Category Archives: automation

AI and activism, a Terminator-sized threat targeting you soon

You should be familiar with the Terminator scenario. If you aren’t then you should watch one of the Terminator series of films because you really should be aware of it. But there is another issue related to AI that is arguably as dangerous as the Terminator scenario, far more likely to occur and is a threat in the near term. What’s even more dangerous is that in spite of that, I’ve never read anything about it anywhere yet. It seems to have flown under our collective radar and is already close.

In short, my concern is that AI is likely to become a heavily armed Big Brother. It only requires a few components to come together that are already well in progress. Read this, and if you aren’t scared yet, read it again until you understand it 🙂

Already, social media companies are experimenting with using AI to identify and delete ‘hate’ speech. Various governments have asked them to do this, and since they also get frequent criticism in the media because some hate speech still exists on their platforms, it seems quite reasonable for them to try to control it. AI clearly offers potential to offset the huge numbers of humans otherwise needed to do the task.

Meanwhile, AI is already used very extensively by the same companies to build personal profiles on each of us, mainly for advertising purposes. These profiles are already alarmingly comprehensive, and increasingly capable of cross-linking between our activities across multiple platforms and devices. Latest efforts by Google attempt to link eventual purchases to clicks on ads. It will be just as easy to use similar AI to link our physical movements and activities and future social connections and communications to all such previous real world or networked activity. (Update: Intel intend their self-driving car technology to be part of a mass surveillance net, again, for all the right reasons:

Although necessarily secretive about their activities, government also wants personal profiles on its citizens, always justified by crime and terrorism control. If they can’t do this directly, they can do it via legislation and acquisition of social media or ISP data.

Meanwhile, other experiences with AI chat-bots learning to mimic human behaviors have shown how easily AI can be gamed by human activists, hijacking or biasing learning phases for their own agendas. Chat-bots themselves have become ubiquitous on social media and are often difficult to distinguish from humans. Meanwhile, social media is becoming more and more important throughout everyday life, with provably large impacts in political campaigning and throughout all sorts of activism.

Meanwhile, some companies have already started using social media monitoring to police their own staff, in recruitment, during employment, and sometimes in dismissal or other disciplinary action. Other companies have similarly started monitoring social media activity of people making comments about them or their staff. Some claim to do so only to protect their own staff from online abuse, but there are blurred boundaries between abuse, fair criticism, political difference or simple everyday opinion or banter.

Meanwhile, activists increasingly use social media to force companies to sack a member of staff they disapprove of, or drop a client or supplier.

Meanwhile, end to end encryption technology is ubiquitous. Malware creation tools are easily available.

Meanwhile, successful hacks into large company databases become more and more common.

Linking these various elements of progress together, how long will it be before activists are able to develop standalone AI entities and heavily encrypt them before letting them loose on the net? Not long at all I think.  These AIs would search and police social media, spotting people who conflict with the activist agenda. Occasional hacks of corporate databases will provide names, personal details, contacts. Even without hacks, analysis of publicly available data going back years of everyone’s tweets and other social media entries will provide the lists of people who have ever done or said anything the activists disapprove of.

When identified, they would automatically activate armies of chat-bots, fake news engines and automated email campaigns against them, with coordinated malware attacks directly on the person and indirect attacks by communicating with employers, friends, contacts, government agencies customers and suppliers to do as much damage as possible to the interests of that person.

Just look at the everyday news already about alleged hacks and activities during elections and referendums by other regimes, hackers or pressure groups. Scale that up and realize that the cost of running advanced AI is negligible.

With the very many activist groups around, many driven with extremist zeal, very many people will find themselves in the sights of one or more activist groups. AI will be able to monitor everyone, all the time.  AI will be able to target each of them at the same time to destroy each of their lives, anonymously, highly encrypted, hidden, roaming from server to server to avoid detection and annihilation, once released, impossible to retrieve. The ultimate activist weapon, that carries on the fight even if the activist is locked away.

We know for certain the depths and extent of activism, the huge polarization of society, the increasingly fierce conflict between left and right, between sexes, races, ideologies.

We know about all the nice things AI will give us with cures for cancer, better search engines, automation and economic boom. But actually, will the real future of AI be harnessed to activism? Will deliberate destruction of people’s everyday lives via AI be a real problem that is almost as dangerous as Terminator, but far more feasible and achievable far earlier?

AI is mainly a stimulative technology that will create jobs

AI has been getting a lot of bad press the last few months from doom-mongers predicting mass unemployment. Together with robotics, AI will certainly help automate a lot of jobs, but it will also create many more and will greatly increase quality of life for most people. By massively increasing the total effort available to add value to basic resources, it will increase the size of the economy and if that is reasonably well managed by governments, that will be for all our benefit. Those people who do lose their jobs and can’t find or create a new one could easily be supported by a basic income financed by economic growth. In short, unless government screws up, AI will bring huge benefits, far exceeding the problems it will bring.

Over the last 20 years, I’ve often written about the care economy, where the more advanced technology becomes, the more it allows to concentrate on those skills we consider fundamentally human – caring, interpersonal skills, direct human contact services, leadership, teaching, sport, the arts, the sorts of roles that need emphatic and emotional skills, or human experience. AI and robots can automate intellectual and physical tasks, but they won’t be human, and some tasks require the worker to be human. Also, in most careers, it is obvious that people focus less and less on those automatable tasks as they progress into the most senior roles. Many board members in big companies know little about the industry they work in compared to most of their lower paid workers, but they can do that job because being a board member is often more about relationships than intellect.

AI will nevertheless automate many tasks for many workers, and that will free up much of their time, increasing their productivity, which means we need fewer workers to do those jobs. On the other hand, Google searches that take a few seconds once took half a day of research in a library. We all do more with our time now thanks to such simple AI, and although all those half-days saved would add up to a considerable amount of saved work, and many full-time job equivalents, we don’t see massive unemployment. We’re all just doing better work. So we can’t necessarily conclude that increasing productivity will automatically mean redundancy. It might just mean that we will do even more, even better, like it has so far. Or at least, the volume of redundancy might be considerably less. New automated companies might never employ people in those roles and that will be straight competition between companies that are heavily automated and others that aren’t. Sometimes, but certainly not always, that will mean traditional companies will go out of business.

So although we can be sure that AI and robots will bring some redundancy in some sectors, I think the volume is often overestimated and often it will simply mean rapidly increasing productivity, and more prosperity.

But what about AI’s stimulative role? Jobs created by automation and AI. I believe this is what is being greatly overlooked by doom-mongers. There are three primary areas of job creation:

One is in building or programming robots, maintaining them, writing software, or teaching them skills, along with all the associated new jobs in supporting industry and infrastructure change. Many such jobs will be temporary, lasting a decade or so as machines gradually take over, but that transition period is extremely valuable and important. If anything, it will be a lengthy period of extra jobs and the biggest problem may well be filling those jobs, not widespread redundancy.

Secondly, AI and robots won’t always work direct with customers. Very often they will work via a human intermediary. A good example is in medicine. AI can make better diagnoses than a GP, and could be many times cheaper, but unless the patient is educated, and very disciplined and knowledgeable, it also needs a human with human skills to talk to a patient to make sure they put in correct information. How many times have you looked at an online medical diagnosis site and concluded you have every disease going? It is hard to be honest sometimes when you are free to interpret every possible symptom any way you want, much easier to want to be told that you have a special case of wonderful person syndrome. Having to explain to a nurse or technician what is wrong forces you to be more honest about it. They can ask you similar questions, but your answers will need to be moderated and sensible or you know they might challenge you and make you feel foolish. You will get a good diagnosis because the input data will be measured, normalized and scaled appropriately for the AI using it. When you call a call center and talk to a human, invariably they are already the front end of a massive AI system. Making that AI bigger and better won’t replace them, just mean that they can deal with your query better.

Thirdly, and I believe most importantly of all, AI and automation will remove many of the barriers that stop people being entrepreneurs. How many business ideas have you had and not bothered to implement because it was too much effort or cost or both for too uncertain a gain? 10? 100? 1000? Suppose you could just explain your idea to your home AI and it did it all for you. It checked the idea, made a model, worked out how to make it work or whether it was just a crap idea. It then explained to you what the options were and whether it would be likely to work, and how much you might earn from it, and how much you’d actually have to do personally and how much you could farm out to the cloud. Then AI checked all the costs and legal issues, did all the admin, raised the capital by explaining the idea and risks and costs to other AIs, did all the legal company setup, organised the logistics, insurance, supply chains, distribution chains, marketing, finance, personnel, ran the payroll and tax. All you’d have to do is some of the fun work that you wanted to do when you had the idea and it would find others or machines or AI to fill in the rest. In that sort of world, we’d all be entrepreneurs. I’d have a chain of tea shops and a fashion empire and a media empire and run an environmental consultancy and I’d be an artist and a designer and a composer and a genetic engineer and have a transport company and a construction empire. I don’t do any of that because I’m lazy and not at all entrepreneurial, and my ideas all ‘need work’ and the economy isn’t smooth and well run, and there are too many legal issues and regulations and it would all be boring as hell. If we automate it and make it run efficiently, and I could get as much AI assistance as I need or want at every stage, then there is nothing to stop me doing all of it. I’d create thousands of jobs, and so would many other people, and there would be more jobs than we have people to fill them, so we’d need to build even more AI and machines to fill the gaps caused by the sudden economic boom.

So why the doom? It isn’t justified. The bad news isn’t as bad as people make out, and the good news never gets a mention. Adding it together, AI will stimulate more jobs, create a bigger and a better economy, we’ll be doing far more with our lives and generally having a great time. The few people who will inevitably fall through the cracks could easily be financed by the far larger economy and the very generous welfare it can finance. We can all have the universal basic income as our safety net, but many of us will be very much wealthier and won’t need it.


Future sex, gender and relationships: how close can you get?

Using robots for gender play

Using robots for gender play

I recently gave a public talk at the British Academy about future sex, gender, and relationship, asking the question “How close can you get?”, considering particularly the impact of robots. The above slide is an example. People will one day (between 2050 and 2065 depending on their budget) be able to use an android body as their own or even swap bodies with another person. Some will do so to be young again, many will do so to swap gender. Lots will do both. I often enjoy playing as a woman in computer games, so why not ‘come back’ and live all over again as a woman for real? Except I’ll be 90 in 2050.

The British Academy kindly uploaded the audio track from my talk at

If you want to see the full presentation, here is the PowerPoint file as a pdf:


I guess it is theoretically possible to listen to the audio while reading the presentation. Most of the slides are fairly self-explanatory anyway.

Needless to say, the copyright of the presentation belongs to me, so please don’t reproduce it without permission.


Chat-bots will help reduce loneliness, a bit

Amazon is really pushing its Echo and Dot devices at the moment and some other companies also use Alexa in their own devices. They are starting to gain avatar front ends too. Microsoft has their Cortana transforming into Zo, Apple has Siri’s future under wraps for now. Maybe we’ll see Siri in a Sari soon, who knows. Thanks to rapidly developing AI, chatbots and other bots have also made big strides in recent years, so it’s obvious that the two can easily be combined. The new voice control interfaces could become chatbots to offer a degree of companionship. Obviously that isn’t as good as chatting to real people, but many, very many people don’t have that choice. Loneliness is one of the biggest problems of our time. Sometimes people talk to themselves or to their pet cat, and chatting to a bot would at least get a real response some of the time. It goes further than simple interaction though.

I’m not trying to understate the magnitude of the loneliness problem, and it can’t solve it completely of course, but I think it will be a benefit to at least some lonely people in a few ways. Simply having someone to chat to will already be of some help. People will form emotional relationships with bots that they talk to a lot, especially once they have a visual front end such as an avatar. It will help some to develop and practice social skills if that is their problem, and for many others who feel left out of local activity, it might offer them real-time advice on what is on locally in the next few days that might appeal to them, based on their conversations. Talking through problems with a bot can also help almost as much as doing so with a human. In ancient times when I was a programmer, I’d often solve a bug by trying to explain how my program worked, and in doing so i would see the bug myself. Explaining it to a teddy bear would have been just as effective, the chat was just a vehicle for checking through the logic from a new angle. The same might apply to interactive conversation with a bot. Sometimes lonely people can talk too much about problems when they finally meet people, and that can act as a deterrent to future encounters, so that barrier would also be reduced. All in all, having a bot might make lonely people more able to get and sustain good quality social interactions with real people, and make friends.

Another benefit that has nothing to do with loneliness is that giving a computer voice instructions forces people to think clearly and phrase their requests correctly, just like writing a short computer program. In a society where so many people don’t seem to think very clearly or even if they can, often can’t express what they want clearly, this will give some much needed training.

Chatbots could also offer challenges to people’s thinking, even to help counter extremism. If people make comments that go against acceptable social attitudes or against known facts, a bot could present the alternative viewpoint, probably more patiently than another human who finds such viewpoints frustrating. I’d hate to see this as a means to police political correctness, though it might well be used in such a way by some providers, but it could improve people’s lack of understanding of even the most basic science, technology, culture or even politics, so has educational value. Even if it doesn’t convert people, it might at least help them to understand their own views more clearly and be better practiced at communicating their arguments.

Chat bots could make a significant contribution to society. They are just machines, but those machines are tools for other people and society as a whole to help more effectively.


AI presents a new route to attack corporate value

As AI increases in corporate, social, economic and political importance, it is becoming a big target for activists and I think there are too many vulnerabilities. I think we should be seeing a lot more articles than we are about what developers are doing to guard against deliberate misdirection or corruption, and already far too much enthusiasm for make AI open source and thereby giving mischief-makers the means to identify weaknesses.

I’ve written hundreds of times about AI and believe it will be a benefit to humanity if we develop it carefully. Current AI systems are not vulnerable to the terminator scenario, so we don’t have to worry about that happening yet. AI can’t yet go rogue and decide to wipe out humans by itself, though future AI could so we’ll soon need to take care with every step.

AI can be used in multiple ways by humans to attack systems.

First and most obvious, it can be used to enhance malware such as trojans or viruses, or to optimize denial of service attacks. AI enhanced security systems already battle against adaptive malware and AI can probe systems in complex ways to find vulnerabilities that would take longer to discover via manual inspection. As well as AI attacking operating systems, it can also attack AI by providing inputs that bias its learning and decision-making, giving AI ‘fake news’ to use current terminology. We don’t know the full extent of secret military AI.

Computer malware will grow in scope to address AI systems to undermine corporate value or political campaigns.

A new route to attacking corporate AI, and hence the value in that company that relates in some way to it is already starting to appear though. As companies such as Google try out AI-driven cars or others try out pavement/sidewalk delivery drones, so mischievous people are already developing devious ways to misdirect or confuse them. Kids will soon have such activity as hobbies. Deliberate deception of AI is much easier when people know how they work, and although it’s nice for AI companies to put their AI stuff out there into the open source markets for others to use to build theirs, that does rather steer future systems towards a mono-culture of vulnerability types. A trick that works against one future AI in one industry might well be adaptable to another use in another industry with a little devious imagination. Let’s take an example.

If someone builds a robot to deliberately step in front of a self-driving car every time it starts moving again, that might bring traffic to a halt, but police could quickly confiscate the robot, and they are expensive, a strong deterrent even if the pranksters are hiding and can’t be found. Cardboard cutouts might be cheaper though, even ones with hinged arms to look a little more lifelike. A social media orchestrated campaign against a company using such cars might involve thousands of people across a country or city deliberately waiting until the worst time to step out into a road when one of their vehicles comes along, thereby creating a sort of denial of service attack with that company seen as the cause of massive inconvenience for everyone. Corporate value would obviously suffer, and it might not always be very easy to circumvent such campaigns.

Similarly, the wheeled delivery drones we’ve been told to expect delivering packages any time soon will also have cameras to allow them to avoid bumping into objects or little old ladies or other people, or cats or dogs or cardboard cutouts or carefully crafted miniature tank traps or diversions or small roadblocks that people and pets can easily step over but drones can’t, that the local kids have built from a few twigs or cardboard from a design that has become viral that day. A few campaigns like that with the cold pizzas or missing packages that result could severely damage corporate value.

AI behind websites might also be similarly defeated. An early experiment in making a Twitter chat-bot that learns how to tweet by itself was quickly encouraged by mischief-makers to start tweeting offensively. If people have some idea how an AI is making its decisions, they will attempt to corrupt or distort it to their own ends. If it is heavily reliant on open source AI, then many of its decision processes will be known well enough for activists to develop appropriate corruption tactics. It’s not to early to predict that the proposed AI-based attempts by Facebook and Twitter to identify and defeat ‘fake news’ will fall right into the hands of people already working out how to use them to smear opposition campaigns with such labels.

It will be a sort of arms race of course, but I don’t think we’re seeing enough about this in the media. There is a great deal of hype about the various AI capabilities, a lot of doom-mongering about job cuts (and a lot of reasonable warnings about job cuts too) but very little about the fight back against AI systems by attacking them on their own ground using their own weaknesses.

That looks to me awfully like there isn’t enough awareness of how easily they can be defeated by deliberate mischief or activism, and I expect to see some red faces and corporate account damage as a result.


This article appeared yesterday that also talks about the bias I mentioned:

Since I wrote this blog, I was asked via Linked-In to clarify why I said that Open Source AI systems would have more security risk. Here is my response:

I wasn’t intending to heap fuel on a dying debate (though since current debate looks the same as in early 1990s it is dying slowly). I like and use open source too. I should have explained my reasoning better to facilitate open source checking: In regular (algorithmic) code, programming error rate should be similar so increasing the number of people checking should cancel out the risk from more contributors so there should be no a priori difference between open and closed. However:

In deep learning, obscurity reappears via neural net weightings being less intuitive to humans. That provides a tempting hiding place.

AI foundations are vulnerable to group-think, where team members share similar world models. These prejudices will affect the nature of OS and CS code and result in AI with inherent and subtle judgment biases which will be less easy to spot than bugs and be more visible to people with alternative world models. Those people are more likely to exist in an OS pool than a CS pool and more likely to be opponents so not share their results.

Deep learning may show the equivalent of political (or masculine and feminine). As well as encouraging group-think, that also distorts the distribution of biases and therefore the cancelling out of errors can no longer be assumed.

Human factors in defeating security often work better than exploiting software bugs. Some of the deep learning AI is designed to mimic humans as well as possible in thinking and in interfacing. I suspect that might also make them more vulnerable to meta-human-factor attacks. Again, exposure to different and diverse cultures will show a non-uniform distribution of error/bias spotting/disclosure/exploitation.

Deep learning will become harder for humans to understand as it develops and becomes more machine dependent. That will amplify the above weaknesses. Think of optical illusions that greatly distort human perception and think of similar in advanced AI deep learning. Errors or biases that are discovered will become more valuable to an opponent since they are less likely to be spotted by others, increasing their black market exploitation risk.

I have not been a programmer for over 20 years and am no security expert so my reasoning may be defective, but at least now you know what my reasoning was and can therefore spot errors in it.

Can we automate restaurant reviews?

Reviews are an important part of modern life. People often consult reviews before buying things, visiting a restaurant or booking a hotel. There are even reviews on the best seats to choose on planes. When reviews are honestly given, they can be very useful to potential buyers, but what if they aren’t honestly give? What if they are glowing reviews written by friends of the restaurant owners, or scathing reviews written by friends of the competition? What if the service received was fine, but the reviewer simply didn’t like the race or gender of the person delivering it? Many reviews fall into these categories, but of course we can’t be sure how many, because when someone writes a review, we don’t know whether they were being honest or not, or whether they are biased or not. Adding a category of automated reviews would add credibility provided the technology is independent of the establishment concerned.

Face recognition software is now so good that it can read lips better than human lip reading experts. It can be used to detect emotions too, distinguishing smiles or frowns, and whether someone is nervous, stressed or relaxed. Voice recognition can discern not only words but changes in pitch and volume that might indicate their emotional context. Wearable devices can also detect emotions such as stress.

Given this wealth of technology capability, cameras and microphones in a restaurant could help verify human reviews and provide machine reviews. Using the checking in process it can identify members of a group that might later submit a review, and thus compare their review with video and audio records of the visit to determine whether it seems reasonably true. This could be done by machine using analysis of gestures, chat and facial expressions. If the person giving a poor review looked unhappy with the taste of the food while they were eating it, then it is credible. If their facial expression were of sheer pleasure and the review said it tasted awful, then that review could be marked as not credible, and furthermore, other reviews by that person could be called into question too. In fact, guests would in effect be given automated reviews of their credibility. Over time, a trust rating would accrue, that could be used to group other reviews by credibility rating.

Totally automated reviews could also be produced, by analyzing facial expressions, conversations and gestures across a whole restaurant full of people. These machine reviews would be processed in the cloud by trusted review companies and could give star ratings for restaurants. They could even take into account what dishes people were eating to give ratings for each dish, as well as more general ratings for entire chains.

Service could also be automatically assessed to some degree too. How long were the people there before they were greeted/served/asked for orders/food delivered. The conversation could even be automatically transcribed in many cases, so comments about rudeness or mistakes could be verified.

Obviously there are many circumstances where this would not work, but there are many where it could, so AI might well become an important player in the reviews business. At a time when restaurants are closing due to malicious bad reviews, or ripping people off in spite of poor quality thanks to dishonest positive reviews, then this might help a lot. A future where people are forced to be more honest in their reviews because they know that AI review checking could damage their reputation if they are found to have been dishonest might cause some people to avoid reviewing altogether, but it could improve the reliability of the reviews that still do happen.

Still not perfect, but it could be a lot better than today, where you rarely know how much a review can be trusted.

Carbethium, a better-than-scifi material

How to build one of these for real:


Halo light bridge, from

Or indeed one of these:



I recently tweeted that I had an idea how to make the glowy bridges and shields we’ve seen routinely in sci-fi games from Half Life to Destiny, the bridges that seem to appear in a second or two from nothing across a divide, yet are strong enough to drive tanks over, and able to vanish as quickly and completely when they are switched off. I woke today realizing that with a bit of work, that it could be the basis of a general purpose material to make the tanks too, and buildings and construction platforms, bridges, roads and driverless pod systems, personal shields and city defense domes, force fields, drones, planes and gliders, space elevator bases, clothes, sports tracks, robotics, and of course assorted weapons and weapon systems. The material would only appear as needed and could be fully programmable. It could even be used to render buildings from VR to real life in seconds, enabling at least some holodeck functionality. All of this is feasible by 2050.

Since it would be as ethereal as those Halo structures, I first wanted to call the material ethereum, but that name was already taken (for a 2014 block-chain programming platform, which I note could be used to build the smart ANTS network management system that Chris Winter and I developed in BT in 1993), and this new material would be a programmable construction platform so the names would conflict, and etherium is too close. Ethium might work, but it would be based on graphene and carbon nanotubes, and I am quite into carbon so I chose carbethium.

Ages ago I blogged about plasma as a 21st Century building material. I’m still not certain this is feasible, but it may be, and it doesn’t matter for the purposes of this blog anyway.

Around then I also blogged how to make free-floating battle drones and more recently how to make a Star Wars light-saber.

Carbethium would use some of the same principles but would add the enormous strength and high conductivity of graphene to provide the physical properties to make a proper construction material. The programmable matter bits and the instant build would use a combination of 3D interlocking plates, linear induction,  and magnetic wells. A plane such as a light bridge or a light shield would extend from a node in caterpillar track form with plates added as needed until the structure is complete. By reversing the build process, it could withdraw into the node. Bridges that only exist when they are needed would be good fun and we could have them by 2050 as well as the light shields and the light swords, and light tanks.

The last bit worries me. The ethics of carbethium are the typical mixture of enormous potential good and huge potential for abuse to bring death and destruction that we’re learning to expect of the future.

If we can make free-floating battle drones, tanks, robots, planes and rail-gun plasma weapons all appear within seconds, if we can build military bases and erect shield domes around them within seconds, then warfare moves into a new realm. Those countries that develop this stuff first will have a huge advantage, with the ability to send autonomous robotic armies to defeat enemies with little or no risk to their own people. If developed by a James Bond super-villain on a hidden island, it would even be the sort of thing that would enable a serious bid to take over the world.

But in the words of Professor Emmett Brown, “well, I figured, what the hell?”. 2050 values are not 2016 values. Our value set is already on a random walk, disconnected from any anchor, its future direction indicated by a combination of current momentum and a chaos engine linking to random utterances of arbitrary celebrities on social media. 2050 morality on many issues will be the inverse of today’s, just as today’s is on many issues the inverse of the 1970s’. Whatever you do or however politically correct you might think you are today, you will be an outcast before you get old:

We’re already fucked, carbethium just adds some style.

Graphene combines huge tensile strength with enormous electrical conductivity. A plate can be added to the edge of an existing plate and interlocked, I imagine in a hexagonal or triangular mesh. Plates can be designed in many diverse ways to interlock, so that rotating one engages with the next, and reversing the rotation unlocks them. Plates can be pushed to the forward edge by magnetic wells, using linear induction motors, using the graphene itself as the conductor to generate the magnetic field and the design of the structure of the graphene threads enabling the linear induction fields. That would likely require that the structure forms first out of graphene threads, then the gaps between filled by mesh, and plates added to that to make the structure finally solid. This would happen in thickness as well as width, to make a 3D structure, though a graphene bridge would only need to be dozens of atoms thick.

So a bridge made of graphene could start with a single thread, which could be shot across a gap at hundreds of meters per second. I explained how to make a Spiderman-style silk thrower to do just that in a previous blog:

The mesh and 3D build would all follow from that. In theory that could all happen in seconds, the supply of plates and the available power being the primary limiting factors.

Similarly, a shield or indeed any kind of plate could be made by extending carbon mesh out from the edge or center and infilling. We see that kind of technique used often in sci-fi to generate armor, from lost in Space to Iron Man.

The key components in carbetheum are 3D interlocking plate design and magnetic field design for the linear induction motors. Interlocking via rotation is fairly easy in 2D, any spiral will work, and the 3rd dimension is open to any building block manufacturer. 3D interlocking structures are very diverse and often innovative, and some would be more suited to particular applications than others. As for linear induction motors, a circuit is needed to produce the travelling magnetic well, but that circuit is made of the actual construction material. The front edge link between two wires creates a forward-facing magnetic field to propel the next plates and convey enough intertia to them to enable kinetic interlocks.

So it is feasible, and only needs some engineering. The main barrier is price and material quality. Graphene is still expensive to make, as are carbon nanotubes, so we won’t see bridges made of them just yet. The material quality so far is fine for small scale devices, but not yet for major civil engineering.

However, the field is developing extremely quickly because big companies and investors can clearly see the megabucks at the end of the rainbow. We will have almost certainly have large quantity production of high quality graphene for civil engineering by 2050.

This field will be fun. Anyone who plays computer games is already familiar with the idea. Light bridges and shields, or light swords would appear much as in games, but the material would likely  be graphene and nanotubes (or maybe the newfangled molybdenum equivalents). They would glow during construction with the plasma generated by the intense electric and magnetic fields, and the glow would be needed afterward to make these ultra-thin physical barriers clearly visible,but they might become highly transparent otherwise.

Assembling structures as they are needed and disassembling them just as easily will be very resource-friendly, though it is unlikely that carbon will be in short supply. We can just use some oil or coal to get more if needed, or process some CO2. The walls of a building could be grown from the ground up at hundreds of meters per second in theory, with floors growing almost as fast, though there should be little need to do so in practice, apart from pushing space vehicles up so high that they need little fuel to enter orbit. Nevertheless, growing a  building and then even growing the internal structures and even furniture is feasible, all using glowy carbetheum. Electronic soft fabrics, cushions and hard surfaces and support structures are all possible by combining carbon nanotubes and graphene and using the reconfigurable matter properties carbethium convents. So are visual interfaces, electronic windows, electronic wallpaper, electronic carpet, computers, storage, heating, lighting, energy storage and even solar power panels. So is all the comms and IoT and all the smart embdedded control systems you could ever want. So you’d use a computer with VR interface to design whatever kind of building and interior furniture decor you want, and then when you hit the big red button, it would appear in front of your eyes from the carbethium blocks you had delivered. You could also build robots using the same self-assembly approach.

If these structures can assemble fast enough, and I think they could, then a new form of kinetic architecture would appear. This would use the momentum of the construction material to drive the front edges of the surfaces, kinetic assembly allowing otherwise impossible and elaborate arches to be made.

A city transport infrastructure could be built entirely out of carbethium. The linear induction mats could grow along a road, connecting quickly to make a whole city grid. Circuit design allows the infrastructure to steer driverless pods wherever they need to go, and they could also be assembled as required using carbethium. No parking or storage is needed, as the pod would just melt away onto the surface when it isn’t needed.

I could go to town on military and terrorist applications, but more interesting is the use of the defense domes. When I was a kid, I imagined having a house with a defense dome over it. Lots of sci-fi has them now too. Domes have a strong appeal, even though they could also be used as prisons of course. A supply of carbetheum on the city edges could be used to grow a strong dome in minutes or even seconds, and there is no practical limit to how strong it could be. Even if lasers were used to penetrate it, the holes could fill in in real time, replacing material as fast as it is evaporated away.

Anyway, lots of fun. Today’s civil engineering projects like HS2 look more and more primitive by the day, as we finally start to see the true potential of genuinely 21st century construction materials. 2050 is not too early to expect widespread use of carbetheum. It won’t be called that – whoever commercializes it first will name it, or Google or MIT will claim to have just invented it in a decade or so, so my own name for it will be lost to personal history. But remember, you saw it here first.

Diabetes: Electronically controlled drug delivery via smart membrane

This is an invention I made in 2001 as part of my active skin suite to help diabetics. I’ve just been told I am another of the zillions of diabetics in the world so was reminded of it.

This wasn’t feasible in 2001 but it will be very soon, and could be an ideal way of monitoring blood glucose and insulin levels, checking with clinic AI for the correct does, and then opening the membrane pores just enough and long enough to allow the right dose of insulin to pass through. Obviously pore and drug particle design have to be coordinated, but this should be totally feasible. Here’s some pics:

Active skin principles

Active skin principles

Drug delivery overview

Drug delivery overview

Drug delivery mechanism

Drug delivery mechanism

New book: Society Tomorrow

It’s been a while since my last blog. That’s because I’ve been writing another book, my 8th so far. Not the one I was doing on future fashion, which went on the back burner for a while, I’ve only written a third of that one, unless I put it out as a very short book.

This one follows on from You Tomorrow and is called Society Tomorrow, 20% shorter at 90,000 words. It is ready to publish now, so I’m just waiting for feedback from a few people before hitting the button.


Here’s the introduction:

The one thing that we all share is that we will get older over the next few decades. Rapid change affects everyone, but older people don’t always feel the same effects as younger people, and even if we keep up easily today, some of us may find it harder tomorrow. Society will change, in its demographic and ethnic makeup, its values, its structure. We will live very differently. New stresses will come from both changing society and changing technology, but there is no real cause for pessimism. Many things will get better for older people too. We are certainly not heading towards utopia, but the overall quality of life for our ageing population will be significantly better in the future than it is today. In fact, most of the problems ahead are related to quality of life issues in society as a whole, and simply reflect the fact that if you don’t have to worry as much about poor health or poverty, something else will still occupy your mind.

This book follows on from 2013’s You Tomorrow, which is a guide to future life as an individual. It also slightly overlaps my 2013 book Total Sustainability which looks in part at future economic and social issues as part of achieving sustainability too. Rather than replicating topics, this book updates or omits them if they have already been addressed in those two companion books. As a general theme, it looks at wider society and the bigger picture, drawing out implications for both individuals and for society as a whole to deal with. There are plenty to pick from.

If there is one theme that plays through the whole book, it is a strong warning of the problem of increasing polarisation between people of left and right political persuasion. The political centre is being eroded quickly at the moment throughout the West, but alarmingly this does not seem so much to be a passing phase as a longer term trend. With all the potential benefits from future technology, we risk undermining the very fabric of our society. I remain optimistic because it can only be a matter of time before sense prevails and the trend reverses. One day the relative harmony of living peacefully side by side with those with whom we disagree will be restored, by future leaders of higher quality than those we have today.

Otherwise, whereas people used to tolerate each other’s differences, I fear that this increasing intolerance of those who don’t share the same values could lead to conflict if we don’t address it adequately. That intolerance currently manifests itself in increasing authoritarianism, surveillance, and an insidious creep towards George Orwell’s Nineteen Eighty-Four. The worst offenders seem to be our young people, with students seemingly proud of trying to ostracise anyone who dares agree with what they think is correct. Being students, their views hold many self-contradictions and clear lack of thought, but they appear to be building walls to keep any attempt at different thought away.

Altogether, this increasing divide, built largely from sanctimony, is a very dangerous trend, and will take time to reverse even when it is addressed. At the moment, it is still worsening rapidly.

So we face significant dangers, mostly self-inflicted, but we also have hope. The future offers wonderful potential for health, happiness, peace, prosperity. As I address the significant problems lying ahead, I never lose my optimism that they are soluble, but if we are to solve problems, we must first recognize them for what they are and muster the willingness to deal with them. On the current balance of forces, even if we avoid outright civil war, the future looks very much like a gilded cage. We must not ignore the threats. We must acknowledge them, and deal with them.

Then we can all reap the rich rewards the future has to offer.

It will be out soon.


Self-sterilizing surfaces & packaging