These days it seems that we are witnessing waves of extreme disruption rather than incremental technology change. While some tech news stories have been just so much noise, unlikely to have long-term impact, a few are important signals of much bigger, longer-term changes afoot.
From bots to blockchains, augmented realities to human-machine convergence, a number of rapidly advancing technological capabilities hit important inflection points in 2016. We looked at five important emerging technology news stories that happened this year and the trends set in motion that will have an impact for a long time to come.
Immersive experiences were one of three top-level trends identified by Gartner for 2016, and that was evident in the enormous popularity of Pokémon Go. While the hype may have come and gone, the immersive technologies that have been quietly advancing in the background for years are ready to boil over into the big time—and into the enterprise.
The free location-based augmented reality (AR) game took off shortly after Nintendo launched it in July, and it became the most downloaded app in Apple’s app store history in its first week, as reported by TechCrunch. Average daily usage of the app on Android devices in July 2016 exceeded that of the standard-bearers Snapchat, Instagram, and Facebook, according to SimilarWeb. Within two months, Pokémon Go had generated more than US$440 million, according to Sensor Tower.
Unlike virtual reality (VR), which immerses us in a simulated world, AR layers computer-generated information such as graphics, sound, or other data on top of our view of the real world. In the case of Pokémon Go, players venture through the physical world using a digital map to search for Pokémon characters.
The game’s instant global acceptance was a surprise. Most watching this space expected an immersive headset device like Oculus Rift or Google Cardboard to steal the headlines. But it took Pikachu and the gang to break through. Pokémon Go capitalized on a generation’s nostalgia for its childhood and harnessed the latest advancements in key AR enabling technologies such as geolocation and computer vision.
Blockchains, the decentralized digital ledgers of transactions that are processed by a distributed network, first made headlines as the foundation for new types of financial transactions beginning with Bitcoin in 2009. According to Greenwich Associates, financial and technology companies will invest an estimated $1 billion in blockchain technology in 2016. But, as Gartner recently pointed out, there could be even more rapid evolution and acceptance in the areas of manufacturing, government, healthcare, and education.
By the 2020s, blockchain-based systems will reduce or eliminate many points of friction for a variety of business transactions. Individuals and companies will be able to exchange a wide range of digitized or digitally represented assets and value with anyone else, according to PwC. The supervised peer-to-peer network concept “is the future,” says Leonhard.
But the most important blockchain-related news of 2016 revealed a weak link in the application of technology that is touted as an immutable record.
In theory, blockchain technology creates a highly tamper-resistant structure that makes transactions secure and verifiable through a massively distributed digital ledger. All the transactions that take place are recorded in this ledger, which lives on many computers. High-grade encryption makes it nearly impossible for someone to cheat the system.
In practice, however, blockchain-based transactions and contracts are only as good as the code that enables them.
Case in point: The DAO, one of the first major implementations of a “Decentralized Autonomous Organization” (for which the fund is named). The DAO was a crowdfunded venture capital fund using cryptocurrency for investments and run through smart contracts. The rules that govern those smart contracts, along with all financial transaction records, are maintained on the blockchain. In June, the DAO revealed that an individual exploited a vulnerability in the company’s smart contract code to take control of nearly $60 million worth of the company’s digital currency.
The fund’s investors voted to basically rewrite the smart contract code and roll back the transaction, in essence going against the intent of blockchain-based smart contracts, which are supposed to be irreversible once they self-execute.
The DAO’s experience confirmed one of the inherent risks of distributed ledger technology—and, in particular, the risk of running a very large fund autonomously through smart contracts based on blockchain technology. Smart contract code must be as error-free as possible. As Cornell University professor and hacker Emin Gün Sirer wrote in his blog, “writing a robust, secure smart contract requires extreme amounts of diligence. It’s more similar to writing code for a nuclear power reactor, than to writing loose web code.” Since smart contracts are intended to be executed irreversibly on the blockchain, their code should not be rewritten and improved over time, as software typically is. But since no code can ever be completely airtight, smart contracts may have to build in contingency plans for when weaknesses in their code are exploited.
Importantly, the incident was not a result of any inherent weakness in the blockchain or distributed ledger technology generally. It will not be the end of cryptocurrencies or smart contracts. And it’s leading to more consideration of editable blockchains, which proponents say would only be used in extraordinary circumstances, according to Technology Review.
Application programming interfaces (APIs), the computer codes that serve as a bridge between software applications, are not traditionally a hot topic outside of coder circles. But they are critical components in much of the consumer technology we’ve all come to rely on day-to-day.
One of the most important events in API history was the introduction of such an interface for Google Maps a decade ago. The map app was so popular that everyone wanted to incorporate its capabilities into their own systems. So Google released an API that enabled developers to connect to and use the technology without having to hack into it. The result was the launch of hundreds of inventive location-enabled apps using Google technology. Today, millions of web sites and apps use Google Maps APIs, from Allstate’s GoodHome app, which shows homeowners a personalized risk assessment of their properties, to Harley-Davidson’s Ride Planner to 7-Eleven’s app for finding the nearest Slurpee.
In June, Swiss citizens voted on a proposal to introduce a guaranteed basic income for all of its citizens, as reported by BBC News. It was the first country to take the issue to the polls, but it won’t be the last. Discussions about the impact of both automation and the advancing gig economy on individual livelihoods are happening around the world. Other countries—including the United States—are looking at solutions to the problem. Both Finland and the Netherlands have universal guaranteed income pilots planned for next year. Meanwhile, American startup incubator Y Combinator is launching an experiment to give 100 families in Oakland, California, a minimum wage for five years with no strings attached, according to Quartz.
The world is on the verge of potential job loss at a scale and speed never seen before. The Industrial Revolution was more of an evolution, happening over more than a century. The ongoing digital revolution is happening in relative hyper speed.
No one is exactly sure how increased automation and digitization will affect the world’s workforce. One 2013 study suggests as much as 47% of the U.S workforce is at risk of being replaced by machines over the next two decades, but even a conservative estimate of 10% could have a dramatic impact, not just on workers but on society as a whole.
The proposed solution in Switzerland did not pass, in part because a major political party did not introduce it, and citizens are only beginning to consider the potential implications of digitization on their incomes. What’s more, the idea of simply guaranteeing pay runs contrary to long-held notions in many societies that humans ought to earn their keep.
Whether or not state-funded support is the answer is just one of the questions that must be answered. The votes and pilots underway make it clear that governments will have to respond with some policy measures. The question is: What will those measures be? The larger impact of mass job displacement, what future employment conditions might look like, and what the responsibilities of institutions are in ensuring that we can support ourselves are among the issues that policy makers will need to address.
New business models resulting from digitization will create some new types of roles—but those will require training and perhaps continued education. And not all of those who will be displaced will be in a position to remake their careers. Just consider taxi drivers: In the United States, about 223,000 people currently earn their living behind the wheel of a hired car. The average New York livery driver is 46 years old, according to the New York City Taxi and Limousine Commission, and no formal education is required. When self-driving cars take over, those jobs will go away and the men and women who held them may not be qualified for the new positions that emerge.
As digitization dramatically changes the constructs of commerce and work, no one is quite sure how people will be impacted. But waiting to see how it all shakes out is not a winning strategy. Companies and governments today will have to experiment with potential solutions before the severity of the problem is clear. Among the questions that will have to be answered: How can we retrain large parts of the workforce? How will we support those who fall through the cracks? Will we prioritize and fund education? Technological progress and shifting work models will continue, whether or not we plan for their consequences.
In April, a young man, who was believed to have permanently lost feeling in and control over his hands and legs as the result of a devastating spine injury, became able to use his right hand and fingers again. He used technology that transmits his thoughts directly to his hand muscles, bypassing his injured spinal cord. Doctors implanted a computer chip into the quadriplegic’s brain two years ago and—with ongoing training and practice—he can now perform everyday tasks like pouring from a bottle and playing video games.
The system reconnected the man’s brain directly to his muscles—the first time that engineers have successfully bypassed the nervous system’s information superhighway, the spinal cord. It’s the medical equivalent of moving from wired to wireless computing.
The man has in essence become a cyborg, that term first coined in 1960 to describe “self-regulating human-machine systems.” Yet the beneficiary of this scientific advance himself said, “You’re not going to be looked on as, ‘Oh, I’m a cyborg now because I have this big huge prosthetic on the side of my arm.’ It’s something a lot more natural and intuitive to learn because I can see my own hand reacting.”
As described in IEEE Spectrum, the “neural-bypass system” records signals that the man generates when thinking about moving his hand, decodes those signals, and routes them to the electric sleeve around his arm to stimulate movement: “The result looks surprisingly simple and natural: When Burkhart thinks about picking up a bottle, he picks up the bottle. When he thinks about playing a chord in Guitar Hero, he plays the chord.”
What seems straightforward on the surface is powered by a sophisticated algorithm that can analyze the vast amounts of data the man’s brain produces, separating important signals from noise.
The fact that engineers have begun to unlock the complex code that controls brain-body communication opens up enormous possibilities. Neural prostheses (cochlear implants) have already reversed hearing loss. Light-sensitive chips serving as artificial retinas are showing progress in restoring vision. Other researchers are exploring computer implants that can read human thoughts directly to signal an external computer to help people speak or move in new ways. “Human and machine are converging,” says Leonhard.
The National Academy of Engineering predicts that “the intersection of engineering and neuroscience promises great advances in healthcare, manufacturing, and communication.”
Burkhart spent two years in training with the computer that has helped power his arm to get this far. It’s the result of more than a decade of development in brain-computer interfaces. And it can currently be used only in the lab; researchers are working on a system for home use. But it’s a clear indication of how quickly the lines between man and machine are blurring—and it opens the door for further computerized reanimation in many new scenarios.
This fall, Switzerland hosted its first cyborg Olympics, in which disabled patients compete using the latest assistive technologies, including robot exoskeletons and brainwave-readers. Paraplegic athletes use electrical simulation systems to compete in cycling, for example. The winners are those who can control their device the best. “Instead of celebrating the human body moving under its own power,” said a recent article in the IEEE Spectrum, “the cyborg games will celebrate the strength and ingenuity of human-machine collaborations.” D!
Read more thought provoking articles in the latest issue of the Digitalist Magazine, Executive Quarterly.