# Annoyed by annoyed AI: can we fight AI hype?

Recently the Wall Street Journal reported that an AI got testy with its programmer when he asked about ethics. This is based on a neat paper by Vinyals and Le on training recurrent networks to do conversations based on past example conversations, essentially making neural network chatbots. I posted about that particular dialogue myself to the office list, joking about AI not digging ethics.

However, others got annoyed by the annoyed AI. Mbeckman on Slashdot posted WSJ Overstates the Case Of the Testy A.I. and George Dvorsky on Io9 followed up with No, an AI Did Not Just “Lash Out” at Its Human Programmer.

Mbeckman wrote: “AI hype to the public has gotten progressively more strident in recent years, misleading lay people into believing researchers are much further along than they really are — by orders of magnitude. I’d love to see legitimate A.I. researchers condemn this kind of hucksterism.

Of course, the question is what the hucksterism actually is, who is doing it, and what to do about it.

## Who are the hucksters?

A huckster is “One who uses aggressive, showy, and sometimes devious methods to promote or sell a product”.

### The paper?

In this case the paper is not doing anything obviously hucksterish – it has several dialogue examples where the software responds to VPN or browser issues, general knowledge Q&A, chatting and opinions. That the system thinks Cleopatra is very regal or that it manages to instruct the user into doing an apt-update for a browser is neat, but not terribly impressive. Many of the dialogues are clearly Eliza-level associations with little actual thinking, but amusing random combinations:

Human:what is the purpose of life ?
Machine:to serve the greater good .
Human:what is the purpose of living ?
Machine:to live forever .
Human:what is the purpose of existence ?
Machine: to find out what happens when we get to the planet earth .
Human:where are you now ?
Machine:i ’m in the middle of nowhere .
Human:what is the purpose of dying ?
Machine:to have a life .
Human:what is the purpose of being intelligent?
Machine:to find out what it is .
Human:what is the purpose of emotions ?
Machine:i don ’t know

If this is hucksterism, then nearly any computer science paper is hucksterism. After all, they tend to show the successful runs of software and generally overestimate the utility of the algorithm or method.

### Wall Street Journal?

Mbeckman probably felt that the WSJ was more guilty. After all, the title and opening suggest there is some kind of attitude going on. But there is actually rather little editorializing: rather, a somewhat bland overview of machine learning with an amusing dialogue example thrown in. It could have been Eliza instead, and the article would have made sense too (“AI understands programmer’s family problems”). There is an element of calculation here: AI is hot, and the dialogue can be used as a hook to make a story that both mentions real stuff and provides a bit of entertainment. But again, this is not so much aggressive promotion of a product/idea as opportunitistic promotion.

### Media in general?

I suspect that the real target of Mbeckman’s wrath is the unnamed sources of AI hype. There is no question that AI is getting hyped these days. Big investments by major corporations, sponsored content demystifying it, Business Insider talking about how to invest into it, corporate claims of breakthroughs that turn out to be mistakes/cheating, invitations to governments to join the bandwagon, the whole discussion about AI safety where people quote and argue about Hawking’s and Musk’s warnings (rather than going to the sources reviewing the main thinking), and of course a bundle of films. The nature of hype is that it is promotion, especially based on exaggerated claims. This is of course where the hucksterism accusation actually bites.

## Hype: it is everybody’s fault

But while many of the agents involved do exaggerate their own products, hype is also a social phenomenon. In many ways it is similar to an investment bubble. Some triggers occur (real technology breakthroughs, bold claims, a good story) and media attention flows to the field. People start investing in the field, not just with money, but with attention, opinion and other contributions. This leads to more attention, and the cycle feeds itself. Like an investment bubble overconfidence is rewarded (you get more attention and investment) while sceptics do not gain anything (of course, you can participate as a sharp-tounged sceptic: everybody loves to claim they listen to critical voices! But now you are just as much part of the hype as the promoters). Finally the bubble bursts, fashion shifts, or attention just wanes and goes somewhere else. Years later, whatever it was may reach the plateau of productivity.

The problem with this image is that it is everybody’s fault. Sure, tech gurus are promoting their things, but nobody is forced to naively believe them. Many of the detractors are feeding the hype by feeding it attention. There is ample historical evidence: I assume the Dutch tulip bubble is covered in Economics 101 everywhere, and AI has a history of terribly destructive hype bubbles… yet few if any learn from it (because this time it is different, because of reasons!)

### Fundamentals

In the case of AI, I do think there have been real changes that give good reason to expect big things. Since the 90s when I was learning the field computing power and sizes of training data have expanded enormously, making methods that looked like dead ends back them actually blossom. There has also been conceptual improvements in machine learning, among other things killing off neural networks as a separate field (we bio-oriented researchers reinvented ourselves as systems biologists, while the others just went with statistical machine learning). Plus surprise innovations that have led to a cascade of interest – the kind of internal innovation hype that actually does produce loads of useful ideas. The fact that papers and methods that surprise experts in the field are arriving at a brisk pace is evidence of progress. So in a sense, the AI hype has been triggered by something real.

I also think that the concerns about AI that float around have been triggered by some real insights. There was minuscule AI safety work done before the late 1990s inside AI; most was about robots not squishing people. The investigations of amateurs and academics did bring up some worrying concepts and problems, at first at the distal “what if we succeed?” end and later also when investigating the more proximal impact of cognitive computing on society through drones, autonomous devices, smart infrastructures, automated jobs and so on. So again, I think the “anti-AI hype” has also been triggered by real things.

### Copy rather than check

But once the hype cycle starts, just like in finance, fundamentals matter less and less. This of course means that views and decisions become based on copying others rather than truth-seeking. And idea-copying is subject to all sorts of biases: we notice things that fit with earlier ideas we have held, we give weight to easily available images (such as frequently mentioned scenarios) and emotionally salient things, detail and nuance are easily lost when a message is copied, and so on.

### Science fact

This feeds into the science fact problem: to a non-expert, it is hard to tell what the actual state of art is. The sheer amount of information, together with multiple contradictory opinions, makes it tough to know what is actually true. Just try figuring out what kind of fat is good for your heart (if any). There is so much reporting on the issue, that you can easily find support for any side, and evaluating the quality of the support requires expert knowledge. But even figuring out who is an expert in a contested big field can be hard.

In the case of AI, it is also very hard to tell what will be possible or not. Expert predictions are not that great, nor different from amateur predictions. Experts certainly know what can be done today, but given the number of surprises we are seeing this might not tell us much. Many issues are also interdisciplinary, making even confident and reasoned predictions by a domain expert problematic since factors they know little about also matters (consider the the environmental debates between ecologists and economists – both have half of the puzzle, but often do not understand that the other half is needed).

### Bubble inflation forces

Different factors can make hype more or less intense. During summer “silly season” newspapers copy entertaining stories from each other (some stories become perennial, like the “BT soul-catcher chip” story that emerged in 1996 and is still making its rounds). Here easy copying and lax fact checking boost the effect. During a period with easy credit financial and technological bubbles become more intense. I suspect that what is feeding the current AI hype bubble is a combination of the usual technofinancial drivers (we may be having dotcom 2.0, as some think), but also cultural concerns with employment in a society that is automating, outsourcing, globalizing and disintermediating rapidly, plus very active concerns with surveillance, power and inequality. AI is in a sense a natural lightening rod for these concerns, and they help motivate interest and hence hype.

## So here we are.

AI professionals are annoyed because the public fears stuff that is entirely imaginary, and might invoke the dreaded powers of legislators or at least threaten reputation, research grants and investment money. At the same time, if they do not play up the coolness of their ideas they will not be noticed. AI safety people are annoyed because the rather subtle arguments they are trying to explain to the AI professionals get wildly distorted into “Genius Scientists Say We are Going to be Killed by the TERMINATOR!!!” and the AI professionals get annoyed and refuse to listen. Yet the journalists are eagerly asking for comments, and sometimes they get things right, so it is tempting to respond. The public are annoyed because they don’t get the toys they are promised, and it simultaneously looks like Bad Things are being invented for no good reason. But of course they will forward that robot wedding story. The journalists are annoyed because they actually do not want to feed hype. And so on.

What should we do? “Don’t feed the trolls” only works when the trolls are identifiable and avoidable. Being a bit more cautious, critical and quiet is not bad: the world is full of overconfident hucksters, and learning to recognize and ignore them is a good personal habit we should appreciate. But it only helps society if most people avoid feeding the hype cycle: a bit like the unilateralist’s curse, nearly everybody need to be rational and quiet to starve the bubble. And since there are prime incentives for hucksterism in industry, academia and punditry that will go to those willing to do it, we can expect hucksters to show up anyway.

The marketplace of ideas could do with some consumer reporting. We can try to build institutions to counter problems: good ratings agencies can tell us whether something is overvalued, maybe a federal robotics commission can give good overviews of the actual state of the art. Reputation systems, science blogging marking what is peer reviewed, various forms of fact-checking institutions can help improve epistemic standards a bit.

AI safety people could of course pipe down and just tell AI professionals about their concerns, keeping the public out of it by doing it all in a formal academic/technical way. But a pure technocratic approach will likely bite us in the end, since (1) incentives to ignore long term safety issues with no public/institutional support exist, and (2) the public gets rather angry when it finds that “the experts” have been talking about important things behind their back. It is better to try to be honest and try to say the highest-priority true things as clearly as possible to the people who need to hear it, or ask.

AI professionals should recognize that they are sitting on a hype-generating field, and past disasters give much reason for caution. Insofar they regard themselves as professionals, belonging to a skilled social community that actually has obligations towards society, they should try to manage expectations. It is tough, especially since the field is by no means as unified professionally as (say) lawyers and doctors. They should also recognize that their domain knowledge both obliges them to speak up against stupid claims (just like Mbeckman urged), but that there are limits to what they know: talking about the future or complex socioecotechnological problems requires help from other kinds of expertise.

And people who do not regard themselves as either? I think training our critical thinking and intellectual connoisseurship might be the best we can do. Some of that is individual work, some of it comes from actual education, some of it from supporting better epistemic institutions – have you edited Wikipedia this week? What about pointing friends towards good media sources?

In the end, I think the AI system got it right: “What is the purpose of being intelligent? To find out what it is”. We need to become better at finding out what is, and only then can we become good at finding out what intelligence is.

# What is the largest possible inhabitable world?

The question is of course ill-defined, since “largest”, “possible”, “inhabitable” and “world” are slippery terms. But let us aim at something with maximal surface area that can be inhabited by at least terrestrial-style organic life of human size and is allowed by the known laws of physics. This gives us plenty of leeway.

# Piled higher and deeper

We could simply imagining adding more and more mass to a planet. At first we might get something like my double Earths, ocean worlds surrounding a rock core. The oceans are due to the water content of the asteroids and planetesimals we build them from: a huge dry planet is unlikely without some process stripping away water. As we add more material the ocean gets deeper until the extreme pressure makes the bottom solidify into exotic ice – which slows down the expansion somewhat.

Adding even more matter will produce a denser atmosphere too. A naturally accreting planet will acquire gas if it is heavy and cold enough, at first producing something like Neptune and then a gas giant. Keep it up, and you get a brown dwarf and eventually a star. These gassy worlds are also far more compressible than a rock- or water-world, so their radius does not increase when they get heavier. In fact, most gas giants are expected to be about the size of Jupiter.

If this is true, why is the sun and some hot Jupiters much bigger? Jupiter’s radius is  69,911 km, the sun radius is 695,800 km,  and the largest exoplanets known today have radii around 140,000 km.  The answer is that another factor determining size is temperature. As the ideal gas law states, to a first approximation pressure times volume equals temperature: the pressure at the core due to the weight of all the matter stays roughly the same, but at higher temperatures the same planet/star gets larger. But I will assume inhabitable worlds are reasonably cold.

Planetary models also suggest that a heavy planet will tend to become denser: adding more mass compresses the interior, making the radius climb more slowly.

The central pressure of a uniform body is $P = 2\pi G R^2 \rho^2/3$. In reality planets do not tend to be uniform, but let us ignore this. Given an average density we see that the pressure grows with the square of the radius and quickly becomes very large (in Earth, the core pressure is somewhere in the vicinity of 350 GPa). If we wanted something huge and heavy we need to make it out of something incompressible, or in the language of physics, something with a stiff equation of state. There is a fair amount of research about super-earth compositions and mass-radius relationships in the astrophysics community, with models of various levels of complexity.

This paper by Seager, Kuchner, Hier-Majumder and Militzer provides a lovely approximate formula: $\log_{10}(R/r_1) = k_1+(1/3)\log_{10}(M/m_1)-k_2M^{k_3}$ up to about 20 earth masses. Taking the derivative and setting it to zero gives us the mass where the radius is maximal as

$M=\left [\frac{m_1^{k_3}}{3k_2k_3\ln(10)}\right ]^{1/k_3}$.

Taking the constants (table 4) corresponding to iron gives a maximum radius at the mass of 274 Earths, perovskite at 378 Earths, and for ice at 359 Earths. We should likely not trust the calculation very much around the turning point, since we are well above the domain of applicability. Still, looking at figure 4 shows that the authors at least plot the curves up to this range. The maximal iron world is about 2.7 times larger than Earth, the maximal perovskite worlds manage a bit more than 3 times Earth’s radius, and the waterworlds just about reach 5 times. My own plot of the approximation function gives somewhat smaller radii:

Mordasini et al. have a paper producing similar results; for masses around 1000 Earth masses their maximum sizes are about 3.2 times for a Earthlike 2:1 silicate-to-iron ratio, 4 times for an 50% ice, 33% silicate and 70% iron planet, and 4.8 times for planets made completely of ice.

The upper size limit is set by the appearance of degenerate matter. Electrons are not allowed to be in the same energy state in the same place. If you squeeze atoms together, eventually the electrons will have to start piling into higher energy states due to lack of space. This is resisted, producing the degeneracy pressure. However, it grows rather slowly with density, so degenerate cores will readily compress. For fully degenerate bodies like white dwarves and neutron stars the radius declines with increasing mass (making the largest neutron stars the lightest!). And of course, beyond a certain limit the degeneracy pressure is unable to stop gravitational collapse and they implode into black holes.

For maximum-size planets the really exotic physics is (unfortunately?) irrelevant. Normal gravity is however applicable: the  surface gravity scales as $g =GM/R^2 = 4 \pi G \rho R / 3$. So for a 274 times heavier and 2.7 times larger iron-Earth surface gravity is 38 times Earth’s.  This is not habitable for humans (although immersion in a liquid tank and breathing through oxygenated liquids might allow survival). However, bacteria have been cultured at 403,627 g in centrifuges! The 359 times heavier and 5 times large ice world just has 14.3 times our surface gravity. Humans could probably survive if they were lying down, although this is way above any long-term limits found by NASA.

What about rotating the planet fast enough? As Mesklin in Hal Clement’s Mission of Gravity demonstrates, we can have a planet with hundreds of Gs of gravity at the poles, yet a habitable mere 3 G equator. Of course, this is cheating somewhat with the habitability condition: only a tiny part is human-habitable, yet there is a lot of unusable (to humans, not mesklinites) surface area. Estimating the maximum size becomes fairly involved since the acceleration and pressure fields inside are not spherically symmetric. A crude guesstimate would be to look at the polar radius and assume it is limited by the above degeneracy conditions, and then note that the limiting eccentricity is about 0.4: that would make the equatorial radius 2.5 times larger than the polar radius. So for the spun-up ice world we might get an equatorial radius 12 times Earth and a surface area about 92 times larger. If we want to go beyond this we might consider torus-worlds; they can potentially have an arbitrarily large area with a low gravity outer equator. Unfortunately they are likely not very stable: any tidal forces or big impacts (see below) might introduce a fatal wobble and breakup.

So in some sense the maximal size planets would be habitable. However, as mentioned above, they would also likely turn into waterworlds and warm Neptunes.

## Getting a solid mega-Earth (and keeping it solid)

The most obvious change is to postulate that the planet indeed just has the right amount of water to make decent lakes and oceans, but does not turn into an ocean-world. Similarly we may hand-wave away the atmosphere accretion and end up with a huge planet with a terrestrial surface.

Although it is not going to stay that way for long. The total heat production inside the planet is proportional to the volume which is proportional to the cube of the radius, but the surface area that radiates away heat is proportional to the square of the radius. Large planets will have more heat per square meter of surface, and hence have more volcanism and plate tectonics. That big world will soon get a fair bit of atmosphere from volcanic eruptions, and not the good kind – lots of sulphuric oxides, carbon dioxide and other nasties. (A pure ice-Earth would escape this, since all hydrogen and oxygen isotopes are short lived – once it solidified it would stay solid and boring).

And the big planet will get hit by comets too. The planet will sweep up stuff that comes inside its capture cross section $\sigma_c = \sigma_{geom} (1 + v_e^2/v_0^2)$ where $\sigma_{geom}=\pi R^2$ is the geometric cross section, $v_e = \sqrt{2GM/R} = R \sqrt{8 G \pi \rho / 3}$ the escape velocity and $v_0$ the original velocity of the stuff. Putting it all together gives a capture cross section proportional to $R^4$: double-Earth will get hit by $2^4=16$ times as much space junk as Earth. Iron-Earth by 53 times as much.

So over time the planet will accumulate an atmosphere denser than it started. But the impact cataclysms might also be worse for habitability – the energy released when something hits is roughly proportional to the square of the escape velocity, which scales as $R^2$. On Double-Earth the Chicxulub impact would have been $2^2=4$ four times more energetic. So the mean energy per unit of time due to impacts scales like $R^4 R^2=R^6$. Ouch. Crater sizes scale as $\propto g^{1/6} W^{1/3.4}$ where $W$ is the energy. So for our big worlds the scars will scale as $\propto R^{1/6 + 2/3.4}=R^{0.75}$. Double-Earth will have craters 70% larger than Earth, and iron-Earth 121% larger.

## Big and light worlds

Surface gravity scales as $g =GM/R^2 = 4 \pi G \rho R / 3$. So if we want R to be huge but g modest, the density has to go down. This is also a good strategy for reducing internal pressure, which is compressing our core. This approach is a classic in science fiction, perhaps most known from Jack Vance’s Big Planet.

Could we achieve this by assuming it to be made out of something very light like lithium hydride (LiH)?  Lithium hydride is nicely low density (0.78 g/cm3) but also appears to be rather soft (3.5 on the Mohs scale), plus of course that it reacts with oxygen and water, which is bad for habitability. Getting something that doesn’t react badly rules out most stuff at the start of the periodic table: I think the first compound (besides helium) that doesn’t decompose in water or is acutely toxic is likely pure boron. Of course, density is not a simple function of atomic number: amorphous carbon and graphite have lower densities than boron.

A carbon planet is actually not too weird. There are exoplanets that are believed to be carbon worlds where a sizeable amount of mass is carbon. They are unlikely to be very habitable for terrestrial organisms since oxygen would tend to react with all the carbon and turn into carbon dioxide, but would have interesting surface environments with tars, graphite and diamonds. We could imagine a “pure” carbon planet composed largely of graphite, diamond and a core of metallic carbon. If we handwave that on top of the carbon core there is some intervening rock layer or that the oxidation processes are slow enough, then we could have a habitable surface (until volcanism and meteors get it). A diamond planet with 1 G gravity is would be $R = (\rho_{earth}/\rho_{diamond}) R_{earth}=5.513/3.5= 10,046$ km. We get a 1.6 times larger radius than earth this way, and 2.5 times more surface area. (Here I ignore all the detailed calculations in real planetary astrophysics and just assume uniformity; I suspect the right diamond structure will be larger.)

A graphite planet would have radius 16,805 km, 2.6 times ours and with about 7 times our surface area. Unfortunately it would likely turn (cataclysmically) into a diamond planet as the core compressed.

Another approach to low density is of course to use stiff materials with voids. Aerogels have densities close to 1 kg per cubic meter, but that is of course mostly the air: the real density of a silica aerogel is 0.003-0.35 g/cm3. Now that would allow a fluffy world up to 1837 times Earth’s radius! We can do even better with metallic microlattices, where the current  record is about 0.0009 g/cm– this metal fluffworld would have a radius 39,025,914 km, 6125 times Earth, with 3.8 million times our surface area!

The problem is that aerogels and microlattices do not have that great bulk modulus, the ability to resist compression. Their modulus scales with the cube or square of density, so the lighter they are, the more compressible they get – wonderful for many applications, but very bad for keeping planets from imploding. Imagine trying to build a planet out of foam rubber. Diamond is far, far better. What we should look for is something with a high specific modulus, the ratio between bulk modulus and density. Looking at this table suggests carbon fiber is best at 417 million m2/s2, followed by diamond at 346 million m2/s2. So pure carbon worlds are likely the largest we could get, a few times Earth’s size.

# Artificial worlds

We can do better if we abandon the last pretence of the world being able to form naturally (natural metal microlattices, seriously?).

## Shellworld

Consider roofing over the entire Earth’s surface: it would take a fair amount of material, but we could mine it by digging tunnels under the surface. At the end we would have more than doubled the available surface (roof, old ground, plus some tunnels). We can continue the process, digging up material to build a giant onion of concentric floors and giant pillars holding up the rest. The end result is akin to the megastructure in Iain M. Banks’ Matter.

If each floor has material density $\rho$ kg/m2 (lets ignore the pillars for the moment) and ceiling height h, then the total mass from all floors is $M = \sum_{n=0}^N 4 \pi (hn)^2 \rho$. Moving terms over to the left we get $M/4 \pi \rho h^2 = \sum_{n=0}^N n^2 = N(N+1)(2N+1)/6= N^3/3 +N^2/2+N/6$. If N is very large the N^3/3 term dominates (just consider the case of N=1000: the first term is a third of a billion, the second half a million and the final one 166.6…) and we get

$N \approx \left [\frac{3M}{4\pi \rho h^2}\right ]^{1/3}$

with radius $R=hN$.

The total surface area is

$A=\sum_{n=0}^N 4\pi (hn)^2 = 4 \pi h^2 \left (\frac{N^3}{3} +\frac{N^2}{2}+\frac{N}{6}\right )$.

So the area grows proportional to the total mass (since N scales as $M^{1/3}$). It is nearly independent of $h$ ($N^3$ scales as $h^{-2}$) – the closer together the floors are, the more floors you get, but the radius increases only slowly. Area also scales as $1/\rho$: if we just sliced the planet into microthin films with maximal separation we could get a humongous area.

If we set $h=3$ meters, $\rho=500$ kg per square meter, and use the Earth’s mass, then $N \approx 6.8\cdot 10^6$, with a radius of 20,000 km. Not quite xkcd’s billion floor skyscraper, but respectable floorspace: $1.2\cdot 10^{22}$ square meters, about 23 million times Earth’s area.

If we raise the ceiling to $h=100$ meters the number of floors drops to 660,000 and the radius balloons to 65,000 km. If we raise them a fair bit more, $h=20$ kilometres, then we reach the orbit of the moon with the 19,000th floor. However, the area stubbornly remains about 23 million times Earth. We will get back to this ballooning shortly.

## Keeping the roof up

The single floor shell has an interesting issue with gravity. If you stand on the surface of a big hollow sphere the surface gravity will be the same as for a planet with the same size and mass (it will be rather low, of course). However, on the inside you would be weightless. This follows from Newton’s shell theorem, which states that the force from a spherically symmetric distribution of mass is proportional to the amount of mass at radii closer to the centre: outside shells of mass do not matter.

This means that the inner shells do not have to worry about the gravity of the outer shells, which is actually a shame: they still weigh a lot, and that has to be transferred inwards by supporting pillars – some upward gravity would really have helped construction, if not habitability. If the shells were amazingly stiff they could just float there as domes with no edge (see discussion of Dyson shells below), but for real materials we need pillars.

How many pillars do we need? Let’s switch the meaning of $\rho$ to denote mass per cubic meter again, making the mass inside a radius $M(r)=4\pi \rho r^3/3$. A shell at radius $r$ needs to support the weight of all shells above it, a total force of $F(r) = \int_r^R (4 \pi x^2 \rho) (G M(x)/x^2) dx$ (mass of the shell times the gravitational force). Then $F(r) = (16 \pi^2 G \rho^2/3) \int_r^R x^3 dx$ $= (16 \pi^2 G \rho^2/3) [x^4/4]^{R}_r$ $= (4 \pi^2 G \rho^2/3)(R^4 - r^4)$.

If our pillars have compressive strength $P$ per square meter, we need $F(r)/P$ square meters of pillars at radius $r$: a fraction $F(r)/4 \pi r^2 P = (\pi G \rho^2/3P)(R^4/r^2 - r^2)$ of the area needs to be pillars. Note that at some radius 100% of the floor has to be pillars.

Plugging in our original $h=3$ m, $\rho=500/4$ kg per cubic meter, $R=20\cdot 10^6$ meter world, and assuming $P=443$ GPa (diamond), and assuming I have done my algebra right, we get $r \approx 880$ km – this is the core, where there is actually no floors left. The big moonscraper has a core with radius 46 km, far less.

We have so far ignored the weight of all these pillars. They are not going to be insignificant, and if they are long we need to think about buckling and all those annoying real world engineering considerations that actually keep our buildings standing up.

We may think of topological shape optimization: start with a completely filled shell and remove material to make voids, while keeping everything stiff enough to support a spherical surface. At first we might imagine pillars that branch to hold up the surface. But the gravity on those pillars depend on how much stuff is under them, so minimizing it will make the the whole thing lighter. I suspect that in the end we get just a shell with some internal bracing, and nothing beneath. Recall the promising increase in area we got for fewer but taller levels: if there are no levels above a shell, there is no need for pillars. And since there is almost nothing beneath it, there will be little gravity.

## Single shell worlds

Making a single giant shell is actually more efficient than the concentric shell world. – no wasted pillars, all material used to generate area That shell has $R = \sqrt{M/4 \pi \rho}$ and area $A=4 \pi M/4 \pi \rho = M/\rho$ (which, when you think about units, is the natural answer). For Earth mass shells with 500 kg per square meter, the radius becomes 31 million km, and the surface area is $1.2\cdot 10^{22}$ square meters, 23 million times the Earth’s surface.

The gravity will however be microscopic, since it scales as $1/R^2$ – for all practical purposes it is zero. Bad for keeping an atmosphere in. We can of course cheat by simply putting a thin plastic roof on top of this sphere to maintain the atmosphere, but we would still be floating around.

Building shells around central masses seems to be a nice way of getting gravity at first. Just roof over Jupiter at the right radius ($\sqrt{GM/g}=$ 113,000 km) and you have a lot of 1 G living area. Or why not do it with a suitably quiet star? For the sun, that would be a shell with radius 3.7 million km, with an area 334,000 times Earth.

Of course, we may get serious gravity by constructing shells around black holes. If we use the Sagittarius A* hole we get a radius of 6.9 light-hours, with 1.4 trillion times Earth’s area. Of course, it also needs a lot of shell material, something on the order of 20% of a sun mass if we still assume 500 kg per square meter.

As an aside, the shell theorem still remains true: the general relativity counterpart, Birkhoff’s theorem, shows that spherical arrangements of mass produce either flat spacetime (in central voids) or Schwartzschild spacetimes (outside the mass). The flat spacetimes still suffer gravitational time dilation, though.

A small problem is that the shell theorem means the shell will not remain aligned with the internal mass: there is no net force. Anything that hits the surface will give it a bit of momentum away from where it should be. However, this can likely solved with dynamical corrections: just add engines here and there to realign it.

A far bigger problem is that the structure will be in compression. Each piece will be pulled towards the centre with a force $G M \rho/R^2$ per m^2, and to remain in place it needs to be held up by neighbouring pieces with an equal force. This must be summed across the entire surface. Frank Palmer pointed out one could calculate this as two hemispheres joined at a seam, finding a total pressure of $g \rho R /2$. If we have a maximum strength $P_{max}$ the maximal radius for this gravity becomes $R = 2 P_{max}/g \rho$. Using diamond and 1 G we get $R=180,000$ km. That is not much, at least if we dream about enclosing stars (Jupiter is fine). Worse, buckling is a real problem.

## Bubbleworlds

Dani Eder suggested another way of supporting the shell: add gas inside, and let its pressure keep it inflated. Such bubble worlds have an upper limit set by self-gravity; Eder calculated the maximal radius as 240,000 km for a hydrogen bubble. It has 1400  times the Earth’s area, but one could of course divide the top layers into internal floors too. See also the analysis at gravitationalballoon.blogspot.se for more details (that blog itself is a goldmine for inflated megastructures).

Eder also points out that one limit of the size of such worlds is the need to radiate heat from the inhabitants. Each human produces about 100 W of waste heat; this has to be radiated away from a surface area of $4 \pi R^2$ at around 300K: this means that the maximum number of inhabitants is $N = 4 \pi \sigma R^2 300^4 / 100$. For a bubbleworld this is $3.3\cdot 10^{18}$ people. For Earth, it is $2.3\cdot 10^{15}$ people.

## Living space

If we accept volume instead of area, we may think of living inside such bubbles. Karl Schroeder’s Virga books come to mind, although he modestly went for something like a 5,000 mile diameter. Niven discusses building an air-filled volume around a Dyson shell surrounding the galactic core, with literally cubic lightyears of air.

The ultimate limit is avoiding Jeans instability: sufficiently large gas volumes are unstable against gravitational contraction and will implode into stars or planets. The Jeans length is

$L=\sqrt{15 kT/4\pi G m \rho}$

where $m$ is the mass per particle. Plugging in 300 K, the mass of nitrogen molecules and air density I get a radius of 40,000 km (see also this post for some alternate numbers). This is a liveable volume of $2.5\cdot 10^{14}$ cubic kilometres, or 0.17 Jupiter volumes. The overall calculation is somewhat approximate, since such a gas mass will not have constant density throughout and there has to be loads of corrections, but it gives a rough sense of the volume. Schroeder does OK, but Niven’s megasphere is not possible.

Living on surfaces might be a mistake. At least if one wants a lot of living space.

## Bigger than worlds

The locus classicus on artificial megastructures is Larry Niven’s essay Bigger than worlds. Beside the normal big things like O’Neill cylinders it leads up to the truly big ones like Dyson spheres. It mentions that Dan Alderson suggested a double Dyson sphere, where two concentric shells had atmosphere between them and gravity provided by the internal star. (His Alderson Disk design is ruled out for consideration in my essay because we do not know any physics that would allow that strong materials.) Of course, as discussed above, solid Dyson shells are problematic to build. A Dyson swarm of free-floating habitats and solar collectors is far more physically plausible, but fails at being *a* world: it is a collection of lot of worlds.

One fun idea mentioned by Niven is the topopolis suggested by Pat Gunkel. Consider a very long cylinder rotating about its axis: it has internal pseudogravity, it is mechanically possible (there is some stress on the circumferential material, but unless the radius or rotation is very large or fast we know how to build this from existing materials like carbon fibers). There is no force between the hoops making up the cylinder: were we to cut them apart they would still rotate in line.

Now make the cylinder $2 \pi R$ km long and bend it into a torus with major radius R. If the cylinder has radius r, the difference in circumference between the inner and outer edge is $2 \pi (R+r)-(R-r)=4\pi r$. Spread out around the circumference, that means each hoop is subjected to a compression of size $4 \pi r / 2\pi R=2 (r/R)$ if it continues to rotate like it did before. Since R is huge, this is a very small factor. This is also why the curvature of the initial bend can be ignored. For a topopolis orbiting Earth in geostationary orbit, if r is 1 km the compression factor is $4.7\cdot 10^{-5}$; if it loops around the sun and is a 1000 km across the effect is just $10^{-5}$. Heat expansion is likely a bigger problem. At large enough scales O’Neill cylinders are like floppy hoses.

The area would be $2 \pi R r$. In the first case 0.0005 of Earth’s area, in the second case 1842 times.

The funny thing about topopolis is that there is no reason for it to go just one turn around the orbited object. It could form a large torus knot winding around the object. So why not double, triple or quadruple the area? In principle we could just keep going and get nearly any area (up until the point where self-gravity started to matter).

There is some trouble with Kepler’s second law: parts closer to the central body will tend to move faster, causing tension and compression along the topopolis, but if the change in radial distance is small these forces will also be small and spread out along a enormous length.

Unfortunately topopolis has the same problem as a ringworld: it is not stably in orbit if it is rigid (any displacement tends to be amplified), and the flexibility likely makes things far worse. Like the ringworld and Dyson shell it can plausibly be kept in shape by active control, perhaps solar sails or thrusters that fire to keep it where it should. This also serves to ensure that it does not collide with itself: effectively there are carefully tuned transversal waves progressing around the circumference keeping it shaped like a proper knot. But I do not want to be anywhere close if there is an error: this kind of system will not fail gracefully.

# Discussion

 Radius (Earths) Area (Earths) Notes Iron earth 2.7 7.3 Perovskite earth 3 9 Ice earth 5 25 Rotating ice 2.5x12x12 92 Diamond 1G planet 1.6 2.56 Graphite 1G planet 2.6 7 Unstable Aerogel 1G planet 1837 337,000 Unstable Microlattice 1G planet 6125 50 million Unstable Shellworld (h=3) 3.1 23 million Shellworld (h=100) 10.2 23 million Single shell 4865 23 million Jupiter roof 17.7 313 Stability? Sun roof 581 334000 Strength issue Sag A roof $1.20\cdot 10^6$ $1.36\cdot 10^{12}$ Strength issue Bubbleworld 37.7 1400 Jeans length 6.27 39 1 AU ring 1842 Stability?

Why aim for a large world in the first place? There are three apparent reasons. The first is simply survival, or perhaps Lebensraum: large worlds have more space for more beings, and this may be a good thing in itself. The second is to have more space for stuff of value, whether that is toys, gardens or wilderness. The third is to desire for diversity: a large world can have more places that are different from each other. There is more space for exploration, for divergent evolution. Even if the world is deliberately made parts can become different and unique.

Planets are neat, self-assembling systems. They also use a lot of mass to provide gravity and are not very good at producing living space. Artificial constructs can become far larger and are far more efficient at living space per kilogram. But in the end they tend to be limited by gravity.

Our search for the largest possible world demonstrates that demanding a singular world may be a foolish constraint: a swarm of O’Neill cylinders, or a Dyson swarm surrounding a star, has enormously much more area than any singular structure and few of the mechanical problems. Even a carefully arranged solar system could have far more habitable worlds within (relatively) easy reach.

One world is not enough, no matter how large.

# Enhancing dogs not to lie

Or more specifically, the ethics of indigenous hunting practices where dogs are enhanced in various ways by drugs – from reducing their odour over stimulants to hallucinogens that may enhance their perception. Is this something unnatural, too instrumental, or harm their dignity? I unsurprisingly disagree. These drugs may even be in the interest of the dog itself. In fact, the practice might be close to true to animal enhancement.

Still, one can enhance for bad reasons. I am glad I discovered Kohn’s paper “How dogs dream: Amazonian natures and the politics of transspecies engagement” on human-dog relationships in Amazon, since it shows just how strange – for an outsider – the epistemic and ethical thinking of a culture can be. Even if we take a cultural relativist position and say that of course dogs should be temporarily uplifted along the chain of being so they can be told by a higher species how to behave, from an instrumental standpoint it looks unlikely that that particular practice actually works. A traditionally used drug or method may actually not work for the purpose its users intend (from what I know of traditional European medicine, a vast number of traditional remedies were actually pointless yet persisted), but because of epistemic problems it persists (it is traditional, no methods for evidence based medicine, hard to tell apart the intended effect from the apparent effect). It wouldn’t surprise me that a fair number of traditional dog enhancements are in this domain.

# Harming virtual bodies

I was recently interviewed by Anna Denejkina for Vertigo, and references to the article seems to be circulating around. Given the hot button topic – transhumanism and virtual rape – I thought it might be relevant to bring out what I said in the email interview.

(Slightly modified for clarity, grammar and links)

> How are bioethicists and philosophers coping with the ethical issues which may arise from transhumanist hacking, and what would be an outcome of hacking into the likes of full body haptic suit, a smart sex toy, e-spot implant, i.e.: would this be considered act of kidnapping, or rape, or another crime?

There is some philosophy of virtual reality and augmented reality, and a lot more about the ethics of cyberspace. The classic essay is this 1998 one, dealing with a text-based rape in the mid-90s.

My personal view is that our bodies are the interfaces between our minds and the world. The evil of rape is that it involves violating our ability to interact with the world in a sensual manner: it involves both coercion of bodies and inflicting a mental violation. So from this perspective it does not matter much if the rape happens to a biological body, or a virtual body connected via a haptic suit, or some brain implant. There might of course be lesser violations if the coercion is limited (you can easily log out) or if there is a milder violation (a hacked sex toy might infringe on privacy and ones sexual integrity, but it is not able to coerce): the key issue is that somebody is violating the body-mind interface system, and we are especially vulnerable when this involves our sexual, emotional and social sides.

Widespread use of virtual sex will no doubt produce many tricky ethical situations. (what about recording the activities and replaying them without the partner’s knowledge? what if the partner is not who I think it is? what mapping the sexual encounter onto virtual or robot bodies that look like children and animals? what about virtual sexual encounters that break the laws in one country but not another?)

Much of this will sort itself out like with any new technology: we develop norms for it, sometimes after much debate and anguish. I suspect we will become much more tolerant of many things that are currently weird and taboo. The issue ethicists may worry about is whether we would also become blasé about things that should not be accepted. I am optimistic about it: I think that people actually do react to things that are true violations.

> If such a violation was to occur, what can be done to ensure that today’s society is ready to treat this as a real criminal issue?
Criminal law tends to react slowly to new technology, and usually tries to map new crimes onto old ones (if I steal your World of Warcraft equipment I might be committing fraud rather than theft, although different jurisdictions have very different views – some even treat this as gambling debts). This is especially true for common law systems like the US and UK. In civil law systems like most of Europe laws tend to get passed when enough people convince politicians that There Ought To Be a Law Against It (sometimes unwisely).

So to sum up, look at whether people involuntarily actually suffer real psychological anguish, loss of reputations or lose control over important parts of their exoselves due to the actions of other people. If they do, then at least something immoral has happened. Whether laws, better software security, social norms or something else (virtual self defence? built-in safewords?) is the best remedy may depend on the technology and culture.

I think there is an interesting issue in what role the body plays here. As I said, the body is an interface between our minds and the world around us. It is also a nontrivial thing: it has properties and states of its own, and these affect how we function. Even if one takes a nearly cybergnostic view that we are merely minds interfacing with the world rather than a richer embodiment view this plays an important role. If I have a large, small, hard or vulnerable body, it will affect how I can act in the world – and this will undoubtedly affect how I think of myself. Our representations of ourselves are strongly tied to our bodies and the relationship between them and our environment. Our somatosensory cortex maps itself to how touch distributes itself on our skin, and our parietal cortex not only represents the body-environment geometry but seems involved in our actual sense of self.

This means that hacking the body is more serious than hacking other kinds of software or possessions. Currently it is our only way of existing in the world. Even in an advanced VR/transhuman society where people can switch bodies simply and freely, infringing on bodies has bigger repercussions than changing other software outside the mind – especially if it is subtle. The violations discussed in the article are crude, overt ones. But subtle changes to ourselves may fly under the radar of outrage, yet do harm.

Most people are no doubt more interested in the titillating combination of sex and tech – there is a 90’s cybersex vibe coming off this discussion, isn’t it? The promise of new technology to give us new things to be outraged or dream about. But the philosophical core is about the relation between the self, the other, and what actually constitutes harm – very abstract, and not truly amenable to headlines.

# 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

## Space

In 1957 the space age began.

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.

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.

## Nuclear

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!

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

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.

## Computers

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].

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.

## Biotechnology

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…

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.

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

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

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.

## Risk

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.

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).

## Coordination

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.

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