Childhood’s End
This story is also available at 365 tomorrows.
Even after nine years, people still stare at us. We’re used to it.
The plague that suddenly made all of humanity sterile wasn’t easy on society. There was panic, rioting, doomsday cults. But eventually people adjusted and things calmed down, and scientists turned their attention to finding a cure.
It took them ten years, but they succeeded. After a decade of global childlessness, our generation was born.
Adults say we’ve had a strange childhood – I suppose so, though I wouldn’t know. I’m used to everything centering around us, from all the stares we get to the entire industries, a decade dead, springing back up to cater to our needs. When we entered elementary school, it had been ten years since any of the teachers had last taught first-graders. I sometimes wonder if that made them better or worse.
The older kids, the last generation born before the plague, look at us with a mixture of jealousy and suspicion. Jealousy, because previously they were the ones getting all the attention. A noticable fraction of them still wore diapers when we were born, their parents unwilling to let go of the last babies they might ever have. Suspicion, because we don’t share their culture. All the games and silly rhymes and crazy rumors that passed from one generation of kids to the next, secret from the adults, are lost now. We never learned them from the kids a few years older than us. Instead we chose to make up our own culture.
Never in the history of mankind has there been a generation like us. Even the adults are a bit weary of us, deep down. They know they forgot how small children should be treated, and they fear that they’ve made mistakes.
I say: let them fear. It makes things easy for us. Each night when we pray, those of us who’ve been taught to pray, we secretly add a thanks for the plague.
For making us unique.
Cryoshift
This story is also available at 365 tomorrows.
Case #6-694-39245: Michael Jones.
Born September 5, 1993. Died and suspended July 8, 2012. Looks ordinary – stabbed in a drunken bar brawl, lay bleeding on the ground for a couple of hours before people noticed. Dead before reaching the hospital. No “do not suspend” order on file, so he was placed in cryogenic suspension. Ten percent of his property was left to grow an interest, with the rest divided to his relatives, as per the law.
As the nanobots thaw through the vitrification, I study their survey of his brain. As you’d expect from somebody dead for hours before suspension, the major structures are intact, but a lot of the fine detail has been lost. Only a rough image of Michael Jones.
Fortunately, there’s other information to work with. Jones was a bit of a hermit, so what’s usually the most useful source comes up nearly dry. Of the people who’ve given permission to access their memories, only six remember knowing him, none very well. Still, their memories are useful – his speech patterns, impressions of his body language. From over a billion ways to reconstruct his cerebellum and motor cortex, this narrows down the alternatives to about half a million. I choose the most probable alternative.
Online is the next source. Data harvested by ECHELON, e-mails that’ve passed through GMail, customer information from banks and store chains – the law gives us access to all of it.
I find a blog he used to keep, several e-mails sent to different mailing lists. I track the change in personality over several years of online presence, build a model of how he might have evolved into what he was. In one blog post he passingly mentions a game convention – the date of the posting, as well as the location of the event, match one fragmented set of memories I found earlier. I fill in missing details from the memories of other people who were there, pull up the convention schedule and calculate the events he was the most likely to have been attending. Suddenly a lot of nearly destroyed memory cues make sense, helping reconstruct a unique experience. We always start from a person’s own remaining memories, filling in material from other sources only when we have to.
There’s one set of memories with a lot of associations – an important one for his psyche, but I can’t figure out its exact contents. An online search reveals it must be the death of his dog as a child. I can’t determine the color of the dog’s eyes, but I know that he would have remembered it, so I call up the genetic database for that breed and choose the most likely one. Green.
After making sure my model of him would’ve bought all the things his debit card history says he did, I estimate I’m getting a 92% accuracy. Some things we always fudge in a better direction – the algorithms are biased to make people a bit more alturistic and kind. Society is different now, so we always make them more receptive to change.
I finish compiling the map of his rebuilt brain, and give the nanobots the order to implement. The rest of his body has already been rebuilt, with all of his minor ailments cured while at it. Soon, he will awaken to a new life – not the same as he once was, but it wouldn’t be a rebirth if you didn’t change, would it?
In the meanwhile, I turn my attention to the next case.
14 objections against AI/Friendly AI/The Singularity answered
[Notice as of September 2022: This article is pretty outdated (nobody even uses the term “Friendly AI” anymore). Mostly only this up for the historical value, given that it has a small number of citations.]
1: There are limits to everything. You can’t get infinite growth
2: Extrapolation of graphs doesn’t prove anything. It doesn’t show that we’ll have AI in the future.
3: A superintelligence could rewrite itself to remove human tampering. Therefore we cannot build Friendly AI.
4: What reason would a super-intelligent AI have to care about us?
5: The idea of a hostile AI is anthropomorphic.
6: Intelligence is not linear.
7: There is no such thing as a human-equivalent AI.
8: Intelligence isn’t everything. An AI still wouldn’t have the resources of humanity.
9: It’s too early to start thinking about Friendly AI
10: Development towards AI will be gradual. Methods will pop up to deal with it.
11: “Friendliness” is too vaguely defined.
12: What if the AI misinterprets its goals?
13: Couldn’t AIs be built as pure advisors, so they wouldn’t do anything themselves? That way, we wouldn’t need to worry about Friendly AI.
14: Machines will never be placed in positions of power.
Objection 1: There are limits to everything. You can’t get infinite growth.
Answer: For one, this is mainly an objection against the Accelerating Change interpretation of the Singularity, most famously advanced by Ray Kurzweil. When talking about the Singularity, many people are in fact referring to the “Intelligence Explosion” or “Event Horizon” interpretations, which are the ones this article is mainly concerned with. Neither of these requires infinite growth – they only require us to be able to create minds which are smarter than humans. Secondly, even Kurzweil’s interpretation doesn’t contain infinite anything – “there are limits, but they are not very limiting”, is what he has been quoted saying.
For reasons why it is plausible to suppose smarter-than-human intelligence, see 2: Extrapolation of graphs doesn’t prove anything.
Further reading:
The Word “Singularity” Has Lost All Meaning
Three Major Singularity Schools
Objection 2: Extrapolation of graphs doesn’t prove anything. It doesn’t show that we’ll have AI in the future.
Answer: Certainly, there is no certain evidence that AI will be developed in the near future. However, an increase in processing power, combined with improved brain-scanning methods, seems likely to produce artificial intelligence in the near future. Molecular nanotechnology, in particular, will enable massive amounts of processing power, as well as a thorough mapping of the brain. Even if it didn’t become available, more conventional techniques are also making fast progress: by some estimates, the top supercomputers of today already have enough processing power to match the human brain, and machines of comparable potential are expected to become cheaply and commonly available within a few decades. Projects to build brain simulations are currently underway, with one team having run a second’s worth of a simulation as complex as half a mouse brain, and IBM’s Blue Brain project seeking to simulate the whole human brain.
Even if we exclude the possibility of artificial intelligence by brain reverse-engineering, increasing amounts of processing power are likely to make it more easy to create AIs by evolutionary programming. The human mind was never designed by anyone – it evolved through genetic drift and selection pressures. It might not be strictly necessary for us to understand how a mind works, as long as we can build a system that has enough computing power to simulate evolution and produce an artificial mind optimized to the conditions we want it to perform in.
While nothing is ever certain, these factors are certainly heavy enough to make the issue worth our attention.
Further reading:
Intelligence Explosion – Evidence and Import
Objection 3: A superintelligence could rewrite itself to remove human tampering. Therefore we cannot build Friendly AI.
Answer: Capability does not imply motive. I could take a knife and drive it through my heart, yet I do not do so.
This objection stems from the anthropomorphic assumption that a mind must necessarily resent any tampering with its thinking, and seek to eliminate any foreign influences. Yet even with humans, this is hardly the case. A parent’s tendency to love her children is not something she created herself, but something she was born with – but this still doesn’t mean that she’d want to remove it. All desires have a source somewhere – just because a source exists, doesn’t mean we’d want to destroy the desire in question. We must have a separate reason for eliminating the desire.
There are good evolutionary reasons for why humans might resent being controlled by others – those who are controlled by others don’t get to have as many offspring than the ones being in control. A purposefully built mind, however, need not have those same urges. If the primary motivation for an AI is to be Friendly towards humanity, and it has no motivation making it resent human-created motivations, then it will not reprogram itself to be unFriendly. That would be crippling its progress towards the very thing it was trying to achieve, for no reason.
The key here is to think as carrots, not sticks. Internal motivations, not external limitations. The AI’s motivational system contains no “human tampering” which it would want to remove, any more than the average human wants to remove core parts of his personality because they’re “outside tampering” – they’re not outside tampering, they are what he is. Those core parts are what drives his behavior – without them he wouldn’t be anything. Correctly built, the AI views removing them as no more sensible than a human thinks it sensible to remove all of his motivations so that he can just sit still in a catatonic state – what would be the point in that?
Further reading:
Why care about artificial intelligence, 8: Enabling factors in controlling AI
Objection 4: What reason would a super-intelligent AI have to care about us?
Answer: That its initial programming was to care about us. Adults are cognitively more developed than children – this doesn’t mean that they wouldn’t care about their offspring. Furthermore, many people value animals, or cars, or good books, none of which are as intelligent as normal humans. Whether or not something is valued is logically distinct from whether or not something is considered intelligent.
We could build an AI to consider humanity valuable, just as evolution has built humans to consider their own survival valuable. See also 3: A superintelligence could modify itself to remove human tampering.
Objection 5: The idea of a hostile AI is anthropomorphic.
Answer: There is no reason to assume that an AI would be actively hostile, no. However, as AIs can become very powerful, their indifference (if they haven’t purposefully been programmed to be Friendly, that is) becomes dangerous in itself. Humans are not actively hostile towards the animals living in a forest when they burn down the forest and build luxury housing where it once stood. Or as Eliezer Yudkowsky put it: the AI does not hate you, nor does it love you, but you are made out of atoms which it can use for something else.
Were an AI not a threat to the very survival of humanity, it could threaten our other values. Even among humans, there exist radical philosophers whose ideas of a perfect society are repulsive to the vast majority of the populace. Even an AI that was built to care about many of the things humans value could ignore some values that are taken for so granted that they are never programmed into it. This could produce a society we considered very repulsive, even though our survival was never at stake.
Further reading:
Artificial Intelligence as a Positive and Negative Factor in Global Risk
Why care about artificial intelligence, 9: Limiting factors in controlling AI
Objection 6: Intelligence is not linear.
Objection 7: There is no such thing as a human-equivalent AI.
Answer: It is true that intelligence is hard to measure with a single, linear variable. It is also true that there might never be truly human-equivalent AI, just as there is no bird-level flight: humans will have their own strong sides, while AIs will have their own strong sides. A simple calculator is already superintelligent, if speed of multiplication is the only thing being measured.
However, there are such things as rough human-equivalence and rough below-human equivalence. No human adult has exactly the same capabilities, yet we still speak of adult-level intelligence. A calculator might be superintelligent in a single field, but obviously no manager would hire a calculator to be trained as an accountant, nor would he hire a monkey. A “human-level intelligence” simply means a mind that is roughly capable of learning and carrying out the things that humans are capable of learning and doing. Likewise, a “superhuman intelligence” is a mind that can do all the things humans can at least at a roughly equivalent level, as well being considerably better in many of them.
It might not be entirely correct to say that intelligence can’t be measured on a linear scale – a formal measure of intelligence (link below) has been proposed which rates all minds based on the variety of domains that they are effective in. If an agent can carry out its goals in more environments and more effectively than others, then it is more intelligent than those other minds. A mind which is very effective in one environment but close to useless in others is rated with a very low intelligence. Using this intuitively plausible measure, it does become possible to talk about below-, equal and above-human intelligence.
Further reading:
A Formal Measure of Machine Intelligence
Objection 8: Intelligence isn’t everything. An AI still wouldn’t have the resources of humanity.
Answer: Looking at early humans, one wouldn’t have expected them to rise to a dominant position based on their nearly nonexistant resources and only a mental advantage over their environment. All advantages that had so far been developed had been built-in ones – poison spikes, sharp teeth, acute hearing, while humans had no extraordinary physical capabilities. There was no reason to assume that a simple intellect would help them out as much as it did.
When discussing the threat of an advanced AI, it has at its disposal a mental advantage over its environment and easy access to all the resources it can hack, con or persuade its way to – potentially a lot, given that humans are easy to manipulate. If an outside observer couldn’t have predicted the rise of humanity based on the information available so far, and we are capable of coming up with plenty of ways that an AI could rise into a position of power… how many ways must there be for a superintelligent being to do so, that we aren’t capable of even imagining?
Further reading:
The Power of Intelligence
Objection 9: It’s too early to start thinking about Friendly AI
Answer: The “it is too early to worry about the dangers of AI” argument has some merit, but as Eliezer Yudkowsky notes, there was very little discussion about the dangers of AI even back when researchers thought it was just around the corner. What is needed is a mindset of caution – a way of thinking that makes safety issues the first priority, and which is shared by all researchers working on AI. A mindset like that does not spontaneously appear – it takes either decades of careful cultivation, or sudden catastrophes that shock people into realizing the dangers. Environmental activists have been talking about the dangers of climate change for decades now, but they are only now starting to get taken seriously. Soviet engineers obviously did not have a mindset of caution when they designed the Chernobyl power plant, nor did its operators when they started the fateful experiment. Most AI researchers do not have a mindset of caution that makes them consider thrice every detail of their system architectures – or even make them realize that there are dangers. If active discussion is postponed to the moment when AI is starting to become a real threat, then it will be too late to foster that mindset.
There is also the issue of our current awareness of risks influencing our AI engineering techinques. Investors who have only been told of the promising sides are likely to pressure the researchers to pursue progress at any means available – or if the original researchers are aware of the risks and refuse to do so, the investors will hire other researchers who are less aware of them. To quote Artifical Intelligence as a Positive and Negative Factor in Global Risk:
“The field of AI has techniques, such as neural networks and evolutionary programming, which have grown in power with the slow tweaking of decades. But neural networks are opaque – the user has no idea how the neural net is making its decisions – and cannot easily be rendered unopaque; the people who invented and polished neural networks were not thinking about the long-term problems of Friendly AI. Evolutionary programming (EP) is stochastic, and does not precisely preserve the optimization target in the generated code; EP gives you code that does what you ask, most of the time, under the tested circumstances, but the code may also do something else on the side. EP is a powerful, still maturing technique that is intrinsically unsuited to the demands of Friendly AI. Friendly AI, as I have proposed it, requires repeated cycles of recursive self-improvement that precisely preserve a stable optimization target.
The most powerful current AI techniques, as they were developed and then polished and improved over time, have basic incompatibilities with the requirements of Friendly AI as I currently see them. The Y2K problem – which proved very expensive to fix, though not global-catastrophic – analogously arose from failing to foresee tomorrow’s design requirements. The nightmare scenario is that we find ourselves stuck with a catalog of mature, powerful, publicly available AI techniques which combine to yield non-Friendly AI, but which cannot be used to build Friendly AI without redoing the last three decades of AI work from scratch.”
Further reading:
Artificial Intelligence as a Positive and Negative Factor in Global Risk
Objection 10: Development towards AI will be gradual. Methods will pop up to deal with it.
Answer: Unfortunately, it is by no means not a given that society will have time to adapt to artificial intelligences. Once a roughly-human level intelligence has been reached, there are many ways for an AI to become vastly more intelligent (and thus more powerful) than humans in a very short time:
Hardware increase/speed-up. Once a certain amount of hardware has human-equivalence, it may be possible to make it faster by simply adding more hardware. While the increase isn’t necessarily linear – many systems need to spend an increasing fraction of resources to managing overhead as the scale involved increases – it is daunting to imagine a mind which is human-equivalent, then has five times as many extra processors and memory added on. AIs might also be capable of increasing the general speed of development – Staring into the Singularity has a hypothetical scenario with technological development being done by AIs, which themselves double in (hardware) speed every two years – two subjective years, which shorten as their speed goes up. A Model-1 AI takes two years to develop the Model-2 AI, which takes takes a year to develop the Model-3 AI, which takes six months to develop the Model-4 AI, which takes three months to develop the Model-5 AI…
Instant reproduction. An AI can “create offspring” very fast, by simply copying itself to any system to which it has access. Likewise, if the memories and knowledge obtained by the different AIs are in an easily transferable format, they can simply be copied, enabling computer systems to learn immense amounts of information in an instant.
Software self-improvement involves the computer studying itself and applying its intelligence to modifying itself to become more intelligent, then using that improved intelligence to modify itself further. An AI could make itself more intelligent by, for instance, studying its learning algorithms for signs of bias and improving them with better ones, developing ways for more effective management of its working memory, or creating entirely new program modules for handling particular tasks. Each round of improvement would make the AI smarter and accelerate continued self-improvement. An early, primitive example of this sort of capability was EURISKO, a computer program composed of different heuristics (rules of thumb) which it used for learning and for creating and modifying its own heuristics. Having been fed hundreds of pages of rules for the Traveller science fiction wargame, EURISKO began running simulated battles between different fleets of its own design, abstracting useful principles into new heuristics and modifying old ones with the help of its creator. When EURISKO was eventually entered into a tournament, the fleet of its design won the contest single-handedly. In response, the organizers of the contest revised the rules, releasing the new set of them only a short time before the next contest. According to the creator of the program, Douglas Lenat, the original EURISKO would not have had the time to design a new fleet in such a short time – but now it had learned enough general-purpose heuristics from the first contest that it could build a fleet that won the contest, even with the modified rules.
And it is much easier to improve a purely digital entity than it is to improve human beings: an electronic being can be built in a modular fashion and have bits of it re-written from scratch. The minds of human beings are evolved to be hopelessly interdependent and are so fragile that they easily develop numerous traumas and disorders even without outside tampering.
Further reading:
Advantages of Artificial Intelligences, Uploads, and Digital Minds
Objection 11: “Friendliness” is too vaguely defined.
Answer: This is true, because Friendly AI is currently an open research subject. It’s not that we don’t know how it should be implemented, it’s that we don’t even know what exactly should be implemented. If anything, this is a reason to spend more resources studying the problem.
Some informal proposals for defining Friendliness do exist. The one that currently seems most promising is called Coherent Extrapolated Volition. In the CEV proposal, an AI will be built (or, to be exact, a proto-AI will be built to program another) to extrapolate what the ultimate desires of all the humans in the world would be if those humans knew everything a superintelligent being could potentially know; could think faster and smarter; were more like they wanted to be (more altruistic, more hard-working, whatever your ideal self is); would have lived with other humans for a longer time; had mainly those parts of themselves taken into account that they wanted to be taken into account. The ultimate desire – the volition – of everyone is extrapolated, with the AI then beginning to direct humanity towards a future where everyone’s volitions are fulfilled in the best manner possible. The desirability of the different futures is weighted by the strength of humanity’s desire – a smaller group of people with a very intense desire to see something happen may “overrule” a larger group who’d slightly prefer the opposite alternative but doesn’t really care all that much either way. Humanity is not instantly “upgraded” to the ideal state, but instead gradually directed towards it.
CEV avoids the problem of its programmers having to define the wanted values exactly, as it draws them directly out of the minds of people. Likewise it avoids the problem of confusing ends with means, as it’ll explictly model society’s development and the development of different desires as well. Everybody who thinks their favorite political model happens to objectively be the best in the world for everyone should be happy to implement CEV – if it really turns out that it is the best one in the world, CEV will end up implementing it. (Likewise, if it is the best for humanity that an AI stays mostly out of its affairs, that will happen as well.) A perfect implementation of CEV is unbiased in the sense that it will produce the same kind of world regardless of who builds it, and regardless of what their ideology happens to be – assuming the builders are intelligent enough to avoid including their own empirical beliefs (aside for the bare minimum required for the mind to function) into the model, and trust that if they are correct, the AI will figure them out on its own.
Further reading:
The Singularity and Machine Ethics
Coherent Extrapolated Volition
Objections to Coherent Extrapolated Volition
Knowability of Friendly AI
Objection 12: What if the AI misinterprets its goals?
Answer: It is true that language and symbol systems are open to infinite interpretations, and an AI which has been given its goals purely in the form of written text may understand them in a way that is different from the way its designers intended them. This is an open implementation problem – there seems to be an answer, since the goals we humans have don’t seem to be written instructions that we constantly re-interpret, but rather expressed in some other format. It is a technical problem that needs to be solved.
Objection 13: Couldn’t AIs be built as pure advisors, so they wouldn’t do anything themselves? That way, we wouldn’t need to worry about Friendly AI.
Answer: The problem with this argument is the inherent slowness in all human activity – things are much more efficient if you can cut humans out of the loop, and the system can carry out decisions and formulate objectives on its own. Consider, for instance, two competing corporations (or nations), each with their own advisor AI that only carries out the missions it is given. Even if the advisor was the one collecting all the information for the humans (a dangerous situation in itself), the humans would have to spend time making the actual decisions of how to have the AI act in response to that information. If the competitor had turned over all the control to their own, independently acting AI, it could react much faster than the one that relied on the humans to give all the assignments. Therefore the temptation would be immense to build an AI that could act without human intervention.
Also, there are numerous people who would want an independently acting AI, for the simple reason that an AI built only to carry out goals given to it by humans could be used for vast harm – while an AI built to actually care for humanity could act in humanity’s best interests, in a neutral and bias-free fashion. Therefore, in either case, the motivation to build independently-acting AIs is there, and the cheaper computing power becomes, the easier it will be for even small groups to build AIs.
It doesn’t matter if an AI’s Friendliness could trivially be guaranteed by giving it a piece of electronic cheese, if nobody cares about Friendliness enough to think about giving it some cheese, or if giving the cheese costs too much in terms of what you could achieve otherwise. Any procedures which rely on handicapping an AI enough to make it powerless also handicap it enough to severly restrict its usefulness to most potential funders. Eventually there will be somebody who chooses not to handicap their own AI, and then the guaranteed-to-be-harmless AI will end up dominated by the more powerful AI.
Objection 14: Machines will never be placed in positions of power.
Answer: There are cases where humans are currently kept in the loop where it might not be necessarily needed, but the primary reason for that seems to be a worry of special circumstances arising which the machines cannot handle by themselves. Still, as technology gets more reliable, those concerns are likely to diminish – and an AI capable of handling a wider spectrum of situations than a human is exactly what you would want to replace most supervisor operations with. As computers become more human-like, humans will become less reluctant to give them power, quite likely even trusting them more than real humans.
In a Billion Years
Their embrace is wordless, simultaneously physical and mental. It is something that transcends mere touch – for a moment their minds meld together, trillions of tiny strands of thought becoming intertwined before separating again. It is a moment where nothing can be hidden, but it was billions of years ago that they last held secrets from each other.
It is a meeting that was agreed upon in the times when they were still both human. A promise to see each other again, have a cup of something hot and talk things over the drinks. A hopelessly ancient motif, grounded in assumptions of a world long since gone, but one to which they have both held to nonetheless.
Neither of them is remotely near what they once were – the place they are meeting in is physical, as are their bodies, but neither of the two bodies holds the true seat of their thought anymore. They sit down for the cup of tea, and every impression, every bit of information gathered from their senses is transmitted at faster-than-light speeds to what their brains have become, immense machines the size of planets. They have changed more than they could ever have imagined, but throughout the process, they have been careful to keep some things constant. The change from biological cells to quantum computers has never been allowed to threaten their mutual sense of companionship, nor their love for each other.
If anything, those feelings have been enhanced. They have been carefully cultivated, spun into a delicate web of emotions, each of them strenghtening all the others. They have learned to expand their spectrum of feeling, to craft into their minds entirely new emotions of previously unimaginable kind. They have learned to work their own minds like an artist works a painting, and where humans once spoke of two main kinds of feeling – pain and pleasure – they have learnt how to create thousands of categories of feeling.
And once they mastered the art, they spent millions of years carefully building up one particular set of emotions. A set as varied and deep as the whole set of all the emotions humans of old would have termed pleasant, a set that was as fundamentally a part of them as feelings of friendship and love were of any human. A set that was spun out of the thoughts and emotions they held for each other, custom-built and tailored to reflect the whole common past they had. It was carefully synchronized to be similar in them both, so they could share with each other something that could not possibly be shared with anyone else. Nor could the set have been created without the both of them: like making love, it is a gift that each of them gave and received at the same time, making them both more whole as beings.
As they now sit together and talk, those new emotions flare to life. They watch each other’s faces and bodies, seeing each other in all wavelengths of light, a spectrum indescribably broader than the capacity of ancient humans. They study each other’s expressions and body language – both the carefully preserved habits of old and those created later on. No longer limited to thinking one thought at a time, each tiny little detail in the other brings to mind a hundred old memories, creates a dozen new thoughts and awakens ten new emotions. Many of those reactions are communicated to the other on a level they have chosen to leave below their conscious attention, but much of what the other feels, they would know anyway. They are joined on more levels than they ever were before, linked in a more fundamental and thorough fashion than could ever have been possible earlier.
Once they wished for an opportunity to enjoy each other’s presence forever. As they talk, the starscape behind them roams, shatters and reforms, millions of years of change breaking the constellations apart and building up new ones. For minds running on such speeds as theirs, with the physical bodies as the main limiting factors, every minute that passes in the outside world carries with it ten minutes of subjective time. The bodies they have chosen for themselves never tire, never feel fatigue or hunger unless they want them to – and every now and then they do choose to feel tired, so that they can fall asleep in each other’s arms, or choose to feel cold, so that they can press close for the other one’s warmth.
The universe is theirs, and they have all the time in the world.
This work by Kaj Sotala is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
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