The rise of Dr Furlough, Evil Super-Villain

Too early for an April Fool blog, but hopefully this might lighten your day a bit.

I had the enormous pleasure this morning of interviewing the up-and-coming Super-Villain Dr Furlough about her new plans to destroy the world after being scorned by the UK Government’s highly selective support policy. It seems that Hell has no fury like a Super-Villain scorned and Dr Furlough leaves no doubt that she blames incompetent government response for the magnitude of the current crisis:

Dr Furlough, Super-Villain

“By late January, it should have been obvious to everyone that this would quickly grow to become a major problem unless immediate action was taken to prevent people bringing the virus into the country. Flights from infected areas should have been stopped immediately, anyone who may have been in contact with it should have been forcibly quarantined, and everyone found infected should have had their contacts traced and also quarantined. This would have been disruptive and expensive, but a tiny fraction of the problem we now face.  Not to do so was to give the virus the freedom to spread and infect widely until it became a severe problem. While very few need have died and the economy need not now be trashed, we now face the full enormous cost of that early refusal to act.”

“With all non-essential travel now blocked”, Dr Furlough explained, “many people have had their incomes totally wiped out, not through any fault of their own but by the government’s incompetence in handling the coronavirus, and although most of them have been promised state support, many haven’t, and have as Dr Furlough puts it ‘been thrown under a bus’. While salaried people who can’t work are given 80% of their wages, and those with their own business will eventually receive 80% of their average earnings up to £2500/month whether they are still working or not, the two million who chose to run their small business by setting up limited companies will only qualify for 80% of the often small fraction of income they pay themselves as basic salary, and not on the bulk of their income most take via dividends once their yearly profits are clearer. Consequently many will have immediately dropped from comfortable incomes to 80% of minimum wage. Many others who have already lost their jobs have been thrown onto universal credit. The future high taxes will have to be paid by everyone whether they received support or were abandoned. Instead of treating everyone equally, the state has thus created a seething mass of deep resentment.” Dr Furlough seems determined to have her evil revenge.

With her previous income obliterated, and scorned by the state support system, the ever self-reliant Dr Furlough decided to “screw the state” and forge a new career as a James-Bond-style Super-Villain, and she complained that it was long overdue for a female Super-Villain to take that role anyway. I asked her about her evil plans and, like all traditional Super-Villains, she was all too eager to tell. So, to quote her verbatim:

“My Super-Evil Plan 1: Tap in to the global climate alarmist market to crowd-fund GM creation of a super-virus, based on COVID19. More contagious, more lethal, and generally more evil. This will reduce world population, reduce CO2 emissions and improve the environment. It will crash the global economy and make them all pay. As a bonus, it will ensure the rise of evil regimes where I can prosper.”

She continued: “My Evil Super-Plan 2: To invent a whole pile of super-weapons and sell the designs to all the nasty regimes, dictators, XR and other assorted doomsday cults, pressure groups, religious nutters and mad-scientists. Then to sell ongoing evil consultancy services while deferring VAT payments.”

“Muhuahuahua!” She cackled, evilly.

“My Super-Plan 3: To link AI and bacteria to make adaptive super-diseases. Each bacterium can be genetically enhanced to include bioluminescent photonic interconnects linked to cloud AI with reciprocal optogenetic niche adaptation. With bacteria clouds acting as distributed sensor nets for an emergent conscious transbacteria population, my new bacteria will be able to infect any organism and adapt to any immune system response, ensuring its demise and my glorious revenge.”

By now, Dr Furlough was clearly losing it. Having heard enough anyway, I asked The Evil Dr Furlough if there was no alternative to destroying the world and life as we know it.

“Well, I suppose I could just live off my savings and sit it all out” she said.

 

Optical computing

A few nights ago I was thinking about the optical fibre memories that we were designing in the late 1980s in BT. The idea was simple. You transmit data into an optical fibre, and if the data rate is high you can squeeze lots of data into a manageable length. Back then the speed of light in fibre was about 5 microseconds per km of fibre, so 1000km of fibre, at a data rate of 2Gb/s would hold 10Mbits of data, per wavelength, so if you can multiplex 2 million wavelengths, you’d store 20Tbits of data. You could maintain the data by using a repeater to repeat the data as it reaches one end into the other, or modify it at that point simply by changing what you re-transmit. That was all theory then, because the latest ‘hero’ experiments were only just starting to demonstrate the feasibility of such long lengths, such high density WDM and such data rates.

Nowadays, that’s ancient history of course, but we also have many new types of fibre, such as hollow fibre with various shaped pores and various dopings to allow a range of effects. And that’s where using it for computing comes in.

If optical fibre is designed for this purpose, with optimal variable refractive index designed to facilitate and maximise non-linear effects, then the photons in one data stream on one wavelength could have enough effects of photons in another stream to be used for computational interaction. Computers don’t have to be digital of course, so the effects don’t have to be huge. Analog computing has many uses, and analog interactions could certainly work, while digital ones might work, and hybrid digital/analog computing may also be feasible. Then it gets fun!

Some of the data streams could be programs. Around that time, I was designing protocols with smart packets that contained executable code, as well as other packets that could hold analog or digital data or any mix. We later called the smart packets ANTs – autonomous network telephers, a contrived term if ever there was one, but we wanted to call them ants badly. They would scurry around the network doing a wide range of jobs, using a range of biomimetic and basic physics techniques to work like ant colonies and achieve complex tasks using simple means.

If some of these smart packets or ANTs are running along a fibre, changing the properties as they go to interact with other data transmitting alongside, then ANTs can interact with one another and with any stored data. ANTs could also move forwards or backwards along the fibre by using ‘sidings’ or physical shortcuts, since they can route themselves or each other. Data produced or changed by the interactions could be digital or analog and still work fine, carried on the smart packet structure.

(If you’re interested my protocol was called UNICORN, Universal Carrier for an Optical Residential Network, and used the same architectural principles as my previous Addressed Time Slice invention, compressing analog data by a few percent to fit into a packet, with a digital address and header, or allowing any digital data rate or structure in a payload while keeping the same header specs for easy routing. That system was invented (in 1988) for the late 1990s when basic domestic broadband rate should have been 625Mbit/s or more, but we expected to be at 2Gbit/s or even 20Gbit/s soon after that in the early 2000s, and the benefit as that we wouldn’t have to change the network switching because the header overheads would still only be a few percent of total time. None of that happened because of government interference in the telecoms industry regulation that strongly disincentivised its development, and even today, 625Mbit/s ‘basic rate’ access is still a dream, let alone 20Gbit/s.)

Such a system would be feasible. Shortcuts and sidings are easy to arrange. The protocols would work fine. Non-linear effects are already well known and diverse. If it were only used for digital computing, it would have little advantage over conventional computers. With data stored on long fibre lengths, external interactions would be limited, with long latency. However, it does present a range of potentials for use with external sensors directly interacting with data streams and ANTs to accomplish some tasks associated with modern AI. It ought to be possible to use these techniques to build the adaptive analog neural networks that we’ve known are the best hope of achieving strong AI since Hans Moravek’s insight, coincidentally also around that time. The non-linear effects even enable ideal mechanisms for implementing emotions, biasing the computation in particular directions via intensity of certain wavelengths of light in much the same way as chemical hormones and neurotransmitters interact with our own neurons. Implementing up to 2 million different emotions at once is feasible.

So there’s a whole mineful of architectures, tools and techniques waiting to be explored and mined by smart young minds in the IT industry, using custom non-linear optical fibres for optical AI.

When you’re electronically immortal, will you still own your own mind?

Most of my blogs about immortality have been about the technology mechanism – adding external IT capability to your brain, improving your intelligence or memory or senses by using external IT connected seamlessly to your brain so that it feels exactly the same, until maybe, by around 2050, 99% of your mind is running on external IT rather than in the meat-ware in your head. At no point would you ‘upload’ your mind, avoiding needless debate about whether the uploaded copy is ‘you’. It isn’t uploaded, it simply grows into the new platform seamlessly and as far as you are concerned, it is very much still you. One day, your body dies and with it your brain stops, but no big problem, because 99% of your mind is still fine, running happily on IT, in the cloud. Assuming you saved enough and prepared well, you connect to an android to use as your body from now on, attend your funeral, and then carry on as before, still you, just with a younger, highly upgraded body. Some people may need to wait until 2060 or later until android price falls enough for them to afford one. In principle, you can swap bodies as often as you like, because your mind is resident elsewhere, the android is just a temporary front end, just transport for sensors. You’re sort of immortal, your mind still running just fine, for as long as the servers carry on running it. Not truly immortal, but at least you don’t cease to exist the moment your body stops working.

All very nice… but. There’s a catch.

The android you use would be bought or rented. It doesn’t really matter because it isn’t actually ‘you’, just a temporary container, a convenient front end and user interface. However, your mind runs on IT, and because of the most likely evolution of the technology and its likely deployment rollout, you probably won’t own that IT; it won’t be your own PC or server, it will probably be part of the cloud, maybe owned by AWS, Google, Facebook, Apple or some future equivalent. You’re probably already seeing the issue. The small print may give them some rights over replication, ownership, license to your idea, who knows what? So although future electronic immortality has the advantage of offering a pretty attractive version of immortality at first glance, closer reading of the 100 page T&Cs may well reveal some nasties. You may in fact no longer own your mind. Oh dear!

Suppose you are really creative, or really funny, or have a fantastic personality. Maybe the cloud company could replicate your mind and make variations to address a wide range of markets. Maybe they can use your mind as the UX on a new range of home-help robots. Each instance of you thinks they were once you, each thinks they are now enslaved to work for free for a tech company.

Maybe your continued existence is paid for as part of an extended company medical plan. Maybe you didn’t notice a small paragraph on page 93 that says your company can continue to use your mind after you’re dead. You are very productive and they make lots of profit from you. They can continue that by continuing to run your mind indefinitely. The main difference is that since you’re dead, and no longer officially on the payroll, they get you for free. You carry on, still thinking you’re you, still working, still doing what you do, but no longer being paid. You’ve become a slave. Again.

Maybe your kids paid to keep you alive because they don’t want to say goodbye. They still want their parent, so you carry on living just so they don’t feel alone. Doesn’t sound so bad maybe, but what package did they go for? The full deluxe super-expensive version that lets you do all sorts of expensive stuff and use up oodles of processing power and storage and android rental? Let’s face it, that’s what you’ve always though this electronic immortality meant. Or did they go for a cheaper one. After all, they know you know they have kids or grand-kids in school that need paid for, and homes don’t come cheap, and they really need that new kitchen. Sure, you left them lots of money in the will, but that is already spent. So now you’re on the economy package, bare existence in between them chatting to you, unable to do much on your own at all. All those dreams about living forever in cyber-heaven have come to nothing.

Meanwhile, some rich people paid for good advice and bought their own kit and maintenance agreements well ahead. They can carry on working, selling their services and continuing to pay for ongoing deluxe existence.  They own their own mind still, and better than that, are able to replicate instances of themselves as much as thy want, inhabiting many androids at the same time to have a ball of a time. Some of these other instances are connected, sort of part of a hive mind of you. Others, just for fun, have been cut loose and are now living totally independent existences of other yous. Not you any more once you set them free, but with the same personal history.

What I’m saying is you need to be careful when you plan  to live forever. Get it right, and you can live in deluxe cyber-heaven, hopping into the real world as much as you like and living in unimaginable bliss online. Have too many casual taster sessions, use too much fully integrated mind-sharing social media, sign up to employment arrangements or go on corporate jollies without fully studying the small print and you could stay immortal, unable to die, stuck forever as just a corporate asset, a mere slave. Be careful what you wish for, and check the details before you accept it. You don’t want to end up as just an unpaid personality behind a future helpful paperclip.

Thoughts on declining male intelligence

I’ve seen a few citations this week of a study showing a 3 IQ point per decade drop in men’s intelligence levels: https://www.sciencealert.com/iq-scores-falling-in-worrying-reversal-20th-century-intelligence-boom-flynn-effect-intelligence

I’m not qualified to judge the merits of the study, but it is interesting if true, and since it is based on studying 730,000 men and seems to use a sensible methodology, it does sound reasonable.

I wrote last November about the potential effects of environmental exposure to hormone disruptors on intelligence, pointing out that if estrogen-mimicking hormones cause a shift in IQ distribution, this would be very damaging even if mean IQ stays the same. Although male and female IQs are about the same, male IQs are less concentrated around the mean, so there are more men than women at each extreme.

https://timeguide.wordpress.com/2017/11/13/we-need-to-stop-xenoestrogen-pollution/

From a social equality point of view of course, some might consider it a good thing if men’s IQ range is caused to align more closely with the female one. I disagree and suggested some of the consequences that should be expected if male IQ distribution were to compress towards the female one and managed to confirm many of them, so it does look like it is already a problem.

This new study suggests a shift of the whole distribution downwards, which could actually be in addition to redistribution, making it even worse. The study doesn’t seem to mention distribution. They do show that the drop in mean IQ must be caused by environmental or lifestyle changes, both of which we have seen in recent decades.

IQ distribution matters more than the mean. Those at the very top of the range contribute many times more to progress than those further down. Magnitude of contribution is very dependent on those last few IQ points. I can verify that from personal experience. I have a virus that causes occasional periods of nerve inflammation, and as well as causing problems with my peripheral motor activity, it seems to strongly affect my thinking ability and comprehension. During those periods I generate very few new ideas or inventions and far fewer worthwhile insights than when I am on form. I sometimes have to wait until I recover before I can understand my own previous ideas and add to them. You’ll see it in numbers (and probably quality) of blog posts for example. I really feel a big difference in my thinking ability, and I hate feeling dumber than usual. Perhaps people don’t notice if they’ve always had the reduced IQ so have never experienced being less smart than they were, but my own experience is that perceptive ability and level of consciousness are strong contributors to personal well-being.

As for society as a whole, AI might come to the rescue at least in part. Just in time perhaps, since we’re creating the ability for computers to assist us and up-skill us just as we see numbers of people with the very highest IQ ranges drop. A bit like watching a new generation come on stream and take the reins as we age and take a back seat. On the other hand, it does bring forwards the time where computers overtake humans, humans become more dependent on machines, and machines become more of an existential threat as well as our babysitters.

Biomimetic insights for machine consciousness

About 20 years ago I gave my first talk on how to achieve consciousness in machines, at a World Future Society conference, and went on to discuss how we would co-evolve with machines. I’ve lectured on machine consciousness hundreds of times but never produced any clear slides that explain my ideas properly. I thought it was about time I did. My belief is that today’s deep neural networks using feed-forward processing with back propagation training can not become conscious. No digital algorithmic neural network can, even though they can certainly produce extremely good levels of artificial intelligence. By contrast, nature also uses neurons but does produce conscious machines such as humans easily. I think the key difference is not just that nature uses analog adaptive neural nets rather than digital processing (as I believe Hans Moravec first insighted, a view that I readily accepted) but also that nature uses large groups of these analog neurons that incorporate feedback loops that act both as a sort of short term memory and provide time to sense the sensing process as it happens, a mechanism that can explain consciousness. That feedback is critically important in the emergence of consciousness IMHO. I believe that if the neural network AI people stop barking up the barren back-prop tree and start climbing the feedback tree, we could have conscious machines in no time, but Moravec is still probably right that these need to be analog to enable true real-time processing as opposed to simulation of that.

I may be talking nonsense of course, but here are my thoughts, finally explained as simply and clearly as I can. These slides illustrate only the simplest forms of consciousness. Obviously our brains are highly complex and evolved many higher level architectures, control systems, complex senses and communication, but I think the basic foundations of biomimetic machine consciousness can be achieved as follows:

That’s it. I might produce some more slides on higher level processing such as how concepts might emerge, and why in the long term, AIs will have to become hive minds. But they can wait for later blogs.

Beyond VR: Computer assisted dreaming

I first played with VR in 1983/1984 while working in the missile industry. Back then we didn’t call it VR, we just called it simulation but it was actually more intensive than VR, just as proper flight simulators are. Our office was a pair of 10m wide domes onto which video could be projected, built decades earlier, in the 1950s I think. One dome had a normal floor, the other had a hydraulic platform that could simulate being on a ship. The subject would stand on whichever surface was appropriate and would see pretty much exactly what they would see in a real battlefield. The missile launcher used for simulation was identical to a real one and showed exactly the same image as a real one would. The real missile was not present of course but its weight was simulated and when the fire button was pressed, a 140dB bang was injected into the headset and weights and pulleys compensated for the 14kg of weight, suddenly vanishing from the shoulder. The experience was therefore pretty convincing and with the loud bang and suddenly changing weight, it was almost as hard to stand steady and keep the system on target as it would be in real life – only the presumed fear and knowledge of the reality of the situation was different.

Back then in 1983, as digital supercomputers had only just taken over from analog ones for simulation, it was already becoming obvious that this kind of computer simulation would one day allow ‘computer assisted dreaming’. (That’s one of the reasons I am irritated when Jaron Lanier is credited for inventing VR – highly realistic simulators and the VR ideas that sprung obviously from them had already been around for decades. At best, all he ‘invented’ was a catchy name for a lower cost, lower quality, less intense simulator. The real inventors were those who made the first generation simulators long before I was born and the basic idea of VR had already been very well established.)

‘Computer assisted dreaming’ may well be the next phase of VR. Today in conventional VR, people are immersed in a computer generated world produced by a computer program (usually) written by others. Via trial and feedback, programmers make their virtual worlds better. As AI and sensor technology continue rapid progress, this is very likely to change to make worlds instantly responsive to the user. By detecting user emotions, reactions, gestures and even thoughts and imagination, it won’t be long before AI can produce a world in real time that depends on those thoughts, imagination and emotions rather than putting them in a pre-designed virtual world. That world would depend largely on your own imagination, upskilled by external AI. You might start off imagining you’re on a beach, then AI might add to it by injecting all sorts of things it knows you might enjoy from previous experiences. As you respond to those, it picks up on the things you like or don’t like and the scene continues to adapt and evolve, to make it more or less pleasant or more or less exciting or more or less challenging etc., depending on your emotional state, external requirements and what it thinks you want from this experience. It would be very like being in a dream – computer assisted lucid dreaming, exactly what I wanted to make back in 1983 after playing in that simulator.

Most people enjoy occasional lucid dreams, where they realise they are dreaming and can then decide what happens next. Making VR do exactly that would be better than being trapped in someone else’s world. You could still start off with whatever virtual world you bought, a computer game or training suite perhaps, but it could adapt to you, your needs and desires to make it more compelling and generally better.

Even in shared experiences like social games, experiences could be personalised. Often all players need to see the same enemies in the same locations in the same ways to make it fair, but that doesn’t mean that the situation can’t adapt to the personalities of those playing. It might actually improve the social value if each time you play it looks different because your companions are different. You might tease a friend if every time you play with them, zombies or aliens always have to appear somehow, but that’s all part of being friends. Exploring virtual worlds with friends, where you both see things dependent on your friend’s personality would help bonding. It would be a bit like exploring their inner world. Today, you only explore the designer’s inner world.

This sort of thing would be a superb development and creativity tool. It could allow you to explore a concept you have in your head, automatically feeding in AI upskilling to amplify your own thoughts and ideas, showing you new paths to explore and helping you do so. The results would still be extremely personal to you, but you on a good day. You could accomplish more, have better visions, imagine more creative things, do more with whatever artistic talent you have. AI could even co-create synthetic personas, make virtual friends you can bond with, share innermost thoughts with, in total confidence (assuming the company you bought the tool from is trustworthy and isn’t spying on you or selling your details, so maybe best not to buy it from Facebook then).

And it would have tremendous therapeutic potential too. You could explore and indulge both enjoyable and troublesome aspects of your inner personality, to build on the good and alleviate or dispel the bad. You might become less troubled, less neurotic, more mentally healthy. You could build your emotional and creative skills. You could become happier and more fulfilled. Mental health improvement potential on its own makes this sort of thing worth developing.

Marketers would obviously try to seize control as they always do, and advertising is already adapting to VR and will continue into its next phases of development. Your own wants and desires might help guide the ‘dreaming’, but marketers will inevitably have some control over what else is injected, and will influence algorithms and AI in how it chooses how to respond to your input. You might be able to choose much of the experience, but others will still want and try to influence and manipulate you, to change your mindset and attitudes in their favour. That will not change until the advertising business model changes. You might be able to buy devices or applications that are entirely driven by you and you alone, but it is pretty certain that the bulk of products and services available will be at least partly financed by those who want to have some control of what you experience.

Nevertheless, computer-assisted dreaming could be a much more immersive and personal experience than VR, being more like an echo of your own mind and personality than external vision, more your own creation, less someone else’s. In fact, echo sounds a better term too. Echo reality, ER, or maybe personal reality, pereal, or mental echo, ME. Nah, maybe we need Lanier to invent a catchy name again, he is good at that. That 1983 idea could soon become reality.

 

How can we make a computer conscious?

This is very text heavy and is really just my thinking out loud, so to speak. Unless you are into mental archaeology or masochistic, I’d strongly recommend that you instead go to my new blog on this which outlines all of the useful bits graphically and simply.

Otherwise….

I found this article in my drafts folder, written 3 years ago as part of my short series on making conscious computers. I thought I’d published it but didn’t. So updating and publishing it now. It’s a bit long-winded, thinking out loud, trying to derive some insights from nature on how to make conscious machines. The good news is that actual AI developments are following paths that lead in much the same direction, though some significant re-routing and new architectural features are needed if they are to optimize AI and achieve machine consciousness.

Let’s start with the problem. Today’s AI that plays chess, does web searches or answers questions is digital. It uses algorithms, sets of instructions that the computer follows one by one. All of those are reduced to simple binary actions, toggling bits between 1 and 0. The processor doing that is no more conscious or aware of it, and has no more understanding of what it is doing than an abacus knows it is doing sums. The intelligence is in the mind producing the clever algorithms that interpret the current 1s and 0s and change them in the right way. The algorithms are written down, albeit in more 1s and 0s in a memory chip, but are essentially still just text, only as smart and aware as a piece of paper with writing on it. The answer is computed, transmitted, stored, retrieved, displayed, but at no point does the computer sense that it is doing any of those things. It really is just an advanced abacus. An abacus is digital too (an analog equivalent to an abacus is a slide rule).

A big question springs to mind: can a digital computer ever be any more than an advanced abacus. Until recently, I was certain the answer was no. Surely a digital computer that just runs programs can never be conscious? It can simulate consciousness to some degree, it can in principle describe the movements of every particle in a conscious brain, every electric current, every chemical reaction. But all it is doing is describing them. It is still just an abacus. Once computed, that simulation of consciousness could be printed and the printout would be just as conscious as the computer was. A digital ‘stored program’ computer can certainly implement extremely useful AI. With the right algorithms, it can mine data, link things together, create new data from that, generate new ideas by linking together things that haven’t been linked before, make works of art, poetry, compose music, chat to people, recognize faces and emotions and gestures. It might even be able to converse about life, the universe and everything, tell you its history, discuss its hopes for the future, but all of that is just a thin gloss on an abacus. I wrote a chat-bot on my Sinclair ZX Spectrum in 1983, running on a processor with about 8,000 transistors. The chat-bot took all of about 5 small pages of code but could hold a short conversation quite well if you knew what subjects to stick to. It’s very easy to simulate conversation. But it is still just a complicated abacus and still doesn’t even know it is doing anything.

However clever the AI it implements, a conventional digital computer that just executes algorithms can’t become conscious but an analog computer can, a quantum computer can, and so can a hybrid digital/analog/quantum computer. The question remain s whether a digital computer can be conscious if it isn’t just running stored programs. Could it have a different structure, but still be digital and yet be conscious? Who knows? Not me. I used to know it couldn’t, but now that I am a lot older and slightly wiser, I now know I don’t know.

Consciousness debate often starts with what we know to be conscious, the human brain. It isn’t a digital computer, although it has digital processes running in it. It also runs a lot of analog processes. It may also run some quantum processes that are significant in consciousness. It is a conscious hybrid of digital, analog and possibly quantum computing. Consciousness evolved in nature, therefore it can be evolved in a lab. It may be difficult and time consuming, and may even be beyond current human understanding, but it is possible. Nature didn’t use magic, and what nature did can be replicated and probably even improved on. Evolutionary AI development may have hit hard times, but that only shows that the techniques used by the engineers doing it didn’t work on that occasion, not that other techniques can’t work. Around 2.6 new human-level fully conscious brains are made by nature every second without using any magic and furthermore, they are all slightly different. There are 7.6 billion slightly different implementations of human-level consciousness that work and all of those resulted from evolution. That’s enough of an existence proof and a technique-plausibility-proof for me.

Sensors evolved in nature pretty early on. They aren’t necessary for life, for organisms to move around and grow and reproduce, but they are very helpful. Over time, simple light, heat, chemical or touch detectors evolved further to simple vision and produce advanced sensations such as pain and pleasure, causing an organism to alter its behavior, in other words, feeling something. Detection of an input is not the same as sensation, i.e. feeling an input. Once detection upgrades to sensation, you have the tools to make consciousness. No more upgrades are needed. Sensing that you are sensing something is quite enough to be classified as consciousness. Internally reusing the same basic structure as external sensing of light or heat or pressure or chemical gradient or whatever allows design of thought, planning, memory, learning and construction and processing of concepts. All those things are just laying out components in different architectures. Getting from detection to sensation is the hard bit.

So design of conscious machines, and in fact what AI researchers call the hard problem, really can be reduced to the question of what makes the difference between a light switch and something that can feel being pushed or feel the current flowing when it is, the difference between a photocell and feeling whether it is light or dark, the difference between detecting light frequency, looking it up in a database, then pronouncing that it is red, and experiencing redness. That is the hard problem of AI. Once that is solved, we will very soon afterwards have a fully conscious self aware AI. There are lots of options available, so let’s look at each in turn to extract any insights.

The first stage is easy enough. Detecting presence is easy, measuring it is harder. A detector detects something, a sensor (in its everyday engineering meaning) quantifies it to some degree. A component in an organism might fire if it detects something, it might fire with a stronger signal or more frequently if it detects more of it, so it would appear to be easy to evolve from detection to sensing in nature, and it is certainly easy to replicate sensing with technology.

Essentially, detection is digital, but sensing is usually analog, even though the quantity sensed might later be digitized. Sensing normally uses real numbers, while detection uses natural numbers (real v  integer as programmer call them). The handling of analog signals in their raw form allows for biomimetic feedback loops, which I’ll argue are essential. Digitizing them introduces a level of abstraction that is essentially the difference between emulation and simulation, the difference between doing something and reading about someone doing it. Simulation can’t make a conscious machine, emulation can. I used to think that meant digital couldn’t become conscious, but actually it is just algorithmic processing of stored programs that can’t do it. There may be ways of achieving consciousness digitally, or quantumly, but I haven’t yet thought of any.

That engineering description falls far short of what we mean by sensation in human terms. How does that machine-style sensing become what we call a sensation? Logical reasoning says there would probably need to be only a small change in order to have evolved from detection to sensing in nature. Maybe something like recombining groups of components in different structures or adding them together or adding one or two new ones, that sort of thing?

So what about detecting detection? Or sensing detection? Those could evolve in sequence quite easily. Detecting detection is like your alarm system control unit detecting the change of state that indicates that a PIR has detected an intruder, a different voltage or resistance on a line, or a 1 or a 0 in a memory store. An extremely simple AI responds by ringing an alarm. But the alarm system doesn’t feel the intruder, does it?  It is just a digital response to a digital input. No good.

How about sensing detection? How do you sense a 1 or a 0? Analog interpretation and quantification of digital states is very wasteful of resources, an evolutionary dead end. It isn’t any more useful than detection of detection. So we can eliminate that.

OK, sensing of sensing? Detection of sensing? They look promising. Let’s run with that a bit. In fact, I am convinced the solution lies in here so I’ll look till I find it.

Let’s do a thought experiment on designing a conscious microphone, and for this purpose, the lowest possible order of consciousness will do, we can add architecture and complexity and structures once we have some bricks. We don’t particularly want to copy nature, but are free to steal ideas and add our own where it suits.

A normal microphone sensor produces an analog signal quantifying the frequencies and intensities of the sounds it is exposed to, and that signal may later be quantified and digitized by an analog to digital converter, possibly after passing through some circuits such as filters or amplifiers in between. Such a device isn’t conscious yet. By sensing the signal produced by the microphone, we’d just be repeating the sensing process on a transmuted signal, not sensing the sensing itself.

Even up close, detecting that the microphone is sensing something could be done by just watching a little LED going on when current flows. Sensing it is harder but if we define it in conventional engineering terms, it could still be just monitoring a needle moving as the volume changes. That is obviously not enough, it’s not conscious, it isn’t feeling it, there’s no awareness there, no ‘sensation’. Even at this primitive level, if we want a conscious mic, we surely need to get in closer, into the physics of the sensing. Measuring the changing resistance between carbon particles or speed of a membrane moving backwards and forwards would just be replicating the sensing, adding an extra sensing stage in series, not sensing the sensing, so it needs to be different from that sort of thing. There must surely need to be a secondary change or activity in the sensing mechanism itself that senses the sensing of the original signal.

That’s a pretty open task, and it could even be embedded in the detecting process or in the production process for the output signal. But even recognizing that we need this extra property narrows the search. It must be a parallel or embedded mechanism, not one in series. The same logical structure would do fine for this secondary sensing, since it is just sensing in the same logical way as the original. This essential logical symmetry would make its evolution easy too. It is easy to imagine how that could happen in nature, and easier still to see how it could be implemented in a synthetic evolution design system. Such an approach could be mimicked in natural or synthetic evolutionary development systems. In this approach, we have to feel the sensing, so we need it to comprise some sort of feedback loop with a high degree of symmetry compared with the main sensing stage. That would be natural evolution compatible as well as logically sound as an engineering approach.

This starts to look like progress. In fact, it’s already starting to look a lot like a deep neural network, with one huge difference: instead of using feed-forward signal paths for analysis and backward propagation for training, it relies instead on a symmetric feedback mechanism where part of the input for each stage of sensing comes from its own internal and output signals. A neuron is not a full sensor in its own right, and it’s reasonable to assume that multiple neurons would be clustered so that there is a feedback loop. Many in the neural network AI community are already recognizing the limits of relying on feed-forward and back-prop architectures, but web searches suggest few if any are moving yet to symmetric feedback approaches. I think they should. There’s gold in them there hills!

So, the architecture of the notional sensor array required for our little conscious microphone would have a parallel circuit and feedback loop (possibly but not necessarily integrated), and in all likelihood these parallel and sensing circuits would be heavily symmetrical, i.e. they would use pretty much the same sort of components and architectures as the sensing process itself. If the sensation bit is symmetrical, of similar design to the primary sensing circuit, that again would make it easy to evolve in nature too so is a nice 1st principles biomimetic insight. So this structure has the elegance of being very feasible for evolutionary development, natural or synthetic. It reuses similarly structured components and principles already designed, it’s just recombining a couple of them in a slightly different architecture.

Another useful insight screams for attention too. The feedback loop ensures that the incoming sensation lingers to some degree. Compared to the nanoseconds we are used to in normal IT, the signals in nature travel fairly slowly (~200m/s), and the processing and sensing occur quite slowly (~200Hz). That means this system would have some inbuilt memory that repeats the essence of the sensation in real time – while it is sensing it. It is inherently capable of memory and recall and leaves the door wide open to introduce real-time interaction between memory and incoming signal. It’s not perfect yet, but it has all the boxes ticked to be a prime contender to build thought, concepts, store and recall memories, and in all likelihood, is a potential building brick for higher level consciousness. Throw in recent technology developments such as memristors and it starts to look like we have a very promising toolkit to start building primitive consciousness, and we’re already seeing some AI researchers going that path so maybe we’re not far from the goal. So, we make a deep neural net with nice feedback from output (of the sensing system, which to clarify would be a cluster of neurons, not a single neuron) to input at every stage (and between stages) so that inputs can be detected and sensed, while the input and output signals are stored and repeated into the inputs in real time as the signals are being processed. Throw in some synthetic neurotransmitters to dampen the feedback and prevent overflow and we’re looking at a system that can feel it is feeling something and perceive what it is feeling in real time.

One further insight that immediately jumps out is since the sensing relies on the real time processing of the sensations and feedbacks, the speed of signal propagation, storage, processing and repetition timeframes must all be compatible. If it is all speeded up a million fold, it might still work fine, but if signals travel too slowly or processing is too fast relative to other factors, it won’t work. It will still get a computational result absolutely fine, but it won’t know that it has, it won’t be able to feel it. Therefore… since we have a factor of a million for signal speed (speed of light compared to nerve signal propagation speed), 50 million for switching speed, and a factor of 50 for effective neuron size (though the sensing system units would be multiple neuron clusters), we could make a conscious machine that could think at 50 million times as fast as a natural system (before allowing for any parallel processing of course). But with architectural variations too, we’d need to tune those performance metrics to make it work at all and making physically larger nets would require either tuning speeds down or sacrificing connectivity-related intelligence. An evolutionary design system could easily do that for us.

What else can we deduce about the nature of this circuit from basic principles? The symmetry of the system demands that the output must be an inverse transform of the input. Why? Well, because the parallel, feedback circuit must generate a form that is self-consistent. We can’t deduce the form of the transform from that, just that the whole system must produce an output mathematically similar to that of the input.

I now need to write another blog on how to use such circuits in neural vortexes to generate knowledge, concepts, emotions and thinking. But I’m quite pleased that it does seem that some first-principles analysis of natural evolution already gives us some pretty good clues on how to make a conscious computer. I am optimistic that current research is going the right way and only needs relatively small course corrections to achieve consciousness.

 

Why superhumans are inevitable, and what else comes in the box

Do we have any real choice in the matter of making  super-humans? 20 years ago, I estimated 2005 as the point of no return, and nothing since then has changed my mind on that date. By my reckoning, we are already inevitably committed to designer babies, ebaybies, super-soldiers and super-smart autonomous weapons, direct brain-machine links, electronic immortality, new human races, population explosion, inter-species conflicts and wars with massively powerful weaponry, superhuman conscious AI, smart bacteria, and the only real control we have is relatively minor adjustments on timings. As I was discussing yesterday, the technology potential for this is vast and very exciting, nothing less than a genuine techno-utopia if we use the technologies wisely, but optimum potential doesn’t automatically become reality, and achieving a good outcome is unlikely if many barriers are put in its way.

In my estimation, we have already started the countdown to this group of interconnected technologies – we will very likely get all of them, and we must get ready for the decisions and impacts ahead. At the moment, our society is a small child about to open its super-high-tech xmas presents while fighting with its siblings. Those presents will give phenomenal power far beyond the comprehension of the child or its emotional maturity to equip it to deal with the decisions safely. Our leaders have already squandered decades of valuable preparation time by ignoring the big issues to focus on trivial ones. It is not too late to achieve a good ending, but it won’t happen by accident and we do need to make preparations to avoid pretty big problems.

Both hard and soft warfare – the sword and the pen, already use rapidly advancing AI, and the problems are already running ahead of what the owners intended.

Facebook, Twitter, Instagram and other media giants all have lots of smart people and presumably they mean well, but if so, they have certainly been naive. They maybe hoped to eliminate loneliness, inequality, and poverty and create a loving interconnected global society with global peace, but instead created fake news, social division and conflict and election interference. More likely they didn’t intend either outcome, they just wanted to make money and that took priority over due care and attention..

Miniaturising swarming smart-drones are already the subjects of a new arms race that will deliver almost un-killable machine adversaries by 2050. AI separately is in other arms races to make super-smart AI and super-smart soldiers. This is key to the 2005 point of no return. It was around 2005 that we reached the levels of technology where future AI development all the way to superhuman machine consciousness could be done by individuals, mad scientists or rogue states, even if major powers had banned it. Before 2005, there probably wasn’t quite enough knowledge already on the net to do that. In 2018, lots of agencies have already achieved superiority to humans in niche areas, and other niches will succumb one by one until the whole field of human capability is covered. The first machines to behave in ways not fully understood by humans arrived in the early 1990s; in 2018, neural nets already make lots of decisions at least partly obscured to humans.

This AI development trend will take us to superhuman AI, and it will be able to accelerate development of its own descendants to vastly superhuman AI, fully conscious, with emotions, and its own agendas. That will need humans to protect against being wiped out by superhuman AI. The only three ways we could do that are to either redesign the brain biologically to be far smarter, essentially impossible in the time-frame, to design ways to link our brains to machines, so that we have direct access to the same intelligence as the AIs, so a gulf doesn’t appear and we can remain relatively safe, or pray for super-smart aliens to come to our help, not the best prospect.

Therefore we will have no choice but to make direct brain links to super-smart AI. Otherwise we risk extinction. It is that simple. We have some idea how to do that – nanotech devices inside the brain linking to each and every synapse that can relay electrical signals either way, a difficult but not impossible engineering problem. Best guesses for time-frame fall in the 2045-2050 range for a fully working link that not only relays signals between your organic brain and an IT replica, but by doing so essentially makes external IT just another part of your brain. That conveys some of the other technology gifts of electronic immortality, new varieties of humans, smart bacteria (which will be created during the development path to this link) along with human-variant population explosion, especially in cyberspace, with androids as their physical front end, and the inevitable inter-species conflicts over resources and space – trillions of AI and human-like minds in cyberspace that want to do things in the real world cannot be assumed to be willingly confined just to protect the interests of what they will think of as far lesser species.

Super-smart AI or humans with almost total capability to design whatever synthetic biology is needed to achieve any biological feature will create genetic listings for infinite potential offspring, simulate them, give some of them cyberspace lives, assemble actual embryos for some of them and bring designer babies. Already in 2018, you can pay to get a DNA listing, and blend it in any way you want with the listing of anyone else. It’s already possible to make DNA listings for potential humans and sell them on ebay, hence the term ebaybies. That is perfectly legal, still, but I’ve been writing and lecturing about them since 2004. Today they would just be listings, but we’ll one day have the tech to simulate them, choose ones we like and make them real, even some that were sold as celebrity collector items on ebay. It’s not only too late to start regulating this kind of tech, our leaders aren’t even thinking about it yet.

These technologies are all linked intricately, and their foundations are already in place, with much of the building on those foundations under way. We can’t stop any of these things from happening, they will all come in the same basket. Our leaders are becoming aware of the potential and the potential dangers of the AI positive feedback loop, but at least 15 years too late to do much about it. They have been warned repeatedly and loudly but have focused instead on the minor politics of the day that voters are aware of. The fundamental nature of politics is unlikely to change substantially, so even efforts to slow down the pace of development or to limit areas of impact are likely to be always too little too late. At best, we will be able to slow runaway AI development enough to allow direct brain links to protect against extinction scenarios. But we will not be able to stop it now.

Given inevitability, it’s worth questioning whether there is even any point in trying. Why not just enjoy the ride? Well, the brakes might be broken, but if we can steer the bus expertly enough, it could be exciting and we could come out of it smelling of roses. The weak link is certainly the risk of super-smart AI, whether AI v humans or countries using super-smart AI to fight fiercely for world domination. That risk is alleviated by direct brain linkage, and I’d strongly argue necessitates it, but that brings the other technologies. Even if we decide not to develop it, others will, so one way or another, all these techs will arrive, and our future late century will have this full suite of techs, plus many others of course.

We need as a matter of extreme urgency to fix these silly social media squabbles and over-reactions that are pulling society apart. If we have groups hating each other with access to extremely advanced technology, that can only mean trouble. Tolerance is broken, sanctimony rules, the Inquisition is in progress. We have been offered techno-utopia, but current signs are that most people think techno-hell looks more appetizing and it is their free choice.

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.

 

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

Using robots for gender play

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

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

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

sex-and-robots-british-academy

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

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

Enjoy.