The future of the car industry

I’ve blogged and lectured many times now on the future of cars, public transport, trains, and I’ve retained my view that private cars and public transport (taxis, buses and trains, apart from very high density systems like London’s Underground) will eventually be replaced by fleets of driverless pods or self-driving cars (most probably the pods in city areas and some self-driving cars for non-urban areas). It can’t happen overnight of course, and there are various routes to getting there, but now that we know Tesla is setting up a big factory in Germany, the fog has lifted a little on the near and mid-term future.

Tesla will make electric cars. They have always been the future, but efforts and laws to reduce CO2 emissions are significantly expediting the trend. For the purposes of analyzing the future of the industry, there are really three distinct parts to consider. Electric vehicles can be considered to be a chassis, that can be adapted and re-used across a wide range of vehicles, a cabin, with its more individual appeals and decor, physical comforts and luxuries, and all the electronics, intelligence, sensors, displays, comms, entertainment.

With expertise in all camps, Tesla can flourish, but its much greater global expertise in the battery industry puts it in pole position to make a few standard electric chassis models that can be marketed to other manufacturers. The existence of those standard chassis allows new small manufacturers to spring up to offer a wide range of vehicles customized for every niche. These manufacturers don’t need the range of expertise of the conventional car industry, with many decades of expertise making relatively dumb vehicles with combustion engines. They will only have to learn the skills of making the comfortable cabins to sit on those chassis. (Don’t you hate that word too, with no proper plural!)

The car industry is therefore finding that much of the value of its historic core skills is quickly evaporating while having to compete on fairly equal terms in a new market using new technology with new manufacturers.

An electric chassis can include the motors to drive each wheel, and could also be easily adapted if and when new energy delivery systems using inductive pickups from the road surface move into the market (already successfully demonstrated in buses), and if and when lithium batteries are substituted by super-capacitors. So companies like Tesla can carry on making their own high-spec electric cars/vans/lorries but also flourish in a parallel market selling chassis with built-in drives to other companies who just need to put a decent cabin on top. It’s good strategy to see competitors as a potential market. Co-opetition works too.

This could be devastating to most of the big car manufacturers. Where will their market differential lie? Basic everyday markets could use the standardized chassis. How could they differentiate a high performance car when Tesla already offer ones that go 0-60 in under 3 seconds? The various electronics and AI systems will not compete only with Tesla but with all the big IT companies who also see roles in these markets: Apple, Sony, Google already but likely Samsung, LG, Microsoft and Amazon following soon.

It is possible that some existing car manufacturers will adapt just fine. They’ve known for many years that this future was coming and those with good strategies will cope. It is very likely though that some won’t cope and that very many jobs will be lost from the existing vehicle manufacturing industry, already bleeding jobs thanks to automation. It’s certainly not an industry I’d want to invest in for a decade or so until the weaker players have been removed from the field.

The main uncertainty that remains is whether the new industry goes the self-driving vehicle route, with lots of expensive sensors and IT in every vehicle, or the dumb pod/smart infrastructure route, with cheap cabins and simple chassis powered and navigated by the infrastructure. The latter could be much cheaper in urban areas, while the former would be better outside towns. My guess is that in the far future, we’ll have both, with self-driving vehicles outside urban areas, and pod systems inside urban areas (self-driving vehicles can easily be made downwards compatible so that they can behave like pods when in town).

AI could use killer drone swarms to attack people while taking out networks

In 1987 I discovered a whole class of security attacks that could knock out networks, which I called correlated traffic attacks, creating particular patterns of data packet arrivals from particular sources at particular times or intervals. We simulated two examples to successfully verify the problem. One example was protocol resonance. I demonstrated that it was possible to push a system into a gross overload state with a single call, by spacing the packets precise intervals apart. Their arrival caused a strong resonance in the bandwidth allocation algorithms and the result was that network capacity was instantaneously reduced by around 70%. Another example was information waves, whereby a single piece of information appearing at a particular point could, by its interaction with particular apps on mobile devices (the assumption was financially relevant data that would trigger AI on the devices to start requesting voluminous data, triggering a highly correlated wave of responses, using up bandwidth and throwing the network into overload, very likely crashing due to initiation of rarely used software. When calls couldn’t get through, the devices would wait until the network recovered, then they would all simultaneously detect recovery and simultaneously try again, killing the net again, and again, until people were asked to turn  their devices off and on again, thereby bringing randomness back into the system. Both of these examples could knock out certain kinds of networks, but they are just two of an infinite set of possibilities in the correlated traffic attack class.

Adversarial AI pits one AI against another, trying things at random or making small modifications until a particular situation is achieved, such as the second AI accepting an image is acceptable. It is possible, though I don’t believe it has been achieved yet, to use the technique to simulate a wide range of correlated traffic situations, seeing which ones achieve network resonance or overloads, which trigger particular desired responses from network management or control systems, via interactions with the network and its protocols, commonly resident apps on mobile devices or computer operating systems.

Activists and researchers are already well aware that adversarial AI can be used to find vulnerabilities in face recognition systems and thereby prevent recognition, or to deceive autonomous car AI into seeing fantasy objects or not seeing real ones. As Noel Sharkey, the robotics expert, has been tweeting today, it will be possible to use adversarial AI to corrupt recognition systems used by killer drones, potentially to cause them to attack their controllers or innocents instead of their intended targets. I have to agree with him. But linking that corruption to the whole extended field of correlated traffic attacks extends the range of mechanisms that can be used greatly. It will be possible to exploit highly obscured interactions between network physical architecture, protocols and operating systems, network management, app interactions, and the entire sensor/IoT ecosystem, as well as software and AI systems using it. It is impossible to check all possible interactions, so no absolute defence is possible, but adversarial AI with enough compute power could randomly explore across these multiple dimensions, stumble across regions of vulnerability and drill down until grand vulnerabilities are found.

This could further be linked to apps used as highly invisible Trojans, offering high attractiveness to users with no apparent side effects, quietly gathering data to help identify potential targets, and simply waiting for a particular situation or command before signalling to the attacking system.

A future activist or terrorist group or rogue state could use such tools to make a multidimensional attack. It could initiate an attack, using its own apps to identify and locate targets, control large swarms of killer drones or robots to attack them, simultaneously executing a cyberattack that knocks out selected parts of the network, crashing or killing computers and infrastructure. The vast bulk of this could be developed, tested and refined offline, using simulation and adversarial AI approaches to discover vulnerabilities and optimise exploits.

There is already debate about killer drones, mainly whether we should permit them and in what circumstances, but activists and rogue states won’t care about rules. Millions of engineers are technically able to build such things and some are not on your side. It is reasonable to expect that freely available AI tools will be used in such ways, using their intelligence to design, refine, initiate and control attacks using killer drones, robots and self-driving cars to harm us, while corrupting systems and infrastructure that protect us.

Worrying, especially since the capability is arriving just as everyone is starting to consider civil war.

 

 

The future for women, pdf version

It is several years since my last post on the future as it will affect women so here is my new version as a pdf presentation:

Women and the Future

With automation driving us towards UBI, we should consider a culture tax

Regardless of party politics, most people want a future where everyone has enough to live a dignified and comfortable life. To make that possible, we need to tweak a few things.

Universal Basic Income

I suggested a long time ago that in the far future we could afford a basic income for all, without any means testing on it, so that everyone has an income at a level they can live on. It turned out I wasn’t the only one thinking that and many others since have adopted the idea too, under the now usual terms Universal Basic Income or the Citizen Wage. The idea may be old, but the figures are rarely discussed. It is harder than it sounds and being a nice idea doesn’t ensure  economic feasibility.

No means testing means very little admin is needed, saving the estimated 30% wasted on admin costs today. Then wages could go on top, so that everyone is still encouraged to work, and then all income from all sources is totalled and taxed appropriately. It is a nice idea.

The difference between figures between parties would be relatively minor so let’s ignore party politics. In today’s money, it would be great if everyone could have, say, £30k a year as a state benefit, then earn whatever they can on top. £30k is around today’s average wage. It doesn’t make you rich, but you can live on it so nobody would be poor in any sensible sense of the word. With everyone economically provided for and able to lead comfortable and dignified lives, it would be a utopia compared to today. Sadly, it can’t work with those figures yet. 65,000,000 x £30,000 = £1,950Bn . The UK economy isn’t big enough. The state only gets to control part of GDP and out of that reduced budget it also has its other costs of providing health, education, defence etc, so the amount that could be dished out to everyone on this basis is therefore a lot smaller than 30k. Even if the state were to take 75% of GDP and spend most of it on the basic income, £10k per person would be pushing it. So a couple would struggle to afford even the most basic lifestyle, and single people would really struggle. Some people would still need additional help, and that reduces the pool left to pay the basic allowance still further. Also, if the state takes 75% of GDP, only 25% is left for everything else, so salaries would be flat, reducing the incentive to work, while investment and entrepreneurial activity are starved of both resources and incentive. It simply wouldn’t work today.

Simple maths thus forces us to make compromises. Sharing resources reduces costs considerably. In a first revision, families might be given less for kids than for the adults, but what about groups of young adults sharing a big house? They may be adults but they also benefit from the same economy of shared resources. So maybe there should be a household limit, or a bedroom tax, or forms and means testing, and it mustn’t incentivize people living separately or house supply suffers. Anyway, it is already getting complicated and our original nice idea is in the bin. That’s why it is such a mess at the moment. There just isn’t enough money to make everyone comfortable without doing lots of allowances and testing and admin. We all want utopia, but we can’t afford it. Even the modest £30k-per-person utopia costs at least 3 times more than the UK can afford. Switzerland is richer per capita but even there they have rejected the idea.

However, if we can get back to the average 2.5% growth per year in real terms that used to apply pre-recession, and surely we can, it would only take 45 years to get there. That isn’t such a long time. We have hope that if we can get some better government than we have had of late, and are prepared to live with a little economic tweaking, we could achieve good quality of life for all in the second half of the century.

So I still really like the idea of a simple welfare system, providing a generous base level allowance to everyone, topped up by rewards of effort, but recognise that we in the UK will have to wait decades before we can afford to put that base level at anything like comfortable standards though other economies could afford it earlier.

Meanwhile, we need to tweak some other things to have any chance of getting there. I’ve commented often that pure capitalism would eventually lead to a machine-based economy, with the machine owners having more and more of the cash, and everyone else getting poorer, so the system will fail. Communism fails too. Thankfully much of the current drive in UBI thinking is coming from the big automation owners so it’s comforting to know that they seem to understand the alternative.

Capitalism works well when rewards are shared sensibly, it fails when wealth concentration is too high or when incentive is too low. Preserving the incentive to work and create is a mainly matter of setting tax levels well. Making sure that wealth doesn’t get concentrated too much needs a new kind of tax.

Culture tax

The solution I suggest is a culture tax. Culture in the widest sense.

When someone creates and builds a company, they don’t do so from a state of nothing. They currently take for granted all our accumulated knowledge and culture – trained workforce, access to infrastructure, machines, governance, administrative systems, markets, distribution systems and so on. They add just another tiny brick to what is already a huge and highly elaborate structure. They may invest heavily with their time and money but actually when  considered overall as part of the system their company inhabits, they only pay for a fraction of the things their company will use.

That accumulated knowledge, culture and infrastructure belongs to everyone, not just those who choose to use it. It is common land, free to use, today. Businesses might consider that this is what they pay taxes for already, but that isn’t explicit in the current system.

The big businesses that are currently avoiding paying UK taxes by paying overseas companies for intellectual property rights could be seen as trailblazing this approach. If they can understand and even justify the idea of paying another part of their company for IP or a franchise, why should they not pay the host country for its IP – access to the residents’ entire culture?

This kind of tax would provide the means needed to avoid too much concentration of wealth. A future businessman might still choose to use only software and machines instead of a human workforce to save costs, but levying taxes on use of  the cultural base that makes that possible allows a direct link between use of advanced technology and taxation. Sure, he might add a little extra insight or new knowledge, but would still have to pay the rest of society for access to its share of the cultural base, inherited from the previous generations, on which his company is based. The more he automates, the more sophisticated his use of the system, the more he cuts a human workforce out of his empire, the higher his taxation. Today a company pays for its telecoms service which pays for the network. It doesn’t pay explicitly for the true value of that network, the access to people and businesses, the common language, the business protocols, a legal system, banking, payments system, stable government, a currency, the education of the entire population that enables them to function as actual customers. The whole of society owns those, and could reasonably demand rent if the company is opting out of the old-fashioned payments mechanisms – paying fair taxes and employing people who pay taxes. Automate as much as you like, but you still must pay your share for access to the enormous value of human culture shared by us all, on which your company still totally depends.

Linking to technology use makes good sense. Future AI and robots could do a lot of work currently done by humans. A few people could own most of the productive economy. But they would be getting far more than their share of the cultural base, which belongs equally to everyone. In a village where one farmer owns all the sheep, other villagers would be right to ask for rent for their share of the commons if he wants to graze them there.

I feel confident that this extra tax would solve many of the problems associated with automation. We all equally own the country, its culture, laws, language, human knowledge (apart from current patents, trademarks etc. of course), its public infrastructure, not just businessmen. Everyone surely should have the right to be paid if someone else uses part of their share. A culture tax would provide a fair ethical basis to demand the taxes needed to pay the Universal basic Income so that all may prosper from the coming automation.

The extra culture tax would not magically make the economy bigger, though automation may well increase it a lot. The tax would ensure that wealth is fairly shared. Culture tax/UBI duality is a useful tool to be used by future governments to make it possible to keep capitalism sustainable, preventing its collapse, preserving incentive while fairly distributing reward. Without such a tax, capitalism simply may not survive.

Will urbanization continue or will we soon reach peak city?

For a long time, people have been moving from countryside into cities. The conventional futurist assumption is that this trend will continue, with many mega-cities, some with mega-buildings. I’ve consulted occasionally on future buildings and future cities from a technological angle, but I’ve never really challenged the assumption that urbanization will continue. It’s always good  to challenge our assumptions occasionally, as things can change quite rapidly.

There are forces in both directions. Let’s list those that support urbanisation first.

People are gregarious. They enjoy being with other people. They enjoy eating out and having coffees with friends. They like to go shopping. They enjoy cinemas and theatre and art galleries and museums. They still have workplaces. Many people want to live close to these facilities, where public transport is available or driving times are relatively short. There are exceptions of course, but these still generally apply.

Even though many people can and do work from home sometimes, most of them still go to work, where they actually meet colleagues, and this provides much-valued social contact, and in spite of recent social trends, still provides opportunities to meet new friends and partners. Similarly, they can and do talk to friends via social media or video calls, but still enjoy getting together for real.

Increasing population produces extra pressure on the environment, and governments often try to minimize it by restricting building on green field land. Developers are strongly encouraged to build on brown field sites as far as possible.

Now the case against.

Truly Immersive Interaction

Talking on the phone, even to a tiny video image, is less emotionally rich than being there with someone. It’s fine for chats in between physical meetings of course, but the need for richer interaction still requires ‘being there’. Augmented reality will soon bring headsets that provide high quality 3D life-sized images of the person, and some virtual reality kit will even allow analogs of physical interaction via smart gloves or body suits, making social comms a bit better. Further down the road, active skin will enable direct interaction with the peripheral nervous system to produce exactly the same nerve signals as an actual hug or handshake or kiss, while active contact lenses will provide the same resolution as your retina wherever you gaze. The long term is therefore communication which has the other person effectively right there with you, fully 3D, fully rendered to the capability of your eyes, so you won’t be able to tell they aren’t. If you shake hands or hug or kiss, you’ll feel it just the same as if they were there too. You will still know they are not actually there, so it will never be quite as emotionally rich as if they were, but it can get pretty close. Close enough perhaps that it won’t really matter to most people most of the time that it’s virtual.

In the same long term, many AIs will have highly convincing personalities, some will even have genuine emotions and be fully conscious. I blogged recently on how that might happen if you don’t believe it’s possible:

https://timeguide.wordpress.com/2018/06/04/biomimetic-insights-for-machine-consciousness/

None of the technology required for this is far away, and I believe a large IT company could produce conscious machines with almost human-level AI within a couple of years of starting the project. It won’t happen until they do, but when one starts trying seriously to do it, it really won’t be long. That means that as well as getting rich emotional interaction from other humans via networks, we’ll also get lots from AI, either in our homes, or on the cloud, and some will be in robots in our homes too.

This adds up to a strong reduction in the need to live in a city for social reasons.

Going to cinemas, theatre, shopping etc will also all benefit from this truly immersive interaction. As well as that, activities that already take place in the home, such as gaming will also advance greatly into more emotionally and sensory intensive experiences, along with much enhanced virtual tourism and virtual world tourism, virtual clubbing & pubbing, which barely even exist yet but could become major activities in the future.

Socially inclusive self-driving cars

Some people have very little social interaction because they can’t drive and don’t live close to public transport stops. In some rural areas, buses may only pass a stop once a week. Our primitive 20th century public transport systems thus unforgivably exclude a great many people from social inclusion, even though the technology needed to solve that has existed for many years.  Leftist value systems that much prefer people who live in towns or close to frequent public transport over everyone else must take a lot of the blame for the current epidemic of loneliness. It is unreasonable to expect those value systems to be replaced by more humane and equitable ones any time soon, but thankfully self-driving cars will bypass politicians and bureaucrats and provide transport for everyone. The ‘little old lady’ who can’t walk half a mile to wait 20 minutes in freezing rain for an uncomfortable bus can instead just ask her AI to order a car and it will pick her up at her front door and take her to exactly where she wants to go, then do the same for her return home whenever she wants. Once private sector firms like Uber provide cheap self-driving cars, they will be quickly followed by other companies, and later by public transport providers. Redundant buses may finally become extinct, replaced by better socially inclusive transport, large fleets of self-driving or driverless vehicles. People will be able to live anywhere and still be involved in society. As attendance at social events improves, so they will become feasible even in small communities, so there will be less need to go into a town to find one. Even political involvement might increase. Loneliness will decline as social involvement increases, and we’ll see many other social problems decline too.

Distribution drones

We hear a lot about upcoming redundancy caused by AI, but far less about the upside. AI might mean someone is no longer needed in an office, but it also makes it easier to set up a company and run it, taking what used to be just a hobby and making it into a small business. Much of the everyday admin and logistics can be automated Many who would never describe themselves as entrepreneurs might soon be making things and selling them from home and this AI-enabled home commerce will bring in the craft society. One of the big problems is getting a product to the customer. Postal services and couriers are usually expensive and very likely to lose or damage items. Protecting objects from such damage may require much time and expense packing it. Even if objects are delivered, there may be potential fraud with no-payers. Instead of this antiquated inefficient and expensive system, drone delivery could collect an object and take it to a local customer with minimal hassle and expense. Block-chain enables smart contracts that can be created and managed by AI and can directly link delivery to payment, with fully verified interaction video if necessary. If one happens, the other happens. A customer might return a damaged object, but at least can’t keep it and deny receipt. Longer distance delivery can still use cheap drone pickup to take packages to local logistics centers in smart crates with fully block-chained g-force and location detectors that can prove exactly who damaged it and where. Drones could be of any size, and of course self-driving cars or pods can easily fill the role too if smaller autonomous drones are inappropriate.

Better 3D printing technology will help to accelerate the craft economy, making it easier to do crafts by upskilling people and filling in some of their skill gaps. Someone with visual creativity but low manual skill might benefit greatly from AI model creation and 3D printer manufacture, followed by further AI assistance in marketing, selling and distribution. 3D printing might also reduce the need to go to town to buy some things.

Less shopping in high street

This is already obvious. Online shopping will continue to become a more personalized and satisfying experience, smarter, with faster delivery and easier returns, while high street decline accelerates. Every new wave of technology makes online better, and high street stores seem unable or unwilling to compete, in spite of my wonderful ‘6s guide’:

https://timeguide.wordpress.com/2013/01/16/the-future-of-high-street-survival-the-6s-guide/

Those that are more agile still suffer decline of shopper numbers as the big stores fail to attract them so even smart stores will find it harder to survive.

Improving agriculture

Farming technology has doubled the amount of food production per hectare in the last few decades. That may happen again by mid-century. Meanwhile, the trend is towards higher vegetable and lower meat consumption. Even with an increased population, less land will be needed to grow our food. As well as reducing the need to protect green belts, that will also allow some of our countryside to be put under better environmental stewardship programs, returning much of it to managed nature. What countryside we have will be healthier and prettier, and people will be drawn to it more.

Improving social engineering

Some objections to green-field building can be reduced by making better use of available land. Large numbers of new homes are needed and they will certainly need some green field to be used, but given the factors already listed above, a larger number of smaller communities might be better approach. Amazingly, in spite of decades of dating technology proving that people can be matched up easily using AI, there is still no obvious use of similar technology to establish new communities by blending together people who are likely to form effective communities. Surely it must be feasible to advertise a new community building program that wants certain kinds of people in it – even an Australian style points system might work sometimes. Unless sociologists have done nothing for the past decades, they must surely know what types of people work well together by now? If the right people live close to each other, social involvement will be high, loneliness low, health improved, care costs minimized, the need for longer distance travel reduced and environmental impact minimized. How hard can it be?

Improving building technology such as 3D printing and robotics will allow more rapid construction, so that when people are ready and willing to move, property suited to them can be available soon.

Lifestyle changes also mean that homes don’t need to be as big. A phone today does what used to need half a living room of technology and space. With wall-hung displays and augmented reality, decor can be partly virtual, and even a 450 sq ft apartment is fine as a starter place, half as big as was needed a few decades ago, and that could be 3D printed and kitted out in a few days.

Even demographic changes favor smaller communities. As wealth increases, people have smaller families, i.e fewer kids. That means fewer years doing the school run, so less travel, less need to be in a town. Smaller schools in smaller communities can still access specialist lessons via the net.

Increasing wealth also encourages and enables people to a higher quality of life. People who used to live in a crowded city street might prefer a more peaceful and spacious existence in a more rural setting and will increasingly be able to afford to move. Short term millennial frustrations with property prices won’t last, as typical 2.5% annual growth more than doubles wealth by 2050 (though automation and its assorted consequences will impact on the distribution of that wealth).

Off-grid technology

Whereas one of the main reasons to live in urban areas was easy access to telecomms, energy and water supply and sewerage infrastructure, all of these can now be achieved off-grid. Mobile networks provide even broadband access to networks. Solar or wind provide easy energy supply. Water can be harvested out of the air even in arid areas (http://www.dailymail.co.uk/sciencetech/article-5840997/The-solar-powered-humidity-harvester-suck-drinkable-water-AIR.html) and human and pet waste can be used as biomass for energy supply too, leaving fertilizer as residue.

There are also huge reasons that people won’t want to live in cities, and they will also cause deurbansisation.

The biggest by far in the problem of epidemics. As antibiotic resistance increases, disease will be a bigger problem. We may find good antibiotics alternatives but we may not. If not, then we may see some large cities where disease runs rampant and kills hundreds of thousands of people, perhaps even millions. Many scientists have listed pandemics among their top ten threats facing humanity. Obviously, being in a large city will incur a higher risk of becoming a victim, so once one or two incidents have occurred, many people will look for options to leave cities everywhere. Linked to this is bioterrorism, where the disease is deliberate, perhaps created in a garden shed by someone who learned the craft in one of today’s bio-hacking clubs. Disease might be aimed at a particular race, gender or lifestyle group or it may simply be designed to be as contagious and lethal as possible to everyone.

I’m still not saying we won’t have lots of people living in cities. I am saying that more people will feel less need to live in cities and will instead be able to find a small community where they can be happier in the countryside. Consequently, many will move out of cities, back to more rural living in smaller, friendlier communities that improving technology makes even more effective.

Urbanization will slow down, and may well go into reverse. We may reach peak city soon.

 

 

AI that talks to us could quickly become problematic

Google’s making the news again adding evidence to the unfortunate stereotype of the autistic IT nerd that barely understands normal people, and they have therefore been astonished at the backlash that normal people would all easily have predicted. (I’m autistic and work in IT mostly too, and am well used to the stereotype it so it doesn’t bother me, in fact it is a sort of ‘get out of social interactions free’ card). Last time it was Google Glass, where it apparently didn’t occur to them that people may not want other people videoing them without consent in pubs and changing rooms. This time it is Google Duplex, that makes phone calls on your behalf to arrange appointment using voice that is almost indistinguishable from normal humans. You could save time making an appointment with a hairdresser apparently, so the Googlanders decided it must be a brilliant breakthrough, and expected everyone to agree. They didn’t.

Some of the objections have been about ethics: e.g. An AI should not present itself as human – Humans have rights and dignity and deserve respectful interactions with other people, but an AI doesn’t and should not masquerade as human to acquire such privilege without knowledge of the other party and their consent.

I would be more offended by the presumed attitude of the user. If someone thinks they are so much better then me that they can demand my time and attention without the expense of any of their own, delegating instead to a few microseconds of processing time in a server farm somewhere, I’ll treat them with the contempt they deserve. My response will not be favourable. I am already highly irritated by the NHS using simple voice interaction messaging to check I will attend a hospital appointment. The fact that my health is on the line and notices at surgeries say I will be banned if I complain on social media is sufficient blackmail to ensure my compliance, but it still comes at the expense of my respect and goodwill. AI-backed voice interaction with better voice wouldn’t be any better, and if it asking for more interaction such as actually booking an appointment, it would be extremely annoying.

In any case, most people don’t speak in fully formed grammatically and logically correct sentences. If you listen carefully to everyday chat, a lot of sentences are poorly pronounced, incomplete, jumbled, full of ums and er’s, likes and they require a great deal of cooperation by the listener to make any sense at all. They also wander off topic frequently. People don’t stick to a rigid vocabulary list or lists of nicely selected sentences.  Lots of preamble and verbal meandering is likely in a response that is highly likely to add ambiguity. The example used in a demo, “I’d like to make a hairdressing appointment for a client” sounds fine until you factor in normal everyday humanity. A busy hairdresser or a lazy receptionist is not necessarily going to cooperate fully. “what do you mean, client?”, “404 not found”, “piss off google”, “oh FFS, not another bloody computer”, “we don’t do hairdressing, we do haircuts”, “why can’t your ‘client’ call themselves then?” and a million other responses are more likely than “what time would you like?”

Suppose though that it eventually gets accepted by society. First, call centers beyond the jurisdiction of your nuisance call blocker authority will incessantly call you at all hours asking or telling you all sorts of things, wasting huge amounts of your time and reducing quality of life. Voice spam from humans in call centers is bad enough. If the owners can multiply productivity by 1000 by using AI instead of people, the result is predictable.

We’ve seen the conspicuous political use of social media AI already. Facebook might have allowed companies to use very limited and inaccurate knowledge of you to target ads or articles that you probably didn’t look at. Voice interaction would be different. It uses a richer emotional connection that text or graphics on a screen. Google knows a lot about you too, but it will know a lot more soon. These big IT companies are also playing with tech to log you on easily to sites without passwords. Some gadgets that might be involved might be worn, such as watches or bracelets or rings. They can pick up signals to identify you, but they can also check emotional states such as stress level. Voice gives away emotion too. AI can already tell better then almost all people whether you are telling the truth or lying or hiding something. Tech such as iris scans can also tell emotional states, as well as give health clues. Simple photos can reveal your age quite accurately to AI, (check out how-old.net).  The AI voice sounds human, but it is better then even your best friends at guessing your age, your stress and other emotions, your health, whether you are telling the truth or not, and it knows far more about what you like and dislike and what you really do online than anyone you know, including you. It knows a lot of your intimate secrets. It sounds human, but its nearest human equivalent was probably Machiavelli. That’s who will soon be on the other side of the call, not some dumb chatbot. Now re-calculate political interference, and factor in the political leaning and social engineering desires of the companies providing the tools. Google and Facebook and the others are very far from politically neutral. One presidential candidate might get full cooperation, assistance and convenient looking the other way, while their opponent might meet rejection and citation of the official rules on non-interference. Campaigns on social issues will also be amplified by AI coupled to voice interaction. I looked at some related issue in a previous blog on fake AI (i.e. fake news type issues): https://timeguide.wordpress.com/2017/11/16/fake-ai/

I could but won’t write a blog on how this tech could couple well to sexbots to help out incels. It may actually have some genuine uses in providing synthetic companionship for lonely people, or helping or encouraging them in real social interactions with real people. It will certainly have some uses in gaming and chatbot game interaction.

We are not very far from computers that are smarter then people across a very wide spectrum, and probably not very far from conscious machines that have superhuman intelligence. If we can’t even rely on IT companies to understand likely consequences of such obvious stuff as Duplex before thy push it, how can we trust them in other upcoming areas of AI development, or even closer term techs with less obvious consequences? We simply can’t!

There are certainly a few such areas where such technology might help us but most are minor and the rest don’t need any deception, but they all come at great cost or real social and political risk, as well as more abstract risks such as threats to human dignity and other ethical issues. I haven’t give this much thought yet and I am sure there must be very many other consequences I have not touched on yet. Google should do more thinking before they release stuff. Technology is becoming very powerful, but we all know that great power comes with great responsibility, and since most people aren’t engineers so can’t think through all the potential technology interactions and consequences, engineers such as Google’s must act more responsibly. I had hoped they’d started, and they said they had, but this is not evidence of that.

 

Futurist memories: The leisure society and the black box economy

Things don’t always change as fast as we think. This is a piece I wrote in 1994 looking forward to a fully automated ‘black box economy, a fly-by-wire society. Not much I’d change if I were writing it new today. Here:

The black box economy is a strictly theoretical possibility, but may result where machines gradually take over more and more roles until the whole economy is run by machines, with everything automated. People could be gradually displaced by intelligent systems, robots and automated machinery. If this were to proceed to the ultimate conclusion, we could have a system with the same or even greater output as the original society, but with no people involved. The manufacturing process could thus become a ‘black box’. Such a system would be so machine controlled that humans would not easily be able to pick up the pieces if it crashed – they would simply not understand how it works, or could not control it. It would be a fly-by-wire society.

The human effort could be reduced to simple requests. When you want a new television, a robot might come and collect the old one, recycling the materials and bringing you a new one. Since no people need be involved and the whole automated system could be entirely self-maintaining and self-sufficient there need be no costs. This concept may be equally applicable in other sectors, such as services and information – ultimately producing more leisure time.

Although such a system is theoretically possible – energy is free in principle, and resources are ultimately a function of energy availability – it is unlikely to go quite this far. We may go some way along this road, but there will always be some jobs that we don’t want to automate, so some people may still work. Certainly, far fewer people would need to work in such a system, and other people could spend their time in more enjoyable pursuits, or in voluntary work. This could be the leisure economy we were promised long ago. Just because futurists predicted it long ago and it hasn’t happened yet does not mean it never will. Some people would consider it Utopian, while others possibly a nightmare, it’s just a matter of taste.

AIs of a feather flocking together to create global instability

Hawking and Musk have created a lot of media impact with their warnings about AI, so although terminator scenarios resulting from machine consciousness have been discussed, as have more mundane use of non-conscious autonomous weapon systems, it’s worth noting that I haven’t yet heard them mention one major category of risks from AI – emergence. AI risks have been discussed frequently since the 1970s, and in the 1990s a lot of work was done in the AI community on emergence. Complex emergent patterns of behavior often result from interactions between entities driven by simple algorithms. Genetic algorithms were demonstrated to produce evolution, simple neighbor-interaction rules were derived to illustrate flocking behaviors that make lovely screen saver effects. Cellular automata were played with. In BT we invented ways of self-organizing networks and FPGAs, played with mechanism that could be used for evolution and consciousness, demonstrated managing networks via ANTs – autonomous network telephers, using smart packets that would run up and down wires sorting things out all by themselves. In 1987 discovered a whole class of ways of bringing down networks via network resonance, information waves and their much larger class of correlated traffic – still unexploited by hackers apart from simple DOS attacks. These ideas have slowly evolved since, and some have made it into industry or hacker toolkits, but we don’t seem to be joining the dots as far as risks go.

I read an amusing article this morning by an ex-motoring-editor who was declined insurance because the AI systems used by insurance companies had labelled him as high risk because he maybe associated with people like Clarkson. Actually, he had no idea why, but that was his broker’s theory of how it might have happened. It’s a good article, well written and covers quite a few of the dangers of allowing computers to take control.

http://www.dailymail.co.uk/sciencetech/article-5310031/Evidence-robots-acquiring-racial-class-prejudices.html

The article suggested how AIs in different companies might all come to similar conclusions about people or places or trends or patterns in a nice tidy positive feedback loop. That’s exactly the sort of thing that can drive information waves, which I demonstrated in 1987 can bring down an entire network in less than 3 milliseconds, in such a way that it would continue to crash many times when restarted. That isn’t intended by the algorithms, which individually ought to make good decisions, but when interacting with one another, create the emergent phenomenon.  Automated dealing systems are already pretty well understood in this regard and mechanisms prevent frequent stock market collapses, but that is only one specific type of behavior in one industry that is protected. There do not seem to be any industry-wide mechanisms to prevent the rest of this infinite class of problems from affecting any or all of the rest, simultaneously.

As we create ever more deep learning neural networks, that essentially teach themselves from huge data pools, human understanding of their ‘mindsets’ decreases. They make decisions using algorithms that are understood at a code level, but the massive matrix of derived knowledge they create from all the data they receive becomes highly opaque. Often, even usually, nobody quite knows how a decision is made. That’s bad enough in a standalone system, but when many such systems are connected, produced and owned and run by diverse companies with diverse thinking, the scope for destructive forms of emergence increases geometrically.

One result could be gridlock. Systems fed with a single new piece of data could crash. My 3 millisecond result in 1987 would still stand since network latency is the prime limiter. The first AI receives it, alters its mindset accordingly, processes it, makes a decision and interacts with a second AI. This second one might have different ‘prejudice’ so makes its own decision based on different criteria, and refuses to respond the way intended. A 3rd one looks at the 2nd’s decision and takes that as evidence that there might be an issue, and with its risk-averse mindset, also refuse to act, and that inaction spreads through the entire network in milliseconds. Since the 1st AI thinks the data is all fine and it should have gone ahead, it now interprets the inaction of the others as evidence that that type of data is somehow ‘wrong’ so itself refuses to process any further of that type, whether from its own operators or other parts of the system. So it essentially adds its own outputs to the bad feeling and the entire system falls into sulk mode. As one part of infrastructure starts to shut down, that infects other connected parts and our entire IT could fall into sulk mode – entire global infrastructure. Since nobody knows how it all works, or what has caused the shutdown, it might be extremely hard to recover.

Another possible result is a direct information wave, almost certainly a piece of fake news. Imagine our IT world in 5 years time, with all these super-smart AIs super-connected. A piece of fake news says a nuke has just been launched somewhere. Stocks will obviously decline, whatever the circumstances, so as the news spreads, everyone’s AIs will take it on themselves to start selling shares before the inevitable collapse, triggering a collapse, except it won’t because the markets won’t let that happen. BUT… The wave does spread, and all those individual AIs want to dispose of those shares, or at least find out what’s happening, so they all start sending messages to one another, exchanging data, trying to find what’s going on. That’s the information wave. They can’t sell shares of find out, because the network is going into overload, so they try even harder and force it into severe overload. So it falls over. When it comes back online, they all try again, crashing it again, and so on.

Another potential result is smartass AI. There is always some prat somewhere who sees an opportunity to take advantage and ruins if for everyone else by doing something like exploiting a small loophole in the law, or in this case, most likely, a prejudice our smartass AI has discovered in some other AI that means it can be taken advantage of by doing x, y, or z. Since nobody quite knows how any of their AIs are making their decisions because their mindsets ate too big and too complex, it will be very hard to identify what is going on. Some really unusual behavior is corrupting the system because some AI is going rogue somewhere somehow, but which one, where, how?

That one brings us back to fake news. That will very soon infect AI systems with their own varieties of fake news. Complex networks of AIs will have many of the same problems we are seeing in human social networks. An AI could become a troll just the same as a human, deliberately winding others up to generate attention of drive a change of some parameter – any parameter – in its own favour. Activist AIs will happen due to people making them to push human activist causes, but they will also do it all by themselves. Their analysis of the system will sometimes show them that a good way to get a good result is to cause problems elsewhere.

Then there’s climate change, weather, storms, tsunamis. I don’t mean real ones, I mean the system wide result of tiny interactions of tiny waves and currents of data and knowledge in neural nets. Tiny effects in one small part of a system can interact in unforeseen ways with other parts of other systems nearby, creating maybe a breeze, which interacts with breezes in nearby regions to create hurricanes. I think that’s a reasonable analogy. Chaos applies to neural net societies just as it does to climate, and 50 year waves equivalents will cause equivalent havoc in IT.

I won’t go on with more examples, long blogs are awful to read. None of these requires any self-awareness, sentience, consciousness, call it what you will. All of these can easily happen through simple interactions of fairly trivial AI deep learning nets. The level of interconnection already sounds like it may already be becoming vulnerable to such emergence effects. Soon it definitely will be. Musk and Hawking have at least joined the party and they’ll think more and more deeply in coming months. Zuckerberg apparently doesn’t believe in AI threats but now accepts the problems social media is causing. Sorry Zuck, but the kind of AI you’re company is messing with will also be subject to its own kinds of social media issues, not just in its trivial decisions on what to post or block, but actual inter-AI socializing issues. It might not try to eliminate humanity, but if it brings all of our IT to a halt and prevents rapid recovery, we’re still screwed.

 

Artificial muscles using folded graphene

Folded Graphene Concept

Two years ago I wrote a blog on future hosiery where I very briefly mentioned the idea of using folded graphene as synthetic muscles:

https://timeguide.wordpress.com/2015/11/16/the-future-of-nylon-ladder-free-hosiery/

Although I’ve since mentioned it to dozens of journalists, none have picked up on it, so now that soft robotics and artificial muscles are in the news, I guess it’s about time I wrote it up myself, before someone else claims the idea. I don’t want to see an MIT article about how they have just invented it.

The above pic gives the general idea. Graphene comes in insulating or conductive forms, so it will be possible to make sheets covered with tiny conducting graphene electromagnet coils that can be switched individually to either polarity and generate strong magnetic forces that pull or push as required. That makes it ideal for a synthetic muscle, given the potential scale. With 1.5nm-thick layers that could be anything from sub-micron up to metres wide, this will allow thin fibres and yarns to make muscles or shape change fabrics all the way up to springs or cherry-picker style platforms, using many such structures. Current can be switched on and off or reversed very rapidly, to make continuous forces or vibrations, with frequency response depending on application – engineering can use whatever scales are needed. Natural muscles are limited to 250Hz, but graphene synthetic muscles should be able to go to MHz.

Uses vary from high-rise rescue, through construction and maintenance, to space launch. Since the forces are entirely electromagnetic, they could be switched very rapidly to respond to any buckling, offering high stabilisation.

The extreme difference in dimensions between folded and opened state mean that an extremely thin force mat made up of many of these cherry-picker structures could be made to fill almost any space and apply force to it. One application that springs to mind is rescues, such as after earthquakes have caused buildings to collapse. A sheet could quickly apply pressure to prize apart pieces of rubble regardless of size and orientation. It could alternatively be used for systems for rescuing people from tall buildings, fracking or many other applications.

It would be possible to make large membranes for a wide variety of purposes that can change shape and thickness at any point, very rapidly.

One such use is a ‘jellyfish’, complete with stinging cells that could travel around in even very thin atmospheres all by itself. Upper surfaces could harvest solar power to power compression waves that create thrust. This offers use for space exploration on other planets, but also has uses on Earth of course, from surveillance and power generation, through missile defense systems or self-positioning parachutes that may be used for my other invention, the Pythagoras Sling. That allows a totally rocket-free space launch capability with rapid re-use.

Much thinner membranes are also possible, as shown here, especially suited for rapid deployment missile defense systems:

Also particularly suited to space exploration o other planets or moons, is the worm, often cited for such purposes. This could easily be constructed using folded graphene, and again for rescue or military use, could come with assorted tools or lethal weapons built in.

A larger scale cherry-picker style build could make ejector seats, elevation platforms or winches, either pushing or pulling a payload – each has its merits for particular types of application.  Expansion or contraction could be extremely rapid.

An extreme form for space launch is the zip-winch, below. With many layers just 1.5nm thick, expanding to 20cm for each such layer, a 1000km winch cable could accelerate a payload rapidly as it compresses to just 7.5mm thick!

Very many more configurations and uses are feasible of course, this blog just gives a few ideas. I’ll finish with a highlight I didn’t have time to draw up yet: small particles could be made housing a short length of folded graphene. Since individual magnets can be addressed and controlled, that enables magnetic powders with particles that can change both their shape and the magnetism of individual coils. Precision magnetic fields is one application, shape changing magnets another. The most exciting though is that this allows a whole new engineering field, mixing hydraulics with precision magnetics and shape changing. The powder can even create its own chambers, pistons, pumps and so on. Electromagnetic thrusters for ships are already out there, and those same thrust mechanisms could be used to manipulate powder particles too, but this allows for completely dry hydraulics, with particles that can individually behave actively or  passively.

Fun!

 

 

The age of dignity

I just watched a short video of robots doing fetch and carry jobs in an Alibaba distribution centre:

http://uk.businessinsider.com/inside-alibaba-smart-warehouse-robots-70-per-cent-work-technology-logistics-2017-9

There are numerous videos of robots in various companies doing tasks that used to be done by people. In most cases those tasks were dull, menial, drudgery tasks that treated people as machines. Machines should rightly do those tasks. In partnership with robots, AI is also replacing some tasks that used to be done by people. Many are worried about increasing redundancy but I’m not; I see a better world. People should instead be up-skilled by proper uses of AI and robotics and enabled to do work that is more rewarding and treats them with dignity. People should do work that uses their human skills in ways that they find rewarding and fulfilling. People should not have to do work they find boring or demeaning just because they have to earn money. They should be able to smile at work and rest at the end of the day knowing that they have helped others or made the world a better place. If we use AI, robots and people in the right ways, we can build that world.

Take a worker in a call centre. Automation has already replaced humans in most simple transactions like paying a bill, checking a balance or registering a new credit card. It is hard to imagine that anyone ever enjoyed doing that as their job. Now, call centre workers mostly help people in ways that allow them to use their personalities and interpersonal skills, being helpful and pleasant instead of just typing data into a keyboard. It is more enjoyable and fulfilling for the caller, and presumably for the worker too, knowing they genuinely helped someone’s day go a little better. I just renewed my car insurance. I phoned up to cancel the existing policy because it had increased in price too much. The guy at the other end of the call was very pleasant and helpful and met me half way on the price difference, so I ended up staying for another year. His company is a little richer, I was a happier customer, and he had a pleasant interaction instead of having to put up with an irate customer and also the job satisfaction from having converted a customer intending to leave into one happy to stay. The AI at his end presumably gave him the information he needed and the limits of discount he was permitted to offer. Success. In billions of routine transactions like that, the world becomes a little happier and just as important, a little more dignified. There is more dignity in helping someone than in pushing a button.

Almost always, when AI enters a situation, it replaces individual tasks that used to take precious time and that were not very interesting to do. Every time you google something, a few microseconds of AI saves you half a day in a library and all those half days add up to a lot of extra time every year for meeting colleagues, human interactions, learning new skills and knowledge or even relaxing. You become more human and less of a machine. Your self-actualisation almost certainly increases in one way or another and you become a slightly better person.

There will soon be many factories and distribution centres that have few or no people at all, and that’s fine. It reduces the costs of making material goods so average standard of living can increase. A black box economy that has automated mines or recycling plants extracting raw materials and uses automated power plants to convert them into high quality but cheap goods adds to the total work available to add value; in other words it increases the size of the economy. Robots can make other robots and together with AI, they could make all we need, do all the fetching and carrying, tidying up, keeping it all working, acting as willing servants in every role we want them in. With greater economic wealth and properly organised taxation, which will require substantial change from today, people could be freed to do whatever fulfills them. Automation increases average standard of living while liberating people to do human interaction jobs, crafts, sports, entertainment, leading, inspiring, teaching, persuading, caring and so on, creating a care economy. 

Each person knows what they are good at, what they enjoy. With AI and robot assistance, they can more easily make that their everyday activity. AI could do their company set-up, admin, billing, payments, tax, payroll – all the crap that makes being an entrepreneur a pain in the ass and stops many people pursuing their dreams.  Meanwhile they would do that above a very generous welfare net. Many of us now are talking about the concept of universal basic income, or citizen wage. With ongoing economic growth at the average rate of the last few decades, the global economy will be between twice and three times as big as today in the 2050s. Western countries could pay every single citizen a basic wage equivalent to today’s average wage, and if they work or run a company, they can earn more.

We will have an age where material goods are high quality, work well and are cheap to buy, and recycled in due course to minimise environmental harm. Better materials, improved designs and techniques, higher efficiency and land productivity and better recycling will mean that people can live with higher standards of living in a healthier environment. With a generous universal basic income, they will not have to worry about paying their bills. And doing only work that they want to do that meets their self-actualisation needs, everyone can live a life of happiness and dignity.

Enough of the AI-redundancy alarmism. If we elect good leaders who understand the options ahead, we can build a better world, for everyone. We can make real the age of dignity.