Reverse engineering the brain is a very slow way to make a smart computer

The race is on to build conscious and smart computers and brain replicas. This article explains some of Markam’s approach. http://www.wired.com/wiredscience/2013/05/neurologist-markam-human-brain/all/

It is a nice project, and its aims are to make a working replica of the brain by reverse engineering it. That would work eventually, but it is slow and expensive and it is debatable how valuable it is as a goal.

Imagine if you want to make an aeroplane from scratch.  You could study birds and make extremely detailed reverse engineered mathematical models of the structures of individual feathers, and try to model all the stresses and airflows as the wing beats. Eventually you could make a good model of a wing, and by also looking at the electrics, feedbacks, nerves and muscles, you could eventually make some sort of control system that would essentially replicate a bird wing. Then you could scale it all up, look for other materials, experiment a bit and eventually you might make a big bird replica. Alternatively, you could look briefly at a bird and note the basic aerodynamics of a wing, note the use of lightweight and strong materials, then let it go. You don’t need any more from nature than that. The rest can be done by looking at ways of propelling the surface to create sufficient airflow and lift using the aerofoil, and ways to achieve the strength needed. The bird provides some basic insight, but it simply isn’t necessary to copy all a bird’s proprietary technology to fly.

Back to Markam. If the real goal is to reverse engineer the actual human brain and make a detailed replica or model of it, then fair enough. I wish him and his team, and their distributed helpers and affiliates every success with that. If the project goes well, and we can find insights to help with the hundreds of brain disorders and improve medicine, great. A few billion euros will have been well spent, especially given the waste of more billions of euros elsewhere on futile and counter-productive projects. Lots of people criticise his goal, and some of their arguments are nonsensical. It is a good project and for what it’s worth, I support it.

My only real objection is that a simulation of the brain will not think well and at best will be an extremely inefficient thinking machine. So if a goal is to achieve thought or intelligence, the project as described is barking up the wrong tree. If that isn’t a goal, so what? It still has the other uses.

A simulation can do many things. It can be used to follow through the consequences of an input if the system is sufficiently well modelled. A sufficiently detailed and accurate brain simulation could predict the impacts of a drug or behaviours resulting from certain mental processes. It could follow through the impacts and chain of events resulting from an electrical impulse  this finding out what the eventual result of that will be. It can therefore very inefficiently predict the result of thinking, but by using extremely high speed computation, it could in principle work out the end result of some thoughts. But it needs enormous detail and algorithmic precision to do that. I doubt it is achievable simply because of the volume of calculation needed.  Thinking properly requires consciousness and therefore emulation. A conscious circuit has to be built, not just modelled.

Consciousness is not the same as thinking. A simulation of the brain would not be conscious, even if it can work out the result of thoughts. It is the difference between printed music and played music. One is data, one is an experience. A simulation of all the processes going on inside a head will not generate any consciousness, only data. It could think, but not feel or experience.

Having made that important distinction, I still think that Markam’s approach will prove useful. It will generate many useful insights into the workings of the brain, and many of the processes nature uses to solve certain engineering problems. These insights and techniques can be used as input into other projects. Biomimetics is already proven as a useful tool in solving big problems. Looking at how the brain works will give us hints how to make a truly conscious, properly thinking machine. But just as with birds and airbuses, we can take ideas and inspiration from nature and then do it far better. No bird can carry the weight or fly as high or as fast as an aeroplane. No proper plane uses feathers or flaps its wings.

I wrote recently about how to make a conscious computer:

http://timeguide.wordpress.com/2013/02/15/how-to-make-a-conscious-computer/ and http://timeguide.wordpress.com/2013/02/18/how-smart-could-an-ai-become/

I still think that approach will work well, and it could be a decade faster than going Markam’s route. All the core technology needed to start making a conscious computer already exists today. With funding and some smart minds to set the process in motion, it could be done in a couple of years. The potential conscious and ultra-smart computer, properly harnessed, could do its research far faster than any human on Markam’s team. It could easily beat them to the goal of a replica brain. The converse is not true, Markam’s current approach would yield a conscious computer very slowly.

So while I fully applaud the effort and endorse the goals, changing the approach now could give far more bang for the buck, far faster.

Killing machines

There is rising concern about machines such as drones and battlefield robots that could soon be given the decision on whether to kill someone. Since I wrote this and first posted it a couple of weeks ago, the UN has put out their thoughts as the DM writes today:

http://www.dailymail.co.uk/news/article-2318713/U-N-report-warns-killer-robots-power-destroy-human-life.html 

At the moment, drones and robots are essentially just remote controlled devices and a human makes the important decisions. In the sense that a human uses them to dispense death from a distance, they aren’t all that different from a spear or a rifle apart from scale of destruction and the distance from which death can be dealt. Without consciousness, a missile is no different from a spear or bullet, nor is a remote controlled machine that it is launched from. It is the act of hitting the fire button that is most significant, but proximity is important too. If an operator is thousands of miles away and isn’t physically threatened, or perhaps has never even met people from the target population, other ethical issues start emerging. But those are ethical issues for the people, not the machine.

Adding artificial intelligence to let a machine to decide whether a human is to be killed or not isn’t difficult per se. If you don’t care about killing innocent people, it is pretty easy. It is only made difficult because civilised countries value human lives, and because they distinguish between combatants and civilians.

Personally, I don’t fully understand the distinction between combatants and soldiers. In wars, often combatants have no real choice but to fight or are conscripted, and they are usually told what to do, often by civilian politicians hiding in far away bunkers, with strong penalties for disobeying. If a country goes to war, on the basis of a democratic mandate, then surely everyone in the electorate is guilty, even pacifists, who accept the benefits of living in the host country but would prefer to avoid the costs. Children are the only innocents.

In my analysis, soldiers in a democratic country are public sector employees like any other, just doing a job on behalf of the electorate. But that depends to some degree on them keeping their personal integrity and human judgement. The many military who take pride in following orders could be thought of as being dehumanised and reduced to killing machines. Many would actually be proud to be thought of as killing machines. A soldier like that, who merely follow orders, deliberately abdicates human responsibility. Having access to the capability for good judgement, but refusing to use it, they reduce themselves to a lower moral level than a drone. At least a drone doesn’t know what it is doing.

On the other hand, disobeying a direct order may save soothe issues of conscience but invoke huge personal costs, anything from shaming and peer disapproval to execution. Balancing that is a personal matter, but it is the act of balancing it that is important, not necessarily the outcome. Giving some thought to the matter and wrestling at least a bit with conscience before doing it makes all the difference. That is something a drone can’t yet do.

So even at the start, the difference between a drone and at least some soldiers is not always as big as we might want it to be, for other soldiers it is huge. A killing machine is competing against a grey scale of judgement and morality, not a black and white equation. In those circumstances, in a military that highly values following orders, human judgement is already no longer an essential requirement at the front line. In that case, the leaders might set the drones into combat with a defined objective, the human decision already taken by them, the local judgement of who or what to kill assigned to adaptive AI, algorithms and sensor readings. For a military such as that, drones are no different to soldiers who do what they’re told.

However, if the distinction between combatant and civilian is required, then someone has to decide the relative value of different classes of lives. Then they either have to teach it to the machines so they can make the decision locally, or the costs of potential collateral damage from just killing anyone can be put into the equations at head office. Or thirdly, and most likely in practice, a compromise can be found where some judgement is made in advance and some locally. Finally, it is even possible for killing machines to make decisions on some easier cases and refer difficult ones to remote operators.

We live in an electronic age, with face recognition, friend or foe electronic ID, web searches, social networks, location and diaries, mobile phone signals and lots of other clues that might give some knowledge of a target and potential casualties. How important is it to kill or protect this particular individual or group, or take that particular objective? How many innocent lives are acceptable cost, and from which groups – how many babies, kids, adults, old people? Should physical attractiveness or the victim’s professions be considered? What about race or religion, or nationality, or sexuality, or anything else that could possibly be found out about the target before killing them? How much should people’s personal value be considered, or should everyone be treated equal at point of potential death? These are tough questions, but the means of getting hold of the date are improving fast and we will be forced to answer them. By the time truly intelligent drones will be capable of making human-like decisions, they may well know who they are killing.

In some ways this far future with a smart or even conscious drone or robot making informed decisions before killing people isn’t as scary as the time between now and then. Terminator and Robocop may be nightmare scenarios, but at least in those there is clarity of which one is the enemy. Machines don’t yet have anywhere near that capability. However, if an objective is considered valuable, military leaders could already set a machine to kill people even when there is little certainty about the role or identity of the victims. They may put in some algorithms and crude AI to improve performance or reduce errors, but the algorithmic uncertainty and callous uncaring dispatch of potentially innocent people is very worrying.

Increasing desperation could be expected to lower barriers to use. So could a lower regard for the value of human life, and often in tribal conflicts people don’t consider the lives of the opposition to have a very high value. This is especially true in terrorism, where the objective is often to kill innocent people. It might not matter that the drone doesn’t know who it is killing, as long as it might be killing the right target as part of the mix. I think it is reasonable to expect a lot of battlefield use and certainly terrorist use of semi-smart robots and drones that kill relatively indiscriminatingly. Even when truly smart machines arrive, they might be set to malicious goals.

Then there is the possibility of rogue drones and robots. The Terminator/Robocop scenario. If machines are allowed to make their own decisions and then to kill, can we be certain that the safeguards are in place that they can always be safely deactivated? Could they be hacked? Hijacked? Sabotaged by having their fail-safes and shut-offs deactivated? Have their ‘minds’ corrupted? As an engineer, I’d say these are realistic concerns.

All in all, it is a good thing that concern is rising and we are seeing more debate. It is late, but not too late, to make good progress to limit and control the future damage killing machines might do. Not just directly in loss of innocent life, but to our fundamental humanity as armies get increasingly used to delegating responsibility to machines to deal with a remote dehumanised threat. Drones and robots are not the end of warfare technology, there are far scarier things coming later. It is time to get a grip before it is too late.

When people fought with sticks and stones, at least they were personally involved. We must never allow personal involvement to disappear from the act of killing someone.

Isn’t graphene even more fun? Carbon chainmail

Thought for the day:

Graphene, picture from cnx.org

 

A Chainmail structure, picture from 123rf.com

It’s a bit easier to see how the links overlap in this pic:

 

pic from mediafocus.com

So, just thinking out loud, perhaps the rings in the chainmail above could be rings of carbon, just 6 atoms each. If so, would this be better than graphene at anything useful, or not? Would longer rings work better? The idea of carbon nanotube chainmail is about a decade old.

 

Powerpoint really is not designed as a proper drawing tool and not having a week to spare, I didn’t bother doing the link overlaps or even the bonds properly in my pic, but together with the other two, I think you will get the idea fine.

I don’t know if this will work or not, but it might be an idea worth looking at further.

 

 

 

The rise and fall of the web

This is my part of a joint newsletter with Rohit Talwar, his was published just now as a guest blog.

The rise and fall of the web

20 years ago, the web was in its infancy and the first conferences appeared where we could all discuss what was coming next. Even then the need was obvious for search engines, portal sites, firewalls, social networking, online shopping, auctions, discount buying schemes and so on and even the seedier side of the web was already obvious back then. Not much around today on the web wasn’t being discussed 20 years ago. It just took that long to emerge and evolve into what was anticipated. What has happened is exposure of the naïve optimism of some of the early debate.

Over the coming years we saw the expected creation of companies like Amazon and ebay, Facebook, Twitter and Google, and the rise of already existing companies such as Microsoft, Apple and Samsung, in some cases from niche player to market dominance. Without exception, the companies I mentioned deserve praise for struggling through the difficult phases of market creation and the sometimes huge and prolonged losses leading up to break-even and eventual profitability. They all started with a dream and made it happen, knowing they would succeed if they worked hard enough at it.

Without wanting to remove any of that praise, it is hard not to wonder if at least part of the dream is starting to turn sour. Is there evidence now that power corrupts? Does possession of a strong market position always lead inevitably to market abuse?

In each case, there are recent examples of less-than-saintly behaviour, but some issues are spreading as a problem, so rather than pick on individual companies, I’ll focus on the issues. In each case, a large company with little effective competition is in strong position to force these policies since they know customers and clients can’t easily just walk away. There is no cartel, but if a problem happens to affect all the main providers for a service, or it is a de-facto monopoly, you really have no choice.

Privacy invasion or at least scant regard for privacy is the biggest issue for some, introducing policies that make it hard for users to remain private. In this case, the reason is obvious. Privacy conflicts with extracting maximum market value from a customer’s personal data. I don’t personally want everyone to know what I just bought online, what I watch on TV, what games I play or what music I am listening to, or to have full access to everything I ever typed on a social networking page. The choice we seem to be presented with is simple. If you don’t want to be fully exposed 24-7, either don’t use the web or a mobile app, or be prepared to spend time frequently to check every site you use carefully for their latest policy changes to make sure an oversight doesn’t allow your privacy doesn’t fall through a new hole they just dug. But even that may not be the real choice now. The emerging pattern seem to be that changes may be introduced retrospectively, eradicating any value in privacy commitments in existing policy. If that behaviour spreads, then any privacy you think you have today is merely an illusion.

Burning the candle at both ends is another recent issue. Although the web has few of the costs associated the with high street, large web companies are charging high fees now to companies to sell via their site, much the same as property developers with the best locations can charge high fees to shops. That end of the candle is well alight, but customers are finding the discounts offered are often far less now too. Now that they have been psychologically hooked by the web empires, prices are rising.

Walled gardens were a consideration for regulators when mobile and broadband networks were emerging – I took part in several workshops discussing their merits and drawbacks. Telecoms regulators understood well that dominant telecoms companies might try to force customers to use only services within their own areas of control, i.e. to stay in their walled garden, and they legislated accordingly to protect customers. It was presumed that competition would suffer greatly if people were not free to wander as they pleased and exploitation would follow soon after.  However, although some of the web giants are heading rapidly and determinedly down exactly that path, the authorities are either looking the other direction or unable to do anything about it. It seems that any regulators that do exist have too vague boundaries on their remits, or the companies fall outside their jurisdiction geographically, or they simply have too many issues to deal with and can’t keep up. It is unacceptable that we now by default have arrived at a business platform that lends itself to abuse but isn’t being properly controlled by the normal regulator processes that apply as standard elsewhere.

Arrogance is a term we hear thrown at web giants frequently now, and it does seem appropriate when a large company ignores protests by its customers and imposes policies that significantly affect the terms and conditions that applied when they first became a customer. Even incrementally small changes can add up to large change in a short time, but if customers have invested time and effort building a profile or establishing a place or network on a site, the personal costs of migration can be too high. There ought to be equivalent rights protecting the interests of customers online just as in the physical world, but online providers appear to be able to make their own conditions of use with much greater scope for abuses, knowing that very few customers will read many pages of small print. Especially where websites feature heavily in everyday use, and where not being a user might even may be a career or social impediment, there should be more protection from arrogance and unilateral determination and management of user rights. Some regulatory body should be making sure terms and conditions are fair and balanced because the market isn’t doing that by itself.

Another aspect of arrogance is the enthusiasm to avoid taxes by exploiting holes in the law, and reading between the lines, it is as if the companies think they know best how money should be spent for humankind’s best interests, not governments. They may be right about government, but that doesn’t excuse arrogance.

Reintermediation is a direct consequence of walled gardens but is an issue in its own right. Early analysis of the web suggested it would lead to perfect markets, where people would be in direct contact with suppliers, thereby cutting out the middle man and his costs while forcing perfect information and hence maximum competitiveness. With good search, it would be easy to find all potential suppliers for something and compare them directly, and there would be no need to go via an agency. What we have now is interesting in that the search sites have themselves become intermediaries, and comparison sites another layer of that, listing results from a subset of suppliers. So instead of removing an intermediary we generated two new ones, three if you use an app store to do it. Everyone wants a slice of the pie of course, but the web was meant to bypass that, and it simply hasn’t. People can go direct, but it doesn’t take long to discover that using a search engine will often put hundreds of pages of the wrong sites before the one you search for. Most of the listings on the first several pages will often be intermediary sites.

In spite of all this, the potential of the web hasn’t gone away. It still allows word of new sites to spread rapidly, for reputations to be made and lost, for empires to spring up overnight, and for old ones to crash and burn. Boredom is under-rated as a motivation to change too. Social network sites in particular are highly vulnerable to their customers simply getting bored and leaving, but new designs and novel ideas can present a real threat to any of them. The sword of Damocles hangs over all.

For all their size and momentum, none of the web giants is guaranteed longevity. As some of yesterday’s giants discovered, a startup can replace them in just a few years. Maybe the first generation of web giants has climbed high, but decadence and abuse of power have made them ripe for conquest. All we need now is to wait for the imminent emergence of the second generation.

Technology Convergence – What’s your Plan? Guest post by Rohit Talwar

Rohit is CEO of Fastfuture and a long-standing friend as well as an excellent futurist. He and I used to do a joint newsletter, and we have started again. Rohit sends it out to his mailing list as a proper newletter and because I don’t use mailing lists, I guest post it here. I’ll post my bit immediately after this one. I’m especially impressed since his bit ticks almost as many filing category boxes as it uses words.

Here is Rohit’s piece:

Technology Convergence – What’s your Plan?

I have just returned from South Korea where I was delivering a keynote speech to a cross-industry forum on how to prepare for and benefit from the opportunities arising from industry convergence. South Korea has made a major strategic commitment starting with government and running through the economy to be a leader in exploiting the potential opportunities arising from the convergence of industries made possible by advances in a range of disciplines. These include information and communications technology, biological and genetic sciences, energy and environmental sciences, cognitive science, materials science and nanotechnology.  From environmental monitoring, smart cars, and intelligent grids through to adaptive bioengineered materials and clothing-embedded wearable sensor device that monitor our health on a continuous basis – the potential is vast.

What struck me about the situation in Korea was how the opportunity is being viewed as a central component of the long-term future of Korea’s economy and how this is manifested in practice. Alongside a national plan, a government sponsored association has been established to drive and facilitate cross-industry collaboration to achieve convergence. In addition to various government-led support initiatives, a range of conferences are being created to help every major sector of the economy understand, explore, act on and realise the potential arising out of convergence.

I am fortunate to get the opportunity to visit 20-25 countries a year across all six continents and get to study and see a lot of what is happening to create tomorrow’s economy. Whilst my perspective is by no means complete, I am not aware of any country where such a systematic and rigorous approach is being taken to driving industry convergence. Those who study Korea know that this approach is nothing new for them – long term research and strategic planning are acknowledged to have played a major role in the evolution of its knowledge economy and rise of Korea and its technology brands on the global stage. Coming from the UK, where it seems that long term thinking and national policy are now long lost relatives, I wonder why it is that so few countries are willing to or capable of taking such a strategic approach.

Rohit on the Road

In the next few months Rohit will delivering speeches in Oslo, Paris, Vilnius, Warsaw, Frankfurt, Helsinki, Denver, Las Vegas, Oman, Leeds and London. Topics to be covered include human enhancement, the future of professional services, the future of HR, transformational forces in business, global drivers of change, how smart businesses create the future, the future technology timeline, the future of travel and tourism, the future of airlines and airports and the future of education. If you would like to arrange a meeting with Rohit in one of these cities or are interested in arranging a presentation or workshop for your organisation, please contact rohit@fastfuture.com

Magic fingers and digital spells

There can’t be many readers who haven’t seen some film or TV programme or at least read a book where a witch or fairy points her finger and magic flows from her fingertip to execute her intent. Wizards can do it too, but they tend to use wands. Is it just that men like gadgets more and women are more in touch with their bodies? Maybe to a point, but that certainly isn’t universally true. Anyway, digital spells will be here soon.

Gesture recognition such as pointing at something has been around as a games interface since the Nintendo Wii, maybe before that. The Wii needed a cumbersome remote control, but with more recent machines, you can just use your fingers. That’s fine when you have the detector in front of you, and the computer only has to follow the direction of pointing and detect a key click or movement. But most of the time, you don’t. 

Some wristwatches have had digital compasses for decades, proving that they don’t need to be large. So do my iPhone and Nexus. But my iphone and Nexus are usually somewhere else, like my jacket pocket or briefcase, though I usually have a watch on when I am away from home. Some people seem glued to their mobiles, and they could also be used, but for those of us who aren’t, digital jewellery such as watches or signet rings offers a potential substitute to detect hand or finger gestures.

Knowing location and direction of pointing is fine if you can determine them cheaply and accurately in small devices, but adding a tiny and cheap camera to capture some visual context such as the shape of buildings nearby can help home in much on the target more accurately. Something like a signet ring, or indeed a watch, could easily house all that is needed. GPS positioning isn’t the only kid on the block. Wireless LANs, mobile phone networks and other gadgets you have in a pocket or bag will do just as well. I also think we will soon get urban positioning systems that give location to millimetre accuracy throughout urban areas.

Accelerometers can measure both the path and speed pattern of movements so fancy gestures could be used to determine the purpose of the point, i.e which digital spell to activate.

Also, your hand can make a lot of different shapes, and these can be determined by wearing a few rings and automatically monitoring their relative orientation. They don’t have to be bulky, even a very thin band could be enough.

So, pointing a finger and making a shape with the other fingers, or making some special hand movement before or during the gesture, you could make hundreds of spells. One to make a frog, another if you prefer mice. In augmented reality you’ll be able to do that. Your memory of which gesture links to which spell would run out long before the library of potential combinations would.

Digital spells could link into any electronic system or app as an intuitive interface. Paying for a drink, sending a message to an attractive stranger, passing a business card, authenticating identity to a bank machine, controlling a TV or a PC display to pretend it is touch sensitive. All of these could be easy. As augmented reality takes shape, your hands will become building tools.

Digital spells will make us feel more powerful too. Who wouldn’t get a thrill from making a gesture at an annoying person and turning them into something horrible?

And as Arthur C. Clarke used to say, any sufficiently advanced technology is indistinguishable from magic.

Towards the singularity

This piece was originally written a year ago for ACM proceedings but got lost in their review process, so rather than waste it, here it is before it passes its use-by date. A recent powerpoint presentation highlighting the potential of the singularity but setting that against some of the dangers that we may instead be dragged into a dark age is here.

http://futurizon.com/articles/singularitydarkage.pdf

Anyway, here is my article:

Towards the singularity

About 25 years ago, inspired by the invention of field programmable gate arrays, many engineers recognised that in principle these could be used as the basis of an evolving machine, using a biomimetic approach.  Starting with an array of FPGA-like machines and evolutionary algorithms, clearly the hardware would be able to evolve to its physical limits. It wasn’t long after that before the first simple evolving software and then hardware was achieved. The early 90s saw an explosion in evolutionary development, with evolutionary software as the prime focus due to low range of reconfigurable circuitry. While evolutionary computing got bogged down in biomimetic integrity and genetic algorithms, those of us engineers with futurist mindsets looked towards the far end of the development wedge. We saw that positive feedback across the wider science and technology R&D system would cause development eventually to race ahead of Moore’s Law, as smarter machines enabled faster development and faster discovery in every field. What we now call the singularity is a simple extrapolation of ongoing positive feedback in technology development.

We know that evolution works in nature, and have already proved that we don’t have to fully understand stuff to develop it, just point it in vaguely the right direction and let it evolve and find its own way. Whether via evolution or design, computers will eventually surpass human intelligence, amplify positive feedback still further, and that will lead to the extremely rapid invention with the familiar almost vertical development curve. That is inevitable. Even without evolutionary computing, the singularity will still come, but will be slower, since it would be limited by human knowledge, squandering the potential contribution of machine assistance.

The singularity initially is appealing, inspiring visions of potential technotopia, and the potential would be real if mankind was ready to deal with it, but problems are starting to show through and realisation of them and the consequential actions will slow it down.

Firstly, invention is only the first stage of development, and there are limits on how fast physical development can take place, even with all the self-replicating machines we may expect, however smart they get. So the way the singularity manifests itself at best will be as a rapidly growing gap between creativity and realisation. It will be as if advanced ETs had landed and given us a manual on how to build all their technology. But we still wouldn’t be able to have it all instantly and would have to decide on a priority list.

This isn’t just a theoretical problem. We already have a large creativity gap (i.e., the pile of spare inventions that have been thought up but haven’t yet been developed) – and that indicates that the impact of the singularity will be restricted. If you go to the R&D department of any large technology company, you will find a huge pool of ideas backed by a relatively small pot of funding. Most engineers will be familiar with the frustration of brainstorms where most of the ideas they scribble on post-its get thrown away. Ideas are two a penny even today, but only so many can be developed. If the singularity is to have any real economic significance, it needs to be about more than just quantity of ideas. Even an infinite creativity gap isn’t valuable per se; it needs to be about quality and purpose too. By focusing on the near vertical invention curve, perhaps we miss the point. If you are offered anything you want this afternoon, you still need to ask yourself what it is you want, and that introduces another hurdle to jump over. Clearly, while humans control the allocation of resources and permission to build things, we will hold back development to our human imagination and cultural limits. The singularity could theoretically arrive around 2025, but the practical implications of it will arrive much more slowly.

Secondly, the decisions on what to build depend on our economic culture. In a pure capitalist system, if a new technology allows cheap automation, fewer employees will be needed, and wealth moves towards capital owners. While new jobs are created sufficient quickly, this is just a retraining issue and the economy as a whole can grow, but when automation exceeds the rate at which new jobs can be created, it becomes a problem. If too few people have enough money to buy output, demand falls and the economy spirals downwards. Consequently, many people are already looking at new designs for capitalism to make it economically and socially sustainable (environmentally sustainability is moving quickly towards third place). We don’t have to wait for the singularity; again, signs of this downward spiral are already starting to appear.

In a world eager for the next pad, it is easy to be enthused about future technology if your future income is secure. As technology catches up with human intelligence and even people in well-paid professional jobs start to be replaced, it is easy also to imagine a backlash building, especially if new technologies are used to increase government control of our lives, as they often are. The potential backlash would build until politicians are forced to deal with it, one way or another. Capitalism can’t properly exploit the singularity in its current form, and will have to be redesigned. But how? It will take time to decide.

Thirdly, the singularity presents many existential threats and thereby another reason to force powerful restrictions on scope and rate of development. These could and may well force very different development paths and delay it very significantly, perhaps by decades. It is likely that the military will want to push for powerful new weapons, but a singularity-based arms race could tip the balance rapidly and greatly increase temptation for first strike action. Laser and plasma rifles already exist, at least in experimental form (http://en.wikipedia.org/wiki/Shiva_Star). Terawatt solar wind deflector ray-guns and zombie viruses are within the scope of the 2025 singularity technology (http://futurizon.com/articles/madscientists.pdf). Many more can be listed. Starting with only six known ways that life on earth could be wiped out back in 2000 (nearby supernova, major solar storm, asteroid or comet strike, GM accident, or global nuclear war), my own studies suggest that the number increases exponentially to over 100 by 2050. If each optimistically has a 1 in 10,000 chance of occurring in a single year by accident or deliberate action, the probability of extinction rises to 1% per annum and continues to grow exponentially. Do the sums and you end up with an ETA for extinction of 2085, hardly the technotopian future promised by the singularity up front. To avoid such a result, we will be forced to intervene. But how? At the very least we need more time.

Fourthly, we are becoming more and more vulnerable. In a world containing many people who wish to harm us, our dependence on highly complex technology systems is already a significant known military risk, as well as social and economic. Asymmetry is the key word here. But it isn’t just deliberate harm we need to worry about. Recently, solar storms brought our dependency problem into sharp focus. We no longer have the old systems as a backup, nor even people who knew how they worked. As we engineer in ever more complexity and systemic interdependence, we surely build our prosperity on sand. A failure of any part of our critical systems for any reason could quickly lead to cascade failures, and riots for the last bottles of water. Before we rush to grab hold of the singularity, we need first to get a hold of failsafe design and the practice of keeping a backup, not just for our computers but for our whole life support system. I don’t worry about complexity or whether I understand how the system works. I worry about how I and my family will manage when it fails.  But complexity isn’t the only vulnerability.

One of the well-known scenarios that results from all of this is the Terminator scenario, and I am not convinced at all that we have solved this problem yet. (For the uninitiated, the Terminator Scenario is thus called after the Terminator series of film. In this series, the US military develops a powerful satellite-based computer system called Skynet to control their missiles so that they could respond faster to a threat, but the computer system achieves consciousness, decides that humans are actually the threat, and sets about wiping out humanity).  Machines already do most of the design work on the next generation machines. Human engineers make some of the key decisions and tell the machines what to design, mostly, but the proportion of human input is falling. Particularly when we use evolutionary design, the human understanding of the technology that results can be very low indeed. Imagine a scenario where a few smart students plan a prank, and use an off-the-net virus pack to infect millions of machines with an algorithm. The algorithm is very crude but attempts to achieve elements of consciousness or thinking, just for fun, to see what happens, to see how far they can get. Some of the students are in IT, some from bio-tech and nano-tech, some from neuroscience, and a few others. The algorithms are crude but designed as well as they can, using all their latest knowledge of how the neural networks in the brain work. And so they spawn them, on a million machines, each with 1% of the raw processing power of the human brain. And they use evolution in that huge aggregated processing pot to experiment with variants of the algorithm. Over time, the system accumulates a toolbox of different algorithms and circuits that achieve a wide variety of neural functions to some degree to achieve key components of mind or consciousness or awareness. By experimenting with automatically linking these together in many combinations, the students hope to achieve larger and larger degrees of AI. And they might as well harness that AI to refine the evolutionary algorithms too, and make the virus better at infecting even more machines and adapting better, and hiding better. All automatically. Can we be sure that such a prank would always fail? Or could it work, and achieve consciousness in a distributed machine, just like the Skynet from Terminator?

But if you go to singularity timeframes, there are even further dangers. Some people already belong to hobbyist genetic engineering groups or play with 3d printing – and some of those mess with printing electronics too. Circuits can harvest energy from changes in the environment or passing radio waves and so won’t necessarily need batteries. People will try to push the boundaries via those routes too and 2025 is a good way off so lots of progress will occur in all these fields by then. With feedback among all these bio-nano-info-cogno technologies, it is not hard to imagine how students or a terrorist group could make good progress even without proper funding, even while staying anonymous, based anywhere. As hidden net-based programs become smarter and more autonomous, they could notionally get to the point where they interact with genetic assemblers and printers and design biological and electronic devices in a feedback loop. When thinking of a grey goo scenario, forget little micro-mechanical machines. Think bacteria, think GM assemblers, think AI-led environmental adaptation and think of a distributed organism that is part in the machine world and part in the ecosystem. Much of that is achievable long before we get the singularity and the rest very soon after. Transhumanists forget that transbacteria may not allow them to proceed. Smart bacteria may link together into super-smart organisms that think of humans merely as competition for resources. We could be building the engines of our own destruction, even while aiming for technotopia.

I am no doom monger, and I always manage to convince myself that we will muddle through. Sure, we’ll do it badly and get half of the benefit at twice the price and twice the mess. We already know the problems above. They are being addressed in organisations such as the Lifeboat Foundation, there are often conferences or symposia along singularity lines. Government is even starting to react. Studies covering NBIC (nano, bio, info, cogno) convergence issues were initiated by the EU before 2000. The US and Canadian governments have bother run conferences debating ways that mad scientists could use future technologies to cause great harm. So the problems won’t come unexpectedly. Where do we end up?

The problems above are possibilities and even likely if we take the default path of ongoing unfettered development. Positive feedback would deliver on some of the promises, and some of the problems would appear along the way. In the real world, it won’t happen like that. Social and political feedback loops, educated by many ongoing debates such as this symposium, will ensure that regulation is implemented that slows it down, restricting what can legally be done, what can be developed, what can be bought, and by whom. It has to. What we can also be sure of is that much of the regulation will be reactive and badly thought out. So it will be a mess, we will barely muddle through, but muddle through we will. What we can hope for is that it might be a relatively safe mess and the reward at the end is worth it. But let’s start by acknowledging that what we call the singularity is only a theoretical concept, and it can’t be achieved in its pure form. The real world development path will surely be very different, constrained and forced down different paths by physical, cultural and economic limits and forced to comply with a wide range of legal precautions.

How smart could an AI become?

I got an interesting question in a comment from Jim T on my last blog.

What is your opinion now on how powerful machine intelligence will become?

Funny, but my answer relates to the old question: how many angels can sit on the head of a pin?

The brain is not a digital computer, and don’t think a digital processor will be capable of consciousness (though that doesn’t mean it can’t be very smart and help make huge scientific progress). I believe a conscious AI will be mostly analog in nature, probably based on some fancy combo of adaptive neural nets. as suggested decades ago by Moravec.

Taking that line, and looking at how far miniaturisation can go, then adding all the zeros that arise from the shorter signal transmission paths, faster switching speeds, faster comms, and the greater number of potential pathways using optical WDM than electronic connectivity, I calculated that a spherical pinhead (1mm across) could ultimately house the equivalent of 10,000 human brains. (I don’t know how smart angels are so didn’t quite get to the final step). You could scale that up for as much funding, storage and material and energy you can provide.

However, what that quantifies is how many human equivalent AIs you could support. Very useful to know if you plan to build a future server farm to look after electronically immortal people. You could build a machine with the equivalent intelligence of the entire human race. But it doesn’t answer the question of how smart a single AI could ever be, or how powerful it could be. Quantity isn’t quality. You could argue that 1% of the engineers produce 99% of the value, even with only a fairly small IQ difference. 10 billion people may not be as useful for progress as 10 people with 5 times the IQ. And look at how controversial IQ is. We can’t even agree what intelligence is or how to quantify it.

Just based on loose language, how powerful or smart or intelligent an AI could become depends on the ongoing positive feedback loop. Adding  more AI of the same intelligence level will enable the next incremental improvement, then using those slightly smarter AIs would get you to the next stage, a bit faster, ad infinitum. Eventually, you could make an AI that is really, really, really smart.

How smart is that? I don’t have the terminology to describe it. I can borrow an analogy though. Terry Pratchett’s early book ‘The Dark Side of the Sun’ has a character in it called The Bank. It was a silicon planet, with the silicon making a hugely smart mind. Imagine if a pinhead could house 10,000 human brains, and you have a planet of the stuff, and it’s all one big intellect instead of lots of dumb ones. Yep. Really, really, really smart.

How to make a conscious computer

The latest generation of supercomputers have processing speed that is higher than the human brain on a simple digital comparison, but they can’t think, aren’t conscious. It’s not even really appropriate to compare them because the brain mostly isn’t digital. It has some digital processing in the optics system but mostly uses adaptive analog neurons whereas digital computers use digital chips for processing and storage and only a bit of analog electronics for other circuits. Most digital computers don’t even have anything we would equate to senses.

Analog computers aren’t used much now, but were in fairly widespread use in some industries until the early 1980s. Most IT people have no first hand experience of them and some don’t seem to even be aware of analog computers, what they can do or how. But in the AI space, a lot of the development uses analog approaches.

http://timeguide.wordpress.com/2011/09/18/gel-computing/ discusses some of my previous work on conscious computer design. I won’t reproduce it here.

I firmly believe consciousness, whether externally or internally focused, is the result of internally directed sensing, (sensing can be thought of as the solicitation of feeling) so that you feel your thoughts or sensory inputs in much the same way. The easy bit is figuring out how thinking can work once you have that, how memories can be relived, concepts built, how self-awareness, sentience, intelligence emerge. All those are easy once you have figured out how feeling works. That is the hard problem.

Detection is not the same as feeling. It is easy to build a detector or sensor that flips a switch or moves a dial when something happens or even precisely quantifies something . Feeling it is another layer on that. Your skin detects touch, but your brain feels it, senses it. Taking detection and making it feel and become a sensation, that’s hard. What is it about a particular circuit that adds sensation? That is the missing link, the hard problem, and all the writing available out there just echoes that. Philosophers and scientists have written about this same problem in different ways for ages, and have struggled in vain to get a grip on it, many end up running in circles. So far they don’t know the answer, and neither do I. The best any offer is elucidation of aspects of the problem and at occasionally some hints of things that they think might somehow be connected with the answer. There exists no answer or explanation yet.

There is no magic in the brain. The circuitry involved in feeling something is capable of being described, replicated and even manufactured. It is possible to find out how to make a conscious circuit, even if we still don’t know what consciousness is or how it works, via replication, reverse engineering or evolutionary development. We manage to make conscious children several times every second.

How far can we go? Having studied a lot of what is written, it is clear that even after a lot of smart people thinking a long time about it, there is a great deal of confusion out there, and at least some of it comes basically from trying to use too big words and some comes from trying to analyse too much at once. When it is so obvious that it is a tough problem, simplifying it will undoubtedly help.  So let’s narrow it down a bit.

Feeling needs to be separated out from all the other things going on. What is it that happens that makes something feel? Well, detecting something pre-empts feeling it, and interpreting it or thinking about it comes later. So, ignore the detection and interpretation and thinking bits for now. Even sensation can be modelled as solicitation of feeling, essentially adding qualitative information to it. We ought to be able to make an abstraction model as for any IT system, where feeling is a distinct layer, coming between the physical detection layer and sensation, well below any of the layers associated with thinking or analysis.

Many believe that very simple organisms can detect stimuli and react to them, but can’t feel,  but more sophisticated ones can. Logical deduction tells us either that feeling may require fairly complex neural networks but certainly well below human levels, or alternatively, feeling may not be fundamentally linked to complexity but may emerge from architectural differences that arose in parallel with increasing complexity but aren’t dependent on it. It is also very likely due to evolutionary mechanisms that feeling emerges from similar structures to detection, though not the same. Architectural modifications, feedbacks, or additions to detection circuits might be an excellent point to start looking.

So we don’t know the answer, but we do have some good clues. Better than nothing. Coming at it from a philosophical direction, even the smartest people quickly get tied in knots, but from an engineering direction, I think the problem is soluble.

If feeling is, as I believe, a modified detection system, then we could for example seed an evolutionary design system with detection systems. Mutating, restructuring and rearranging detection systems and adding occasional random components here and there might eventually create some circuits that feel. It did in nature, and would in an evolutionary design system, given time. But how would we know? An evolutionary design system needs some means of selection to distinguish the more successful branches for further development.

Using feedback loops would probably help. A system with built in feedback so that it feels that it is feeling something would be symmetrical, maybe even fractal. Self-reinforcement of a feeling process would also create a little vortex of activity. A simple detection system (with detection of detection) would not exhibit such strong activity peaks due to necessary lack of symmetry in detection of initial and processed stimuli. So all we need do is to introduce feedback loops in each architecture and look for the emergence of activity peaks. Possibly, some non-feeling architectures might also show activity peaks so not all peaks would necessarily show successes, but all successes would show peaks.

So, the evolutionary system would take basic detection circuits as input, modify them, add random components, then connect them in simple symmetrical feedback loops. Most results would do nothing. Some would show self-reinforcement, evidenced by activity peaks. Those are the ones we need.

The output from such an evolutionary design system would be circuits that feel (and some junk). We have our basic components. Now we can start to make a conscious computer.

Let’s go back to the gel computing idea and plug them in. We have some basic detectors, for light, sound, touch etc. Pretty simple stuff, but we connect those to our new feeling circuits, so now those inputs stop being just information and become sensations. We add in some storage, recording the inputs, again with some feeling circuits added into the mix, and just for fun, let’s make those recording circuits replay those inputs over and over, indefinitely. Those sensations will be felt again and again, the memory relived. Our primitive little computer can already remember and experience things it has experienced before. Now add in some processing. When a and b happen, c results. Nothing complicated. Just the sort of primitive summation of inputs we know neurons can do all the time. But now, when that processing happens, our computer brain feels it. It feels that it is doing some thinking. It feels the stimuli occurring, a result occurring. And as it records and replays it, an experience builds. It now has knowledge. It may not be the answer to life the universe and everything just yet, but knowledge it is. It now knows and remembers the experience that when it links these two inputs, it gets that output. These processes and recordings and replays and further processing and storage and replays echo throughout the whole system. The sensory echoes and neural interference patterns result in some areas of reinforcement and some of cancellation. Concepts form. The whole process is sensed by the brain. It is thinking, processing, reliving memories, linking inputs and results into concepts and knowledge, storing concepts, and most importantly, it is feeling itself doing so.

The rest is just design detail. There’s your conscious computer.

When will AI marriage become legal?

Gay marriage is so yesterday. OK, it isn’t quite yet, but everything has been said a million times and I don’t intend to repeat it. A related but much more interesting debate is already gathering volume globally. When will you be able to marry your robot or AI?

The traditional Oxford English definition of marriage:

The formal union of a man and a woman, typically recognized by law, by which they become husband and wife. 

But, as is being asked by some, who says they have to be a man and a woman? Why can’t they be any sex? I don’t want to get into the arguments, because people on both sides argue passionately, often flying in the face of logic, but here is a gender neutral alternative definition:

Marriage is a social union or legal contract between people called spouses that establishes rights and obligations between the spouses, between the spouses and their children, and between the spouses and their in-laws.

Well, I am all for equality for all, but who says they have to be people?

If we are going to fight over definitions, surely we should try to finish with one that might survive more than a decade or two. This one simply won’t.

Artificial intelligence, or AI as it is usually called now, is making good progress. We already have computers with more raw number crunching power than the human brain. Their software, and indeed their requirement to use software, makes them far from equivalent overall, but I don’t think we will be waiting very long now for AI machines that we will agree are conscious, self aware, intelligent, sentient, with emotions, capable of forming human-like relationships. A few cranks will still object maybe, but so what?

These AIs will likely be based on adaptive analog neural networks rather than digital processing so they will not be so different from us really. Different futurists list different dates for AIs with man-machine equivalence, depending mostly on the prejudices and experiences bequeathed by their own backgrounds. I’d say 10 years, some say 15 or 20. Some say we will never get there, but they are just wrong, so wrong. We will soon have artificially intelligent entities comparable to humans in intellect and emotional capability. So how about this definition? :

Marriage is a social union or legal contract between conscious entities called spouses that establishes rights and obligations between the spouses, between the spouses and their derivatives, and those legally connected to them.

An AI might or might not be connected to a robot. An AI may not have any permanent physical form, and robots are really a red herring here. The mind is what is surely important, not the container. An AI can still be an entity that lives for a long enough time to be eligible for a long term relationship. I often watch sci-fi or play computer games, and many have AI characters that take on some sort of avatar – Edi in Mass Effect or Cortana in Halo for example. Sometimes these avatars are made to look very attractive, even super-attractive. It is easy to imaging how someone could fall in love with their AI. It isn’t much harder to imagine that they could fall in love with each other.

It’s a while since I last wrote about machine consciousness so I’ll say how I think it will work again now.

http://timeguide.wordpress.com/2011/09/18/gel-computing/ tells of my ideas on gel computing. A lot of adaptive electronic devices suspended in gel that can set up free space optical links to each other would be an excellent way of making an artificial brain-like processor.

Using this as a base, and with each of the tiny capsules being able to perform calculations, an extremely powerful digital processor could be created. But I don’t believe digital processors can become conscious, however much their processing increases in speed. It is an act of faith I guess, I can’t prove it, but coming from a computer modelling background it seems to me that a digital computer can simulate the processes in consciousness but it can’t emulate them and that difference is crucial.

I firmly believe consciousness is a matter of internal sensing. The same way that you sense sound or images or touch, you can sense the processes based on those same neural functions and their derivatives in your brain. Emotions ditto. We make ideas and concepts out of words and images and sounds and other sensory things and emotions too. We regenerate the same sorts of patterns, and filter them similarly to create new knowledge, thoughts and memories, a sort of vortex of sensory stimuli and echoes. Consciousness might not actually just be internal sensing, we don’t know yet exactly how it works, but even if it isn’t, you could do it that way. Internal sensing can be the basis of a conscious machine, an AI. Here’s a picture. This would work. I am sure of it. There will also be other ways of achieving consciousness, and they might have different flavours. But for the purposes of arguing for AI marriage, we only need one method of achieving consciousness to be feasible.

I think this sort of AI design could work and it would certainly be capable of emotions. In fact, it would be capable of a much wider range of emotions than human experience. I believe it could fall in love, with a human, alien, or another AI. AIs will have a range and variety of gender capabilities and characteristics. People will be able to link to them in new ways, creating new forms of intimacy. The same technology will also enable new genders for people too, as I discussed recently. In the long term view, gay marriage is just another point on a long line.

When we set aside the arguing over gender equality, what we usually agree on is the importance of love. People can fall in love with any other human of any age, race or gender, but they are also capable of loving a sufficiently developed AI. As we rush to legislate for gender equality, it really is time to start opening the debate. AI will come in a very wide range of capability and flavour. Some will be equivalent or even superior to humans in many ways. They will have needs, they will want rights, and they will become powerful enough to demand them. Sooner or later, we will need to consider equality for them too. And I for one will be on their side.