Category Archives: AI

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

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

Universal Basic Income

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

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

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

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

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

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

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

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

Culture tax

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

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

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

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

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

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

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

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

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Monopoly and diversity laws should surely apply to political views too

With all the calls for staff diversity and equal representation, one important area of difference has so far been left unaddressed: political leaning. In many organisations, the political views of staff don’t matter. Nobody cares about the political views of staff in a double glazing manufacturer because they are unlikely to affect the qualities of a window. However, in an organisation that has a high market share in TV, social media or internet search, or that is a government department or a public service, political bias can have far-reaching effects. If too many of its staff and their decisions favor a particular political view, it is danger of becoming what is sometimes called ‘the deep state’. That is, their everyday decisions and behaviors might privilege one group over another. If most of their colleagues share similar views, they might not even be aware of their bias, because they are the norm in their everyday world. They might think they are doing their job without fear of favor but still strongly preference one group of users over another.

Staff bias doesn’t only an organisation’s policies, values and decisions. It also affects recruitment and promotion, and can result in increasing concentration of a particular world view until it becomes an issue. When a vacancy appears at board level, remaining board members will tend to promote someone who thinks like themselves. Once any leaning takes hold, near monopoly can quickly result.

A government department should obviously be free of bias so that it can carry out instructions from a democratically elected government with equal professionalism regardless of its political flavor. Employees may be in positions where they can allocate resources or manpower more to one area than another, or provide analysis to ministers, or expedite or delay a communication, or emphasize or dilute a recommendation in a survey, or may otherwise have some flexibility in interpreting instructions and even laws. It is important they do so without political bias so transparency of decision-making for external observers is needed along with systems and checks and balances to prevent and test for bias or rectify it when found. But even if staff don’t deliberately abuse their positions to deliberately obstruct or favor, if a department has too many staff from one part of the political spectrum, normalization of views can again cause institutional bias and behavior. It is therefore important for government departments and public services to have work-forces that reflect the political spectrum fairly, at all levels. A department that implements a policy from a government of one flavor but impedes a different one from a new government of opposite flavor is in strong need of reform and re-balancing. It has become a deep state problem. Bias could be in any direction of course, but any public sector department must be scrupulously fair in its implementation of the services it is intended to provide.

Entire professions can be affected. Bias can obviously occur in any direction but over many decades of slow change, academia has become dominated by left-wing employees, and primary teaching by almost exclusively female ones. If someone spends most of their time with others who share the same views, those views can become normalized to the point that a dedicated teacher might think they are delivering a politically balanced lesson that is actually far from it. It is impossible to spend all day teaching kids without some personal views and values rub off on them. The young have always been slightly idealistic and left leaning – it takes years of adult experience of non-academia to learn the pragmatic reality of implementing that idealism, during which people generally migrate rightwards -but with a stronger left bias ingrained during education, it takes longer for people to unlearn naiveté and replace it with reality. Surely education should be educating kids about all political viewpoints and teaching them how to think so they can choose for themselves where to put their allegiance, not a long process of political indoctrination?

The media has certainly become more politically crystallized and aligned in the last decade, with far fewer media companies catering for people across the spectrum. There are strongly left-wing and right-wing papers, magazines, TV and radio channels or shows. People have a free choice of which papers to read, and normal monopoly laws work reasonably well here, with proper checks when there is a proposed takeover that might result in someone getting too much market share. However, there are still clear examples of near monopoly in other places where fair representation is particularly important. In spite of frequent denials of any bias, the BBC for example was found to have a strong pro-EU/Remain bias for its panel on its flagship show Question Time:

https://iea.org.uk/media/iea-analysis-shows-systemic-bias-against-leave-supporters-on-flagship-bbc-political-programmes/

The BBC does not have a TV or radio monopoly but it does have a very strong share of influence. Shows such as Question Time can strongly influence public opinion so if biased towards one viewpoint could be considered as campaigning for that cause, though their contributions would lie outside electoral commission scrutiny of campaign funding. Many examples of BBC bias on a variety of social and political issues exist. It often faces accusations of bias from every direction, sometimes unfairly, so again proper transparency must exist so that independent external groups can appeal for change and be heard fairly, and change enforced when necessary. The BBC is in a highly privileged position, paid for by a compulsory license fee on pain of imprisonment, and also in a socially and politically influential position. It is doubly important that it proportionally represents the views of the people rather than acting as an activist group using license-payer funds to push the political views of the staff, engaging in their own social engineering campaigns, or otherwise being propaganda machines.

As for private industry, most isn’t in a position of political influence, but some areas certainly are. Social media have enormous power to influence the views its users are exposed to, choosing to filter or demote material they don’t approve of, as well as providing a superb activist platform. Search companies can choose to deliver results according to their own agendas, with those they support featuring earlier or more prominently than those they don’t. If social media or search companies provide different service or support or access according to political leaning of the customer then they can become part of the deep state. And again, with normalization creating the risk of institutional bias, the clear remedy is to ensure that these companies have a mixture of staff representative of social mix. They seem extremely enthusiastic about doing that for other forms of diversity. They need to apply similar enthusiasm to political diversity too.

Achieving it won’t be easy. IT companies such as Google, Facebook, Twitter currently have a strong left leaning, though the problem would be just as bad if it were to swing the other direction. Given the natural monopoly tendency in each sector, social media companies should be politically neutral, not deep state companies.

AI being developed to filter posts or decide how much attention they get must also be unbiased. AI algorithmic bias could become a big problem, but it is just as important that bias is judged by neutral bodies, not by people who are biased themselves, who may try to ensure that AI shares their own leaning. I wrote about this issue here: https://timeguide.wordpress.com/2017/11/16/fake-ai/

But what about government? Today’s big issue in the UK is Brexit. In spite of all its members being elected or reelected during the Brexit process, the UK Parliament itself nevertheless has 75% of MPs to defend the interests of the 48% voting Remain  and only 25% to represent the other 52%. Remainers get 3 times more Parliamentary representation than Brexiters. People can choose who they vote for, but with only candidate available from each party, voters cannot choose by more than one factor and most people will vote by party line, preserving whatever bias exists when parties select which candidates to offer. It would be impossible to ensure that every interest is reflected proportionately but there is another solution. I suggested that scaled votes could be used for some issues, scaling an MP’s vote weighting by the proportion of the population supporting their view on that issue:

https://timeguide.wordpress.com/2015/05/08/achieving-fair-representation-in-the-new-uk-parliament/

Like company boards, once a significant bias in one direction exists, political leaning tends to self-reinforce to the point of near monopoly. Deliberate procedures need to be put in place to ensure equality or representation, even when people are elected. Obviously people who benefit from current bias will resist change, but everyone loses if democracy cannot work properly.

The lack of political diversity in so many organisations is becoming a problem. Effective government may be deliberately weakened or amplified by departments with their own alternative agendas, while social media and media companies may easily abuse their enormous power to push their own sociopolitical agendas. Proper functioning of democracy requires that this problem is fixed, even if a lot of people like it the way it is.

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.

AI that talks to us could quickly become problematic

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

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

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

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

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

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

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

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

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

 

Futurist memories: The leisure society and the black box economy

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

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

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

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

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.

 

People are becoming less well-informed

The Cambridge Analytica story has exposed a great deal about our modern society. They allegedly obtained access to 50M Facebook records to enable Trump’s team to target users with personalised messages.

One of the most interesting aspects is that unless they only employ extremely incompetent journalists, the news outlets making the biggest fuss about it must be perfectly aware of reports that Obama appears to have done much the same but on a much larger scale back in 2012, but are keeping very quiet about it. According to Carol Davidsen, a senior Obama campaign staffer, they allowed Obama’s team to suck out the whole social graph – because they were on our side – before closing it to prevent Republican access to the same techniques. Trump’s campaign’s 50M looks almost amateur. I don’t like Trump, and I did like Obama before the halo slipped, but it seems clear to anyone who checks media across the political spectrum that both sides try their best to use social media to target users with personalised messages, and both sides are willing to bend rules if they think they can get away with it.

Of course all competent news media are aware of it. The reason some are not talking about earlier Democrat misuse but some others are is that they too all have their own political biases. Media today is very strongly polarised left or right, and each side will ignore, play down or ludicrously spin stories that don’t align with their own politics. It has become the norm to ignore the log in your own eye but make a big deal of the speck in your opponent’s, but we know that tendency goes back millennia. I watch Channel 4 News (which broke the Cambridge Analytica story) every day but although I enjoy it, it has a quite shameless lefty bias.

So it isn’t just the parties themselves that will try to target people with politically massaged messages, it is quite the norm for most media too. All sides of politics since Machiavelli have done everything they can to tilt the playing field in their favour, whether it’s use of media and social media, changing constituency boundaries or adjusting the size of the public sector. But there is a third group to explore here.

Facebook of course has full access to all of their 2.2Bn users’ records and social graph and is not squeaky clean neutral in its handling of them. Facebook has often been in the headlines over the last year or two thanks to its own political biases, with strongly weighted algorithms filtering or prioritising stories according to their political alignment. Like most IT companies Facebook has a left lean. (I don’t quite know why IT skills should correlate with political alignment unless it’s that most IT staff tend to be young, so lefty views implanted at school and university have had less time to be tempered by real world experience.) It isn’t just Facebook of course either. While Google has pretty much failed in its attempt at social media, it also has comprehensive records on most of us from search, browsing and android, and via control of the algorithms that determine what appears in the first pages of a search, is also able to tailor those results to what it knows of our personalities. Twitter has unintentionally created a whole world of mob rule politics and justice, but in format is rapidly evolving into a wannabe Facebook. So, the IT companies have themselves become major players in politics.

A fourth player is now emerging – artificial intelligence, and it will grow rapidly in importance into the far future. Simple algorithms have already been upgraded to assorted neural network variants and already this is causing problems with accusations of bias from all directions. I blogged recently about Fake AI: https://timeguide.wordpress.com/2017/11/16/fake-ai/, concerned that when AI analyses large datasets and comes up with politically incorrect insights, this is now being interpreted as something that needs to be fixed – a case not of shooting the messenger, but forcing the messenger to wear tinted spectacles. I would argue that AI should be allowed to reach whatever insights it can from a dataset, and it is then our responsibility to decide what to do with those insights. If that involves introducing a bias into implementation, that can be debated, but it should at least be transparent, and not hidden inside the AI itself. I am now concerned that by trying to ‘re-educate’ the AI, we may instead be indoctrinating it, locking today’s politics and values into future AI and all the systems that use it. Our values will change, but some foundation level AI may be too opaque to repair fully.

What worries me most though isn’t that these groups try their best to influence us. It could be argued that in free countries, with free speech, anybody should be able to use whatever means they can to try to influence us. No, the real problem is that recent (last 25 years, but especially the last 5) evolution of media and social media has produced a world where most people only ever see one part of a story, and even though many are aware of that, they don’t even try to find the rest and won’t look at it if it is put before them, because they don’t want to see things that don’t align with their existing mindset. We are building a world full of people who only see and consider part of the picture. Social media and its ‘bubbles’ reinforce that trend, but other media are equally guilty.

How can we shake society out of this ongoing polarisation? It isn’t just that politics becomes more aggressive. It also becomes less effective. Almost all politicians claim they want to make the world ‘better’, but they disagree on what exactly that means and how best to do so. But if they only see part of the problem, and don’t see or understand the basic structure and mechanisms of the system in which that problem exists, then they are very poorly placed to identify a viable solution, let alone an optimal one.

Until we can fix this extreme blinkering that already exists, our world can not get as ‘better’ as it should.

 

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.