Do you want to know what war would look like in 2048? The Israeli artist Pavel Postovit has drawn a series of remarkable images depicting soldiers, robots and mechs – all in the service of the Israeli army in 2048. He even drew aerial ships resembling the infamous Triskelion from The Avengers (which had an unfortunate tendency to crash every second week or so).
Pavel is not the first artist to make an attempt to envision the future of war. Jakub Rozalski before him tried to reimagine World War II with robots, and Simon Stalenhag has many drawings that demonstrate what warfare could look like in the future. Their drawings, obviously, are a way to forecast possible futures and bring them to our attention.
Pavel’s drawings may not based on rigorous foresight research, but they don’t have to be. They are mainly focused on showing us one way the future may be unfurled. Pavel himself does not pretend to be a futures researcher, and told me that –
“I was influenced by all kind of different things – Elysium, District 9 [both are sci-fi movies from the last few years], and from my military service. I was in field intelligence, on the border with Syria, and was constantly exposed to all kinds of weapons, both ours and the Syrians.”
Here are a couple of drawings to make you understand Pavel’s vision of the future, divided according to categories I added. Be aware that the last picture is the most haunting of all.
Mechs in the Battlefield
Mechs are a form of ground vehicles with legs – much like Boston Dymanic’s Alpha Dog, which they are presumbaly based on. The most innovative of those mechs is the DreamCatcher – a unit with arms and hands that is used to collect “biological intelligence in hostile territory”. In one particularly disturbing image we can see why it’s called “DreamCatcher”, as the mech beheads a deceased human fighter and takes the head for inspection.
Apparently, mechs in Pavel’s future are working almost autonomously – they can reach hostile areas on the battlefield and carry out complicated tasks on their own.
Soldiers and Aerial Drones
Soldiers in the field will be companied by aerial drones. Some of the drones will be larger than others – the Tinkerbell, for example, can serve both for recon and personal CAS (Close Air Support) for the individual soldier.
Other aerial drones will be much smaller, and will be deployed as a swarm. The Blackmoth, for example, is a swarm of stealthy micro-UAVs used to gather tactical intelligence on the battlefield.
Technology vs. Simplicity
Throughout Pavel’s visions of the future we can see a repeated pattern: the technological prowess of the west is going to collide with the simple lifestyle of natives. Since the images depict the Israeli army, it’s obvious why the machines are essentially fighting or constraining the Palestinians. You can see in the images below what life might look like in 2048 for Arab civillians and combatants.
Another interesting picture shows Arab combatants dealing with a heavily armed combat mech by trying to make it lose its balance. At the same time, one of the combatants is sitting to the side with a laptop – presumbaly trying to hack into the robot.
The Last Image
If the images above have made you feel somewhat shaken, don’t worry – it’s perfectly normal. You’re seeing here a new kind of warfare, in which robots take extremely active parts against human beings. That’s war for you: brutal and horrible, and there’s nothing much to do against that. If robots can actually minimize the amount of suffering on the battlefield by replacing soldiers, and by carrying out tasks with minimal casualties for both sides – it might actually be better than the human-based model of war.
Perhaps that is why I find the last picture the most horrendous one. You can see in it a combatant, presumably an Arab, with a bloody machette next to him and two prisoners that he’s holding in a cage. The combatant is reading a James Bond book. The symbolism is clear: this is the new kind of terrorist / combatant. He is vicious, ruthless, and well-educated in Western culture – at least well enough to develop his own ideas for using technology to carry out his ideology. In other words, this is an ISIS combatant, who begin to employ some of the technologies of the West like aerial drones, without adhering to moral theories that restrict their use by nations.
The future of warfare in Pavel’s vision is beginning to leave the paradigm of human-on-human action, and is rapidly moving into robotic warfare. It is very difficult to think of a military future that does not include robots in it, and obviously we should start thinking right now about the consequences, and how (and whether) we can imbue robots with sufficient autonomous capabilities to carry out missions on their own, while still minimizing casualties on the enemy side.
You can check out the rest of Pavel’s (highly recommended) drawings in THIS LINK.
The future of genetic engineering at the moment is a mystery to everyone. The concept of reprogramming life is an oh-so-cool idea, but it is mostly being used nowadays in the most sophisticated labs. How will genetic engineering change in the future, though? Who will use it? And how?
In an attempt to provide a starting point to a discussion, I’ve analyzed the issue according to Daniel Burrus’ “Eight Pathways of Technological Advancement”, found in his book Flash Foresight. While the book provides more insights about creativity and business skills than about foresight, it does contain some interesting gems like the Eight Pathways. I’ve led workshops in the past, where I taught chief executives how to use this methodology to gain insights about the future of their products, and it had been a great success. So in this post we’ll try applying it for genetic engineering – and we’ll see what comes out.
Eight Pathways of Technological Advancement
Make no mistake: technology does not “want” to advance or to improve. There is no law of nature dictating that technology will advance, or in what direction. Human beings improve technology, generation after generation, to better solve their problems and make their lives easier. Since we roughly understand humans and their needs and wants, we can often identify how technologies will improve in order to answer those needs. The Eight Pathways of Technological Advancement, therefore, are generally those that adapt technology to our needs.
Let’s go briefly over the pathways, one by one. If you want a better understanding and more elaborate explanations, I suggest you read the full Flash Foresight book.
First Pathway: Dematerialization
By dematerialization we mean literally to remove atoms from the product, leading directly to its miniaturization. Cellular phones, for example, have become much smaller over the years, as did computers, data storage devices and generally any tool that humans wanted to make more efficient.
Of course, not every product undergoes dematerialization. Even if we were to minimize cars’ engines, they would still stay large enough to hold at least one passenger comfortably. So we need to take into account that the device should still be able to fulfil its original purpose.
Second Pathway: Virtualization
Virtualization means that we take certain processes and products that currently exist or are being conducted in the physical world, and transfer them fully or partially into the virtual world. In the virtual world, processes are generally streamlined, and products have almost no cost. For example, modern car companies take as little as 12 months to release a new car model to market. How can engineers complete the design, modeling and safety testing of such complicated models in less than a year? They’re simply using virtualized simulation and modeling tools to design the cars, up to the point when they’re crashing virtual cars with virtual crash dummies in them into virtual walls to gain insights about their (physical) safety.
Third Pathway: Mobility
Human beings invent technology to help them fulfill certain needs and take care of their woes. Once that technology is invented, it’s obvious that they would like to enjoy it everywhere they go, at any time. That is why technologies become more mobile as the years go by: in the past, people could only speak on the phone from the post office; today, wireless phones can be used anywhere, anytime. Similarly, cloud computing enables us to work on every computer as though it were our own, by utilizing cloud applications like Gmail, Dropbox, and others.
Fourth Pathway: Product Intelligence
This pathway does not need much of an explanation: we experience its results every day. Whenever our GPS navigation system speaks up in our car, we are reminded of the artificial intelligence engines that help us in our lives. As Kevin Kelly wrote in his WIRED piece in 2014 – “There is almost nothing we can think of that cannot be made new, different, or interesting by infusing it with some extra IQ.”
Fifth Pathway: Networking
The power of networking – connecting between people and items – becomes clear in our modern age: Napster was the result of networking; torrents are the result of networking; even bitcoin and blockchain technology are manifestations of networking. Since products and services can gain so much from being connected between users, many of them take this pathway into the future.
Sixth Pathway: Interactivity
As products gain intelligence of their own, they also become more interactive. Google completes our search phrases for us; Amazon is suggesting for us the products we should desire according to our past purchases. These service providers are interacting with us automatically, to provide a better service for the individual, instead of catering to some averaging of the masses.
Seventh Pathway: Globalization
Networking means that we can make connections all over the world, and as a result – products and services become global. Crowdfunding firms like Kickstarter, that suddenly enable local businesses to gain support from the global community, are a great example for globalization. Small firms can find themselves capable of catering to a global market thanks to improvements in mail delivery systems – like a company that delivers socks monthly – and that is another example of globalization.
Eighth Pathway: Convergence
Industries are converging, and so are services and products. The iPhone is a convergence of a cellular phone, a computer, a touch screen, a GPS receiver, a camera, and several other products that have come together to create a unique device. Similarly, modern aerial drones could also be considered a result of the convergence pathway: a camera, a GPS receiver, an inertia measurement unit, and a few propellers to carry the entire unit in the air. All of the above are useful on their own, but together they create a product that is much more than the sum of their parts.
How could genetic engineering progress along the Eight Pathways of technological improvement?
Pathways for Genetic Engineering
First, it’s safe to assume that genetic engineering as a practice would require less space and tools to conduct (Dematerializing genetic engineering). That is hardly surprising, since biotechnology companies are constantly releasing new kits and appliances that streamline, simplify and add efficiency to lab work. This criteria also answers the need for mobility (the third pathway), since it means complicated procedures could be performed outside the top universities and labs.
As part of streamlining the work process of genetic engineers, some elements would be virtualized. As a matter of fact, the Virtualization of genetic engineering has been taking place over the past two decades, with scientists ordering DNA and RNA codes from the internet, and browsing over virtual genomic databases like NCBI and UCSC. The next step of virtualization seems to be occurring right now, with companies like Genome Compiler creating ‘browsers’ for the genome, with bright colors and easily understandable explanations that reduce the level of skill needed to plan an experiment involving genetic engineering.
How can we apply the pathway of Product Intelligence to genetic engineering? Quite easily: virtual platforms for designing genetic engineering experiments will involve AI engines that will aid the experimenter with his task. The AI assistant will understand what the experimenter wants to do, suggest ways, methodologies and DNA sequences that will help him accomplish it, and possibly even – in a decade or two – conduct the experiment automatically. Obviously, that also answers the criteria of Interactivity.
If this described future sounds far-fetched, you should take into account that there are already lab robots conducting the most convoluted experiments, like Adam and Eve (see below). As the field of robotics makes strides forward, it is actually possible that we will see similar rudimentary robots working in makeshift biology Do-It-Yourself labs.
Networking and Globalization are essentially the same for the purposes of this discussion, and complement Virtualization nicely. Communities of biology enthusiasts are already forming all over the world, and they’re sharing their ideas and virtual schematics with each other. The iGEM (International Genetically Engineered Machines) annual competition is a good evidence for that: undergraduate students worldwide are taking part in this competition, designing parts of useful genetic code and sharing them freely with each other. That’s Networking and Globalization for sure.
Last but not least, we have Convergence – the convergence of processes, products and services into a single overarching system of genetic engineering.
Well, then, what would a convergence of all the above pathways look like?
The Convergence of Genetic Engineering
Taking together all of the pathways and converging them together leads us to a future in which genetic engineering can be performed by nearly anyone, at any place. The process of designing genetic engineering projects will be largely virtualized, and will be aided by artificial assistants and advisors. The actual genetic engineering will be conducted in sophisticated labs – as well as in makers’ houses, and in DIY enthusiasts’ kitchens. Ideas for new projects, and designs of successful past projects, will be shared on the internet. Parts of this vision – like virtualization of experiments – are happening right now. Other parts, like AI involvement, are still in the works.
What does this future mean for us? Well, it all depends on whether you’re optimistic or pessimistic. If you’re prone to pessimism, this future may look to you like a disaster waiting to happen. When teenagers and terrorists are capable of designing and creating deadly bacteria and viruses, the future of mankind is far from safe. If you’re an optimist, you could consider that as the power to re-engineer life comes down to the masses, innovations will rise everywhere. We will see glowing trees replacing lightbulbs in the streets, genetically engineered crops with better traits than ever before, and therapeutics (and drugs) being synthetized in human intestines. The truth, as usual, is somewhere in between – and we still have to discover it.
Twenty years ago, when I was young and beautiful, I picked up a wrapped pack of cards in a computer games store, and read for the first time the tag “Magic: the Gathering”. That was the beginning of my long-time romance with the collectible card game. I imported the game to Israel, translated the rules leaflet to Hebrew for my friends, and went on to play semi-professionally for twenty years, up to the point when I became the Israeli champion. The game has pretty much shaped my years as a teenager, and has helped me make friends and meet interesting people from all over the world.
That is why it’s so sad to me to see the state of the game right now, and realize that it is almost certainly doomed to fail in the long run.
The Rise and Decline of Magic the Gathering
Make no mistake: Magic the Gathering (just Magic in short) is still the top dog among collectible card games in the physical world. According to a report released in 2014, the annual revenue from Magic has grown by 182% between 2009 and 2014, reaching a total value of around $250 million a year. That’s a lot of money, to be sure.
The only problem is that Hearthstone, a digital card game released in the beginning of 2014, has reached annual revenues of around $240 million, in less than two years. I will not be surprised to see the numbers growing even larger that in the future.
This is a bizarre situation. Wizards of the Coast (WotC), the company behind Magic, had twenty years to take the game online and turn it into a success. They failed miserably, and their meager attempts at became a target for scorn and ridicule from players worldwide. While WotC did create an online platform to play Magic on, there were plenty of complaints: for starters, playing was extremely costly since the virtual card packs generally cost the same as packs in the physical world. An evening of playing a draft – a small tournament with only eight players – would’ve cost each player around ten dollars, and would’ve required a time investment of up to four straight hours, much of it wasted in waiting for the other players in the tournament to finish their matches with each other and move on to the next round.
These issues meant that Magic Online was mostly reserved for the top players, who had the money and the willingness to spend it on the game. WotC was aware of the disgruntlement about the state of things, but chose to do nothing – after all, it had no real contenders in the physical or the digital market. What did it have to fear? It had no real reason to change. In fact, the only smart decision WotC managers could take was NOT to take a risk and try to change the online experience, but to keep on making money – and lots of it – from a game that functioned well enough. And they could continue doing so until their business was rudely and abruptly disrupted.
The Business Theory of Disruption
The theory of disruption was originally conceived by Harvard Business School professor Clayton M. Christensen, and described in his best-selling book The Innovator’s Dilemma. Christensen has followed the evolution of several industries, particularly hard drives, but also including metalworking, retail stores and tractors. He found out that in each sector, the managers supported research and development, but all that R&D produced only two general kinds of innovations: sustaining innovations and disruptive ones.
The sustaining innovations were generally those that the customers asked for: increasing hard drive storage capacity, or making data retrieval faster. They led to obvious improvements, which brought immediate and clear benefit to the company in a competitive market.
The disruptive innovations, on the other hand, were those that completely changed the picture, and actually had a good potential to cost the company money in the short-term. Furthermore, the customers saw little value in them, and so the managers saw no advantage in pursuing these innovations. The company-employed engineers who came up with the ideas for disruptive innovations simply couldn’t find support for them in the company.
A good example for the process of disruption is that of the hard drive industry, a few years before the transition from 8-inch drives to 5.25-inch drives occurred. A quick look at the following parameters of the two contenders, back in 1981, explains immediately why managers in the 8-inch drive manufacturing companies were wary of switching over to the 5.25-inch drive market. The 5.25-inch drives were simply inefficient, and lost the competition with 8-inch drives in almost every parameter, except for their size! And while size is obviously important, the computer market at the time consisted mainly of “minicomputers” – computers that cost ~$25,000, and were the size of a small refrigerator. At that size, the physical volume of the hard drives was simply irrelevant.
And so, 8-inch drive companies continued to focus on 8-inch drives, while a few renegade engineers opened new companies and worked hard on developing better 5.25-inch drives. In a few years, the 5.25-inch drives were just as efficient as the 8-inch drives, and a new market formed: that of the personal desktop computer. Suddenly, every computer maker in the market needed 5.25-inch drives.
Now, the 8-inch drive company managers were far from stupid or ignorant. When they saw that there was a market for 5.25-inch drives, they decided to leap on the opportunity as well, and develop their own 5.25-inch drives. Sadly, they were too late. They discovered that it takes time and effort to become acquainted with the demands of the new market, to adapt their manufacturing machinery and to change the entire company’s workflow in order to produce and supply computer makers with 5.25 drives. They joined the competition far too late, and even though they were the leviathans of the industry just ten years ago, they soon sunk to the bottom and were driven out of business.
What happened to the engineers who drove forward the 5.25-inch drives revolution, you may ask? They became CEOs of the new 5.25-inch drive manufacturing companies. A few years later, when their own young engineers came to them and suggested that they invest in developing the new and faulty 3.5-inch drives, they decided that there was no market for this invention right now, no demand for it, and that it’s too inefficient anyway.
Care to guess what happened next? Ten years later, the 3.5-inch drives took over, portable computers utilizing them were everywhere, and the 5.25-inch drive companies crumbled away.
That is the essence of disruption: decisions that make sense in the present, are clearly incorrect in the long term, when markets change. Companies that relax and only invest in sustaining innovations instead of trying to radically change their products and reshape the markets themselves, are doomed to fail. In Peter Diamandis words –
“If you aren’t disrupting yourself, someone else is.”
Now that you understand the basics of the Theory of Disruption, let’s see how it applies to Magic.
Magic and Disruption
Wizards of the Coast has been making almost exclusively sustaining improvements over the last twenty years: its talented R&D team focused almost exclusively on releasing new expansions with new cards and new playing mechanics. WotC also tried to disrupt themselves once by creating the Magic Online platform, but failed to support and nurture this disruptive innovation. The online platform remained mainly as an outdated relic – a relic that made money, to be sure, but was slowly becoming irrelevant in the online world of collectible card games.
In the last five years, many other collectible card games reared their heads online, including minor successes like Shadow Era (200,000 players, ~$156,000 annual revenue) and Urban Rivals (estimated ~$140,000 annual revenue). Each of the above made discoveries in the online world: they realized that players need to be offered cards for free, that they need to be lured to play every day, and that the free-to-play model can still prove profitable since the company’s costs are close to zero: the firm doesn’t need to physically print new cards or to distribute them to retailers. But these upstarts were still so small that WotC could afford to effectively ignore them. They didn’t pose a real threat to Magic.
Then Hearthstone burst into existence in 2014, and everything changed.
Hearthstone’s developers took the best traits of Magic and combined it with all the insights the online gaming industry has developed over recent years. They made the game essentially free to play to attract a large number of players, understanding that their revenues would come from the small fraction of players who spent some money on the game. They minimized time waste by setting a time limit on every player’s turn, and by establishing a rule that players can only act during their own turn (so there’s no need to wait for the other player’s response after every move). They even broke down the Magic draft tournaments of eight people, and made it so that every player who drafted a deck can now play against any other player who drafted a deck at any time. There’s no time waste in Hearthstone – just games to play and fun to be had.
WotC was still deep asleep at that time. In July 2014, Magic brand manager Liz Lamb-Ferro told GamesBeat that –
“If you’re looking for just that immediate face-to-face, back-and-forth action-based game with not a lot of depth to it, then you can find that. … But if you want the extras … then you’re eventually going to find your way to Magic.”
Lamb-Ferro was right – Hearthstone IS a simpler game – but that simplicity streamlines gameplay, and thus makes the game more rapid and enjoyable to many players. And even if we were to accept that Hearthstone does not attract veteran players who “want the extras” (actually, it does), WotC should have realized that other online collectible card games would soon combine Magic’s sophistication with Hearthstone’s mechanisms for streamlining gameplay. And indeed, in 2014 a new game – SolForge – has taken all of the strengths of Hearthstone, while adding a mechanic of card transformation (each card transforming into three different versions of itself) that could only have been possible in card games played online. SolForge doesn’t even have a physical version and could never have one, and the game is already costing Magic a few more veteran players.
This is the point when WotC began realizing that they’re falling far behind the curve. And so, in the middle of 2015 they have released Duels of the Planeswalkers 2016. I won’t even bother detailing all the infuriating problems with the game. Suffice it to say that it has garnered more negative reviews than positive ones, and made clear that WotC were still lagging far behind their competitors in their understanding of the virtual world, user experience, and what players actually want. In short, WotC found themselves in the position of the 8-inch drive manufacturers, realizing suddenly that the market has changed under their noses in less than two years.
What Could WotC do?
The sad truth is that WotC can probably do nothing right now to fix Magic. The firm can continue churning out sustaining improvements – new expansions and new exciting cards – but it will find itself hard pressed to take over the digital landscape. Magic is a game that was designed for the physical world, and not for the current frenzied pace of the virtual collectible card games. Magic simply isn’t suitable for the new market, unless WotC changes the rules so much that it’s no longer the same game.
Could WotC change the rules in such a dramatic fashion? Yes, but at a great cost. The company could recreate the game online with new cards and rules, but it would have to invest time and effort in relearning the workings of the virtual world and creating a new platform for the revised Magic. Unfortunately, it’s not clear that WotC will have time to do that with Hearthstone, SolForge and a horde of other card games snarling at its heels. The future of Magic online does not look bright, to say the least.
Does that mean Magic the Gathering will vanish completely? Probably not. The Magic brand is still strong everywhere except for the virtual world, which means that in the next five years the game will remain in existence mostly in the physical world, where it will bring much joy to children in school breaks, and much money to the pockets of WotC. During these five years, WotC will have the opportunity to rethink and recreate the game for the next big market: virtual and augmented reality. If the firm succeeds in that front, it’s possible that Magic will be reinvented for the new-new market. If it fails and elects to keep the game anchored only in the physical world, then Magic will slowly but surely vanish away as the market changes and new and exciting games take over the attention span of the next generation.
That’s what happens when you disregard the Theory of Disruption.
Whenever a futurist talks about the future and lays out all the dazzling wealth technological advancements hold in store for us, there is one question that is always asked by the audience.
“Where is that flying car you promised me?”
Well, we may be drawing near to a future of flying cars. While the road to that future may still be long and arduous, I’m willing to forecast that in twenty years from now we will have flying cars for use by civilians – but only if three technological and societal conditions will be fulfilled by that time.
In order to understand these conditions, let us first examine briefly the history of flying cars, and understand the reasons behind their absence in the present.
Flying Cars from the Past
Surprising as it may be, the concept of flying cars has been around far longer than the Back to the Future trilogy. Henry Ford himself had produced in 1926 a rudimentary and experimental ‘flying car’, although really it was more of a mini-airplane for the average American consumer. Despite the excitement from the public, the idea crashed and burned in two years, together with the prototype and its test pilot.
Since the 1920s, it seems like innovators and inventors came up with flying cars almost once a decade. You can see pictures of some of these cars in Popular Mechanics’ gallery. Some crashed and burned, in the tradition set by Ford. Others managed to soar sky high. None actually made it to mass production, for two main reasons:
Extremely wasteful: flying cars are extremely wasteful in terms of fuel consumption. Their energy efficiency is abysmal when compared to that of high-altitude and high-speed airplanes.
Extremely unsafe: let’s be honest for a moment, OK? You give people cars that can drive in what is essentially a one-dimensional road, and what do they do? They make traffic accidents. What do you think would happen if you gave everyone the ability to drive a car in three dimensions? Crash, crash and burn all over again. For flying cars to become widely used in society, everyone needs to take flying lessons. Good luck with that.
These two limitations together made sure that flying cars to the masses were left a fantasy – and still largely are. In fact, I would go as far as saying that any new concept or prototype of a flying car that does not take these challenges into account, is only presented to the public as a ‘flying car’ as a publicity stunt.
But now, things are beginning to change, because of three trends that together will provide answers to the main barriers standing in the way of flying cars.
The Three Trends that will Enable Flying Cars
There are three trends that, combined, will enable the use of flying cars by the public within twenty years.
First Trend: Massive Improvement in Aerial Drones Capabilities
If you visit your city’s playgrounds, you may find children there having fun flying drones around. The drones they’re using – which often cost less than $200 – would’ve considered highly sophisticated weapons of war just twenty years ago, and would’ve been sold by arms manufactures at prices in the order of millions of dollars.
Dr. Peter Diamandis, innovator, billionaire and futurist, has written in 2014 about the massive improvement in capabilities of aerial drones. Briefly, current-day drones are a product of exponential improvement in computing elements (inertial measurement units), communications (GPS receivers and system), and even sensors (digital cameras). All of the above – at their current sizes and prices – would not have been available even ten years ago.
Aerial drones are important for many reasons, not least because they may yet serve as the basis for a flying car. Innovators, makers and even firms today are beginning to strap together several drones, and turn them into a flying platform that can carry individuals around.
The most striking example of this kind comes from a Canadian inventor who has recently flown 275 meters on a drone platform he has basically fashioned in his garage.
Another, a more cumbersome version of Human-Transportation Drones (Let’s call them HTD from now on, shall we?) was demonstrated this week at the Las Vegas Convention Center. It is essentially a tiny helicopter with four double-propellers attached, much like a large drone. It has place for just one traveler, and can fly up to 23 minutes according to the manufacturers. Most importantly, the Ehang 184 as it’s called is supposed to be autonomous, which brings us straight to the next trend: the rise of machine intelligence.
Second Trend: Machine Intelligence and Flying Cars
There can be little question that drones will keep on improving in their capabilities. We will improve our understanding of the science and technology behind aerial drones, and develop more efficient tools for aerial travel, including some that will carry people around. But will these tools be available for mass-use?
This is where the safety barrier comes into the picture. You can’t let the ordinary Joe Shmoe control a vehicle like the Ehang 184, or even a light-weight drone platform. Not without teaching them how to fly the thing, which would take a long time to practice, lots of money, and will sharply limit the number of potential users.
This is where machine intelligence comes into the picture.
Autonomous control is virtually a must for publicly usable HTDs. Luckily, machine intelligence is making leaps and bounds forward, with autonomous (driverless) cars travelling the roads even today. If such autonomous systems can function for cars on the roads, why not do the same for drones in the air?
As things currently stand, all aerial drones will have to be controlled at least partly-autonomously, in order to prevent collisions with other drones. NASA is planning a “Traffic Management Convention” for drones, which could include tens of thousands of drones – and much more than that, if the need arises. The next logical step, therefore, is to include future HTDs into this future system, thus taking the control out of the pilot’s hands and transferring it completely to the vehicle and the system controlling it.
If the said system for managing aerial traffic becomes a reality, and assuming that drones capabilities are advanced enough to provide human transportation services, then autonomous HTDs for mass use will not be far behind.
The two last trends have covered the second barrier of inherent unsafety. The third trend I will present now deals with the first barrier of inefficient and wasteful use of energy.
Third Trend: Solar Energy
All small drones rely on electricity to function. Even a larger drone like the Ehang 184 that could be used for human transport, is powered by electricity, and can fly for 23 minutes before requiring a recharge. While 23 minutes may not sound like a lot of time, it’s more than enough for people to ‘hop’ from one side of most cities to the other, as long as there isn’t aerial congestion.
Of course, that’s the situation today. But batteries keep on improving. Elon Musk claims that by 2017, Tesla’s electric cars will have a 600 mile range on a single charge, for example. As batteries improve further, HTDs will be able to stay in the air for even longer periods of time, despite being powered by electricity alone. The adherence to electricity is important since in twenty years from now it is highly likely that we’ll have much cheaper electric energy coming directly from the sun.
Support for this argument comes from the exponential decline in the costs associated with producing and utilizing solar energy. Forty years ago, it would’ve cost about $75 to produce one watt of solar energy. Today the cost is less than a single dollar per watt. And as prices go down, the number of solar panels installation soars sky-high, roughly doubling itself every two years. Worldwide solar capacity in 2014 has been 53 times higher than in 2005.
If the rising trend of solar energy does not grind to a halt sometime in the next decade, then we will obtain much of our electric energy from the sun. We won’t have usable passenger solar airplanes – these need high-energy jet fuel to operate – but we will have solar panels pretty much everywhere: covering the sides and top of every building, and quite possibly every car as well. Buildings would both consume and produce energy. Much of the unneeded energy would be saved in batteries, or almost instantaneously diverted via the smart grid to other spots in the city where it’ll be needed.
If that is the face of the future – and the trends support this view – then HTDs could be an optimal way of transportation in the city of the future. Aerial drones could be deployed on tops of houses and skyscrapers, where they will be constantly charged by solar panels until they need to take a passenger to another house. Such a leap would only take 10-15 minutes, followed by a recharging period of 30 minutes or so. The entire system would operate autonomously – without human control or interference – and be powered by the sun.
Conclusions and Forecast for the Future
When can we expect this system to be deployed? Obviously it’s difficult to be certain about the future, particularly in cases where technological trends meet with societal, legal and political barriers to entry. Current culture will find it difficult to accept autonomous vehicles, and Big Fossil Fuel firms are still trying to pretend solar energy isn’t here to stay.
All the same, it seems that HTDs are already rearing their heads, with several inventors working separately to produce them. Their attempts are still extremely hesitant, but every attempt demonstrates the potential in HTDs and their viability for human transportation. I would therefore expect that in the next five years we will see demonstrations of HTDs (not for public use yet) that can carry individuals to a distance of at least one mile, and can be fully charged within one hour by solar panels alone. That is the easy forecast to make.
The more difficult forecast involves the use of autonomous aerial drones, the assimilation of HTDs into an overarching system that controls all the drones in a shared aerial space, and a mass-deployment of HTDs in a city. Each of these achievements needs to be made separately in order to fulfill the larger vision of a flying car to the masses. I am going to take a wild guess here, and suggest that if no Hindenburg-like disaster happens, then we’ll see real flying cars in our cities in twenty years from now – by the year 2035. It is likely that these HTDs will only be able to carry a single individual, and will probably be used more as a ‘flying taxi’ service between buildings to individual businessmen than a full-blown family flying car.
And then, finally, when people ask me where their flying car is, I will be able to provide a simple answer: “It’s parked on the roof.”
A week ago I lectured in front of an exceedingly intelligent group of young people in Israel – “The President’s Scientists and Inventors of the Future”, as they’re called. I decided to talk about the future of robotics and their uses in society, and as an introduction to the lecture I tried to dispel a few myths about robots that I’ve heard repeatedly from older audiences. Perhaps not so surprisingly, the kids were just as disenchanted with these myths as I was. All the same, I’m writing the five robot myths here, for all the ‘old’ people (20+ years old) who are not as well acquainted with technology as our kids.
As a side note: I lectured in front of the Israeli teenagers about the future of robotics, even though I’m currently residing in the United States. That’s another thing robots are good for!
First Myth: Robots must be shaped as Humanoids
Ever since Karel Capek’s first play about robots, the general notion in the public was that robots have to resemble humans in their appearance: two legs, two hands and a head with a brain. Fortunately, most sci-fi authors stop at that point and do not add genitalia as well. The idea that robots have to look just like us is, quite frankly, ridiculous and stems from an overt appreciation of our own form.
Today, this myth is being dispelled rapidly. Autonomous vehicles – basically robots designed to travel on the roads – obviously look nothing like human beings. Even telepresence robots manufacturers have despaired of notions about robotic arms and legs, and are producing robots that often look more like a broomstick on wheels. Robotic legs are simply too difficult to operate, too costly in energy, and much too fragile with the materials we have today.
Second Myth: Robots have a Computer for a Brain
This myth is interesting in that it’s both true and false. Obviously, robots today are operated by artificial intelligence run on a computer. However, the artificial intelligence itself is vastly different from the simple and rules-dependent ones we’ve had in the past. The state-of-the-art AI engines are based on artificial neural networks: basically a very simple simulation of a small part of a biological brain.
The big breakthrough with artificial neural network came about when Andrew Ng and other researchers in the field showed they could use cheap graphical processing units (GPUs) to run sophisticated simulations of artificial neural networks. Suddenly, artificial neural networks appeared everywhere, for a fraction of their previous price. Today, all the major IT companies are using them, including Google, Facebook, Baidu and others.
Although artificial neural networks were reserved for IT in recent years, they are beginning to direct robot activity as well. By employing artificial neural networks, robots can start making sense of their surroundings, and can even be trained for new tasks by watching human beings do them instead of being programmed manually. In effect, robots employing this new technology can be thought of as having (exceedingly) rudimentary biological brains, and in the next decade can be expected to reach an intelligence level similar to that of a dog or a chimpanzee. We will be able to train them for new tasks simply by instructing them verbally, or even showing them what we mean.
This video clip shows how an artificial neural network AI can ‘solve’ new situations and learn from games, until it gets to a point where it’s better than any human player.
Admittedly, the companies using artificial neural networks today are operating large clusters of GPUs that take up plenty of space and energy to operate. Such clusters cannot be easily placed in a robot’s ‘head’, or wherever its brain is supposed to be. However, this problem is easily solved when the third myth is dispelled.
Third Myth: Robots as Individual Units
This is yet another myth that we see very often in sci-fi. The Terminator, Asimov’s robots, R2D2 – those are all autonomous and individual units, operating by themselves without any connection to The Cloud. Which is hardly surprising, considering there was no information Cloud – or even widely available internet – back in the day when those tales and scripts were written.
Robots in the near future will function much more like a team of ants, than as individual units. Any piece of information that one robot acquires and deems important, will be uploaded to the main servers, analyzed and shared with the other robots as needed. Robots will, in effect, learn from each other in a process that will increase their intelligence, experience and knowledge exponentially over time. Indeed, shared learning will result in an acceleration of AI development rate, since the more robots we have in society – the smarter they will become. And the smarter they will become – the more we will want to assimilate them in our daily lives.
The Tesla cars are a good example for this sort of mutual learning and knowledge sharing. In the words of Elon Musk, Tesla’s CEO –
“The whole Tesla fleet operates as a network. When one car learns something, they all learn it.”
Fourth Myth: Robots can’t make Moral Decisions
In my experience, many people still adhere to this myth, under the belief that robots do not have consciousness, and thus cannot make moral decisions. This is a false correlation: I can easily program an autonomous vehicle to stop before hitting human beings on the road, even without the vehicle enjoying any kind of consciousness. Moral behavior, in this case, is the product of programming.
Things get complicated when we realize that autonomous vehicles, in particular, will have to make novel moral decisions that no human being was ever required to make in the past. What should an autonomous vehicle do, for example, when it loses control over its brakes, and finds itself rushing to collision with a man crossing the road? Obviously, it should veer to the side of the road and hit the wall. But what should it do if it calculates that its ‘driver’ will be killed as a result of the collision into the wall? Who is more important in this case? And what happens if two people cross the road instead of one? What if one of those people is a pregnant woman?
These questions demonstrate that it is hardly enough to program an autonomous vehicle for specific encounters. Rather, we need to program into it (or train it to obey) a set of moral rules – heuristics – according to which the robot will interpret any new occurrence and reach a decision accordingly.
And so, robots must make moral decisions.
As I wrote in the beginning of this post, the youth and the ‘techies’ are already aware of how out-of-date these myths are. Nobody as yet, though, knows where the new capabilities of robots will take us when they are combined together. What will our society look like, when robots are everywhere, sharing their intelligence, learning from everything they see and hear, and making moral decisions not from an individual unit perception (as we human beings do), but from an overarching perception spanning insights and data from millions of units at the same time?
This is the way we are heading to – a super-intelligence composed of a combination of incredibly sophisticated AI, with robots as its eyes, ears and fingertips. It’s a frightening future, to be sure. How could we possibly control such a super-intelligence?
That’s a topic for a future post. In the meantime, let me know if there are any other myths about robots you think it’s time to ditch!
Almost four years ago, the presidential elections took place in the United States. Barack Obama competed against Mitt Romney in the race for the White House. Both candidates delivered inspiring speeches, appeared in every institute that would accept their presence, and employed hundreds of paid consultants and volunteers who advertised them throughout the nation. In the end, Obama won the race for the presidency, possibly because of his opinions and ideas… or because of his reliance on data scientists. In fact, as Sasha Issenberg’s article of the 2012 elections in MIT Technology Review describes –
“Romney’s data science team was less than one-tenth the size of Obama’s analytics department.”
How did Obama utilize all of those data scientists?
Analyzing the Individual Voter
Up to 2012, individual voters were analyzed according to a relatively simplistic system which only took into account very limited parameters such as age, place of living, etc. The messages those potential voters received to their phones, physical mailboxes and virtual inboxes were customized according to these parameters. Obama’s team of data scientists expanded the list of parameters into tens of different parameters and criteria. They then utilized a system in which customized messages were mailed to certain representative voters, who were later surveyed so that the scientists could figure out how their opinions changed according to the structure of the messages sent.
This level of analysis and understanding of the individual voters and the messages that helped them change their opinions aided Obama in delivering the right messages, at the right time, to the persuadable people. If the term “persuadable” strikes you as sinister, as if Obama’s team were preying on the weak of mind or those sitting on the fence, you should be aware that it was used by Terry Walsh, who coordinated Obama’s campaign’s polling and paid-media spending.
Of course, being a “persuadable” voter does not mean that you’re a helpless dummy. Rather, it just means that you’re still uncertain which way to turn. But when political parties can find those undecided voters, focus on them and analyze each one with the most sophisticated computer models available to find out all about their levers and buttons, how much free choice does that leave those people?
I could go on describing other strategies utilized by Obama’s team in the 2012 elections. They identified voters who were likely to ‘switch sides’ following just one phone call, and had about 500,000 conversations with those voters. They supplied to a data collection firm the addresses of many “easily persuadable” voters, and received in return the records of TV watching in those households. That way, the campaign team could maximize the efficiency of TV advertisements – fitting them to the right time, in the right channels, and in the right destinations. All of the above is well recorded, and described in Issenberg’s article and other resources (like this, that, and others).
The Republican Drowning Whale
Obama wasn’t the only one to utilize big data and predictive analytics in the 2012 campaign. His opponent, Mitt Romney, had a team of data scientists of his own. Unfortunately for Romney, his team didn’t even come close to the level of operations of Obama’s team. Romney’s team invested much of its effort in an app named Orca, which was supposed to indicate which of the expected republican voters actually turned up to vote – and to send messages to the republican slackers and encourage them to haul their tucheses to the voting booths. In practice, the app was horribly conceived, and crashed numerous times during Election Day, leading to utter confusion about the goings on.
Regardless of the success of the Democrats data systems vs. the Republicans’ ones, one thing is clear: both parties are going to use big data and predictive analytics in the upcoming 2016 elections. In fact, we are going into a very interesting stage in the history of the 21st century: the Data Race.
From Space to Data
The period in time known as the Space Race took place in the 1960s, when the United States competed against the Soviet Union in a race to space. As a result of the Space Race, space launch technologies developed and made progress in leaps and bounds, with both countries fighting to demonstrate their superior science and technology. Great need – and great budgets – produce great results quickly.
In 2016, we will see a new kind of race starting – the Data Race. In 2012 it wasn’t really a race. The Democrats basically stepped on the Republicans. In 2016, however, the real Data Race in politics will be on: The Democrats will gather their teams of data scientists once more, and build up on the piles of data that were gathered in the 2012 elections and since then. The Republicans – possibly Trump with his self-funded election campaign – will learn from their mistakes in 2012, hire the best data scientists they can find, and utilize methodologies similar or better than those developed by the Democrats.
In short, both parties will find themselves in the midst of a Data Race, striving to obtain as much data as they can about the American citizen, about our lifestyles, habits, choices and any other tidbit of information that can be used to understand the individual voter – and how best to approach him or here and convert him to the party’s point of view. The data gathering and analysis systems will cost a lot, obviously, but since recent rulings in America allow larger contributions to be made to political candidates, money should not be a problem.
Conclusion: Where are We Heading?
It’s quite obvious that both American parties in 2016 are going to compete in a Data Race between them. The bigger questions is whether we should even allow them to do it so freely. Democracy, after all, is based on the assumption that every person can make his or her own mind and decisions. Do we really honor that core assumption, when political candidates can analyze human beings with the power of super-computers, big data and predictive analytics? Can an individual citizen truly choose freely, when powers on both sides are pulling and pushing at that individual’s levers and buttons, with methods tested and proven on millions of similarly-minded individuals?
Using predictive analytics in politics holds an inherent threat to democracy: by understanding each individual, we can also devise approaches and methodologies to influence every individual with maximal efficiency. This approach has the potential to turn most individuals into mere puppets in the hands of the powerful and the affluent.
Does that mean we should refrain from using big data and predictive analytics in politics? Of course not – but we can regulate its use so that instead of campaign managers focusing their efforts on the “easily persuadable”, they will use the data gleaned from the public to understand people’s real concerns and work to address them. We should all hope our politicians are heading in that direction, and if they aren’t – we should give them a shove towards it.
A week ago I covered in this blog the possibility of using aerial drones for terrorist attacks. The following post dealt with the Failure of Myth and covered Causal Layered Analysis (CLA) – a futures studies methodology meant to counter the Failure of Myth and allow us to consider alternative futures radically different from the ones we tend to consider intuitively.
In this blog post I’ll combine insights from both recent posts together, and suggest ways to deal with the terrorism threat posed by aerial drones, in four different layers suggested by CLA: the Litany, the Systemic view, the Worldview, and the Myth layer.
To understand why we have to use such a wide-angle lens for the issue, I would compare the proliferation of aerial drones to another period in history: the transition between the Bronze Age and the Iron Age.
From Bronze to Iron
Sometime around 1300 BC, iron smelting was discovered by our ancient forefathers, assumedly in the Anatolia region. The discovery rapidly diffused to many other regions and civilizations, and changed the world forever.
If you ask people why iron weapons are better than bronze ones, they’re likely to answer that iron is simply stronger, lighter and more durable than bronze. However, the truth is that bronze weapons are not much more efficient than iron weapons. The real importance of iron smelting, according to “A Short History of War” by Richard A. Gabriel and Karen S. Metz, is this:
“Iron’s importance rested in the fact that unlike bronze, which required the use of relatively rare tin to manufacture, iron was commonly and widely available almost everywhere… No longer was it only the major powers that could afford enough weapons to equip a large military force. Now almost any state could do it. The result was a dramatic increase in the frequency of war.”
It is easy to imagine political and national leaders using only the first and second layer of CLA – the Litany and the Systemic view – at the transition from the Bronze to the Iron Age. “We should bring these new iron weapons to all our soldiers”, they probably told themselves, “and equip the soldiers with stronger shields that can deflect iron weapons”. Even as they enacted these changes in their armies, the worldview itself shifted, and warfare was vastly transformed because of the large number of civilians who could suddenly wield an iron weapon. Generals who thought that preparing for the change merely meant equipping their soldiers with an iron weapon, found themselves on the battlefield facing armies much larger than their own, because of new conscription models that their opponents had developed.
Such changes in warfare and in the existing worldview could have been realized in advance by utilizing the third and fourth layers of CLA – the Worldview and the Myth.
Aerial drones are similar to Iron Age weapons in that they are proliferating rapidly. They can be built or purchased at ridiculously low prices, by practically everyone. In the past, only the largest and most technologically-sophisticated governments could afford to employ aerial drones. Nowadays, every child has them. In other words, the world itself is turning against everything we thought we knew about the possession and use of unmanned aerial vehicles. Such dramatic change – that our descendants may yet come to call The Aerial Age when they look back in history – forces us to rethink everything we knew about the world. We must, in short, analyze the issue from a wide-angle view, with an emphasis on the third and fourth layer of CLA.
How, then, do we deal with the threat aerial drones pose to national security?
First Layer: the Litany
The intuitive way to deal with the threat posed by aerial drones, is simply to reinforce the measures and we’ve had in place before. Under the thinking constraints of the first layer, we should basically strive to strengthen police forces, and to provide larger budgets for anti-terrorist operations. In short, we should do just as we did in the past, but more and better.
It’s easy to see why public systems love the litany layer, since these measures create reputation and generate a general feeling that “we’re doing something to deal with the problem”. What’s more, they require extra budget (to be obtained from congress) and make the organization larger along the way. What’s there not to like?
Second Layer: the Systemic View
Under the systemic view we can think about the police forces, and the tools they have to deal with the new problem. It immediately becomes obvious that such tools are sorely lacking. Therefore, we need to improve the system and support the development of new techniques and methodologies to deal with the new threat. We might support the development of anti-drone weapons, for example, or open an entirely new police department dedicated to dealing with drones. Police officers will be trained to deal with aerial drones, so that nothing is left for chance. The judicial and regulatory systems are lending themselves to the struggle at this layer, by issuing highly-regulated licenses to operate aerial drones.
Again, we could stop the discussion here and still have a highly popular set of solutions. As we delve deeper into the Worldview layer, however, the opposition starts building up.
Third Layer: the Worldview
When we consider the situation at the worldview layer, we see that the proliferation of aerial drones is simply a by-product of several technological trends: miniaturization and condensation of electronics, sophisticated artificial intelligence (at least in terms of 20-30 years ago) for controlling the rotor blades, and even personalized manufacturing with 3D-printers, so that anyone can construct his or her own personal drone in the garage. All of the above lead to the Aerial Age – in which individuals can explore the sky as they like.
Looking at the world from this point of view, we immediately see that the vast expected proliferation of aerial drones in the near decade would force us to reconsider our previous worldviews. Should we really focus on local or systemic solutions, rather than preparing ourselves for this new Aerial Age?
We can look even further than that, of course. In a very real way, aerial drones are but a symptom of a more general change in the world. The Aerial Age is but one aspect of the Age of Freedom, or the Age of the Individual. Consider that the power of designing and manufacturing is being taken from nations and granted to individuals via 3D-printers, powerful personal computers, and the internet. As a result of these inventions and others, individuals today hold power that once belonged only to the greatest nations on Earth. The established worldview, in which nations are the sole holders of power is changing.
When one looks at the issue like this, it is clear that such a dramatic change can only be countered or mitigated by dramatic measures. Nations that want to retain their power and prevent terrorist attacks will be forced to break rules that were created long ago, back in the Age of Nations. It is entirely possible that governments and rulers will have to sacrifice their citizens’ privacy, and turn to monitoring their citizens constantly much as the NSA did – and is still doing to some degree. When an individual dissident has the potential to bring harm to thousands and even millions (via synthetic biology, for example), nations can ill afford to take any chances.
What are the myths that such endeavors will disrupt, and what new myths will they be built upon?
Fourth Layer: the Myth
I’ve already identified a few myths that will be disrupted by the new worldview. First and foremost, we will let go of the idea that only a select few can explore the sky. The new myth is that of Shared Sky.
The second myth to be disrupted is that nations hold all the technological power, while terrorists and dissidents are reduced to using crude bombs at best, or pitchforks at worst. This myth is no longer true, and it will be replaced by a myth of Proliferation of Technology.
The third myth to be dismissed is that governments can protect their citizens efficiently with the tools they have in the present. When we have such widespread threats in the Age of Freedom, governments will experience a crisis in governance – unless they turn to monitoring their citizens so closely that any pretense of privacy is lost. And so, it is entirely possible that in many countries we will see the emergence of a new myth: Safety in Exchange for Privacy.
Last week I’ve analyzed the issue of aerial drones being used for terrorist attacks, by utilizing the Causal Layered Analysis methodology. When I look at the results, it’s easy to see why many decision makers are reluctant to solve problems at the third and fourth layer – Worldview and Myth. The solutions found in the lower layers – the Litany and the Systemic view – are so much easier to understand and to explain to the public. Regardless, if you want to actually understand the possibilities the future holds in any subject, you must ignore the first two layers in the long term, and focus instead on the large picture.
And with that said – happy new year to one and all!
A year ago I wrote a short chapter for a book about emerging technologies and their impact on security, published by Yuval Ne’eman Workshop for Science, Technology & Security and curated by Deb Housen-Couriel. The chapter focused on drones and the various ways they’re being used in the hands of criminals to smuggle drugs across borders, to identify and raid urban marijuana farms operated by rival gangs, and to smuggle firearms and lifestyle luxury items over prison walls. At the end of the paper I provided a forecast: drones will soon be used by terrorists to kill people.
Well, it looks like the future is catching up with us, since a report from Syria (as covered in Popular Mechanic) has just confirmed that ISIS is using small drones as weapons, albeit not very sophisticated ones. In fact, the terrorists are simply loading the drones with explosives, and trying to smash them on the enemy forces.
That, of course, is hardly surprising to anyone who has studied the use of drones by ISIS. The organization is drawing young and resourceful Muslims from the West, some of whom have expertise with emerging technologies like 3D-printers and aerial drones. These kinds of technologies can be developed today in the garage for a few hundred dollars, so it should not surprise anyone that ISIS is using aerial drones wherever it can.
The Islamic State started using drones in 2014, but they were utilized mainly for media and surveillance purposes. Drones were used to capture some great images from battles, as well as for battlefield reconnaissance. Earlier in 2015, the U.S. has decided that ISIS drones are important enough to be targeted for destruction, and launched an airstrike to destroy a drone and its operators. In other words, the U.S. has spent tens or even hundreds of thousands of dollars in ammunition and fuel for the most expansive and sophisticated aircraft and missiles in the world, in order to destroy a drone likely costing less than one thousand dollars.
All of this evidence is coming in from just this year and the one before it. How can we expect drones to be used by terrorist organizations in 2016?
Scenarios for Aerial Drones Terrorist Attacks
In a research presented in 2013, two Dutch researchers from TNO Defence Research summed up four scenarios for malicious use of drones. Two of these scenarios are targeting civilians and would therefore count as terrorist attacks against unarmed civilians.
In the first scenario, a drone with a small machine gun is directed into a stadium, where it opens fire on the crowd. While the drone would most probably crash within a few seconds because of the backlash, the panic caused by the attack would cause many people to trample each other in their flight to safety.
In the second scenario, a drone would be used by terrorists to drop an explosive straight on the head of a politician, in the middle of a public speech. Security forces in the present are essentially helpless in the face of such a threat, and at most can order the politician into hiding as soon as they see a drone in the sky – which is obviously an impractical solution.
Both of the above scenarios have been validated in recent years, albeit in different ways. A drone was illegally flown into a stadium in the middle of a soccer game between Serbia and Albania. Instead of carrying a machine gun, the drone carried the national flag of Greater Albania – which one of the Serbian players promptly ripped down. He was assaulted immediately by the Albanian players, and soon enough the fans stormed the field, trampling over fences and policemen in the process.
The second scenario occurred in September 2013, in the midst of an election campaign event in Germany. A drone operated by a 23 years old man was identified taking pictures in the sky. The police ordered the operator to land the drone immediately, and he did just that and crashed the drone – intentionally or not – at the feet of German Chancellor Angela Merkel. If that drone was armed with even a small amount of explosives, the event would’ve ended in a very different fashion.
As you can understand from these examples, aerial drones can easily be used as tools for terrorist attacks. Their potential has not nearly been fulfilled, probably because terrorists are still trying to equip those lightweight drones with enough explosives and shrapnel to make an actual impact. But drones function just as well with other types of ammunition – which can be even scarier than explosives.
Here’s a particularly nasty example: sometime in 2016, in a bustling European city, you are sitting and eating peacefully in a restaurant. You see a drone flashing by, and smile and point at it, when suddenly it makes a sharp turn, dives into the restaurant and floats in the center for a few seconds. Then it sprays all the guests with a red-brown liquid: blood which the terrorists have drawn from a HIV-carrying individual. Just half a liter of blood is more than enough to decorate a room and to cover everyone’s faces. And now imagine that the same happens in ten other restaurants in that city, at the same time.
Would you, as tourists, ever come back to these restaurants? Or to that city? The damages to tourism and to morale would be disastrous – and the terrorists can make all that happen without resorting to the use of any illegal substances or equipment. No explosives at all.
Conclusion and Forecast
Here’s today forecast: by the year 2016, if terrorists have their wits about them (and it seems the ISIS ones certainly do, most unfortunately), they will carry out a terrorist attack utilizing drones. They may use the drones for charting out the grounds, or they may actually use the drones to carry explosives or other types of offensive materials. Regardless, drones are such an incredibly useful tool in the hands of individual terrorists that it’s impossible to believe they will not be used somehow.
How can we defend ourselves from drone terrorist attacks? In the next post I will analyze the problem using a foresight methodology called Causal Layered Analysis, in order to get to the bottom of the issue and consider possible solutions.
Till that time, if you find yourself eating in a restaurant when a drone comes in – duck quickly.
You’re watching MasterChef on TV. The contestants are making their very best dishes and bring them to the judges for tasting. As the judges’ eyes roll back with pleasure, you are left sitting on your couch with your mouth watering at the praises they heap upon the tasty treats.
Well, it doesn’t have to be that way anymore. Meet Moley, the first robotic cook that might actually reach yours household.
Moley is composed mostly of two highly versatile robotic arms that repeat human motions in the kitchen. The arms can basically do anything that a human being can, and in fact receive their ‘training’ by recording highly esteemed chefs at their work. According to the company behind Moley, the robot will come equipped with more than 2,000 digital recipes installed, and will be able to enact each and every one of them with ease.
I could go on describing Moley, but a picture is worth a thousand words, and a video clip is worth around thirty thousand words a second. So take a minute of your time to watch Moley in action. You won’t regret it.
Moley is projected to get to market in 2017, and should cost around $15,000.
What impact could it have for the future? Here are a few thoughts.
Impact on Professional Chefs
Moley is not a chef. It is incapable of thinking up of new dishes on its own. In fact, it is not much more than a ‘monkey’ replicating every movement of the original chef. This description, however, pretty much applies to 99 percent of kitchen workers in restaurants. They spend their work hours doing exactly as the chef tells them to. As a result, they produce dishes that should be close to identical to each other.
As Moley and similar robotic kitchen assistants come into use, we will see a reduced need for cooks and kitchen workers in many restaurants. This trend will be particularly noticeable in large junk food networks like McDonald’s that have the funds to install a similar system in every branch of the network, thereby cutting their costs. And the kitchen workers in those places? Most of them will not be needed anymore.
Professional chefs, though, stand to gain a lot from Moley. In a way, food design could become very similar to creating apps for smartphones. Apps are so hugely successful because everybody has an end device – the smartphone – and can download an app immediately for a small cost. Similarly, when many kitchens make use of Moley, professional chefs can make lots of money by selling new and innovative digital recipes for just one dollar each.
Are We Becoming a Plutonomy?
In 2005, Citigroup sent a memo to its wealthiest clients, suggesting that the United States is rapidly turning into a plutonomy: a nation in which the wealthy and the prosperous are driving the economy, while everybody else pretty much tags along. In the words of the report –
“There is no such thing as “The U.S. Consumer” or “UK Consumer”, but rich and poor consumers in these countries… The rich are getting richer; they dominate spending. Their trend of getting richer looks unlikely to end anytime soon.”
There is much evidence to support Citigroup’s analysis, and Boston Consulting Group has reached similar conclusions when forecasting the increase in financial wealth of the super-rich in the near future. In short, it would seem that the rich keep getting richer, whereas the rest of us are not enjoying anywhere near the same pace of financial growth. It is therefore hardly surprising to find out that one of the top advices given by Citigroup in its Plutonomy Memo was basically to invest in companies and firms that provide services to the rich and the wealthy. After all, they’re the ones whose wealth keeps on increasing as time moves on. Why should companies cater to the poor and the downtrodden, when they can focus on huge gains from the top 10 percent of the population?
Moley could easily be a demonstration for a service that befits a plutonomy. At $15,000 per robot, Moley could find its place in every millionaire’s house. At the same time, it could kick out of employment many of the low-level, low-earning cooks in kitchens worldwide.
You might say, of course, that those low-level cooks would be able to compete in the new app market as well, and offer their own creations to the public. You would be correct, but consider that any digital market becomes a “winner takes all” market. There is simply no place for plenty of big winners in the app – or digital recipe – market.
Moley, then, is essentially another invention driving us closer to plutonomy.
New technologies have always cost some people their livelihood, while helping many others. Matt Ridley, in his masterpiece The Rational Optimist, describes how the guilds fought relentlessly against the industrial revolution in England, even though that revolution led in a relatively short period of time to a betterment of the human condition in England. Some people lost their workplace as a result of the industrial revolution, but they found new jobs. In the meantime, everybody suddenly enjoyed from better and cheaper clothes, better products in the stores, and an overall improvement in the economy since England could export its surplus of products.
Moley and similar robots will almost certainly cost some people their workplaces, but in the meantime it has the potential to minimize the cost of food, minimize time spent on making food in the household (I’m spending 45-60 minutes every day making food for my family and me), and elevate the lifestyle quality of the general public – but only if the technology drops in price and can be deployed in many venues, including personal homes.
If it’s a forecast you want, then here it is. While we can’t know for sure whether Moley itself will conquer the market, or some other robotic company, it seems likely that as AI continues to develop and drop in prices, robots will become part of many households. I believe that the drop in prices would be significant over a period of twenty years so that almost everybody will enjoy the presence of kitchen robots in their homes.
That said, the pricing and services are not a matter of technological prowess alone, but also a social one: will the robotic companies focus on the wealthy and the rich, or will they find financial models with which to provide services for the poor as well?
This decision could shape our future as we know it, and define whether we’ll keep our headlong dive towards plutonomy.
The futurist Ian Pearson, in his fascinating blog The More Accurate Guide to the Future, has recently directed my attention to a new report by Bloomberg Business. Just two days ago, Bloomberg Business published a wonderful short report that identifies ten of the worst-case scenarios for 2016. In order to write the report, Bloomberg’s staff has asked –
“…dozens of former and current diplomats, geopolitical strategists, security consultants, and economists to identify the possible worst-case scenarios, based on current global conflicts, that concern them most heading into 2016.”
I really love this approach, since currently many futurists – particularly the technology-oriented ones – are focusing mainly on all the good that will come to us soon enough. Ray Kurzweil and Tony Seba (in his book Clean Disruption) are forecasting a future with abundant energy; Peter Diamandis believes we are about to experience a new consumerism wave by “the rising billion” from the developing world; Aubrey De-Grey forecasts that we’ll uncover means to stop aging in the foreseeable future. And I tend to agree with them all, at least generally: humanity is rapidly becoming more technologically advanced and more efficient. If these upward trends will continue, we will experience an abundance of resources and a life quality that far surpasses that of our ancestors.
But what if it all goes wrong?
When analyzing the trends of the present, we often tend to ignore the potential catastrophes, the disasters, and the irregularities and ‘breaking points’ that could occur. Or rather, we acknowledge that such irregularities could happen, but we often attempt to focus on the good instead of the bad. If there’s one thing that human beings love, after all, it’s feeling in control – and unexpected events show us the truth about reality: that much of it is out of our hands.
Bloomberg is taking the opposite approach with the current report (more of a short article, really): they have collected ten of the worst-case scenarios that could still conceivably happen, and have tried to understand how they could come about, and what their consequences would be.
The scenarios range widely in the areas they cover, from Putin sidelining America, to Israel attacking Iran’s nuclear facilities, and down to Trump winning the presidential elections in the United States. There’s even mention of climate change heating up, and the impact harsh winters and deadly summers would have on the world.
Strangely enough, the list includes only one scenario dealing with technologies: namely, banks being hit by a massive cyber-attack. In that aspect, I think Bloomberg are shining a light on a very large hole in geopolitical and social forecasting: the fact that technology-oriented futurists are almost never included in such discussions. Their ideas are usually far too bizarre and alienating for the silver-haired generals, retired diplomats and senior consultants who are involved in those discussions. And yet, technologies are a major driving force changing the world. How could we keep them aside?
Technological Worse-Case Scenarios
Here are a few of my own worse-case scenarios for 2016, revolving around technological breakthroughs. I’ve tried to stick to the present as much as possible, so there are no scientific breakthroughs in this list (it’s impossible to forecast those), and no “cure to aging” or “abundant energy” in 2016. That said, quite a lot of horrible stuff could happen with technologies. Such as –
Proliferation of 3D-printed firearms: a single proficient designer could come up with a new design for 3D-printed firearms that will reach efficiency level comparable to that of mass-manufactured weapons. The design will spread like wildfire through peer-to-peer services, and will lead to complete overhaul of the firearm registration protocols in many countries.
First pathogen created by CRISPR technology: biology enthusiasts are now using CRISPR technology – a genetic engineering method so efficient and powerful that ten years ago it would’ve been considered the stuff of science fiction. It’s incredibly easy – at least compared to the past – to genetically manipulate bacteria and viruses using this technology. My worst case scenario in this case is that one bright teenager with the right tools at his hands will create a new pathogen, release it to the environment and worse – brag about it online. Even if that pathogen will prove to be relatively harmless, the mass scare that will follow will stop research in genetic engineering laboratories around the world, and create panic about Do-It-Yourself enthusiasts.
A major, globe-spanning A. disaster: whether it’s due to hacking or to simple programming mistake, an important A.I. will malfunction. Maybe it will be one – or several – of the algorithms currently trading at stock markets, largely autonomously since they’re conducting a new deal every 740 nanoseconds. No human being can follow their deals on the spot. A previous disaster in that front has already led in 2012 to one algorithm operated by Knight Capital, purchasing stocks at inflated costs totaling $7 billion – in just 45 minutes. The stock market survived (even if Knight Capital’s stock did not), but what would happen if a few algorithms go out of order at the same time, or in response to one another? That could easily happen in 2016.
First implant virus: implants like cardiac pacemakers, or external implants like insulin pumps, can be hacked relatively easily. They do not pack much in the way of security, since they need to be as small and energy efficient as possible. In many cases they are also relying on wireless connection with the external environment. In my worst-case scenario for 2016, a terrorist would manage to hack a pacemaker and create a virus that would spread from one pacemaker to another by relying on wireless communication between the devices. Finally, at a certain date – maybe September 11? – the virus would disable all pacemakers at the same time, or make them send a burst of electricity through the patient’s heart, essentially sending them into a cardiac arrest.
This blog post is not meant to create panic or mass hysteria, but to highlight some of the worst-case scenarios in the technological arena. There are many other possible worst-case scenarios, and Ian Perarson details a few others in his blog post. My purpose in detailing these is simple: we can’t ignore such scenarios, or keep on living our lives with the assumption that “everything is gonna be alright”. We need to plan ahead and consider worst-case scenarios to be better prepared for the future.
Do you have ideas for your own technological worst-case scenarios for the year 2016? Write them down in the comments section!