertainment, prestige, community, and voting. Or by folks who defer to specialists who aren’t monitored well enough to drive them to complete strongly to produce or innovate in either the soul or system areas where they claim expertise. Like priests who claim to produce religious soul, or education and medicine experts who claim to produce income or health.
Long ago both system and soul areas changed slowly together, such change being driven mainly by simple adaptive cultural evolution. And there was enormous variety in such things around the world. But then a few centuries ago system areas developed much stronger ways to select for adaptive change. Which greatly increased our long distance interaction via more talk, travel, and trade. Which caused a global convergence in all areas of culture.
At first, soul areas of culture tried to make minimal adjustments to accommodate system changes, but then around 1900, at the “modernism” transition, soul area folk decided that the one thing they agreed on was that prior soul styles were no good. So they switched to eagerly seeking change, via exploring many possibilities and following cultural activists supported by youth movements.
A rationale for this was to help soul areas adapt to fast changing system areas. And some soul changes did do this. But most were not tracking adaptive pressures, and so overall this change has led to our soul culture drifting to into increasing maladaption. Which is the key problem that will cause our civ to fall, and future civs that replace us to also fall, until we either slow system evolution way down, or find ways to induce fast adaptive soul changes.
Financial debt is money you must repay, and technical debt is accumulated when insufficient maintenance costs are paid counter the usual tendencies of complex systems like software to rot. Let me now use the term “macro cultural debt” to describe the costs that cultures that must eventually repay when key parts of them decay into maladaption. Like the “org culture debt” from the org culture literature. For over a century now we have been accumulating big cultural debt in our soul areas.
Maybe we could invent new ways to drive strong cultural evolution in soul areas. I’ve been exploring how futarchy might help. But until we find new better methods, the obvious solution is to allow the proven metric-driven for-profit orgs that have done so well in system areas to take more control over soul areas, such as via for-profit orgs that manage governance, parenting, and style (as outlined above). Early visions expressed in novels like Pictures of a Socialist Future and We may well be have been surprisingly prescient.
I get that I’m not painting a pretty or inspiring picture here. But my first allegiance is to tell the truth. If you don’t want descendant cultures to be as different from us today as we are from most random past cultures, but instead want some precious parts of our present soul culture to last far into the future, then we will need to find a way to package such precious parts with an overall adaptive cultural package. So we will need to somehow induce sufficient adaptive cultural evolution in most parts of soul culture.
Buying News By Metric
For many decades I’ve thought about how to reform areas of life via finding ways to measure the long term outcomes people want from each area, and then paying providers for achieving those outcomes. As soon I’ll be at an event where we will be talking about how to reform news, let me take a stab at doing that for news.
If what news customers want is to read the articles that others read, so they can discuss them together, then readers could pay proportional to how many others will read the same article.
If what customers want from news is a feeling of enjoyment from reading, we might just frequently give consumers two new articles, have them rate which they liked more, estimate personal ELO ratings from such tests, and pay news providers more for higher rated articles.
If what news customers want from news is info to predict the big picture future of humanity, we might test LLMs on their ability to predict such things, then pay for each article based on how much such LLM predictions improve by reading that article.
If, in addition to the above, news customers just want accurate articles, that make fewer false claims, we could just evaluate random articles for accuracy, and pay more for more accurate sources.
Sure there are many details re making each of these approaches work better. But the main problem seems to me to be that customers just don’t like such approaches. Most would feel ashamed to make cultural choices using more mechanical numerical mechanisms. Especially if explicit strong financial incentives were involved. Re culture, self-respecting folks follow their vibes.
For example, few seem interested in my many proposals to reform crime, health, career planning, and other areas of life via strong incentives tied to numerical metrics. And I’ve seen many visibly show me how much less they think less of me from learning that I rely heavily on MetaCritic to pick movies and TV shows.
To solve cultural drift, we are going to have to somehow recruit the same level of intense effort and accuracy that modernity has achieved in tech, science, and business practice to other areas of life now more dominated by norms and vibes. But a big obstacle to that is our norms and vibes against such things.
Added 27Feb: Of course I should mention a big way that news might change soon: it might include far more prediction market prices.
Treat Info Institutions Alike
“Info institutions” solicit contributions, aggregate them into info summaries, and distribute such summaries to audiences. Examples include gossip, courts, journalism, academia, social media, speculative markets, and official reports of orgs (such as govts and churches). Such institutions often dis their competitors. For example, most have long dissed gossip, the oldest. Early journalists were dissed by governments and churches. Recently, academics and journalists have dissed social media.
Lately, journalists have been dissing prediction markets, with complaints that can be made about most info institutions. For example:
Prestige - Its bad if people get info they enjoy, vs what prestigious folks say is good for them.
Waste - People might enjoy it so much they waste time and money on it.
Money - This involves money, which could change incentives.
Privacy - Sometimes it is bad to spread more info. For example, info on candidate chances on election day.
Secrets - People who had promised to keep secrets might be induced instead to reveal them.
Sabotage - Participants might push changes to the world to make their takes more accurate.
On these complaints I say: treat the various info institutions alike. For example, if you want to ban govt officials from trading in prediction markets, for fear they’d reveal secrets, then also ban them from talking to reporters, or from gossiping. If you want to ban sports betting due to possible waste, then ban sports news and entertainment too. If you want to promote democracy by protecting political speech in gossip, journalism, and social media, then protect political prediction markets also.
For some kinds of complaints, we have good evidence that prediction markets are in fact superior to other info institutions:
Errors - In particular cases, predictions have been wrong.
Vagueness - In particular cases, it was unclear to some what exactly was being claimed.
Manipulation - Folks might offer biased contributions to distort audience actions.
Prediction markets have been consistently more accurate than other sources on the same topics at same time with similar resources. And an expectation of manipulation attempts on average makes such markets more accurate. If these issues are important, we should be willing to tolerate doing worse on other problems, to do better on these.
Our Modern Mistake
People hate to be given direct orders, especially if they will have to visibly follow such orders, and especially if they feel rivalrous with those who give the orders. And most of our ancestors managed to avoid this despised scenario most of the time.
Sure, at times kids, servants, and soldiers had to take specific orders, and wives also sometimes. But most of what most people had to do was quite routine and scripted, requiring no new explicit orders. And many of the explicit orders given were by overlords whom the ordered didn’t feel very rivalrous with, like masters ordering servants, or generals ordering troops.
Modern workers, in contrast, are frequently given novel orders, and by people much more similar to them. For example, people of a similar age and class, who were once at the same level as them, and who compete with them for mates and associates. Orders where it is far from clear to the person ordered that such orders are actually better choices for the enterprise or society as a whole.
In fact, a key function of modern schools seems to be to habituate us to such orders. Schools grade students more frequently than adults get graded, and far more than is optimal for student learning. Historically, times and places with smart unschooled adults have found it hard to get such folks to function well in modern workplaces.
Most of our ancestors would be ashamed of us if they saw how servile we are at work; their pride would not have accepted such clear and frequent ranking and domination. But what we gained from this submission is great wealth, including health and security, and they would envy us for those.
Early in the Industrial Revolution, many noted the great productivity that resulted from very regimented and organized workplaces like shipyards and factories. They then expected and feared that such regimentation would spread to all the rest of their lives, including their food, clothes, homes, friends, lovers, and parenting. Novels like Pictures of a Socialist Future and We warned of this coming totalitarianism.
But what happened instead is that we have spent most of our increased wealth on not regimenting our non-work lives. Instead of such things being arranged and regimented efficiently by big orgs, as in our work lives, we instead each make pretty autonomous and artisanal choices. For example, instead of wearing standard uniforms, living in dorms with shared bathrooms, and eating at cafeterias, we each vary and duplicate all this at great expense. But we can afford to do so, at least for now.
Compared to our ancestors, who had similar levels of domination, routine, and poverty in their work and non-work lives, we have become schizophrenic. At work, we are far more dominated and constrained by our bosses and orgs, though they often avoid giving very direct orders. However, outside work we are far more autonomous, rich, and vibe-driven. Which we like.
Now instead of seeing all this as a fundamental modern tradeoff, some are foolish enough to think that we could be similarly autonomous, rich, and vibey at work, if only we would rebel against capitalism. But even the least capitalist modern societies have also had big orgs, and roughly this same split between regimented productive work and relatively free and inefficient non-work.
This work vs non-work split also correlates roughly to where we have healthy vs unhealthy cultural evolution today. Even though many maladaptive norms limit how firms can innovate to make work more productive, capitalist competition has been driving firms to be more productive overall. But our vibe-driven and norm-intensive artisanal non-work practices re food, clothes, homes, friends, lovers, parenting, etc. have been drifting into maladaption.
But such maladaptive culture just can’t last, however much we enjoy it. Sorry, just defying selection pressures was never going to be stable in the long run. And this seems to me to be our most fundamental modern mistake, which our descendants must eventually solve. But how?
My default scenario is that our main world civ falls, to be replaced by insular fertile groups like the Amish and Haredim. Groups whose non-work lives are strongly set by their conservative religious cultures, which do not give individuals much room for rich autonomous artisanal non-work lives. Yes, they may find it harder to organize work as efficiently, and as they grow they may well fall into the modern pattern again, likely resulting in at least one repeat of our civ’s rise and fall.
Another scenario is that we allow capitalist orgs to own and run more people, things, and areas of life. Yes, humans seem quite opposed to this at present, but humans may well start out AIs (or ems) in this sort of situation, and allow that to continue as they grown in power and ability. Perhaps realizing some versions of what many have long feared as totalitarian dystopias.
I’ve outlined other scenarios for making culture more adaptive, but I’ve described those at higher levels of abstraction, as ways to search for more concrete answers. So these may well also result in something like such scenarios.
If you don’t like such options, I sincerely invite you, implore you actually, to help us find more better alternatives.
AI is Acceleration
I was once an AI researcher, and since then I’ve been both an economist and a futurist for many decades. For most of that time, I’ve been one of the few who most specialized in thinking about the social impact of future AI. Furthermore, recent events haven’t actually taught us that much more about this topic. So listen when I tell you: most issues that people have with AI are actually issues they have with the future, even without AI. Except that AI might accelerate the schedule. Seven examples:
People who invent something new must typically pay for the resources that they consume in this process, and any negative externalities they thereby impose. Like how AI data-centers must pay for electricity, water, and noise pollution. Then such inventors gain some intellectual property rights over future versions of what they invent. Those who back such ventures must risk capital, to gain a chance of future rewards, both of which may be taxed or subsidized at some rate. Nations have to decide how much to favor local competitors, due to possible military, economic, and prestige gains for the nation. All of these issues are being considered today re AI.
We’ve long had to make difficult judgements about how to allocate credit and data rights between bosses and subordinates, tool users and makers, and the inspired and the inspiring. Sometimes we must adjust our crude proxies for quality when it becomes too easy to fake such proxies. Recent AI advances force us to yet again reconsider our policies re these divisions. Such as re whether AI “slop” is art, if students can use AI to complete assignments, and who to credit between AI makers and users.
Over history, human environments have continued to drift away from those where humans first evolved. As a result, we notice more “alienation”, and more seek connection to those “natural” environments. But we should expect the future to become even stranger and less comforting to our deep instincts. AI is and seems strange, and seems likely to accelerate our drift into strangeness.
We don’t really know much about which kinds of physical systems produce “hard problem” type consciousness, though we each feel confident that our physical brain does this often while we live. We have some priors, but almost no data. So there has always been a risk that as we change stuff about our bodies and its environment, we might stop being conscious. Such as by changing foods, brain tools, etc. The further we go in using tech to modify our bodies and worlds, the larger this risk becomes. AI may undergo more such changes faster, forcing us to wonder which AIs and AI-augmented humans are actually conscious.
Mostly via culture, humans have long accumulated more abilities, which has increased how many humans Earth can support. We have also increased the rates at which we can so innovate. In the last thousand years, we have not much increased the rate at which we can grow the human population, but we have greatly increased the rate at which we can grow wealth. As a result, we’ve seen increasing wealth per person. But we should expect this situation to end eventually, with a return to subsistence wages, once we find better techs for growing population faster. And as we have ways to grow the population of AIs (and ems) very fast, then when AIs can replace most all human labor, human wages should fall to AI subsistence levels, which is well below human levels. Humans today should thus want to insure against the risk of suddenly losing their jobs during their work years.
In history, descendants consistently grew in capabilities relative to their still-living ancestors, and eventually became powerful enough to win most conflicts with such ancestors. Descendants have also consistently changed their priorities, norms, and values over time, even when ancestors disapproved. Even so, ancestors typically sacrificed greatly to enable and support descendant prosperity. These trends have all continued strongly even as both lifespans and rates of cultural change have greatly increased, which has resulted in a much wider range of conflicting values being around at the same time. Our default expectation should be that this trend continues into the future, including for AIs, who will literally be descended from us, and inherit many features from us; they will change their priorities, and win conflicts with human ancestors. Preventing this requires ancestors to acquire unprecedented powers over descendants.
Up until a few centuries ago, most human culture was quite adaptive, due to high variety, strong selection pressures, reluctance to change, and slow rates of environmental change. Then the rise of strong capitalist selection pressures induced far faster rates of change in tech, work, and business, and the new big capitalist orgs made work far more regimented and less autonomous. While many feared that non-work lives would soon be similarly regimented, we spent our increased wealth on preventing this from happening. So our non-work lives, such as love, friendship, parenting, and governance, have remained relatively autonomous and artisanal. But as a result, non-work culture has been drifting into maladaption, due to greatly fallen variety and selection pressures, and increased rates of internal and environmental change. We should expect that eventually our non-work culture must become adaptive again, likely via becoming more constrained by large capitalist orgs. Strong selection pressures for subsistence wage AIs (or ems) could make this happen sooner.
Added 21Feb: Note that if I’m right that our AI issues are really just future issues, there is less point in thinking about AI in particular, compared to the future in general.
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