AI – Page 2 – Militant Futurist

August 31, 2022September 4, 2022

Aliens and posthumans will look the same

Among people who think about intelligent alien life, the first question is whether the latter exist at all, and the second is usually “What do they look like?” People who claim to have seen aliens on Earth (and often, to have been abducted by them) usually say they are humanoid, but with considerable variation in other aspects of their appearance. Typically, the aliens are said to have larger heads than humans, meaning their brains are larger, giving them higher intelligence and perhaps even special mental abilities like telepathy. Hollywood has provided us with an even more diverse envisagement of alien life, from the beautiful and inspiring to the grotesque and terrifying.

Betty Hill with a sculpture of one of the aliens that allegedly abducted her and her husband in 1961. They became famous five years later when a book was published about it.

“Close Encounters of the Third Kind” was released in 1977 and was a hit film. Its aliens were similar to what the Hills described. The “Grey alien” is now a familiar sci-fi trope.

I think intelligent aliens exist, and look like all of those things, and nothing in particular. They’re probably “shapeshifters,” either because their bodies can morph into different configurations, or because they can transplant their minds from one body to another, just like you change outfits.

As the multitude of animal species on our planet demonstrates, there is no single “best” type of body to have. Depending on your environment (terrestrial, underwater, airborne), role (predator, herbivore, parasite), and other factors, your optimal body plan will vary greatly. The best species is thus one that can change its form and function in response to the needs of the moment.

Humans have been so successful as a species because our big brains and opposable thumbs give us the ability to create technology, which is a way around the limitations of our fixed anatomy. For example, we originated in Africa where it was hot, and so lacked thick fur to keep us warm in cold climates. Rather than being stuck in Africa forever, we invented clothing, and so gained the ability to spread to the temperate and polar regions of the planet.

Our technology has let us spread, but its has limitations. Nothing but a fundamental alteration of human biology will let us live in oceans and lakes, to fly naturally, or to live comfortably in extraterrestrial environments. For example, on other planets and moons, our ideal heights and limb proportions will vary based on gravity and temperature levels, and in the weightlessness of space, legs are almost useless and should be replaced with a second pair of arms.

And making any of those changes to tailor a human to such an environment would make them less suited for conditions on Earth’s land surface, where we are now. Biology is very constraining.

For those reasons, AI’s and some fraction of our human descendants, who I’ll call “posthumans” for this essay, will find it optimal to not have fixed bodies or “default” physical forms at all. Intelligent machines will exist as consciousnesses running on computer servers, and posthumans as brains inside sealed containers. Those containers will have integral machinery to support the biological needs of the brains, and to interface the organ with other devices.

Whenever the AIs or posthumans wanted to do something in the physical world, they would take temporary control of a body or piece of machinery that was best suited for the intended task. For example, if an AI wanted to work at an iron mine, it would assume control over one of the dump trucks at the site that moves around rocks. The AI would see through the truck’s cameras as if it were its own eyes, and hear its surroundings through the vehicle’s microphones. In a sense, the dump truck would become the AI’s “body.” If a posthuman wanted to experience what it was like to be an elephant, it would take control of a real-looking robot elephant whose central computer was compatible with the posthuman’s cybernetic brain implants. The posthuman’s nervous system would be connected to the artificial elephant’s sensors, effectively turning it into the posthuman’s temporary body.

AIs and posthumans could physically implant their minds into those bodies by inserting their servers or brain containers into corresponding slots in the bodies, in the same way you would put a movie disc into a Blu-Ray player to display that movie. The downsides of this are 1) they could only take over larger bodies that had enough internal space for their servers/brain containers and 2) they would put themselves at risk of death if the commandeered bodies got damaged.

A much better option would be for AIs and posthumans to keep their mind substrates in safe locations, and to remotely control whatever bodies they wanted. Your risk of death is very low if your brain is in a bulletproof jar, in a locked room, in an underground bunker. (Additionally, if posthumans were liberated from all the physical constraints of human skulls and bodies, their brains could grow much larger than our own, giving them higher intelligence and other enhanced abilities.)

This kind of existence will be more fulfilling than your current life.

Finally, being able to switch bodies and to indulge in risky activities without fear of death would make life richer and more satisfying in every way. Intelligent aliens would presumably be gifted with logical thinking just as we are, and they would see all these advantages of having changeable, remotely controlled bodies. While such aliens would probably look very different from us during their natural organic phase of existence, once they achieved a high enough level of technology, they wouldn’t have physical bodies anymore, and so wouldn’t look “alien.” They would look like nothing and everything.

This part of why I’m skeptical of people who claim to have been abducted by aliens who tried to cover up their actions by sneaking up on the people at night and then “wiping” the abductees’ memories of the event afterward. If aliens wanted to keep their activities secret, why wouldn’t they temporarily assume human form before abducting people? If they did that, then the abductees would assume they had been kidnapped by a weird cult or maybe a secret government group. Their stories would not attract nearly as much interest from the public as alien stories, and no one would suspect that the abduction phenomenon was related to alien life. It would be assumed that the henchmen were doing some dark religious rituals, were sex fetishists, or were doing medical experiments that were illegal but whose results were potentially valuable.

Have you ever checked to make sure every bird you see flying through the air is actually a real bird?

Surely, if aliens are advanced enough to travel between the stars, their space ships much have manufacturing machines that can scan life forms they encounter on other planets and then build robotic copies of them that the aliens can remotely control from the safety of their ships. Using fake human drones, they could ambush and abduct real humans almost anywhere without risk that anyone would suspect aliens were involved.

A team of scientists built a robot gorilla (right) with a camera in its right eye to infiltrate a troop of real gorillas in Africa.

This belief about the protean nature of advanced aliens is comforting since it lets me dismiss the stories of nightmarish abductions by grey aliens. However, it’s also disquieting since it makes me realize they could be here, possibly in large numbers, disguised as animals or even as people. We could be under mass surveillance.

April 30, 2022

The extraordinary inefficiency of humans

All humans are born ignorant and helpless. A child’s parents, community, and society pays an enormous sum of time and money to provide their basic needs and to prepare them for adulthood. Nearly all children in modern societies are incapable of being anything but economic liabilities until age 16, when they might finally have the right intelligence, strength, and personality traits to work full time and contribute more to the economy than they consume.

Of course, in increasingly advanced societies like ours, economic, scientific, and technological growth depend on having high-quality human capital, and that requires schooling and workplace training well into a person’s 20s. This effectively extends the “liability” phase of such a person’s life just as long, as higher education usually costs more money than a young adult student can make at a side job.

Once that is finished, the productive period of an educated person’s life lasts about 40 years, after which they retire and stop contributing to the economy, science, or technology. In terms of a resource balance sheet, the only difference between this period of a person’s life and his childhood is that, as a retiree, he is probably living off his own accumulated savings rather than other peoples’ money.

And then the person dies, at 80 let’s say. He spent the first 25 years of his life learning and preparing for the workforce, 40 years participating in it and making real, measurable contributions to the world, and the final 15 years hanging around his house and pursuing low-key hobbies. That means this person, who we’ll think of as the “average skilled professional,” had a “lifetime efficiency rate” of 50%. Not bad, right?

Actually, it’s much worse once you also consider this person’s daily time usage:

The average, working-age American only spends about 1/3 of his day working. Sleep takes up just as much time, and the remaining 1/3 of the day is devoted to leisure, satisfying basic physiological needs (e.g. – eating, drinking, cleaning one’s body), running errands, doing chores, and caring for offspring or elderly parents. This means the typical person’s “lifetime efficiency rate” decreases by 2/3, from 50% to 16.6%.

But it gets worse. Any adult who has spent time in a workplace knows that eight hours of real work rarely get done during an eight-hour workday. Large amounts of time are wasted doing pointless assignments that shouldn’t exist and don’t actually help the organization, going to meetings that accomplish nothing and/or take longer than necessary, socializing with colleagues, using computers and smartphones for entertainment and socializing, doing non-value-added training, or doing actual value-added refresher training that must be undertaken because the brains of the human workers constantly forget things. In industrial jobs, there’s often downtime thanks to lack of supplies or to a crucial piece of equipment being unavailable.

From personal experience and from years of observation, I estimate that only 25% of the average American professional’s work day is spend doing real, useful work. That means the lifetime efficiency rate drops to 4.2%.

It still gets worse. Realize that many highly productive people who, let’s say, might actually do eight hours of real work per eight hour work day, are actually doing things that damage the world and slow down the pace of progress in every dimension. Examples include:

A journalist who consciously inserts systematic bias into their news reports, which in turn leave thousands of people misinformed, anxious, and bigoted against another group of people.
An advertising executive whose professional life revolves around tricking thousands of people into buying goods or services that they don’t need, or that are actually inferior to those offered by competitors. The result is a massive misallocation of money, and possible social problems as only people with higher incomes can visibly enjoy the useless products, while poorer people can only watch with envy.
A mathematician who uses his gifts in the service of a Wall Street hedge fund, finding exotic and highly technical ways to aggregate stock market money in his company’s hands at the expense of competitors. The hedge fund creates no value and doesn’t expand the size of the “economic pie”–it merely expands the size of its own slice of that pie.
A bureaucrat who manages a program meant to further some ill-defined social mandate. Though he and his team have won internal agency awards for various accomplishments, by every honest metric, the program has consistently and completely failed to help its target demographic.
A drug dealer who “hustles” his part of the city from sunrise to sunset, doing dozens of deals per day and often dodging bullets. The drugs leave his customers too intoxicated to work or to take care of themselves and their families, and have sent many of them to hospitals thanks to overdoses and chemical contaminants.

These kinds of people do what could be called “counterproductive work” or “undermining work,” and it can be very hard to tell them apart from people who do useful work that helps the whole world. Unfortunately, peripheral people who use their own labors to support the counterproductive people, like the cameraman who films the dishonest newscaster’s reports, are also doing counterproductive work, even if they don’t realize it. Once the foul efforts of these people are subtracted from the equation, the lifetime efficiency rate of the median American professional drops to, I’ll say, 3.5%.

Only 3.5% of this educated and well-trained person’s life is spent doing work that benefits society with no catches or caveats. Examples include:

A heart surgeon who saves the lives of younger people.
A medical researcher who runs experiments that help discover a vaccine for a painful, widespread disease.
A chemist who discovers a way to make solar panels more cheaply, without any reduction to the panels’ efficiency, lifespan, or any other attribute.
A civil engineer who designs a bridge that sharply reduces commute times for local people, resulting in aggregate fuel savings that exceed the bridge’s construction cost in ten years.
A carpenter who helps build affordable housing that meets all building codes, in a place where it is in high demand.

In each case, the person’s labor helps other people while hurting no one, and improves the efficiency of some system.

Let me mention two important caveats to this thought experiment. First, humanity’s 3.5% efficiency rate might sound pitiful, but it beats every other species, which all have 0% efficiency. One-hundred percent of every non-human animal’s time is spent satisfying physiological needs (e.g. – hunger, sleep), avoiding danger, caring for offspring, and indulging in pleasure (which might be fairly lumped in with “satisfying physiological needs”). At the end of its life, the animal leaves behind no surpluses, no inventions, and no works that benefit its species or anything else, except maybe by pure accident. Our measly 3.5% efficiency rate allowed our species to slowly edge out all the others and to dominate the planet.

Second, under my definition of “efficiency,” it’s possible for a person to have 0% efficiency even though they work very hard, create tangible fruits of their labor, and never do “counterproductive work.” A perfect example of such a person would be a primitive hunter or sustenance farmer who is always on the brink of starvation and spends all his time acquiring and eating food, with no time left over for other pursuits. He never invents a new type of spear or plow, never builds anything more than a wooden shack that will collapse shortly after he dies, and never makes up any religions or useful pieces of knowledge. For the first 95% of our species’ existence, our aggregate lifetime efficiency rate was infinitesimally greater than 0%.

Am I doing this thought experiment just to be dour and to cast humanity in a cynical light? No. By illustrating how inefficient we are, I’m just making a case that we’ll be surpassed by intelligent machines that will be invariably more efficient. Ha ha!

The first key advantage intelligent machines will have is perfect memories. They will never forget anything, and will be able to instantly recall all their memories. This will dramatically shorten the amount of time it takes to educate one of them to the same level as the average American professional I’ve profiled in this essay. Much of teaching is repetition of the same things again and again. And since intelligent machines wouldn’t forget anything, there would be no need for periodic retraining in the workplace, which takes time away from doing real work. Machines wouldn’t have “skills degradation,” and they wouldn’t need to practice tasks to remind themselves how to do them.

(Note that I’m not even assuming that machines will be faster at learning new things than humans are. Again, I’m being conservative by only assuming that they don’t forget things.)

The second key advantage would be near-freedom from human physiological needs, like the need to sleep, eat, or clean one’s self. Intelligent machines would need to periodically go offline for maintenance, repairs or upgrades, but this wouldn’t gobble up anywhere near as much time as it does in humans. For example, while a human spends 33% of his life sleeping, a typical server at a major tech company like Amazon or Facebook spends less than 1% of its time “down.” Intelligent machines wouldn’t have a good correlate to “eating,” since they would only consume electricity and do it while simultaneously performing work tasks. And since machines wouldn’t sweat, shed skin, or grow more than trivial amounts of bacteria on themselves, they wouldn’t need to clean their bodies or garb (if they wore any) nearly as often as humans. Intelligent machines also wouldn’t have a need for leisure, or if they did, they might need less than we do, saving them even more time.

Instead of being able to devote just eight hours a day to learning and working, an intelligent machine could devote 20 hours a day to them, as a conservative estimate. This, in turn, would further shorten the amount of time needed to educate a machine to the same level as the average American professional. I wrote earlier that the professional needed schooling until age 25 to be able to start a high-level job. Since the intelligent machine can spend more time each day studying, it can attend the same number of classes in only 10 years. And since it has a perfect memory, it lessons don’t need to contain as much repetition, and remedial lessons are unnecessary. Let’s say that cuts the amount of schooling needed by 30%. An intelligent machine only needs seven years to operate at the same level as a highly educated 25-year-old human.

And in the workplace, an intelligent machine wouldn’t be subject to the distractions that its human colleagues were (e.g. – socializing, surfing the internet), though its human bosses might still give it pointless assignments or force it to attend unproductive meetings. Still, during an eight-hour day, it would get at least seven hours of real work done (and this is another conservative guess). But as noted earlier, it would actually have 20 hour work days, meaning it would get 17.5 hours of real work done each day, dwarfing the two hours of real work the typical American professional does per day.

As for the “counterproductive work” / “undermining work,” I predict that human bosses will someday task intelligent machines with doing it, allowing scams, disinformation peddling, and criminal enterprises to reach new heights of efficiency. However, the victims will all be humans. Intelligent machines themselves would not be dumb enough, impulsive enough, or possessed of the necessary psychological weaknesses to take whatever bait the “counterproductive workers” were offering, and the latter will be laid bare before their eyes and avoided. For example, an intelligent machine looking to buy a new vehicle would have a perfect understanding of its own needs, and would only need a few seconds to thoroughly research all the available vehicle models and identify the one that best met its criteria. Car commercials designed to play on human emotions, insecurities, and lifestyle consciousness to dupe people into buying suboptimal vehicles wouldn’t sway the machine at all.

I won’t do another set of calculations for the hypothetical intelligent machine, but it should be clear that its advantages will be many and will compound on top of each other, resulting in them being much more efficient that even highly trained humans at doing work. Moreover, in a machine-dominated world, where they controlled the economy, government, and resource allocation, parasitic “counterproductive work” that we humans mistake for useful work would probably disappear. Just as humans slowly edged out all other species thanks to our tiny work efficiency advantage over them, intelligent machines will edge out humans in the future. It’s just a question of when.

October 29, 2019

Nihil sub sole novum

While writing my recent blog entry on The Physics of the Future, I discovered that author Michio Kaku’s description of the “Kardashev Scale” was wrong. Kaku said that a “Type 1” civilization on the Kardashev Scale was one that was “planetary” in scope, character and energy consumption, and that trends suggested humans wouldn’t achieve this rank until the year 2111. Kaku said that, we were in fact so pitiful at the time of the book’s writing that our civilization was only “Type 0.”

However, in Dr. Nikolai Kardashev’s science paper that established the Scale, he defined a “Type 1” civilization as being one that consumed as much energy as humans did at that time. That means humanity has been a Type 1 civilization since 1964! Kardashev also didn’t say anything about there being a “Type 0” classification.

Convinced that I alone knew of an embarrassing mistake made by one of the world’s foremost pop-science talking heads, I set out to write a blog entry about it titled “The misused and useless Kardashev Scale.” I spent an afternoon reading Kardashev’s original paper and its cited articles to actually understand it, and in other research found online articles and videos where even more smart people had cluelessly espoused a flawed definition of the Scale. This thing was even bigger than I had thought, and I was about to blow the lid off of it! This would finally put my lousy blog on the map!

And then, I found out someone else had already written about this very subject, and had done so with superior prose than I could probably write. J.N. “Nick” Nielsen beat me by five years with his article “What Kardashev Really Said.”

What a waste of my time.

It got me thinking about how much human effort is duplicative, and how much more efficient and creative we would be if we didn’t needlessly reinvent the wheel. Of course, this is impossible for mere humans since never being derivative requires perfect knowledge of everything that everyone else has already said, done, or created, and our minds are incapable of holding that much information. However, it’s easy to see how technology could change this.

Google Image search results for “red robin bird”

Imagine a smartphone app that was connected to the device’s camera. I’ll call the app “Copycat.” Every time you turn on your camera, Copycat starts watching what’s visible through the viewfinder. Once it detects that you’re steadying the camera to prepare to take a still photo, the app would compare the scene in front of you with trillions of other photos available for free on the internet. If you were about to take a picture that looked identical or nearly identical to one that already existed, Copycat would warn you, show you an image of the other picture, and tell you if there were any ways you could, standing there, produce a new type of image. Maybe snap the photo of the songbird from low on the ground, or walk 10 feet to the right to photograph it with that stone building in the background.

This level of technology is well within reach: the image analysis and recognition feature is no different from Google’s “reverse image search.” The second feature could easily arise from a set of deep learning programs that are trained to recognize visually well-composed and aesthetically pleasing photo compositions, and to come up with ways to reposition the elements within an image to raise or maximize those values. Upload enough training data, and it will figure it out.

Copycat is a highly specific example, but it illustrates technology’s potential to help people make better use of their time by warning them before they do something that has already been done. And an important ancillary benefit is that it will remind us of valuable and interesting things people have already done, but which may have been largely forgotten. In showing you images, Copycat might make you aware of long-dead bird photographers you had never heard of, spurring you to research them further and to beautify your house with framed prints of their (free) artwork.

Along with boosting the originality of artwork, music, and writing, this sort of technology would be invaluable to scientists and engineers who are deciding how to spend their scarce time and R&D money. A machine that had memorized the full body of scientific literature and patents could, respectively, tell a scientist which things had not been researched and tell an engineer which things had not been invented. The result would be no resources wasted on duplicative projects, and an acceleration of scientific and technological advancement, merely due to a sharper grasp of what is already known.

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