Category Archives: business

AI is mainly a stimulative technology that will create jobs

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

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

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

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

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

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

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

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

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

 

Advertisements

AI presents a new route to attack corporate value

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

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

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

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

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

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

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

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

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

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

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

PS

This article appeared yesterday that also talks about the bias I mentioned: https://techcrunch.com/2016/12/10/5-unexpected-sources-of-bias-in-artificial-intelligence/

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

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

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

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

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

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

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

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

Can we automate restaurant reviews?

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

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

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

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

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

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

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

Guest post: The Future of Management, by new futurist Branimir Trošić

Delighted to host a guest post by a new futurist Branimir Trošić sharing his thoughts on

The Future of Management

Self-management includes concepts like no hierarchical structures (where no one has any coercive power over anyone else) and the concept of accountability which explains that people must keep their commitments to each other (Josh Alan Dykstra, 2014). Many understand that concept, but can not quite understand how this concept could work in practical situations, partly because there is a problem of understanding this concept with a learned mental model: learned assumptions how the organization should be organized: a hierarchical structure where information flows from top to bottom. Not being able to imagine the alternative and the idea of an organization without managers frightens many: who would be in control, who would be responsible for the company’s strategy, who will lead the way? This concept purports that there is one god-like leader that sits on top of the organization and shows the way. And, usually, organizations are currently organized in that way, but the problem of that kind of organization is that not everyone in the organization understands what “The” leader is communicating, nor do people find themselves accountable for the organization to reach the common goal. Natural state of mind of every individual is that he or she will work for their own interest. And interestingly, this is one of the axioms of economy: an organization will flourish only if the individual within the organization can flourish. The problem of a hierarchical organization is exactly in hierarchy: different levels have different goals, meaning that the goal of the CEO (increasing the profits) is not the same as the goal of the worker at the bottom (usually to finish his/hers daily chores, not minding the efficiency of the work and head home). Hierarchical organizations repeatedly fail at motivating different levels to accept shared vision and to act upon it.

If motivating every worker in the organization is the problem of a hierarchical organization, and if exactly hierarchy is the show stopper in implementing that, then the logical solution would be to remove hierarchy from the organization. Solution sounds simple, but another question imposes: how can this be done in real life? If there is no boss to tell you what to do and how to do it, who should be the one to define the direction?  There were many attempt to foster self-management throughout history, and some experiments didn’t work out. Partially because people were not ready for self-management because of  wrong image of self-managing and self-organizing organization – the question of the master manipulator hangs above that idea, and assumptions that emerge from that mental model actually destroy any possibility of creating a self-organizing organization. What helps us understand that concept is to look at other things that are self-organizing, that thrive at self-organization. If we look at manmade systems, we will not find any examples because of artificial surroundings. In his book  “The necessary revolution” Senge claims that seeing systems is the most important concept that helps cultivate an intelligence that we all possess and in that way to cultivate the positive force for systems intelligence to flourish on a larger scale. When people start seeing systems, they begin to understand the basic flaws in prevailing mental models and alternative futures that are possible (Senge, P., 2014). So, if “artificial” is a characteristic of something that is not self-organizing but imposed, then everything that is not artificial should have also the characteristic of self-organization. The answer is in the question: nature is self-organizing and gives us numerous examples how human organizations should be structured. The best example that one can come across when thinking about self-organizing communities is the community of ants. Ants teach us that there is no hierarchy but specialization, and that type of social structure is called eusociality. Eusociality is the ability for the certain group of ants (or insects) to specialize for certain job or work, losing the ability to do anything else, but in cooperation work to reach the mutual goal (rising of offspring, gathering food, etc..)

In those terms, when same principles apply to human society and/or organizations, then we can understand that all the answers are in the nature, because nature is self-organized and self-managed. Nature teaches us that there is really no need for the manager in a sense of having one god-like persona that directs and tells everybody what to do, but a leader who can help individuals develop their abilities and help people find one’s own purpose.  This type of self-organization has numerous implications, both on the organization itself and on the individual.

From the organization perspective: having  fifty without a manager people that work relentlessly on mutual goal is usually more productive than having one thousand people with managers, each one working on their own goals not understanding the mutual goal. This is partly because managers tend to tell people what they cannot do, rather to empower them to do it. Google organized their project teams of three individuals, with project leadership rotating between them. Similarly how ants do it, they put in charge the one whose abilities are appropriate for given situation. Leader is appointed not according to mutual consent by deciding who has the best leader traits, but by looking which ones traits are the best answer to current problem. Furthermore, when people are empowered to take lead according to their abilities, they are put in surroundings in which management still exists, but a different kind of management: the one where behaviors of both leaders and followers are induced, rather than compelled (Hock, D., 2000.).  In such self-organizations, power is never used; at least not the one whose sole purpose is to boost an ego of a manager, but power whose purpose is to solve the problem. By giving up power and coercive control – you get it back and have access to power. The question imposes why managers are not willing to give up their power. The problem is fear, they try to manage things, force them to their will. To do that immense energy is wasted solely on defending themselves. When this control is let go, the manager/leader then frees up huge amounts of energy spent in wrong way (Watts, W.A.1968.). To be able to let go that control, one should trust their subordinates and this main characteristic of a leader: leader has faith in his followers to do the job, and this trust is born out of humility, a feeling that your subordinates are equal to you, the leader. That freed power that is gained through letting go of control, having faith in subordinates and considering them equal is then divided throughout organization, and when power is divided – everybody becomes the leader, vision becomes mutual. In organizations where everybody is equal and does his best to reach the shared vision, productivity rises because workers stop being active and start being productive: problems are communicated and solved in order to reach the mutual goal. At this point, we should stop using the term self-management and start using the term self-organization. At this point the mental model of an old hierarchical organization becomes obsolete, and its alternative: self-organization becomes clearer. In comparison to hierarchical organization, self-organized one is decentralized, or in Clevelend’s terms: uncentralized, it becomes a real network of cooperation between groups of people specialized by their passion and gained power to work and achieve the mutual goal. When a network of passionate and specialized people starts communicating in such a way, a vision becomes a flux and not a rigid non-flexible axiom.  Since it is a flux, and everybody is a leader, everybody is also invited to participate in creation of that flux. When a self-organization reaches that state, it also becomes a dynamic organization, the one that has the freedom to change (or not to change) from day to day, and is as a chaordic organization powered from periphery, not from center. In this way, the vision will be a goal that can be reached, and the one that cannot live up to its plans. This is why hierarchical organizations fail: since there is no possibility for the people to participate in the vision (the god-like creature at the top is the one who communicates the vision), to change it according to its possibilities, since the people are not empowered to become leaders in their own fields, since power is used in coercive way and taken from people, since there is no trust, no faith, and rule of fear, the probability to reach the goals of the vision is rarely high. Or to put it better: the vision is not the one that is communicated, but the one that is known and not communicated, the taboo: to fulfill the wishes and achieve the ideas of workers direct superior, that often (due to lack of specialization) has anything to do with productive fulfillment of the vision. In that way, we should understand that in hierarchical organizations the real customer whom the whole organization is serving is actually – the CEO, which is, to put it in a simple term: wrong.

From the perspective of an individual, we have to recognize that simple acts of minifying subordinates mistakes and empowering them to decide for themselves how they will contribute to a mutual goal actually transforms unsatisfied workers that probably do not sleep at night  and are afraid of what will happen to them because of the hierarchical relationship with their boss  to a highly productive workers that like to talk of different subjects, proactively solve the problems of the company  and are repeatedly praised. This is the model of how leadership should look like. A leader has to understand that the most productive system is a uncentralized system, with every center being specialized for a certain job, every specialization center should take over the lead when an organization faces the problem which can be solved exactly by that specialization center. This type of organization should be backed also financially, and this can be done in two ways: everybody should start with the same pay-check. The work people do should be then categorized in order to define what type of work brings what type of revenue (or any other benefit to the company), and the basic pay should be multiplied with the index of complexity of the productivity (not activity). In that way, people can choose to do a lot of little improvements that will lead towards reaching the same goal or one big innovation that will be the game changer. The difference between the first worker and the lateral is simply in the knowledge. Knowledgeable workers tend to be more productive by applying their knowledge into daily business.  Second way is to build profit centers and gather specialized people around them. Each profit center should be responsible for their own budget they would receive after committing to reach a goal negotiated with other profit centers. The budget would be dynamic, going up or down on every quarterly forecast depending on contribution profit center had to fulfillment of a goal.

Furthermore, from the perspective of an individual, working in chaordic organization has several benefits. First, by pursuing their passion, people are intrinsically motivated to do what they love to do. And this is the holy grail of motivation: how to intrinsically motivate the worker. The answer is simple: let him or her do whatever they want to do, while they pursue the mutual goal. It does not matter how long they stay at work, do they work from nine to five, or even if they are coming to work, while they have their own way of contributing to an organization. Being able to organize one self, and not to feel that the punishment will follow because bosses requirements are not met is the crucial thing in letting the team go (Medinnila, A, 1998.)

In terms of self-organization, management has no future. At least, not what under the word “management” we understand today. Management will become just one of the jobs being done within the company, not putting people who manage businesses above nor below anybody else. The characteristic of the third industrial revolution: decentralization of production and distribution of services will apparently happen also within the organizations. Social structures will be disrupted, since fewer and fewer people are prone to be their own boss, there is not a single reason not to create organizations and companies according to those who make the company: people. And only in the moment when every single employee is a leader within his or hers line of work, when every leader works and collaborates with a goal to reach a mutual goal, then the noun “company” will achieve it’s true meaning. Until then, people will work in slaveries, not companies, being unproductive, unimaginative and unmotivated.

We should doubt that there is any possibility of changing current companies in such a way, but new ones with described structure will arise, become disruptive, more efficient and the same thing will happen that happens with all the companies that refuse to adapt and ride the tsunami of the future: they will go bankrupt.  It is a model in which internet replaced tv and other media, how air b’n’b replaced booking the hotel, Uber the taxi and all other examples how new emerging models had disruptive effect towards old economy of scarcity models.

The disruptive transformation of a company is a transformation of doing business, and also, in a way a transformation of how we live.

Branimir’s contact details:

Branimir Trosic, btrosic23@gmail.com

How to decide green policies

Many people in officialdom seem to love putting ticks in boxes. Apparently once all the boxes are ticked, a task can be put in the ‘mission accomplished’ cupboard and forgotten about. So watching some of the recent political debate in the run-up to our UK election, it occurred to me that there must be groups of people discussing ideas for policies and then having meetings to decide whether they tick the right boxes to be included in a manifesto. I had some amusing time thinking about how a meeting might go for the Green Party. A little preamble first.

I could write about any of the UK parties I guess. Depending on your choice of media nicknames, we have the Nasty Party, the Fruitcake Racist Party, the Pedophile Empathy Party, the Pedophile and Women Molesting Party, the National Suicide Party (though they get their acronym in the wrong order) and a few Invisible Parties. OK, I invented some of those based on recent news stories of assorted facts and allegations and make no assertion of any truth in any of them whatsoever. The Greens are trickier to nickname – ‘The Poverty and Oppression Maximization, Environmental Destruction, Economic Collapse, Anti-science, Anti-fun and General Misery Party’ is a bit of a mouthful. I like having greens around, just so long as they never win control. No matter how stupid a mistake I might ever make, I’ll always know that greens would have made a worse one.

So what would a green policy development meeting might be like? I’ll make the obvious assumption that the policies don’t all come from the Green MP. Like any party, there are local groups of people, presumably mostly green types in the wider sense of the word, who produce ideas to feed up the ladder. Many won’t even belong to any official party, but still think of themselves as green. Some will have an interest mainly in socialism, some more interested in environmentalism, most will be a blend of the two. And to be fair, most of them will be perfectly nice people who want to make the world a better place, just like the rest of us. I’ve met a lot of greens, and we do agree at least on motive even if I think they are wrong on most of their ideas of how to achieve the goals. We all want world peace and justice, a healthy environment and to solve poverty and oppression. The main difference between us is deciding how best to achieve all that.

So I’ll look at green debate generally as a source of the likely discussions, rather than any actual Green Party manifesto, even though that still looks pretty scary. To avoid litigation threats and keep my bank balance intact, I’ll state that this is only a personal imagining of what might go into such green meetings, and you can decide for yourself how much it matches up to the reality. It is possible that the actual Green Party may not actually run this way, and might not support some of the policies I discuss, which are included in this piece based on wider green debate, not the Green Party itself. Legal disclaimers in place, I’ll get on with my imagining:

Perhaps there might be some general discussion over the welcome coffee about how awful it is that some nasty capitalist types make money and there might be economic growth, how terrible it is that scientists keep discovering things and technologists keep developing them, how awful it is that people are allowed to disbelieve in a global warming catastrophe and still be allowed to roam free and how there should be a beautiful world one day where a green elite is in charge, the population has been culled down to a billion or two and everyone left has to do everything they say on pain of imprisonment or death. After coffee, the group migrates to a few nice recycled paper flip-charts to start filling them with brainstormed suggestions. Then they have to tick boxes for each suggestion to filter out the ones not dumb enough to qualify. Then make a nice summary page with the ones that get all the boxes ticked. So what boxes do they need? And I guess I ought to give a few real examples as evidence.

Environmental destruction has to be the first one. Greens must really hate the environment, since the majority of green policies damage it, but they manage to get them implemented via cunning marketing to useful idiots to persuade them that the environment will benefit. The idiots implement them thinking the environment will benefit, but it suffers.  Some quick examples:

Wind turbines are a big favorite of greens, but planted on peat bogs in Scotland, the necessary roads cause the bogs to dry out, emitting vast quantities of CO2 and destroying the peat ecosystem. Scottish wind turbines also kill eagles and other birds.

In the Far East, many bogs have been drained to grow palm oil for biofuels, another green favorite that they’ve managed to squeeze into EU law. Again, vast quantities of CO2, and again ecosystem destruction.

Forests around the world have been cut down to make room for palm oil plantations too, displacing local people, destroying an ecosystem to replace it with one to meet green fuel targets.

Still more forests have been cut down to enable new ones to be planted to cash in on  carbon offset schemes to keep corporate greens happy that they can keep flying to all those green conferences without feeling guilt. More people displaced, more destruction.

Staying with biofuels, a lot of organic waste from agriculture is converted to biofuels instead of ploughing it back into the land. Soil structure therefore deteriorates, damaging ecosystem and damaging future land quality. CO2 savings by making the bio-fuel are offset against locking the carbon up in soil organic matter so there isn’t much benefit even there, but the damage holds.

Solar farms are proliferating in the UK, often occupying prime agricultural land that really ought to be growing food for the many people in the world still suffering from malnutrition. The same solar panels could have been sent to otherwise useless desert areas in a sunny country and used to displace far more fossil fuels and save far more CO2 without reducing food production. Instead, people in many African countries have to use wood stoves favored by greens as sustainable, but which produce airborne particles that greatly reduce health. Black carbon resulting from open wood fires also contributes directly to warming.

Many of the above policy effects don’t just tick the environmental destruction box, but also the next ones poverty and oppression maximization. Increasing poverty resulted directly from increasing food prices as food was grown to be converted into bio-fuel. Bio-fuels as first implemented were a mind-numbingly stupid green policy. Very many of the world’s poorest people have been forcefully pushed out of their lands and into even deeper poverty to make space to grow bio-fuel crops. Many have starved or suffered malnutrition. Entire ecosystems have been destroyed, forests replaced, many animals pushed towards extinction by loss of habitat. More recently, even greens have realized the stupidity and these polices are slowly being fixed.

Other green policies see economic development by poor people as a bad thing because it increases their environmental footprint. The poor are therefore kept poor. Again, their poverty means they can’t use modern efficient technology to cook or keep warm, they have to chop trees to get wood to burn, removing trees damages soil integrity, helps flooding, burning them produces harmful particles and black carbon to increase warming. Furthermore, with too little money to buy proper food, some are forced to hunt or buy bushmeat, endangering animal species and helping to spread viruses between closely genetically-related animals and humans.

So a few more boxes appear. All the above polices achieved pretty much the opposite of what they presumably intended, assuming the people involved didn’t actually want to destroy the world. Maybe a counterproductive box needs to be ticked too.

Counterproductive links well to another of the green’s apparent goals, of economic collapse. They want to stop economic growth. They want to reduce obsolescence.  Obsolescence is the force that drives faster and faster progress towards devices that give us a high quality of life with a far lower environmental impact, with less resource use, lower energy use, and less pollution. If you slow obsolescence down because green dogma says it is a bad thing, all those factors worsen. The economy also suffers. The economy suffers again if energy prices are deliberately made very high by adding assorted green levies such as carbon taxes, or renewable energy subsidies.  Renewable energy subsidies encourage more oppression of people who really don’t want wind turbines nearby, causing them stress and health problems, disrupting breeding cycles of small wild animals in the areas, reducing the value of people’s homes, while making the companies that employ hem less able to compete internationally, so increasing bankruptcy, redundancy and making even more poverty. Meanwhile the rich wind farm owners are given lots of money from poor people who are forced to buy their energy and pay higher taxes for the other half of their subsidy. The poor take all the costs, the rich take all the benefits. That could be another box to tick, since it seems pretty universal in green policy So much for  policies that are meant to be socialist! Green manifesto policies would make some of these problems far worse still. Business would be strongly loaded with extra costs and admin, and the profits they can still manage to make would be confiscated to pay for the ridiculous spending plans. With a few Greens in power, damage will be limited and survivable. If they were to win control, our economy would collapse totally in a rapidly accelerating debt spiral.

Greens hate science and technology, another possible box to tick. I once chatted to one of the Green leaders (I do go to environmental events sometimes if I think I can help steer things in a more logical direction), and was told ‘the last thing we need is more science’. But it is science and technology that makes us able to live in extreme comfort today alongside a healthy environment. 100 years ago, pollution was terrible. Rivers caught fire. People died from breathing in a wide variety of pollutants. Today, we have clean water and clean air. Thanks to increasing CO2 levels – and although CO2 certainly does contribute to warming, though not as much as feared by warmist doom-mongers, it also has many positive effects – there is more global greenery today than decades ago. Plants thrive as CO2 levels increase so they are growing faster and healthier. We can grow more food and forests can recover faster from earlier green destruction.

The greens also apparently have a box that ‘prevents anyone having any fun’. Given their way, we’d be allowed no meat, our homes would all have to be dimly lit and freezing cold, we’d have to walk everywhere or wait for buses in the rain. Those buses would still burn diesel fuel, which kills thousands of people every year via inhalation of tiny particulates. When you get anywhere, you’d have to use ancient technologies that have to be fixed instead of replaced. You’d have to do stuff that doesn’t use much energy or involve eating anything nice, going anywhere nice because that would involve travel and travel is bad, except for greens, who can go to as many international conferences as they want.

So if the greens get their way, if people are dumb enough to fall for promises of infinite milk and honey for all, all paid for by taxing 3 bankers, then the world we’d live in would very quickly have a devastated environment, a devastated economy, a massive transfer of wealth from the poor to a few rich people, enormous oppression, increasing poverty, decreasing health, no fun at all. In short, with all the above boxes checked, the final summary box to get the policy into manifesto must be ‘increases general misery‘.

An interesting list of boxes to tick really. It seems that all truly green policies must:

  1. Cause environmental destruction
  2. Increase poverty and oppression
  3. Be counterproductive
  4. Push towards economic collapse
  5. Make the poor suffer all the costs while the rich (and Green elite) reap the benefits
  6. Impede further science and technology development
  7. Prevent anyone having fun
  8. Lead to general misery

This can’t be actually how they run their meetings I suppose: unless they get someone from outside with a working brain to tick the boxes, the participants would need to have some basic understanding of the actual likely consequences of their proposals and to be malign, and there is little evidence to suggest any of them do understand, and they are mostly not malign. Greens are mostly actually quite nice people, even the ones in politics, and I do really think they believe in what they are doing. Their hearts are usually in the right place, it’s just that their brains are missing or malfunctioning. All of the boxes get ticked, it’s just unintentionally.

I rest my case.

 

 

 

The IT dark age – The relapse

I long ago used a slide in my talks about the IT dark age, showing how we’d come through a period (early 90s)where engineers were in charge and it worked, into an era where accountants had got hold of it and were misusing it (mid 90s), followed by a terrible period where administrators discovered it and used it in the worst ways possible (late 90s, early 00s). After that dark age, we started to emerge into an age of IT enlightenment, where the dumbest of behaviors had hopefully been filtered out and we were starting to use it correctly and reap the benefits.

Well, we’ve gone into relapse. We have entered a period of uncertain duration where the hard-won wisdom we’d accumulated and handed down has been thrown in the bin by a new generation of engineers, accountants and administrators and some extraordinarily stupid decisions and system designs are once again being made. The new design process is apparently quite straightforward: What task are we trying to solve? How can we achieve this in the least effective, least secure, most time-consuming, most annoying, most customer loyalty destructive way possible? Now, how fast can we implement that? Get to it!

If aliens landed and looked at some of the recent ways we have started to use IT, they’d conclude that this was all a green conspiracy, designed to make everyone so anti-technology that we’d be happy to throw hundreds of years of progress away and go back to the 16th century. Given that they have been so successful in destroying so much of the environment under the banner of protecting it, there is sufficient evidence that greens really haven’t a clue what they are doing, but worse still, gullible political and business leaders will cheerfully do the exact opposite of what they want as long as the right doublespeak is used when they’re sold the policy.

The main Green laboratory in the UK is the previously nice seaside town of Brighton. Being an extreme socialist party, that one might think would be a binperson’s best friend, the Greens in charge nevertheless managed to force their binpeople to go on strike, making what ought to be an environmental paradise into a stinking litter-strewn cesspit for several weeks. They’ve also managed to create near-permanent traffic gridlock supposedly to maximise the amount of air pollution and CO2 they can get from the traffic.

More recently, they have decided to change their parking meters for the very latest IT. No longer do you have to reach into your pocket and push a few coins into a machine and carry a paper ticket all the way back to your car windscreen. Such a tedious process consumed up to a minute of your day. It simply had to be replaced with proper modern technology. There are loads of IT solutions to pick from, but the Greens apparently decided to go for the worst possible implementation, resulting in numerous press reports about how awful it is. IT should not be awful, it can and should be done in ways that are better in almost every way than old-fashioned systems. I rarely drive anyway and go to Brighton very rarely, but I am still annoyed at incompetent or deliberate misuse of IT.

If I were to go there by car, I’d also have to go via the Dartford Crossing, where again, inappropriate IT has been used incompetently to replace a tollbooth system that makes no economic sense in the first place. The government would be better off if it simply paid for it directly. Instead, each person using it is likely to be fined if they don’t know how it operates, and even if they do, they have to spend a lot more expensive time and effort to pay than before. Again, it is a severe abuse of IT, conferring a tiny benefit on a tiny group of people at the expense of significant extra load on very many people.

Another financial example is the migration to self-pay terminals in shops. In Stansted Airport’s W H Smith a couple of days ago, I sat watching a long queue of people taking forever to buy newspapers. Instead of a few seconds handing over a coin and walking out, it was taking a minute or more to read menus, choose which buttons to touch, inspecting papers to find barcodes, fumbling for credit cards, checking some more boxes, checking they hadn’t left their boarding pass or paper behind, and finally leaving. An assistant stood there idle, watching people struggle instead of serving them in a few seconds. I wanted a paper but the long queue was sufficient deterrent and they lost the sale. Who wins in such a situation? The staff who lost their jobs certainly didn’t. I as the customer had no paper to read so I didn’t win. I would be astonished with all the lost sales if W H Smith were better off so they didn’t win. The airport will likely make less from their take too. Even the terminal manufacturing industry only swaps one type of POS terminal for another with marginally different costs. I’m not knocking W H Smith, they are just another of loads of companies doing this now. But it isn’t progress, it is going backwards.

When I arrived at my hotel, another electronic terminal was replacing a check-in assistant with a check-in terminal usage assistant. He was very friendly and helpful, but check-in wasn’t any easier or faster for me, and the terminal design still needed him to be there too because like so many others, it was designed by people who have zero understanding of how other people actually do things.  Just like those ticket machines in rail stations that we all detest.

When I got to my room, the thermostat used a tiny LCD panel, with tiny meaningless symbols, with no backlight, in a dimly lit room, with black text on a dark green background. So even after searching for my reading glasses, since I hadn’t brought a torch with me, I couldn’t see a thing on it so I couldn’t use the air conditioning. An on/off switch and a simple wheel with temperature marked on it used to work perfectly fine. If it ain’t broke, don’t do your very best to totally wreck it.

These are just a few everyday examples, alongside other everyday IT abuses such as minute fonts and frequent use of meaningless icons instead of straightforward text. IT is wonderful. We can make devices with absolutely superb capability for very little cost. We can make lives happier, better, easier, healthier, more prosperous, even more environmentally friendly.

Why then are so many people so intent on using advanced IT to drag us back into another dark age?

 

 

Stimulative technology

You are sick of reading about disruptive technology, well, I am anyway. When a technology changes many areas of life and business dramatically it is often labelled disruptive technology. Disruption was the business strategy buzzword of the last decade. Great news though: the primarily disruptive phase of IT is rapidly being replaced by a more stimulative phase, where it still changes things but in a more creative way. Disruption hasn’t stopped, it’s just not going to be the headline effect. Stimulation will replace it. It isn’t just IT that is changing either, but materials and biotech too.

Stimulative technology creates new areas of business, new industries, new areas of lifestyle. It isn’t new per se. The invention of the wheel is an excellent example. It destroyed a cave industry based on log rolling, and doubtless a few cavemen had to retrain from their carrying or log-rolling careers.

I won’t waffle on for ages here, I don’t need to. The internet of things, digital jewelry, active skin, AI, neural chips, storage and processing that is physically tiny but with huge capacity, dirt cheap displays, lighting, local 3D mapping and location, 3D printing, far-reach inductive powering, virtual and augmented reality, smart drugs and delivery systems, drones, new super-materials such as graphene and molybdenene, spray-on solar … The list carries on and on. These are all developing very, very quickly now, and are all capable of stimulating entire new industries and revolutionizing lifestyle and the way we do business. They will certainly disrupt, but they will stimulate even more. Some jobs will be wiped out, but more will be created. Pretty much everything will be affected hugely, but mostly beneficially and creatively. The economy will grow faster, there will be many beneficial effects across the board, including the arts and social development as well as manufacturing industry, other commerce and politics. Overall, we will live better lives as a result.

So, you read it here first. Stimulative technology is the next disruptive technology.

 

The future of MBAs

I’ve reached M in my ‘the future of’ series. So, MBAs.

We have all had to sit through talks where the speaker thinks that using lots of points that start with the same letter is somehow impressive. During one such talk, I got bored and produced this one letter fully comprehensive MBA. Enjoy:

Corporate Cycle

The future of walled gardens

In the physical world, walled gardens are pretty places we visit, pay an entry fee, then enjoy the attractions therein. It is well understood that people often only value what they have to pay for and walled gardens capitalise on that. While there, we may buy coffees or snacks from the captive facilities at premium prices and we generally accept that premium as normal practice. Charging an entry fee ensures that people are more likely to stay inside for longer, using services (picnic areas, scenery, toilets etc) they have already paid for rather than similar ones outside that may be free and certainly instead of paying another provider as well.

In the content industry, the term applies to bundles of services from a particular supplier or available on a particular platform. There is some financial, psychological, convenience, time or other cost to enter and then to leave. Just as with the real thing, they have a range of attractions within that make people want to enter, and once there, they will often access local service variants rather than pay the penalty to leave and access perhaps better ones elsewhere. Our regulators started taking notice of them in the early days of cable TV, addressed the potential abuses and sometimes took steps to prevent telecoms or cable companies from locking customers in. More recently, operating system and device manufacturers have also fallen under the same inspection.

Commercial enterprises have an interest in keeping customers within their domain so that they can extract the most profit from them. What is less immediately obvious is why customers allow it. If people want to use a particular physical facility, such as an airport, or a particular tourist attraction such as a city, or indeed a walled garden, then they have to put up with the particular selection of shops and restaurants there, and are vulnerable to exploitation such as higher prices because of the lack of local choice. There is a high penalty in time and expense to find an alternative. With device manufacturers, the manufacturer is in an excellent position to force customers to use services from those they have selected, and that enables them to skim charges for transactions, sometimes from both ends. The customer can only avoid that by using multiple devices, which incurs a severe cost penalty. There may be some competition among apps within the same garden, but all are subject to the rules of the garden. Operating systems are also walled gardens, but the OS usually just goes with the choice of device. It may be possible to swap to an alternative, but few users bother; most just accept the one that it comes with.

Walled gardens in the media are common but easier to avoid. With free satellite and terrestrial TV as well as online video and TV services, there is now abundant choice, though each provider still tries to make cute little walled gardens if they can. Customers can’t get access to absolutely all content unless they pay multiple subscriptions, but can minimize outlay by choosing the most appropriate garden for their needs and staying in it.

The web has disappointed though. When it was young, many imagined it would become a perfect market, with suppliers offering services and everyone would see all the offerings, all the prices and make free decisions where to buy and deal direct without having to pay for intermediaries. It has so badly missed the target that Berners Lee and others are now thinking how it can be redesigned to achieve the original goals. Users can theoretically browse freely, but the services they actually want to use often become natural monopolies, and can then expand organically into other territories, becoming walled gardens. The salvation is that new companies can always emerge that provide an alternative. It’s impossible to monopolize cyberspace. Only bits of it can be walled off.

Natural monopolies arise when people have free access to everything but one supplier offers something unique and thus becomes the only significant player. Amazon wasn’t a walled garden when it started so much as a specialist store that grew into a small mall and is now a big cyber-city. Because it is so dominant and facilitates buying from numerous suppliers, it certainly qualifies as a walled garden now, but it is still possible to easily find many other stores. By contrast, Facebook has been a walled garden since its infancy, with a miniature web-like world inside its walls with its own versions of popular services. It can monitor and exploit the residents for as long as it can prevent them leaving. The primary penalties for leaving are momentarily losing contact with friends and losing interface familiarity, but I have never understood why so many people spend so much of their time locked within its walls rather than using the full range of web offerings available to them. The walls seem very low, and the world outside is obviously attractive, so the voluntary confinement is beyond my comprehension.

There will remain be a big incentive for companies to build walled gardens and plenty of scope for making diverse collections of unique content and functions too and plenty of companies wanting to make theirs as attractive as possible and attempt to keep people inside. However, artificial intelligence may well change the way that networked material is found, so the inconvenience wall may vanish, along with the OS and interface familiarity walls. Deliberate barriers and filters may prevent it gaining access to some things, but without deliberate obstruction, many walled gardens may only have one side walled, that of price for unique content. If that is all it has to lock people in, then it may really be no different conceptually from a big store. Supermarkets offer this in the physical world, but many other shops remain.

If companies try to lock in too much content in one place, others will offer competing packages. It would make it easier for competitors and that is a disincentive. If a walled garden becomes too greedy, its suppliers and customers will go elsewhere. The key to managing them is to ensure diversity by ensuring the capability to compete. Diversity keeps them naturally in check.

Network competition may well be key. If users have devices that can make their own nets or access many externally provided ones, the scope for competition is high, and the ease of communicating and dealing directly is also high. It will be easy for producers to sell content direct and avoid middlemen taking a cut. That won’t eliminate walled gardens, because some companies will still do exclusive deals and not want to deal direct. There are many attractive business models available to potential content producers and direct selling is only one. Also, as new streams of content become attractive, they are sometimes bought, and this can be the intended exit strategy for start-ups.

Perhaps that is where we are already at. Lots of content that isn’t in walled gardens exists and much is free. Much is exclusive to walled gardens. It is easy to be influenced by recent acquisitions and market fluctuations, but really, the nature of the market hasn’t really changed, it just adapts to new physical platforms. In the physical world, we are free to roam but walled gardens offer attractive destinations. The same applies to media. Walled gardens won’t go away, but there is also no reason to expect them to take over completely. With new networks, new business models, new entrepreneurs, new content makers, new viewing platforms, the same business diversity will continue. Fluctuating degrees of substitution rather than full elimination will continue to be the norm.

Or maybe I’m having an off-day and just can’t see something important. Who knows?

 

 

More future fashion fun

A nice light hearted shorty again. It started as one on smart makeup, but I deleted that and will do it soon. This one is easier and in line with today’s news.

I am the best dressed and most fashion conscious futurologist in my office. Mind you, the population is 1. I liked an article in the papers this morning about Amazon starting to offer 3D printed bobble-heads that look like you.

See: http://t.co/iFBtEaRfBd.

I am especially pleased since I suggested it over 2 years ago  in a paper I wrote on 3D printing.

https://timeguide.wordpress.com/2012/04/30/more-uses-for-3d-printing/

In the news article, you see the chappy with a bobble-head of him wearing the same shirt. It is obvious that since Amazon sells shirts too, that it won’t be long at all before they send you cute little avatars of you wearing the outfits you buy from them. It starts with bobble-heads but all the doll manufacturers will bring out versions based on their dolls, as well as character merchandise from films, games, TV shows. Kids will populate doll houses with minis of them and their friends.

You could even give one of a friend to them for a birthday present instead of a gift voucher, so that they can see the outfit you are offering them before they decide whether they want that or something different. Over time, you’d have a collection of minis of you and your friends in various outfits.

3D cameras are coming to phones too, so you’ll be able to immortalize embarrassing office party antics in 3D office ornaments. When you can’t afford to buy an outfit or accessory sported by your favorite celeb, you could get a miniature wearing it. Clothing manufacturers may well appreciate the extra revenue from selling miniatures of their best kit.

Sports manufacturers will make replicas of you wearing their kit, doing sporting activities. Car manufacturers will have ones of you driving the car they want you to buy, or you could buy a fleet of miniatures. Holiday companies could put you in a resort hotspot. Or in a bedroom ….with your chosen celeb.

OK, enough.