1957: Sputnik, atomic cooking, machines that code & central dogmas

What have we learned since 1957? Did we predict what it would be? And what does it tell us about our future?

Some notes for the panel discussion “‘We’ve never had it so good’ – how does the world today compare to 1957?” 11 May 2015 by Dr Anders Sandberg, James Martin Research Fellow at the Future of Humanity Institute, Oxford Martin School, Oxford University.

Taking the topic “how does the world today compare to 1957?” a bit literally and with a definite technological bent, I started reading old issues of Nature to see what people were thinking about back then.

Technology development


In 1957 the space age began.

Sputnik 1
Sputnik 1

Sputnik 1, the first artificial satellite, was launched on 4 October 1957. On November 3 Sputnik 2 was launched, with Laika, the first animal to orbit the Earth. The US didn’t quite manage to follow up within the year, but succeeded with Explorer 1 in January 1958.

Earth rising over the Moon from Apollo 8.
Earth rising over the Moon from Apollo 8.

Right now, Voyager 1 is 19 billion km from earth, leaving the solar system for interstellar space. Probes have visited all the major bodies of the solar system. There are several thousand satellites orbiting Earth and other bodies.  Humans have set their footprint on the Moon – although the last astronaut on the moon left closer to 1957 than the present.

There is a pair of surprises here. The first is how fast humanity went from primitive rockets and satellites to actual moon landings – 12 years. The second is that the space age did not grow into a roaring colonization of the cosmos, despite the confident predictions of nearly anybody in the 1950s. In many ways space embodies the surprises of technological progress – it can go both faster and slower than expected, often at the same time.



1957 also marks the first time that power was generated from a commercial nuclear plant, at Santa Susana, California, and the first full-scale nuclear power plant (Shippingport, Pennsylvania). Now LA housewives were cooking with their friend the atom! Ford announced their Nucleon atomic concept car 1958 – whatever the future held, it was sure to be nuclear powered!

Nuclearcooking LA times

Except that just like the Space Age the Atomic Age turned out to be a bit less pervasive than imagined in 1957.

World energy usage by type. From Our World In Data.
World energy usage by type. From Our World In Data.

One reason might be found in the UK Windscale nuclear power plant accident on 10th October 1957. Santa Susana also turned into an expensive superfund clean-up site. Making safe and easily decommissioned nuclear plants turned out to be far harder than imagined in the 1950s. Maybe, as Freeman Dyson has suggested[1], the world simply choose the wrong branch of the technology tree to walk down, selecting the big and complex plants suitable for nuclear weapons isotopes rather than small, simple and robust plants. In any case, today nuclear power is struggling both against cost and broadly negative public perceptions.


First Fortran compiler. Picture from Grinnel College.
First Fortran compiler. Picture from Grinnel College.

In April 1957 IBM sells the first compiler for the FORTRAN scientific programming language, as a hefty package of punched cards. This represents the first time software allowing a computer to write software is sold.

The term “artificial intelligence” had been invented the year before at the famous Dartmouth conference on artificial intelligence, which set out the research agenda to make machines that could mimic human problem solving. Newell, Shaw and Simon demonstrated the General Problem Solver (GPS) in 1957, a first piece of tangible progress.

While the Fortran compiler was a completely independent project it does represent the automation of programming. Today software development involves using modular libraries, automated development and testing: a single programmer can today do projects far outside what would have been possible in the 1950s. Cars run software on the order of 100s of million lines of code, and modern operating systems easily run into the high tens of millions of lines of code[2].

Moore's law, fitted with Jacknifed sigmoids. Green lines mark 98% confidence interval. Data from Nordhaus.
Moore’s law, fitted with Jacknifed sigmoids. Green lines mark 98% confidence interval. Data from Nordhaus.

In 1957 Moore’s law was not yet coined as a term, but the dynamics was already ongoing: computer operations per second per dollar was increasing exponentially (this is the important form of Moore’s law, rather than transistor density – few outside the semiconductor industry actually care about that). Today we can get about 440 billion times as many computations per second per dollar now as in 1957. Similar laws apply to storage (in 1956 IBM shipped the first hard drive in the RAMAC 305 system. The drive held 5MB of data at $10,000 a megabyte, as big as two refrigerators), memory prices, sizes of systems and sensors.

This tremendous growth have not only made complex and large programs possible, or enabled supercomputing (today’s best supercomputer is about 67 billion times more powerful than the first ones in 1964), but has also allowed smaller and cheaper devices that can be portable and used everywhere. The performance improvement can be traded for price and size.


In 1957 the first electric watch – the Hamilton Ventura – was sold. Today we have the Apple watch. Both have the same main function, to show off the wealth of their owner (and incidentally tell time), but the modern watch is also a powerful computer able to act as a portal into our shared information world. Embedded processors are everywhere, from washing machines to streetlights to pacemakers.

Why did the computers take off? Obviously there was a great demand for computing, but the technology also contained the seeds of making itself more powerful, more flexible, cheaper and useful in ever larger domains. As Gordon Bell noted in 1970, “Roughly every decade a new, lower priced computer class forms based on a new programming platform, network, and interface resulting in new usage and the establishment of a new industry.”[3]

At the same time, artificial intelligence has had a wildly bumpy ride. From confident predictions of human level intelligence within a generation to the 1970s “AI winter” when nobody wanted to touch the overhyped and obsolete area, to the current massive investments in machine learning. The problem was to a large extent that we could not tell how hard problems in the field were: some like algebra and certain games yielded with ease, others like computer vision turned out to be profoundly hard.


In 1957 Francis Crick laid out the “central dogma of molecular biology”, which explained the relationship between DNA, RNA, and proteins (DNA is translated into RNA, which is translated into proteins, and information only flows this way). The DNA structure had been unveiled four years earlier and people were just starting to figure out how genetics truly worked.

(Incidentally, the reason for the term “dogma” was that Crick, a nonbeliever, thought the term meant something that was unsupported by evidence and just had to be taken by faith, rather than the real meaning of the term, something that has to be believed no matter what. Just like “black holes” and the “big bang”, names deliberately coined to mock, it stuck.)

It took time to learn how to use DNA, but in the 1960s we learned the language of the genetic code, by the early 1970s we learned how to write new information into DNA, by the 1980s commercial applications began, by the 1990s short genomes were sequenced…

Price for DNA sequencing and synthesis. From Rob Carlson.
Price for DNA sequencing and synthesis. From Rob Carlson.

Today we have DNA synthesis machines that can be bought on eBay, unless you want to order your DNA sequence online and get a vial in the mail. Conversely, you can send off a saliva sample and get a map (or the entire sequence) of your genome back. The synthetic biology movement are sharing “biobricks”, modular genetic devices that can be combined and used to program cells. Students have competitions in genetic design.

The dramatic fall in price of DNA sequencing and synthesis mimics Moore’s law and is in some sense a result of it: better computation and microtechnology enables better biotechnology. Conversely, the cheaper it is, the more uses can be found – from marking burglars with DNA spray to identifying the true origins of sushi. This also speeds up research, leading to discoveries of new useulf tricks, for example leading to the current era of CRISPR/Cas genetic editing which promises vastly improved precision and efficiency over previous methods.

Average corn yields over time. Image from Biodesic.
Average corn yields over time. Image from Biodesic.

Biotechnology is of course more than genetics. One of the most important aspects of making the world better is food security. The gains in agricultural productivity have also been amazing. One of the important take-home messages in the above graph is that the improvement began before we started to explicitly tinker with the genes: crossing methods in the post-war era already were improving yields. Also, the Green Revolution in the 1960s was driven not just by better varieties, but by changes in land use, irrigation, fertilization and other less glamorous – but important – factors. The utility of biotechnology in the large is strongly linked to how it fits with the infrastructure of society.

Predicting technology

"Science on the March" (Alexander Leydenfrost)
“Science on the March” (Alexander Leydenfrost)

Learning about what is easy and hard requires experience. Space was on one hand easy – it only took 17 years from Sputnik before the astronauts left the moon – but making it sustained turned out to be hard. Nuclear power was easy to make, but hard to make safe enough to be cheap and acceptable.  Software has taken off tremendously, but compilers have not turned into “do what I mean” – yet routine computer engineering is regularly producing feats beyond belief that have transformed our world. AI has died the hype death several times, yet automated translation, driving, games, logistics and information services are major business today. Biotechnology had a slow ramp-up, then erupted and now schoolchildren modifying genes – yet heavy resistance holds it back, largely not because of any objective danger but because of cultural views.

If we are so bad at predicting what future technology will transform the world, what are we to do when we are searching for the Next Big Thing to solve our crises? The best approach is to experiment widely. Technologies with low thresholds of entry – such as software and now biotechnology – allow for more creative exploration. More people, more approaches and more aims can be brought to bear, and will find unexpected use for them.

The main way technologies become cheap and ubiquitous is that they are mass produced. As long as spacecraft and nuclear reactors nearly one-offs they will remain expensive. But as T. P. Wright observed, the learning curve makes each new order a bit cheaper or better. If we can reach the point where many are churned out they will not just be cheap, they will also be used for new things. This is the secret of the transistor and electronic circuit: by becoming so cheap they could be integrated anywhere they also found uses everywhere.

So the most world-transforming technologies are likely to be those that can be mass-produced, even if they from the start look awfully specialized. CCDs were once tools for astronomy, and now are in every camera and phone. Cellphones went from a moveable telephone to a platform for interfacing with the noosphere. Expect the same from gene sequencing, cubesats and machine learning. But predicting what technologies will dominate the world in 60 years’ time will not be possible.

Are we better off?

Having more technology, being able to reach higher temperatures, lower pressures, faster computations or finer resolutions, does not equate to being better off as humans.

Healthy and wise

Life expectancy (male and female) in England and Wales.

Perhaps the most obvious improvement has been health and life expectancy. Our “physiological capital” has been improving significantly. Life expectancy at birth has increased from about 70 in 1957 to 80 at a steady pace. The chance of living until 100 went up from 12.2% in 1957 to 29.9% in 2011[4].

The most important thing here is that better hygiene, antibiotics, and vaccinations happened before 1957! They were certainly getting better afterwards, but the biggest gains were likely early. Since 1957 it is likely that the main causes have been even better nutrition, hygiene, safety, early detection of many conditions, as well as reduction of risk factors like smoking.

Advanced biomedicine certainly has a role here, but it has been smaller than one might be led to think until about the 1970s. “Whether or not medical interventions have contributed more to declining mortality over the last 20 years than social change or lifestyle change is not so clear.”[5] This is in many ways good news: we may have a reserve of research waiting to really make an impact. After all, “evidence based medicine”, where careful experiment and statistics are applied to medical procedure, began properly in the 1970s!

A key factor is good health habits, underpinned by research, availability of information, and education level. These lead to preventative measures and avoiding risk factors. This is something that has been empowered by the radical improvements in information technology.

Consider the cost of accessing an encyclopaedia. In 1957 encyclopaedias were major purchases for middle class families, and if you didn’t have one you better have bus money to go to the local library to look up their copy. In the 1990s the traditional encyclopaedias were largely killed by low-cost CD ROMs… before Wikipedia appeared. Wikipedia is nearly free (you still need an internet connection) and vastly more extensive than any traditional encyclopaedia. But the Internet is vastly larger than Wikipedia as a repository of knowledge. The curious kid also has the same access to the ArXiv preprint server as any research physicist: they can reach the latest paper at the same time. Not to mention free educational courses, raw data, tutorials, and ways of networking with other interested people.

Wikipedia is also good demonstration of how the rules change when you get something cheap enough – having volunteers build and maintain something as sophisticated as an encyclopaedia requires a large and diverse community (it is often better to have many volunteers than a handful of experts, as competitors like Scholarpedia have discovered), and this would not be possible without easy access. It also illustrates that new things can be made in “alien” ways that cannot be predicted before they are tried.


But our risks may have grown too.

1957 also marks the launch of the first ICBM, a Soviet R-7. In many ways it is intrinsically linked to spaceflight: an ICBM is just a satellite with a ground-intersecting orbit. If you can make one, you can build the other.

By 1957 the nuclear warhead stockpiles were going up exponentially and had reached 10,000 warheads, each potentially able to destroy a city. Yields of thermonuclear weapons were growing larger, as imprecise targeting made it reasonable to destroy large areas in order to guarantee destruction of the target.

Nuclear warhead stockpiles. From the Center of Arms Control and Non-Proliferation.

While the stockpiles have decreased and the tensions are not as high as during the peak of the cold war in the early 80s, we have more nuclear powers, some of which are decidedly unstable. The intervening years have also shown a worrying number of close calls – not just the Cuban Missile crisis but many other under-reported crises, flare-ups and technical mishaps (Indeed, in May 22 1957 a 42,000-pound hydrogen bomb accidentally fell from a bomber near Albuquerque). The fact that we got out of the Cold War unscathed is surprising – or maybe not, since we would not be having this discussion if it had turned hot.

The biological risks are also with us. The Asian Bird Flu pandemic in 1957 claimed over 150,000 lives world-wide. Current gain-of-function research may, if we are very unlucky, lead to a man-made pandemic with a worse outcome. The paradox here is that this particular research is motivated by a desire to understand how bird flu can make the jump from birds to an infectious human pathogen: we need to understand this better, yet making new pathogens may be a risky path.

The SARS and Ebola crises show that we both have become better at handling a pandemic emergency, but also have far to go. It seems that the natural biological risk may have gone down a bit because of better healthcare (and increased a bit due to more global travel), but the real risks from misuse of synthetic biology are not here yet. While biowarfare and bioterrorism are rare, they can have potentially unbounded effects – and cheaper, more widely available technology means it may be harder to control what groups can attempt it.

1957 also marks the year when Africanized bees escaped in Brazil, becoming one of the most successful and troublesome invasive (sub)species. Biological risks can be directed to agriculture or the ecosystem too. Again, the intervening 60 years have shown a remarkably mixed story: on one hand significant losses of habitat, the spread of many invasive species, and the development of anti-agricultural bioweapons. On the other hand a significant growth of our understanding of ecology, biosafety, food security, methods of managing ecosystems and environmental awareness. Which trend will win out remains uncertain.

The good news is that risk is not a one-way street. We likely have reduced the risk of nuclear war since the heights of the Cold War. We have better methods of responding to pandemics today than in 1957. We are aware of risks in a way that seems more actionable than in the past: risk is something that is on the agenda (sometimes excessively so).


1957/1958 was the International Geophysical Year. The Geophysical Year saw the US and Soviet Union – still fierce rivals – cooperate on understanding and monitoring the global system, an ever more vital part of our civilization.

1957 was also the year of the treaty of Rome, one of the founding treaties of what would become the EU. For all its faults the European Union demonstrates that it is possible through trade to stabilize a region that had been embroiled in wars for centuries.

Number of international treaties over time. Data from Wikipedia.
Number of international treaties over time. Data from Wikipedia.

The number of international treaties has grown from 18 in 1957 to 60 today. While not all represent sterling examples of cooperation they are a sign that the world is getting somewhat more coordinated.

Globalisation means that we actually care about what goes on in far corners of the world, and we will often hear about it quickly. It took days after the Chernobyl disaster in 1986 before it was confirmed – in 2011 I watched the Fukushima YouTube clip 25 minutes after the accident, alerted by Twitter. It has become harder to hide a problem, and easier to request help (overcoming one’s pride to do it, though, remains as hard as ever).

The world on 1957 was closed in many ways: two sides of the Cold War, most countries with closed borders, news traveling through narrow broadcasting channels and transport/travel hard and expensive. Today the world is vastly more open, both to individuals and to governments. This has been enabled by better coordination. Ironically, it also creates more joint problems requiring joint solutions – and the rest of the world will be watching the proceedings, noting lack of cooperation.

Final thoughts

The real challenges for our technological future are complexity and risk.

We have in many ways plucked the low-hanging fruits of simple, high-performance technologies that vastly extend our reach in energy, material wealth, speed and so on, but run into subtler limits due to the complexity of the vast technological systems we need. The problem of writing software today is not memory or processing speed but handling a myriad of contingencies in distributed systems subject to deliberate attacks, emergence, localization, and technological obsolescence. Biotechnology can do wonders, yet has to contend with organic systems that have not been designed for upgradeability and spontaneously adapt to our interventions. Handling complex systems is going to be the great challenge for this century, requiring multidisciplinary research and innovations – and quite likely some new insights on the same level as the earth-shattering physical insights of the 20th century.

More powerful technology is also more risky, since it can have greater consequences. The reach of the causal chains that can be triggered with a key press today are enormously longer than in 1957. Paradoxically, the technologies that threaten us also have the potential to help us reduce risk. Spaceflight makes ICBMs possible, but allows global monitoring and opens the possibility of becoming a multi-planetary species. Biotechnology allows for bioweapons, but also disease surveillance and rapid responses. Gene drives can control invasive species and disease vectors, or sabotage ecosystems. Surveillance can threaten privacy and political freedom, yet allow us to detect and respond to collective threats. Artificial intelligence can empower us, or produce autonomous technological systems that we have no control over. Handling risk requires both having an adequate understanding of what matters, designing the technologies, institutions or incentives that can reduce the risk – and convincing the world to use them.

The future of our species depends on what combination of technology, insight and coordination ability we have. Merely having one or two of them is not enough: without technology we are impotent, without insight we are likely to go in the wrong direction, and without coordination we will pull apart.

Fortunately, since 1957 I think we have not just improved our technological abilities, but we have shown a growth of insight and coordination ability. Today we are aware of global environmental and systemic problems to a new degree. We have integrated our world to an unprecedented degree, whether through international treaties, unions like the EU, or social media. We are by no means “there” yet, but we have been moving in the right direction. Hence I think we never had it so good.


[1]Freeman Dyson, Imagined Worlds. Harvard University Press (1997) P. 34-37, p. 183-185

[2] http://www.informationisbeautiful.net/visualizations/million-lines-of-code/

[3] https://en.wikipedia.org/wiki/Bell%27s_law_of_computer_classes

[4] https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/223114/diffs_life_expectancy_20_50_80.pdf

[5] http://www.beyondcurrenthorizons.org.uk/review-of-longevity-trends-to-2025-and-beyond/

Objectively evil technology

Dangerous partGeorge Dvorsky has a post on io9: 10 Horrifying Technologies That Should Never Be Allowed To Exist. It is a nice clickbaity overview of some very bad technologies:

  1. Weaponized nanotechnology (he mainly mentions ecophagy, but one can easily come up with other nasties like ‘smart poisons’ that creep up on you or gremlin devices that prevent technology – or organisms – from functioning)
  2. Conscious machines (making devices that can suffer is not a good idea)
  3. Artificial superintelligence (modulo friendliness)
  4. Time travel
  5. Mind reading devices (because of totalitarian uses)
  6. Brain hacking devices
  7. Autonomous robots programmed to kill humans
  8. Weaponized pathogens
  9. Virtual prisons and punishment
  10. Hell engineering (that is, effective production of super-adverse experiences; consider Iain M. Banks’ Surface Detail, or the various strange/silly/terrifying issues linked to Roko’s basilisk)

Some of the these technologies exist, like weaponized pathogens. Others might be impossible, like time travel. Some are embryonic like mind reading (we can decode some brainstates, but it requires spending a while in a big scanner as the input-output mapping is learned).

A commenter on the post asked “Who will have the responsibility of classifying and preventing “objectively evil” technology?” The answer is of course People Who Have Ph.D.s in Philosophy.

Unfortunately I haven’t got one, but that will not stop me.

Existential risk as evil?

I wonder what unifies this list. Let’s see: 1, 3, 7, and 8 are all about danger: either the risk of a lot of death, or the risk of extinction. 2, 9 and 10 are all about disvalue: the creation of very negative states of experience. 5 and 6 are threats to autonomy.

4, time travel, is the odd one out: George suggests that it is dangerous, but this is based on fictional examples, and that contact between different civilizations has never ended well (which is arguable: Japan). I can imagine a consistent universe with time travel might be bad for people’s sense of free will, and if you have time loops you can do super-powerful computation (getting superintelligence risk), but I do not think of any kind of plausible physics where time travel itself is dangerous. Fiction just makes up dangers to make the plot move on.

In the existential risk framework, it is worth noting that extinction is not the only kind of existential risk. We could mess things up so that humanity’s full potential never gets realized (for example by being locked into a perennial totalitarian system that is actually resistant to any change), or that we make the world hellish. These are axiological existential risks. So the unifying aspect of these technologies is that they could cause existential risk, or at least bad enough approximations.

Ethically, existential threats count a lot. They seem to have priority over mere disasters and other moral problems in a wide range of moral systems (not just consequentialism). So technologies that strongly increase existential risk without giving a commensurate benefit (for example by reducing other existential risks more – consider a global surveillance state, which might be a decent defence against people developing bio-, nano- and info-risks at the price of totalitarian risk) are indeed impermissible. In reality technologies have dual uses and the eventual risk impact can be hard to estimate, but the principle is reasonable even if implementation will be a nightmare.

Messy values

However, extinction risk is an easy category – even if some of the possible causes like superintelligence are weird and controversial, at least extinct means extinct. The value and autonomy risks are far trickier. First, we might be wrong about value: maybe suffering doesn’t actually count morally, we just think it does. So a technology that looks like it harms value badly like hell engineering actually doesn’t. This might seem crazy, but we should recognize that some things might be important but we do not recognize them. Francis Fukuyama thought transhumanist enhancement might harm some mysterious ‘Factor X’ (i.e. a “soul) giving us dignity that is not widely recognized. Nick Bostrom (while rejecting the Factor X argument) has suggested that there might be many “quiet values” important for diginity, taking second seat to the “loud” values like alleviation of suffering but still being important – a world where all quiet values disappear could be a very bad world even if there was no suffering (think Aldous Huxley’s Brave New World, for example). This is one reason why many superintelligence scenarios end badly: transmitting the full nuanced world of human values – many so quiet that we do not even recognize them ourselves before we lose them – is very hard. I suspect that most people find it unlikely that loud values like happiness or autonomy actually are parochial and worthless, but we could be wrong. This means that there will always be a fair bit of moral uncertainty about axiological existential risks, and hence about technologies that may threaten value. Just consider the argument between Fukuyama and us transhumanists.

Second, autonomy threats are also tricky because autonomy might not be all that it is cracked up to be in western philosophy. The atomic free-willed individual is rather divorced from the actual neural and social matrix creature. But even if one doesn’t buy autonomy as having intrinsic value, there are likely good cybernetic arguments for why maintaining individuals as individuals with their own minds is a good thing. I often point to David Brin’s excellent defence of the open society where he points out that societies where criticism and error correction are not possible will tend to become corrupt, inefficient and increasingly run by the preferences of the dominant cadre. In the end they will work badly for nearly everybody and have a fair risk of crashing. Tools like surveillance, thought reading or mind control would potentially break this beneficial feedback by silencing criticism. They might also instil identical preferences, which seems to be a recipe for common mode errors causing big breakdowns: monocultures are more vulnerable than richer ecosystems. Still, it is not obvious that these benefits could not exist in (say) a group-mind where individuality is also part of a bigger collective mind.

Criteria and weasel-words

These caveats aside, I think the criteria for “objectively evil technology” could be

(1) It predictably increases existential risk substantially without commensurate benefits,


(2) it predictably increases the amount of death, suffering or other forms of disvalue significantly without commensurate benefits.

There are unpredictable bad technologies, but they are not immoral to develop. However, developers do have a responsibility to think carefully about the possible implications or uses of their technology. And if your baby-tickling machine involves black holes you have a good reason to be cautious.

Of course, “commensurate” is going to be the tricky word here. Is a halving of nuclear weapons and biowarfare risk good enough to accept a doubling of superintelligence risk? Is a tiny probability existential risk (say from a physics experiment) worth interesting scientific findings that will be known by humanity through the entire future? The MaxiPOK principle would argue that the benefits do not matter or weigh rather lightly. The current gain-of-function debate show that we can have profound disagreements – but also that we can try to construct institutions and methods that regulate the balance, or inventions that reduce the risk. This also shows the benefit of looking at larger systems than the technology itself: a potentially dangerous technology wielded responsibly can be OK if the responsibility is reliable enough, and if we can bring a safeguard technology into place before the risky technology it might no longer be unacceptable.

The second weasel word is “significantly”. Do landmines count? I think one can make the case. According to the UN they kill 15,000 to 20,000 people per year. The number of traffic fatalities per year worldwide is about 1.2 million deaths – but we might think cars are actually so beneficial that it outweighs the many deaths.


The landmines are intended to harm (yes, the ideal use is to make people rationally stay the heck away from mined areas, but the harming is inherent in the purpose) while cars are not. This might lead to an amendment of the second criterion:

(2′) The technology  intentionally increases the amount of death, suffering or other forms of disvalue significantly without commensurate benefits.

This gets closer to how many would view things: technologies intended to cause harm are inherently evil. But being a consequentialist I think it let’s designers off the hook. Dr Guillotine believed his invention would reduce suffering (and it might have) but it also led to a lot more death. Dr Gatling invented his gun to “reduce the size of armies and so reduce the number of deaths by combat and disease, and to show how futile war is.” So the intention part is problematic.

Some people are concerned with autonomous weapons because they are non-moral agents making life-and-death decisions over people; they would use deontological principles to argue that making such amoral devices are wrong. But a landmine that has been designed to try to identify civilians and not blow up around them seems to be a better device than an indiscriminate device: the amorality of the decisionmaking is less of problematic than the general harmfulness of the device.

I suspect trying to bake in intentionality or other deontological concepts will be problematic. Just as human dignity (another obvious concept – “Devices intended to degrade human dignity are impermissible”) is likely a non-starter. They are still useful heuristics, though. We do not want too much brainpower spent on inventing better ways of harming or degrading people.

Policy and governance: the final frontier

In the end, this exercise can be continued indefinitely. And no doubt it will.

Given the general impotence of ethical arguments to change policy (it usually picks up the pieces and explains what went wrong once it does go wrong) a more relevant question might be how a civilization can avoid developing things it has a good reason to suspect are a bad idea. I suspect the answer to that is going to be not just improvements in coordination and the ability to predict consequences, but some real innovations in governance under empirical and normative uncertainty.

But that is for another day.