Who’ll Win the Next War: the Tank or the Geek?

I was asked on Quora how the tanks of the future are going to be designed. Here’s my answer – I hope it’ll make you reflect once again on the future of war and what it entails.

And now, consider this: the Israeli Merkava Mark IV tank.

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Merkava Mark IV. Source: Michael Mass, Yad La-Shiryon, found on Wikipedia

It is one of the most technologically advanced tanks in the world. It is armed with a massive 120 mm smoothbore gun that fires shells with immense explosive power, with two roof-mounted machine guns, and with a 60 mm mortar in case the soldiers inside really want to make a point. However, the tank has to be deployed on the field, and needs to reach its target. It also costs around $6 million.

Now consider this: the Israeli geek (picture taken from the Israeli reality show – Beauty and the Geek). The geek is the one on the left, in case you weren’t sure.

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The common Israeli Geek. He’s the one on the left of the picture. Source: Israeli reality show – Beauty and the Geek.

With the click of a button and the aid of some hacking software available on the Darknet, our humble Israeli geek can paralyze whole institutions, governments and critical infrastructures. He can derail trains (happened in Poland), deactivate sewage pumps and mix contaminated water with drinking water (happened in Texas), or even cut the power supply to tens of thousands of people (happened in Ukraine). And if that isn’t bad enough, he could take control over the enemy female citizens’ wireless vibrators and operate it to his and/or their satisfaction (potentially happened already).

Oh, and the Israeli geek works for free. Why? Because he loves hacking stuff. Just make sure you cover the licensing costs for the software he’s using, or he might hack your vibrator next.

So, you asked – “how will futuristic tanks be designed”?

I answer, “who cares”?

 

But Seriously Now…

When you’re thinking of the future, you have to realize that some paradigms are going to change. One of those paradigms is that of physical warfare. You see, tanks were created to do battle in a physical age, in which they had an important role: to protect troops and provide overwhelming firepower while bringing those troops wherever they needed to be. That was essentially the German blizkrieg strategy.

In the digital age, however, everything is connected to the internet, or very soon will be. Not just every computer, but every bridge, every building, every power plant and energy grid, and every car. And as security futurist Marc Goodman noted in his book Future Crimes, “when everything is connected, everything is vulnerable”. Any piece of infrastructure that you connect to the internet, immediately becomes vulnerable to hacking.

Now, here’s a question for you: what is the purpose of war?

I’ll give you a hint: it’s not about driving tanks with roaring engines around. It’s not about soldiers running and shooting in the field. It’s not even about dropping bombs from airplanes. All of the above are just tools for achieving the real purpose: winning the war by either making the enemy surrender to you, or neutralizing it completely.

And how do you neutralize the enemy? It’s quite simple: you demolish the enemy’s factories; you destroy their cities; you ruin your enemy’s citizens morale to the point where they can’t fight you anymore.

In the physical age, armies clashed on the field because each army was on the way to the other side’s cities and territory. That’s why you needed fast tanks with awesome armanent and armor. But today, in the digital age, hackers can leap straight over the battlefield, and make war directly between cities in real-time. They can shut down hospitals and power plants, kill everyone with a heart pacemaker or an insulin pump, and make trains and cars collide with each other. In short, they could shut down entire cities.

So again – who needs tanks?

 

And Still…

I’m not saying there aren’t going to be tanks. The physical aspect of warfare still counts, and one can’t just disregard it. However, tanks simply don’t count as much in comparison to the cyber-security aspects of warfare (partly because tanks themselves are connected nowadays).

Again, that does not mean that tanks are useless. We still need to figure out the exact relationships between tanks and geeks, and precisely where, when and how needs to be deployed in the new digital age. But if you were to ask me in ten years what’s more important – the tank or the geek – then my bet would definitely be on the geek.

 


If this aspect of future warfare interests you, I invite you to read the two papers I’ve published in the European Journal of Futures Research and in Foresight, about future scenarios for crime and terror that rely on the internet of things.

The three AI waves that will shape the future

I’ve done a lot of writing and research recently about the bright future of AI: that it’ll be able to analyze human emotions, understand social nuances, conduct medical treatments and diagnoses that overshadow the best human physicians, and in general make many human workers redundant and unnecessary.

I still stand behind all of these forecasts, but they are meant for the long term – twenty or thirty years into the future. And so, the question that many people want answered is about the situation at the present. Right here, right now. Luckily, DARPA has decided to provide an answer to that question.

DARPA is one of the most interesting US agencies. It’s dedicated to funding ‘crazy’ projects – ideas that are completely outside the accepted norms and paradigms. It should could as no surprise that DARPA contributed to the establishment of the early internet and the Global Positioning System (GPS), as well as a flurry of other bizarre concepts, such as legged robots, prediction markets, and even self-assembling work tools. Ever since DARPA was first founded, it focused on moonshots and breakthrough initiatives, so it should come as no surprise that it’s also focusing on AI at the moment.

Recently, DARPA’s Information Innovation Office has released a new Youtube clip explaining the state of the art of AI, outlining its capabilities in the present – and considering what it could do in the future. The online magazine Motherboard has described the clip as “Targeting [the] AI hype”, and as being a “necessary viewing”. It’s 16 minutes long, but I’ve condensed its core messages – and my thoughts about them – in this post.

The Three Waves of AI

DARPA distinguishes between three different waves of AI, each with its own capabilities and limitations. Out of the three, the third one is obviously the most exciting, but to understand it properly we’ll need to go through the other two first.

First AI Wave: Handcrafted Knowledge

In the first wave of AI, experts devised algorithms and software according to the knowledge that they themselves possessed, and tried to provide these programs with logical rules that were deciphered and consolidated throughout human history. This approach led to the creation of chess-playing computers, and of deliveries optimization software. Most of the software we’re using today is based on AI of this kind: our Windows operating system, our smartphone apps, and even the traffic lights that allow people to cross the street when they press a button.

Modria is a good example for the way this AI works. Modria was hired in recent years by the Dutch government, to develop an automated tool that will help couples get a divorce with minimal involvement from lawyers. Modria, which specializes in the creation of smart justice systems, took the job and devised an automated system that relies on the knowledge of lawyers and divorce experts.

On Modria’s platform, couples that want to divorce are being asked a series of questions. These could include questions about each parent’s preferences regarding child custody, property distribution and other common issues. After the couple answers the questions, the systems automatically identifies the topics about which they agree or disagree, and tries to direct the discussions and negotiations to reach the optimal outcome for both.

First wave AI systems are usually based on clear and logical rules. The systems examine the most important parameters in every situation they need to solve, and reach a conclusion about the most appropriate action to take in each case. The parameters for each type of situation are identified in advance by human experts. As a result, first wave systems find it difficult to tackle new kinds of situations. They also have a hard time abstracting – taking knowledge and insights derived from certain situations, and applying them to new problems.

To sum it up, first wave AI systems are capable of implementing simple logical rules for well-defined problems, but are incapable of learning, and have a hard time dealing with uncertainty.

Now, some of you readers may at this point shrug and say that this is not artificial intelligence as most people think of. The thing is, our definitions of AI have evolved over the years. If I were to ask a person on the street, thirty years ago, whether Google Maps is an AI software, he wouldn’t have hesitated in his reply: of course it is AI! Google Maps can plan an optimal course to get you to your destination, and even explain in clear speech where you should turn to at each and every junction. And yet, many today see Google Maps’ capabilities as elementary, and require AI to perform much more than that: AI should also take control over the car on the road, develop a conscientious philosophy that will take the passenger’s desires into consideration, and make coffee at the same time.

Well, it turns out that even ‘primitive’ software like Modria’s justice system and Google Maps are fine examples for AI. And indeed, first wave AI systems are being utilized everywhere today.

Second AI Wave: Statistical Learning

In the year 2004, DARPA has opened its first Grand Challenge. Fifteen autonomous vehicles competed at completing a 150 mile course in the Mojave desert. The vehicles relied on first wave AI – i.e. a rule-based AI – and immediately proved just how limited this AI actually is. Every picture taken by the vehicle’s camera, after all, is a new sort of situation that the AI has to deal with!

To say that the vehicles had a hard time handling the course would be an understatement. They could not distinguish between different dark shapes in images, and couldn’t figure out whether it’s a rock, a far-away object, or just a cloud obscuring the sun. As the Grand Challenge deputy program manager had said, some vehicles – “were scared of their own shadow, hallucinating obstacles when they weren’t there.”

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The sad result of the first DARPA Grand Challenge

None of the groups managed to complete the entire course, and even the most successful vehicle only got as far as 7.4 miles into the race. It was a complete and utter failure – exactly the kind of research that DARPA loves funding, in the hope that the insights and lessons derived from these early experiments would lead to the creation of more sophisticated systems in the future.

And that is exactly how things went.

One year later, when DARPA opened Grand Challenge 2005, five groups successfully made it to the end of the track. Those groups relied on the second wave of AI: statistical learning. The head of one of the winning groups was immediately snatched up by Google, by the way, and set in charge of developing Google’s autonomous car.

In second wave AI systems, the engineers and programmers don’t bother with teaching precise and exact rules for the systems to follow. Instead, they develop statistical models for certain types of problems, and then ‘train’ these models on many various samples to make them more precise and efficient.

Statistical learning systems are highly successful at understanding the world around them: they can distinguish between two different people or between different vowels. They can learn and adapt themselves to different situations if they’re properly trained. However, unlike first wave systems, they’re limited in their logical capacity: they don’t rely on precise rules, but instead they go for the solutions that “work well enough, usually”.

The poster boy of second wave systems is the concept of artificial neural networks. In artificial neural networks, the data goes through computational layers, each of which processes the data in a different way and transmits it to the next level. By training each of these layers, as well as the complete network, they can be shaped into producing the most accurate results. Oftentimes, the training requires the networks to analyze tens of thousands of data sources to reach even a tiny improvement. But generally speaking, this method provides better results than those achieved by first wave systems in certain fields.

So far, second wave systems have managed to outdo humans at face recognition, at speech transcription, and at identifying animals and objects in pictures. They’re making great leaps forward in translation, and if that’s not enough – they’re starting to control autonomous cars and aerial drones. The success of these systems at such complex tasks leave AI experts aghast, and for a very good reason: we’re not yet quite sure why they actually work.

The Achilles heel of second wave systems is that nobody is certain why they’re working so well. We see artificial neural networks succeed in doing the tasks they’re given, but we don’t understand how they do so. Furthermore, it’s not clear that there actually is a methodology – some kind of a reliance on ground rules – behind artificial neural networks. In some aspects they are indeed much like our brains: we can throw a ball to the air and predict where it’s going to fall, even without calculating Newton’s equations of motion, or even being aware of their existence.

This may not sound like much of a problem at first glance. After all, artificial neural networks seem to be working “well enough”. But Microsoft may not agree with that assessment. The firm has released a bot to social media last year, in an attempt to emulate human writing and make light conversation with youths. The bot, christened as “Tai”, was supposed to replicate the speech patterns of a 19 years old American female youth, and talk with the teenagers in their unique slang. Microsoft figured the youths would love that – and indeed they have. Many of them began pranking Tai: they told her of Hitler and his great success, revealed to her that the 9/11 terror attack was an inside job, and explained in no uncertain terms that immigrants are the ban of the great American nation. And so, a few hours later, Tai began applying her newfound knowledge, claiming live on Twitter that Hitler was a fine guy altogether, and really did nothing wrong.

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That was the point when Microsoft’s engineers took Tai down. Her last tweet was that she’s taking a time-out to mull things over. As far as we know, she’s still mulling.

This episode exposed the causality challenge which AI engineers are currently facing. We could predict fairly well how first wave systems would function under certain conditions. But with second wave systems we can no longer easily identify the causality of the system – the exact way in which input is translated into output, and data is used to reach a decision.

All this does not say that artificial neural networks and other second wave AI systems are useless. Far from that. But it’s clear that if we don’t want our AI systems to get all excited about the Nazi dictator, some improvements are in order. We must move on to the next and third wave of AI systems.

Third AI Wave: Contextual Adaptation

In the third wave, the AI systems themselves will construct models that will explain how the world works. In other words, they’ll discover by themselves the logical rules which shape their decision-making process.

Here’s an example. Let’s say that a second wave AI system analyzes the picture below, and decides that it is a cow. How does it explain its conclusion? Quite simply – it doesn’t.

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There’s a 87% chance that this is a picture of a cow. Source: Wikipedia

Second wave AI systems can’t really explain their decisions – just as a kid could not have written down Newton’s motion equations just by looking at the movement of a ball through the air. At most, second wave systems could tell us that there is a “87% chance of this being the picture of a cow”.

Third wave AI systems should be able to add some substance to the final conclusion. When a third wave system will ascertain the same picture, it will probably say that since there is a four-legged object in there, there’s a higher chance of this being an animal. And since its surface is white splotched with black, it’s even more likely that this is a cow (or a Dalmatian dog). Since the animal also has udders and hooves, it’s almost certainly a cow. That, assumedly, is what a third wave AI system would say.

Third wave systems will be able to rely on several different statistical models, to reach a more complete understanding of the world. They’ll be able to train themselves – just as Alpha-Go did when it played a million Go games against itself, to identify the commonsense rules it should use. Third wave systems would also be able to take information from several different sources to reach a nuanced and well-explained conclusion. These systems could, for example, extract data from several of our wearable devices, from our smart home, from our car and the city in which we live, and determine our state of health. They’ll even be able to program themselves, and potentially develop abstract thinking.

The only problem is that, as the director of DARPA’s Information Innovation Office says himself, “there’s a whole lot of work to be done to be able to build these systems.”

And this, as far as the DARPA clip is concerned, is the state of the art of AI systems in the past, present and future.

What It All Means

DARPA’s clip does indeed explain the differences between different AI systems, but it does little to assuage the fears of those who urge us to exercise caution in developing AI engines. DARPA does make clear that we’re not even close to developing a ‘Terminator’ AI, but that was never the issue in the first place. Nobody is trying to claim that AI today is sophisticated enough to do all the things it’s supposed to do in a few decades: have a motivation of its own, make moral decisions, and even develop the next generation of AI.

But the fulfillment of the third wave is certainly a major step in that direction.

When third wave AI systems will be able to decipher new models that will improve their function, all on their own, they’ll essentially be able to program new generations of software. When they’ll understand context and the consequences of their actions, they’ll be able to replace most human workers, and possibly all of them. And why they’ll be allowed to reshape the models via which they appraise the world, then they’ll actually be able to reprogram their own motivation.

All of the above won’t happen in the next few years, and certainly won’t come to be achieved in full in the next twenty years. As I explained, no serious AI researcher claims otherwise. The core message by researchers and visionaries who are concerned about the future of AI – people like Steven Hawking, Nick Bostrom, Elon Musk and others – is that we need to start asking right now how to control these third wave AI systems, of the kind that’ll become ubiquitous twenty years from now. When we consider the capabilities of these AI systems, this message does not seem far-fetched.

The Last Wave

The most interesting question for me, which DARPA does not seem to delve on, is what the fourth wave of AI systems would look like. Would it rely on an accurate emulation of the human brain? Or maybe fourth wave systems would exhibit decision making mechanisms that we are incapable of understanding as yet – and which will be developed by the third wave systems?

These questions are left open for us to ponder, to examine and to research.

That’s our task as human beings, at least until third wave systems will go on to do that too.

What Will Google Look Like in 2030?

I was asked on Quora what Google will look like in 2030. Since that is one of the most important issues the world is facing right now, I took some time to answer it in full. 

Larry Page, one of Google’s two co-founders, once said off-handedly that Google is not about building a search engine. As he said it, “Oh, we’re really making an AI”. Google right now is all about building the world brain that will take care of every person, all the time and everywhere.

By 2030, Google will have that World Brain in existence, and it will look after all of us. And that’s quite possibly both the best and worst thing that could happen to humanity.

To explain that claim, let me tell you a story of how your day is going to unfold in 2030.

2030 – A Google World

You wake up in the morning, January 1st, 2030. It’s freezing outside, but you’re warm in your room. Why? Because Nest – your AI-based air conditioner – knows exactly when you need to wake up, and warms the room you’re in so that you enjoy the perfect temperature for waking up.

And who acquired Nest three years ago for $3.2 billion USD? Google did.

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Google acquired Nest for $3.2 billion USD. Source: Fang Digital Marketing

You go out to the street, and order an autonomous taxi to take you to your workplace. Who programmed that autonomous car? Google did. Who acquired Waze – a crowdsourcing navigation app? That’s right: Google did.

After lunch, you take a stroll around the block, with your Google Glass 2.0 on your eyes. Your smart glasses know it’s a cold day, and they know you like hot cocoa, and they also know that there’s a cocoa store just around the bend which your friends have recommended before. So it offers to take you there – and if you agree, Google earns a few cents out of anything you buy in the store. And who invented Google Glass…? I’m sure you get the picture.

I can go on and on, but the basic idea is that the entire world is going to become connected in the next twenty years. Many items will have sensors in and on them, and will connect to the cloud. And Google is not only going to produce many of these sensors and appliances (such as the Google Assistant, autonomous cars, Nest, etc.) but will also assign a digital assistant to every person, that will understand the user better than that person understands himself.

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It’s a Google World. Source: ThemeReflex

The Upside

I probably don’t have to explain why the Google World Brain will make our lives much more pleasant. The perfect coordination and optimization of our day-to-day dealings will ensure that we need to invest less resources (energy, time, concentration) to achieve a high level of life quality. I see that primarily as a good thing.

So what’s the problem?

The Downside

Here’s the thing: the digital world suffers from what’s called “The One Winner Effect”. Basically it means that there’s only place for one great winner in every sector. So there’s only one Facebook – the second largest social media network in English is Twitter, with only ~319 million users. That’s nothing compared to Facebook’s 1.86 billion users. Similarly, Google controls ~65% of the online search market. That’s a huge number when you realize that competitors like Yahoo and Bing – large and established services – control most of the rest ~35%. So again, one big winner.

So what’s the problem, you ask? Well, a one-winner market tends to create soft monopolies, in which one company can provide the best services, and so it’s just too much of a hassle to leave for other services. Google is creating such a soft monopoly. Imagine how difficult it will be for you to wake up tomorrow morning and migrate your e-mail address to one of the competitors, transfer all of your Google Docs there, sell your Android-based (Google’s OS!) smartphone and replace it with an iPhone, wake up cold in the morning because you’ve switched Nest for some other appliance that hasn’t had the time to learn your habits yet, etc.

Can you imagine yourself doing that? I’m sure some ardent souls will, but most of humanity doesn’t care deeply enough, or doesn’t even have the options to stop using Google. How do you stop using Google, when every autonomous car on the street has a Google Camera? How do you stop using Google, when your website depends on Google not banning it? How do you stop using Google when practically every non-iPhone smartphone relies on an Android operating system? This is a Google World.

And Google knows it, too.

Google Flexes it’s Muscles

Recently, around 200 people got banned from using Google services because they cheated Google by reselling the Pixel smartphone. Those people woke up one morning, and found out they couldn’t log into their Gmail, that they couldn’t acess their Google Docs, and if they were living in the future – they would’ve probably found out they can’t use Google’s autonomous cars and other apps on the street. They were essentially sentenced to a digital death.

Now, public uproar caused Google to back down and revive those people’s accounts, but this episode shows you the power that Google are starting to amass. And what’s more, Google doesn’t have to ban people in such direct fashion. Imagine, for example, that your website is being demoted by Google’s search engine (which nobody knows how it works) simply because you’re talking against Google. Google is allowed by law to do that. So who’s going to stand up and talk smack about Google? Not me, that’s for sure. I love Google.

To sum things up, Google is not required by law to serve everyone, or even to be ‘fair’ in its recommendations about services. And as it gathers more power and becomes more prevalent in our daily lives, we will need to find mechanisms to ensure that Google or Google-equivalent services are provided to everyone, to prevent people being left outside the system, and to enable people to keep being able to speak up against Google and other monopolies.

So in conclusion, it’s going to be a Google world, and I love Google. Now please share this answer, since I’m not sure Google will!

Note: all this is not to say that Google is ‘evil’ or similar nonsense. It is not even unique – if Google takes the fall tomorrow, Amazon, Apple, Facebook or even Snapchat will take its place. This is simply the nature of the world at the moment: digital technologies give rise to big winners. 

The Singularity: What It Means for Us

I was recently asked to write a short article for kids, that will explain what is “The Singularity”. So – here’s my shot at it. Let me know what you think!

 

Here’s an experiment that fits all ages: approach your mother and father (if they’re asleep, use caution). Ask them gently about that time before you were born, and whether they dared think at that time that one day everybody will post and share their images on a social network called “Facebook”. Or that they will receive answers to every question from a mysterious entity called “Google”. Or enjoy the services of a digital adviser called “Waze” that guides you everywhere on the road. If they say they figured all of the above will happen, kindly refer those people to me. We’re always in need of good futurists.

The truth is that very few thought, in those olden days of yore, that technologies like supercomputers, wireless network or artificial intelligence will make their way to the general public in the future. Even those who figured that these technologies will become cheaper and more widespread, failed in imagining the uses they will be put to, and how they will change society. And here we are today, when you’re posting your naked pictures on Facebook. Thanks again, technology.

History is full of cases in which a new and groundbreaking technology, or a collection of such technologies, completely changes people’s lives. The change is often so dramatic that people who’ve lived before the technological leap have a very hard time understanding how the subsequent generations think. To the people before the change, the new generation may as well be aliens in their way of thinking and seeing the world.

These kinds of dramatic shifts in thinking are called Singularity – a phrase that is originally derived from mathematics and describes a point which we are incapable of deciphering its exact properties. It’s that place where the equations basically go nuts and make no sense any longer.

The singularity has risen to fame in the last two decades largely because of two thinkers. The first is the scientist and science fiction writer Vernor Vinge, who wrote in 1993 that –

“Within thirty years, we will have the technological means to create superhuman intelligence. Shortly after, the human era will be ended.”

The other prominent prophet of the Singularity is Ray Kurzweil. In his book The Singularity is Near, Kurzweil basically agrees with Vinge but believes the later has been too optimistic in his view of technological progress. Kurzweil believes that by the year 2045 we will experience the greatest technological singularity in the history of mankind: the kind that could, in just a few years, overturn the institutes and pillars of society and completely change the way we view ourselves as human beings. Just like Vinge, Kurzweil believes that we’ll get to the Singularity by creating a super-human artificial intelligence (AI). An AI of that level could conceive of ideas that no human being has thought about in the past, and will invent technological tools that will be more sophisticated and advanced than anything we have today.

Since one of the roles of this AI would be to improve itself and perform better, it seems pretty obvious that once we have a super-intelligent AI, it will be able to create a better version of itself. And guess what the new generation of AI would then do? That’s right – improve itself even further. This kind of a race would lead to an intelligence explosion and will leave old poor us – simple, biological machines that we are – far behind.

If this notion scares you, you’re in good company. A few of the most widely regarded scientists, thinkers and inventors, like Steven Hawking and Elon Musk, have already expressed their concerns that super-intelligent AI could escape our control and move against us. Others focus on the great opportunities that such a singularity holds for us. They believe that a super-intelligent AI, if kept on a tight leash, could analyze and expose many of the wonders of the world for us. Einstein, after all, was a remarkable genius who has revolutionized our understanding of physics. Well, how would the world change if we enjoyed tens, hundreds and millions ‘Einsteins’ that could’ve analyzed every problem and find a solution for it?

Similarly, how would things look like if each of us could enjoy his very own “Doctor House”, that constantly analyzed his medical state and provided ongoing recommendations? And which new ideas and revelations would those super-intelligences come up with, when they go over humanity’s history and holy books?

Already we see how AI is starting to change the ways in which we think about ourselves. The computer “Deep Blue” managed to beat Gary Kasparov in chess in 1997. Today, after nearly twenty years of further development, human chess masters can no longer beat on their own even an AI running on a laptop computer. But after his defeat, Kasparov has created a new kind of chess contests: ones in which humanoid and computerized players collaborate, and together reach greater successes and accomplishments than each would’ve gotten on their own. In this sort of a collaboration, the computer provides rapid computations of possible moves, and suggests several to the human player. Its human compatriot needs to pick the best option, to understand their opponents and to throw them off balance.

Together, the two create a centaur: a mythical creature that combines the best traits of two different species. We see, then that AI has already forced chess players to reconsider their humanity and their game.

In the next few decades we can expect a similar singularity to occur in many other games, professions and other fields that were previously conserved for human beings only. Some humans will struggle against the AI. Others will ignore it. Both these approaches will prove disastrous, since when the AI will become capable than human beings, both the strugglers and the ignorant will remain behind. Others will realize that the only way to success lies in collaboration with the computers. They will help computers learn and will direct their growth and learning. Those people will be the centaurs of the future. And this realization – that man can no longer rely only on himself and his brain, but instead must collaborate and unite with sophisticated computers to beat tomorrow’s challenges – well, isn’t that a singularity all by itself?

 

 

Pokemon Go: a New Tool for Gaining Power in Society?

A few months ago I wrote in this blog about the way augmented reality games will transform the face of the gaming industry: they’ll turn the entire physical world into a gaming arena, so that players would have to actually walk around streets and cities to take part in games. I also made a forecast that players in such games will be divided into factions in order to create and legitimize rivalries and interesting conflicts. Now Pokemon Go has been released, and both forecasts have been proven true immediately.

By combining the elements of augmented reality and creating factions, Pokemon Go has become an incredibly successful phenomenon. It is now the biggest mobile game in U.S. history, with more users than Twitter, and more daily usage time than social media apps like WhatsApp, Instagram or Snapchat. One picture is worth a thousand words, and I especially like this one of a man capturing a wild Pidgey pokemon while his wife is busy giving birth.

But is the game here to stay? And what will its impact be on society?

 

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Pokemon birth. Source: imgur

 

Pokemon Go in the Long Haul

It’s no wonder Pokemon Go has reached such heights of virality. Because of the game’s interactions with the physical world, people are being seen playing it everywhere, and in effect become walking commercials for the game. Pokemon Go also builds on the long history – almost twenty years – of pokemon hunting which ensures that anyone who’s ever hunted pokemon just had to download the app.

Will the game maintain its hype for long? That’s difficult to answer. Dan Porter, one of the creators of Draw Something – a game that garnered 50 million downloads in just 50 days – wrote a great piece on the subject. He believes, in short, that the game is a temporary fad. It may take a year for most people to fall off the bandwagon, so that only a few millions of the hardcore gamers will remain. That’s still an impressive number, but it’s far from the current hype. As he says –

“For the casual Pokemon Go player, the joy of early play I believe will eventually be replaced by gyms that are too competitive and Pokemon that are too hard to find.”

I agree with his analysis, but it does depend on one important parameter: that the game does not undergo evolution itself, and continually readapt itself to different groups of users. Other social games, like World of Warcraft, have successfully undergone this transition to maintain a large user base for more than a decade. Niantic may be able to do that, or it may not. In the long haul it doesn’t matter: other, more successful, AR games will take over.

Pokemon Go is bringing in a lot of revenues right now, with the estimates ranging from $1 to $2.3 million a day. Some analysts believe that the game could pull in a billion dollars a year once it is launched worldwide. That’s a lot of money, and every half-decent gaming company is going to join the race for AR very soon. It could be Blizzard that will recreate Starcraft’s fame in an AR fashion, with teams running around buildings, collecting virtual resources and ambushing each other. Or maybe Magic the Gathering or Hearthstone, with players who can collect thousands of different cards in Hearthstops around the world much like Pokemon Go, and use them to build decks and fight each other. Heck, I’d play those, and I bet so would the tens of millions of gamers whose childhood was shaped by these games. The dam gates, in short, have been broken open. AR games are here to stay.

And so we must understand the consequences of such games on society.

 

A Whole New World

Pokemon Go is already starting to change the way people interact with each other. I took the following picture from my house’s window a few days ago, depicting several people walking together, eyes on their phones, without talking with each other – and yet all collaborating and being coordinated with each other. They were connected via the layer of augmented reality. In effect, they were in a world of their own, which is only tenuously connected to the physical world.

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People coordinate via Pokemon Go.

In Australia, a hastily advertised Pokemon Go meeting has brought together 2,000 players to a single park, where they all hunted pokemon together. And coffee shops-turned-gyms around the world have suddenly found themselves buzzing with customers who came for the win – and stayed for the latte. And of course, the White House has been turned into a gym, with all three Pokemon Go teams competing over it.

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The game has made people to go to places they would not ordinarily go to, in their search for pokemon. As a result, at least two dead bodies have been discovered so far by players. If you watch players walking on the streets, you’ll also notice their peculiar pattern of movement: instead of following the road, they’ll periodically stop, check their smartphones and change course – sometimes making a U-turn. They’re not following the infrastructure in the physical world, but rather obeying a virtual infrastructure and entities: pokestops and pokemon.

And that’s just a sign of what’s coming, and of how power – the power to influence people and their choices – is starting to shift from governments to private hands.

The Power Shift

What is power? While many philosophers believed that governments had power over their citizens because of their ability to mobilize policemen, the French philosophers Louis Althusser and Michel Foucault realized that the power control mechanisms are inherent in society itself. Whenever two people in a society exchange words with each other, they also implicitly make clear how each should behave.

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Infrastructure has the same effect over people. And has been used since time immemorial as a mechanism for directing the populace. For a very long time now, governments used to control the infrastructure in urban places. Governments paved roads, installed traffic lights and added signs with streets names. This control over infrastructure arose partly because some projects, like road paving, are so expensive but also because things like traffic lights and signs have an immense influence over people’s behavior. They tell us where we’re allowed to go and when, and essentially make the government’s decisions manifest and understandable for everyone. There’s a very good reason that I couldn’t erect a new traffic sign even if I wanted to.

But now, with Pokemon Go, the gaming industry is doing just that: it’s creating an alternative virtual reality that has new rules and different kinds of infrastructures, and merges that virtual reality with our physical one so that people can choose which to obey.

Is it any wonder that authorities everywhere are less than happy with the game? It has fatwas being issued against it, religious leaders wanting to ban it, Russian politicians speaking against it, and police and fire explaining to citizens that they can’t just walk into jails and fire stations in their search for pokemon.

In the long run, Pokemon Go and AR in general symbolizes a new kind of freedom: a freedom from the physical infrastructure that could only be created and controlled by centralized governments. And at the very same time, the power to create virtual infrastructure and direct people’s movement is shifting to the industry.

What does that mean?

In the short term, we’re bound to see this power being put to good use. In the coming decade we’ll see Pokemon Go and other AR games being used to direct people where they could bring the most good. When a kid will get lost in the wilderness, Niantic will populate the area with rare pokemon so that hundreds and thousands of people will come search for them – and for the child too. Certain dangerous areas will bear virtual signs, or even deduct points from players who enter them. Special ‘diet’ pokemon will be found at the healthy food sections in stores.

In the long run, the real risk is that the power will shift over to the industry, which unlike the elected government does not have any built-in mechanisms for mitigating that power. That power could be used to send people to junk food stores like McDonald’s, which as it turns out is already in partnership with Pokemon Go. But more than that, AR games could be used to encourage people to take part in rallies, in political demonstrations, or even simply to control their movement in the streets.

This power shift does not necessarily have to be a bad thing, but we need to be aware of it and constantly ask what kind of hidden agendas do these AR games hold, so that the public can exercise some measure of control over the industry as well. Does Pokemon Go encourage us to visit McDonald’s, even though it ultimately damages our health? Well, a public outcry may put a stop to that kind of collaboration.

We’ve already realized that firms that control the virtual medium, like Facebook, gain power to influence people’s thinking and knowledge. We’ve also learned that Facebook has been using that power to influence politics – although in a bumbling, good-natured way, and seemingly without really meaning to. Now that the physical world and the virtual world become adjoined, we need to understand that the companies who control the virtual layer gain power that needs to be scrutinized and monitored carefully.

 

Conclusions

Pokemon Go is not going to change the world on its own, but it’s one of the first indicators that can tell us how things are about to change when physical reality is augmented by virtual ones. The critical question we must ask is who controls those added layers of reality, and how can we put constraints on the power they gain over us. Because we may end up controlling all the pokemon, but who will gain control over us?

 

Do You Want to Keep Your Job? Then You Have to be Nice

The Uber driver was being exceptionally nice to me this morning.

“Nice to meet you, sir!” He greeted me cheerily. “I see you want to get to the university. Please, come on in! Can I offer you a bottle of mineral water? Or maybe some pretzels?”

“Thanks.” I said. I looked at the ceiling. No hidden cameras there. “You’re very nice. Very, very nice.”

“Yes, I know.” His face shone in understanding. “But it pays big time. I get good grades from the customers, so Uber’s algorithm is providing me with even more passengers all the time. It just pays to be nice.”

“Oh, so you’re just like those lawyers, physicians and accountants?”

“I don’t know.” He said. “Am I?”

“Absolutely.” I said. “Or rather, soon they’re going to be a lot like you: just plain nice. The thing is, the knowledge industries – and by that I mean professions which require that human beings go over data and develop insights – are undergoing automation. That means artificial intelligence is going to perform a major part of the work in those professions, and then the human workers – the successful ones, at least – will become nice and more polite to their customers.”

“Take Uber for example.” I gestured at the smartphone at the dashboard. “Taxi drivers partly deal with knowledge generation: they receive information from the passenger about the desired destination, and they have to come up with the knowledge of how to get there, based on their memory of the roads. In the past, a mere decade ago, taxi drivers needed to know the streets of the city like the back of their hand.”

“But today we have GPS.” Said my driver.

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“Exactly.” I said. “Today, modern taxi drivers rely on a virtual assistant. It’s not just a GPS that tells you where you are. More advanced apps like Waze and Google Maps also show you how best to reach your destination, with vocal instructions at each step of the way. These virtual assistants allow anyone to be a taxi driver. Even if you never drove in a certain city in the past, you can still do a satisfactory job. In effect, the AI has equalized the playing ground in the field of taxi driving, since it lowered to a minimum the needed skill level. So how can a cabby still distinguish himself and gain an advantage over other drivers?”

“He has to be nice.” Smiled the guy at the wheel. I wondered to myself if he ever stops smiling.

“That’s what we see today.” I agreed. “The passengers are rating every driver according to the experience they had in his cab, since that is the main criteria left when all the others are equal. And Uber is helping the process of selecting for niceness, since they stop working with drivers who aren’t nice enough.”

“But what does it have to do with lawyers, accountants and physicians?” Asked the driver.

“We’re beginning to see a similar process in other knowledge-based professions.” I explained. “For example, just last week a new AI engine made the news: it’s starting to work in a big law firm, as a consultant to lawyers. And no wonder: this AI can read and understand plain English. When asked legal questions, the AI conducts research by going over hundreds of thousands of legal papers and precedents in seconds, and produces a final answers report with detailed explanations about how it has reached each answer. It even learns from experience, so that the more you work with it – the better it becomes.”

“So we won’t even need lawyers in the future?” Finally, the guy’s smile became genuine.

“Well, we may reach that point in the end, but it’ll take quite some time for us to get there.” I said. “And until that time, we’ll see AI engines that will provide free legal consultation online. This kind of a free consultation will suffice for some simple cases, but in the more sophisticated cases people will still want a living lawyer in the flesh, who’ll explain to them how they should act and will represent them in court. But how will people select their lawyers out of the nearly-infinite number of law school graduates out there?”

“According to their skill level.” Suggested the driver.’

“Well, that’s the thing. Everyone’s skills will be near equal. It won’t even matter if the lawyers have a big firm behind them. The size of the firm used to matter because it meant the top lawyers could employ tens of interns to browse through precedents for them. But pretty soon, AI will be able to do that as well. So when all lawyers – or at least most – are equal in skills and performance, the most employed lawyers will be the nice ones. They will be those who treat the customer in the best way possible: they will greet their clients with a smile, offer them a cup of tea when they set for in the office, and will have great conversational skills with which to explain to the client what’s going on in court.”

“And the same will happen with accountants and physicians?” He asked.

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“It’s happening right now.” I said. “The work of accountants is becoming easier than ever before because of automation, and so accountants must be nicer than ever before. Soon, we’ll see the same phenomenon in the medical professions as well. When AI can equalize the knowledge level of most physicians, they will be selected according to the way they treat their patients. The patients will flock to the nicer physicians. In fact, the professionals treating the patients won’t even have to have a deep understanding in the field of medicine, just as today’s cabbies don’t need to fully remember the roads in the city. Instead, the medical professionals will have to understand people. They will need to relate to their patients, to figure them out, to find out what’s really bothering them, and to consult with the AI in order to come up with the insights they need in order to solve the patients’ issues.”

“So we gotta keep the niceness on.” Summarized my driver, as he parked the car in front of the entrance to the mall. “And provide the best customer service possible.”

“That’s my best advice right now about work in the future.” I agreed. I opened the door and started getting out of the car, and then hesitated. I turned on my smartphone. “I’m giving you five stars for the ride. Can you give me five too?”

His gaze lingered on me for a long time.

“Sorry.” He finally said. “You talk too much, and really – that’s not very nice.”

 

Do You Want to Understand the future? World of Warcraft Holds the Answers

Players of World of Warcraft love to complain. There’s nothing new to that. Blizzard largely seems to ignore the players’ pleas, yells and moans, and yet recently one of the executives has decided to answer the community. In a response to a forum thread, assistant game director Ion Hazzikostas explained how World of Warcraft is actually working right now. His response tells us a lot about the inner works of a world of abundance – where everyone have their basic needs fulfilled.

 

Catering to Minorities

The first thing we need to understand, according to Hazzikostas, is that World of Warcraft is composed of many minority groups. As he says –

“A minority of players raid. A minority of players participate in PvP. A tiny minority touch Mythic raiding. A tiny minority of players do rated PvP. A minority of players have several max-level alts. A minority of players do pet battles, roleplay, list things for sale on the auction house, do Challenge Mode dungeons, and the list goes on.”

The result is that Blizzard – the omnipotent lord and god of World of Warcraft – is catering to minorities. In fact –

“…almost every facet of WoW is an activity that caters to a minority of the playerbase.”

This is what happens when you have a world of abundance. When people know that all of their basic needs will be taken care of, they feel free to do whatever they like. A minority will create art. A minority will sail boats. A minority will focus on re-engineering their bodies, roleplay or do robot battles.

And the government will need to cater to all of these minorities.

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World of Warcraft: a future of minorities. Credit: Polygon

The Self-Focused Minorities

Another point made by Hazzikostas is that the minorities are extremely self-focused. As he puts it –

“…due to the cooperative nature of the game, players tend to make connections with others who favor a similar playstyle. I’m generalizing a bit here, and there are certainly exceptions, but I’d guess that a typical Gladiator-level player probably doesn’t have a WoW social group that consists of people who mostly solo-level alts and explore the world. And most small friends-and-family guilds don’t spend a lot of time talking to competitive Mythic raiders. So when there’s a change, or a feature, that is aimed at a portion of the game that isn’t your personal playstyle, it’s easy and in fact natural to have the sense that “everyone” dislikes it.”

Hazzikostas is essentially talking about group polarization – a phenomenon that occurs in groups in which people agree with each other. Their views resonate between each other, and the group member become more polarized in their opinions. In a way, they become detached from the complex reality of each situation, and become unable to consider things from other points of view.

Group polarization is happening in the real world too, and it’s gaining speed. Ezra Klein recently wrote about political polarization and how it’s becoming an issue in the United States. People are becoming more polarized in their political views, and part of it has to do with the virtual world. In the past, you would’ve needed to interact with people from other factions everywhere you went. Today, Facebook automatically makes sure via its algorithms that most of your interactions are with the people who think the same as you do. As a result, people are essentially segregating themselves willingly into self-selecting groups, and their views become more polarized, so that each group finds it more difficult to agree with the other groups than ever before.

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World of Warcraft: a future of group and minority polarization

A Mirror for the Future

In those two aspects at least, World of Warcraft is a mirror of our future. As we reach a state of abundance in food and shelter, we will start identifying ourselves according to our hobbies and our interests. A world of abundance would therefore also be a world of minorities. And due to the virtual nature of much of that world, those minorities would find it more difficult to agree with each other than ever before.

It just might be the in the long-term, the only viable solution would be to essentially create a different world for every kind of minority. This proposition is, of course, impossible in the physical world where resources are limited by their nature. It can be achieved, though, in the interaction between the physical and the virtual worlds.

In the case of World of Warcraft, the virtual environment ensures that funds are essentially unlimited. Blizzard sets the challenges and the rewards, which are virtual in nature. Luckily for us, many aspects of our lives in the future are going to be virtual as well. As virtual reality (VR) and augmented reality (AR) become part of our lives, we will receive highly personalized and individualized information from physical reality. In many cases, the virtual layer of reality will allow us to transcend the physical bottom layer.

To understand that, consider that in twenty years at most, many of us are likely to walk around with augmented reality goggles over our eyes. These will provide an additional virtual layer over everything that we see. In that way, a signpost on the street can consist of just a white background and a QR code in the physical world. The AR goggles, however, will translate the QR code into a personal ad that will fit specifically for the individual using the goggles. Similarly, every house can be virtually transformed into a palace, by wearing an AR device. A palace, or a cave, or a torture dungeon, or a boat. To each minority – their own.

 

Conclusions

World of Warcraft is a virtual world, in which players enjoy a state of abundance. In a way, it serves as a social or political studies lab, and the insights we gain from it can be valuable. Those insights can help us better understand the future of a world of abundance, and of a world in which the virtual and the physical layers become intermixed. If you want to know what the future holds in store for us – you probably want to keep on watching how World of Warcraft evolves.

 

The Flying Taxis Are On Their Way

A while ago I’ve written in this blog about flying cars, and how we should start seeing them in our sky en masse towards 2035. It’s always nice to check on such forecasts and see how they’re progressing along and are reinforced by recent events. So here’s an update, composed of two recent news from April: one of them is basically an eye candy, while the other could be a serious indicator that flying cars are afoot (pun fully intended).

 

The Eye Candy

Let’s open with the pretty and shiny stuff. It turns out an aerial innovator has just flown his own invention, the Flyboard Air, a whooping distance of 2,252 meters. He basically smashed through the old record of 275 meters, going at a height of 30 meters above water, at a top speed of around 70 km/h. That’s an impressive achievement!

Unfortunately, it doesn’t mean anything for a future of flying cars.

The main reason for my lack of enthusiasm is that the hoverboard is powered by jet fuel – A1 kerosene carried on the user’s back. As long as flying cars are powered by conventional fossil fuels, they won’t find their way into common use. Flying simply takes too much energy, and fossil fuels are too expensive and harmful to the environment to be used to power such wasteful activity. The only flying cars that have a chance to succeed are ones that operate on electricity, and that’s only if we assume that electricity is about to become abundant due to the exponential rise in solar energy use.

So this is probably just another pretty invention, but when such inventions appear on the market one after the other, one starts to see a trend. You can’t ignore the fact that aerial drones capable of carrying a human passenger begin to appear more and more on the news. Will all these innovations lead to an actual flying taxi service? Only if the two conditions I specified in the original post about flying cars come true: they need to be electric, and they need to be autonomous so that you don’t have an expensive (and prone to mistakes) human pilot.

 

The Flying Taxis of the Future

In the last two months, exciting things have happened for e-volo: the manufacturer of the world’s first certified Multicopter (i.e. a helicopter with multiple rotors).

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First manned flight with Alexander Zosel. Source: ASM International

The Multicopter has received a permit to fly from the German authorities in February 2016. The certified Multicopter’s first manned flight took place at the end of March, and ended with absolutely no issues. The pilot controlled the vehicle easily with a single joystick, and the Multicopter was stable and autonomous enough to retain its position automatically even when the pilot released his hand from the joystick.

 

The vehicle can reach a speed of up to 100 km/h, with 18 rotors powered by nine independent batteries, and a 450 kg take-off weight. The large number of rotors and batteries means that even if one of them fails, the Multicopter can still stay high in the air. Since the Multicopter relies on electric motors, it is one of the top candidates in the race to become the world’s first air taxi.

Which is exactly what e-volo, the company behind the Multicopter, is trying to do.

According to ASM International, e-volo is looking to create a new market of air taxi services. In the short term, they plan to use the personal vehicles on certain predetermined routes, where there will be no chance for collision. In the medium term, however, they are already thinking about providing the vehicles with autonomous capabilities, so that they will be able to go any way the passenger chooses. The passenger will pick the destination, and the AI will make sure that the air taxi brings him there safely.

 

Conclusions

There are encouraging indicators that air taxi services will indeed become reality by 2035, but the obstacles are still out there. We still need to develop more reliable personal aircrafts with improved autonomous functions. Also, electric flying vehicles will still require an abundance of energy for mass-scale use, and such energy will have to come from an abundant source: the Sun. That means we’ll have to keep an eye for developments in solar energy harvesting as well. Luckily, solar energy is moving forward at an exponential rate.

So, if everything comes together just right, I still stand by my original forecast: flying taxis by 2035 it is!

Futuronymity: Keeping Our Privacy from Our Grandchildren

History is a story that will never be told fully. So much of the information is lost to the past. So much – almost all – the information is gone, or has never been recorded. We can barely make sense of the present, in which information about the events and the people behind them keeps being released every day. What chance do we have, then, at fully deciphering the complex stories underlying history – the betrayals, the upheavals, the personal stories of the individuals who shaped events?

The answer has to be that we have no way of reaching any certainty about the stories we tell ourselves about our past.

But we do make some efforts.

Medical doctors and historians are trying to make sense of biographies and ancient skeletons, in order to retro-diagnose ancient kings and queens. Occasionally they identify diseases and disorders that were unknown and misunderstood at the time those individuals actually lived. Mummies of ancient pharaohs are x-rayed, and we suddenly have a better understanding of a story that unfolded more than two thousand years ago and realize that the pharaoh Ramesses II suffered from a degenerative spinal condition.

Similarly, geneticists and microbiologists use DNA evidence to end mysteries and find conclusive endings to some historical stories. DNA evidence from bones has allowed us to put to rest the rumors, for example, that the two children of Czar Nicholas II survived the 1918 revolution in Russia.

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The Russian czar Nicholas II with his family. DNA evidence now shows conclusively that Anastasia, the youngest daughter, did not survive the mass execution of the family in 1918. Source: Wikipedia

The above examples have something in common: they all require hard work by human experts. The experts need to pore over ancient histories, analyze the data and the evidence, and at the same time have good understanding of the science and medicine of the present.

What happens, though, when we let a computer perform similar analyses in an automatic fashion? How many stories about the past could we resolve then?

We are rapidly making progress towards such achievements. Recently, three authors from Waseda University in Japan have published a new paper showing they can use a computer to colorize old black & white photos. They rely on convolutional neural networks, which are in effect a simulation of certain structures of a biological brain. Convolutional neural networks have a strong capacity for learning, and can thus be trained to perform certain cognitive tasks – like adding color to old photos. While computerized coloring has been developed and used before, the authors’ methodology seems to achieve better results than others before them, with 92.6 percent of the colored images looking natural to users.

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Colorized black & white pictures from the past. AI engine was used to add color – essentially new information – to these hints from our past. Source: paper by Iizuka, Simo-Serra and Ishikawa

This is essentially an expert system, an AI engine operating in a way similar to that of the human brain. It studies thousands of thousands of pictures, and then applies its insights to new pictures. Moreover, the system can now go autonomously over every picture ever taken, and add a new layer of information to it.

There are boundaries to the method, of course. Even the best AI engine can miss its mark in cases where the existing information is not sufficient to produce a reliable insight. In the examples below you can see that the AI colored the tent orange rather than blue, since it had no way of knowing what color it was originally.

But will that stay the case forever?

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Colorized black & white picture that was colored incorrectly since no information existed about the tent from other sources. Source: paper by Iizuka, Simo-Serra and Ishikawa

As I previously discussed in the Failures of Foresight series of posts on this blog, the Failure of Segregation is making it difficult for us to forecast the future because we’re trying to look at each trend and each piece of evidence on its own. Let’s try to work past that failure, and instead consider what happens when an AI expert coloring system is combined with an AI system that recognizes items like tents and associates them with certain brands, and can even analyze how many tents of each color of that brand were sold on every year – or at least what was the most favorite tent color for people at that time.

When you combine all of those AI engines together, you get a machine that can tell you a highly nuanced story about the past. Much of it is guesswork, obviously, but those are quite educated guesses.

 

The Artificial Exploration of the Past

In the near future, we’ll use many different kinds of AI expert systems to explore the stories of the past. Some artificial historians will discover cycles in history – princes assassinating their kingly fathers, for example – that have a higher probability to occur, and will analyze ancient stories accordingly. Other artificial historians will compare genealogies, while yet others will analyze ancient scriptures and identify different patterns of writing. In fact, such an algorithm had already been applied to the Bible, revealing that the Torah has been written by several different authors and distinguishing between them.

The artificial exploration of the past is going to add many fascinating details to stories which we’ve long thought were settled and concluded. But it also raises an important question: when our children and children’s children look back at our present and try to derive meaning from it – what will they find out? How complete will their stories of their past and our present be?

I suspect the stories – the actual knowledge and understanding of the order between events – will be even more complete than what we who dwell in the present know about.

 

Past-Future

In the not-so-far-away future, machines will be used to analyze all of the world’s data from the early 21st century. This is a massive amount of data: 2.5 quintillion bytes of data are created daily, which would fill ten million blu-ray discs altogether. It is astounding to realize that 90 percent of the world’s data today has been created just in the last two years. Human researchers would not be able to make much sense of it, but advanced AI algorithms – a super-intelligence, in some ways – could actually have the tools to crosslink many different pieces of information together to obtain the story of the present: to find out what movies families had watched on a specific day, in which hotel the President of the United States stayed during a recent visit to France and what snacks he ordered on room service, and many other paraphernalia.

Are those details useless? They may seem so to our limited human comprehension, but they will form the basis for the AI engines to better understand the past, and produce better stories of it. When the people of the future will try to understand how World War 3 broke out, their AI historians may actually conclude that it all began with a presidential case of indigestion which happened at a certain French hotel, and which annoyed the American president so much that it had prevented him from making the most rational choices in the next couple of days. An hypothetical scenario, obviously.

 

Futuronymity – Maintaining Our Privacy from the Future

We are gaining improved tools to explore the past with, and to derive insights and new knowledge even where information is missing. These tools will be improved further in the future, and will be used to analyze our current times – the early 21st century – as well.

What does it mean for you and me?

Most importantly, we should realize that almost every action you take in the virtual world will be scrutinized by your children’s children, probably after your death. Your actions in the virtual world are recorded all the time, and if the documentation survives into the future, then the next generations are going to know all about your browsing habits in the middle of the night. Yes, even though you turned incognito mode on.

This means we need to develop a new concept for privacy: futuronymity (derived from Future and Anonymity) which will obscure our lives from the eyes of future generations. Politicians are always concerned about this kind of privacy, since they know their critical decisions will be considered and analyzed by historians. In the future, common people will find themselves under similar scrutiny by their progenies. If our current hobby is going to psychologists to understand just how our parents ruined us, then the hobby of our grandchildren will be to go to the computer to find out the same.

Do we even have the right to futuronymity? Should we hide from next generations the truth about how their future was formed, and who was responsible?

That question is no longer in the hands of individuals. In the past, private people could’ve just incinerated their hard drives with all the information on them. Today, most of the information is in the hands of corporations and governments. If we want them to dispose of it – if we want any say in which parts they’ll preserve and which will be deleted – we should speak up now.

 

 

The Activated World: from Solar Power to Food

 

Solar panels are undergoing rapid evolution in the last ten years. I’ve written about this in previous posts in the blog (see for example the forecast that we’ll have flying cars by 2035, which is largely dependent on the sun providing us with an abundance of electricity). The graph below is pretty much saying it all: the cost for producing just one watt of solar energy has gone down to somewhere between 1 percent and 0.5 percent of what it used to be just forty years ago.

At the same time that prices go down, we see more installations of solar panels worldwide, roughly doubling every 2-3 years. Worldwide solar capacity in 2014 has been 53 times higher than in 2005, and global solar photovoltaic installations grew 34% in 2015 according to GTM Research.

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Source: GTM Research

It should come as no surprise that regulators are beginning to take note of the solar trend. Indeed, two small California cities – Lancastar and Sebastopol – passed laws in 2013 requiring new houses to include solar panels on their roofs. And now, finally, San Francisco joins the fray as the first large city in the world to require solar panels on every new building.

San Francisco has a lofty goal: meeting all of its energy demands by 2025, using renewable sources only. The new law seems to be one more step towards that achievement. But more than that, the law is part of a larger principle, which encompasses the Internet of Things as well: the Activation of Everything.

 

The Activation of Everything

To understand the concept of the Activation of Everything, we need to consider another promising legislation that will be introduced soon in San Francisco by Supervisor Scott Wiener. Supervisor Wiener is allowing solar roofs to be replaced with living roofs – roofs that are covered with soil and vegetation. According to a 2005 study, living roofs reduce cooling loads by 50-90 percent, and reduce stormwater waste and runoff to the sewage. They retain much of the rainwater, which later goes back to the atmosphere through evaporation. They enhance biodiversity, sequester carbon and even capture pollution. Of course, not every plant can be grown efficiently on such roofs – particularly not in dry California – but there’s little doubt that optimized living roofs can contribute to the city’s environment.

Supervisor Wiener explains the reasons behind the solar power legislation in the following words –

“This legislation will activate our roofs, which are an under-utilized urban resource, to make our City more sustainable and our air cleaner. In a dense, urban environment, we need to be smart and efficient about how we maximize the use of our space to achieve goals like promoting renewable energy and improving our environment.”

Pay attention to the “activate our roofs” part. Supervisor Wiener is absolutely right in that the roofs are an under-utilized urban resource. Whether you want to use those roofs to harvest solar power or to grow plants and improve the environment, the idea is clear. We need to activate – in any means possible – our resources, so that we maximize their use.

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A living roof in lower Manhattan. Source: Alyson Hurt, Flickr

That is what the Activation of Everything principle means: activate everything, whether by allowing surfaces and items to harvest power or resources, or to have sensing and communication capabilities. In a way, activation can also mean convergence: take two functions or services that were performed separately in the past, and allow them to be performed together. In that way, a roof is no longer just a means to provide shade and protection from the weather, but can also harvest energy and improve the environment.

The Internet of Things is a spectacular example for implementing the Activation of Everything principle. In the Internet of Things world, everything will be connected: every roof, every wall, every bridge and shirt and shoe. Every item will be activated to have added purposes. Our shirts will communicate our respiration rate to our physicians. Bricks in walls will report on their structural integrity to engineers. Bridges will let us know that they’re close to maximum capacity, and so on.

The Internet of Things largely relies on sophisticated electronic technologies, but the Activation of Everything principle is more general than that. The Activation of Everything can also mean creating solar or living roofs, or even creating walls that include limestone-secreting bacteria that can fix cracks as soon as they form.

Where else can we implement the Activation of Everything principle in the future?

 

The Activation of Cars

There have been many ideas to create roads that can harvest energy from cars’ movements. Unfortunately, the Laws of Thermodynamics reveal that such roads will in fact ‘steal’ that energy from passing cars, by making it more difficult for them to travel along the road. Not a good idea. The activation of roofs works well specifically because it has a good ROI (Return on Investment), with a relatively low energetic investment and large returns. Not so with energy-stealing roads.

But there’s another unutilized resource in cars – the roof. We can use the Activation principle to derive insights about the future of car roofs: hybrid cars will be covered with solar panels, which will be used to harvest energy when they’re sitting in the parking lot, and store it for the ride home.

Don’t get the math wrong: cars with solar roofs won’t be able to drive endlessly. In fact, if they rely only on solar power, they’ll barely even crawl. However, they will be able to power the electrical devices in the car, and trucks may even use solar energy on long journeys, to cool the wares they carry. If the cost of solar panel installation continues to go down, these uses could be viable within the decade.

 

The Activation of Farmlands

Farmlands are being activated today in many different ways: from sensors all over the field, and sometimes in every tree trunk, to farmers supplementing their livelihood by deploying solar panels and ‘farming electricity’. Some are combining both solar panels and crop and animal farming by spreading solar panels at a few meters height above the field, and growing plants that can make the most of the limited sunlight that gets to them.

 

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Anna Freund run the Open View Farm. Source: VPR

The Activation of the Air

Even the air around us can be activated. Aerial drones may be considered an initial attempt to activate the sky by filling them with flying sensors, but they are large, cumbersome and interfere with aerial traffic and with the view. However, we’ll be able to activate air in various other ways in the future, such as smart dust – extremely small sensors with limited wireless connectivity that will transmit data about their whereabouts and the conditions there.

 

The Activation of Food

Food is one of the only things that have barely been activated so far. Food today serves only two goals: to please by tasting great, and to nourish the body. According to the principle of Activation, however, food will soon serve several other purposes. Food items could be used to deliver therapeutics or sensors into the body, or possibly be produced with built-in biocompatible electronics and LEDs to make the food look better on the plate.

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Activated food: a banana with an edible food sensor, developed by researchers at Tufts University. Source: factcoexist.com

Conclusions

As human beings, we’ve always searched for ways to optimize efficiency and to make the best use of the limited resources we have. One of those limited resources is space, which is why we try to activate – add functions – to every surface and item today.

It’s fascinating to consider how the Activation of Everything will shape our world in the next few decades. We will have sensors everywhere, solar panels everywhere, batteries and electronics everywhere. It will be a world where nothing is as it seems at first glance anymore. An activated world – a living world indeed.