Technology is undoubtedly the greatest fosterer for change in the modern world. Overshadowed by risk, technological breakthroughs are a catalyst for problem solving the most pressing global challenges of our time.
From zero-emission cars fueled by hydrogen to computer chips modeled on the human brain, this years emerging technologies list as compiled by the World Economic Forum (WEF) offers a glimpse of the power of innovation to improve lives, transform industries and safeguard our planet.
The WEF’s Meta-Council on Emerging Technologies, a panel of 18 experts, draws on the collective expertise of the Forum’s numerous communities to identify the most important technological trends. The Council’s aim is to raise awareness of their potential and contribute to closing the gaps in investment, regulation and public understanding that so often inhibit progress.
The Following technology trends have been sourced from Bernard Meyerson’s article for Scientific America synopsized to highlight the most salient points within each trend;
Electric or hydrocarbon technology has only now begun to reach the stage where automotive companies are planning launches for consumers.
- Unlike batteries, which must be charged from an external source and can take from five to 12 hours depending on the car and charger, fuel cells generate electricity directly, using hydrogen or natural gas.
- There are a number of ways to produce hydrogen without generating carbon emissions. Most obviously, renewable sources of electricity from wind and solar sources can be used to electrolyze water—although the overall energy efficiency of this process is likely to be quite low.
- As well as the production of cheap hydrogen on a large scale, a significant challenge is the lack of a hydrogen distribution infrastructure that would be needed to parallel and eventually replace gas and diesel filling stations.
- Long-distance transport of hydrogen, even in a compressed state, is not considered economically feasible today.
- Innovative hydrogen storage techniques, such as organic liquid carriers that do not require high-pressure storage, however, will soon lower the cost of long-distance transport and ease the risks associated with gas storage and inadvertent release.
- Mass-market fuel-cell vehicles are an attractive prospect because they will offer the range and fueling convenience of today’s diesel and gas-powered vehicles while providing the benefits of sustainability in personal transportation. Achieving these benefits will, however, require the reliable and economical production of hydrogen from entirely low-carbon sources as well as its distribution to a growing fleet of vehicles, expected to number in the many millions within a decade.
Although heavily used (in the automotive industry, for instance), robots are large and dangerous to human co-workers; they have to be separated by safety cages.
- Advances in robotics technology are making human–machine collaboration an everyday reality. Better and cheaper sensors make a robot more able to “understand” and respond to its environment.
- Robot bodies are becoming more adaptive and flexible, with designers taking inspiration from the extraordinary flexibility and dexterity of complex biological structures, such as the human hand.
- The new age of robotics takes these machines away from the big manufacturing assembly lines and into a wide variety of tasks. Using GPS technology, just like smartphones, robots are beginning to be used in precision agriculture for weed control and harvesting.
- Smaller and more dextrous robots, such as Dexter Bot, Baxter and LBR iiwa, are designed to be easily programmable and to handle manufacturing tasks that are laborious or uncomfortable for human workers.
- Indeed, robots are ideal for tasks that are too repetitive or dangerous for humans to undertake, and can work 24 hours a day at a lower cost than human workers. In reality, new-generation robotic machines are likely to collaborate with humans rather than replace them.
- Even considering advances in design and artificial intelligence, human involvement and oversight will remain essential.
Recyclable thermoset plastics
Plastics are divided into thermoplastics and thermoset plastics. The former can be heated and shaped many times and are ubiquitous in the modern world, comprising everything from children’s toys to lavatory seats.
- Because they can be melted down and reshaped, thermoplastics are generally recyclable. Thermoset plastics, however, can only be heated and shaped once, after which molecular changes mean they are “cured,” retaining their shape and strength even when subjected to intense heat and pressure.
- Due to this durability thermoset plastics are a vital part of our modern world. They are used in everything from mobile phones and circuit boards to the aerospace industry. But the same characteristics that have made them essential in modern manufacturing also make them impossible to recycle. As a result, most thermoset polymers end up as landfill. Given the ultimate objective of sustainability, there has long been a pressing need for recyclability in thermoset plastics.
- In 2014 critical advances were made in this area with the publication of a landmark paper in Science announcing the discovery of new classes of thermosetting polymers that are recyclable. Called poly(hexahydrotriazine)s, or PHTs, these can be dissolved in strong acid, breaking apart the polymer chains into component monomers that can then be reassembled into new products.
- Like traditional unrecyclable thermosets, these new structures are rigid, resistant to heat and tough, with the same potential applications as their unrecyclable forerunners.
- Although no recycling is 100 percent efficient, this innovation—if widely deployed—should speed up the move toward a circular economy, with a big reduction in landfill waste from plastics.
- Recyclable thermoset polymers are expected to replace unrecyclable thermosets within five years, and to be ubiquitous in newly manufactured goods by 2025.
Precise genetic-engineering techniques
Conventional genetic engineering has long caused controversy. Now new techniques are emerging that allow us to directly “edit” the genetic code of plants to make them, for example, more nutritious or better able to cope with a changing climate; we believe the benefits, and the precision in “editing,” could allay the concerns, leading to more widespread adoption.
- Currently, the genetic engineering of crops relies on the bacterium agrobacterium tumefaciens to transfer desired DNA into the target genome. The technique is proved and reliable and, despite widespread public fears, there is a consensus in the scientific community that genetically modifying organisms using this technique is no more risky than modifying them using conventional breeding.
- Whereas agrobacterium is useful, more precise and varied genome-editing techniques have been developed in recent years.
- Many of these innovations will be particularly beneficial to smaller farmers in developing countries. As such, genetic engineering may become less controversial as people recognize its effectiveness at boosting the incomes and improving the diets of millions of people.
- Taken together, these techniques promise to advance agricultural sustainability by reducing input use in multiple areas, from water and land to fertilizer, while also helping crops to adapt to climate change.
As the name suggests, additive manufacturing is the opposite of subtractive manufacturing. The latter is how manufacturing has traditionally been done: Layers are subtracted, or removed from a larger piece of material (wood, metal, stone, etcetera), leaving the desired shape.
- Additive manufacturing instead starts with loose material, either liquid or powder, and then builds it into a three-dimensional shape using a digital template, one layer at a time.
- Three-dimensional products can be highly customized to the end user, unlike mass-produced manufactured goods.
- Medical applications are taking 3-D printing in a more biological direction: Machines can directly print human cells, thereby creating living tissues that may find potential application in drug safety screening and, ultimately, tissue repair and regeneration.
- Bio-printing has already been used to generate skin and bone as well as heart and vascular tissue, which offer huge potential in future personalized medicine.
- An important next stage in additive manufacturing would be the 3-D printing of integrated electronic components, such as circuit boards. Nano-scale computer parts, such as processors, are difficult to manufacture this way because of the challenges of combining electronic components with others made from multiple different materials.
- In other areas 4-D printing now promises to bring in a new generation of products that can alter themselves in response to environmental changes, such as heat and humidity.
- Like distributed manufacturing, additive manufacturing is potentially highly disruptive to conventional processes and supply chains. But it remains a nascent technology today, with applications mainly in the automotive, aerospace and medical sectors.
- Rapid growth is expected over the next decade as more opportunities emerge and innovation in this technology brings it closer to the mass market.
Emergent artificial intelligence
Artificial intelligence (AI) is, in simple terms, the science of doing by computer the things that people can do.
- Over recent years AI has advanced significantly: Most of us now use smartphones that can recognize human speech or have travelled through an airport immigration queue using image-recognition technology. Self-driving cars and automated flying drones are now in the testing stage before anticipated widespread use, and for certain learning and memory tasks, machines now outperform humans.
- Artificial intelligence, in contrast to normal hardware and software, enables a machine to perceive and respond to its changing environment. Emergent AI takes this a step further, with progress arising from machines that learn automatically by assimilating large volumes of information.
- An example is NELL, the Never-Ending Language Learning project from Carnegie Mellon University, a computer system that not only reads facts by crawling through hundreds of millions of Web pages but attempts to improve its reading and understanding competence in the process in order to perform better in the future.
- Like next-generation robotics, improved AI will lead to significant productivity advances as machines take over—and even perform better—certain human tasks.
- Substantial evidence suggests that self-driving cars will reduce the frequency of collisions and avert deaths and injuries from road transport, because machines avoid human errors, lapses in concentration and defects in sight, among other shortcomings.
- Intelligent machines, having faster access to a much larger store of information and the ability to respond without human emotional biases, might also perform better than medical professionals in diagnosing diseases.
- AI clearly comes with risks—the most obvious being that super-intelligent machines might one day overcome humans. This risk, although still decades away, is taken increasingly seriously by experts, many of whom signed an open letter coordinated by the Future of Life Institute in January 2015 to direct the future of AI away from potential pitfalls.
Distributed manufacturing turns on its head the way we make and deliver products. In traditional manufacturing raw materials are brought together, assembled and fabricated in large centralized factories into identical finished products that are then sent to the customer.
- In distributed manufacturing the raw materials and methods of fabrication are decentralized and the final product is manufactured very close to the final customer.
- In essence, the idea is to replace as much of the material supply chain as possible with digital information. Parts can then be assembled by the consumer or by local fabrication workshops that can turn them into finished products.
- Current uses of distributed manufacturing rely heavily on the DIY Maker movement, in which enthusiasts use their own local 3-D printers and make products out of local materials.
- There are elements of open-source thinking here, in that consumers can customize products to their own needs and preferences.
- Distributed manufacturing is expected to enable a more efficient use of resources, with less wasted capacity in centralized factories.
- It also lowers the barriers to market entry by reducing the amount of capital required to build the first prototypes and products.
- Importantly, it should reduce the overall environmental impact of manufacturing: digital information is conveyed over the Web rather than physical products via road, rail or water; and raw materials are sourced locally, further reducing the amount of energy required for transportation.
- If it becomes more widespread, distributed manufacturing will disrupt traditional labour markets and the economics of traditional manufacturing.
- It does pose risks; it may be more difficult to regulate and control remotely manufactured medical devices, for example, whereas products such as weapons may be illegal or dangerous.
- Not everything can be made via distributed manufacturing and traditional manufacturing and supply chains will still have to be maintained for many of the most important and complex consumer goods.
- Distributed manufacturing may encourage broader diversity in objects that are today standardized, such as smartphones and automobiles.
- Product features will evolve to serve different markets and geographies and there will be a rapid proliferation of goods and services to regions of the world not currently well served by traditional manufacturing.
“Sense and avoid” drones
Flying robots (aka unmanned aerial vehicles, or drones) to check power lines or deliver emergency aid have become an important and controversial part of military capacity in recent years. They are also used in agriculture, for filming and numerous other applications that require cheap and extensive aerial surveillance. But so far all these drones have had human pilots; the difference is that their pilots are on the ground and fly the aircraft remotely.
- The next step with drone technology is to develop machines that fly themselves, opening them up to a wider range of applications. For this to happen, drones must be able to sense and respond to their local environments, altering their height and flying trajectories in order to avoid colliding with other objects in their paths.
- With reliable autonomy and collision avoidance, drones can begin to take on tasks too dangerous or remote for humans to carry out: checking electric power lines, for example, or delivering medical supplies in an emergency.
- Drone delivery machines will be able to find the best route to their destination and take into account other flying vehicles and obstacles. In agriculture autonomous drones can collect and process vast amounts of visual data from the air, allowing precise and efficient use of inputs such as fertilizer and irrigation.
- This level of collision avoidance will usher in a future of shared airspace, with many drones flying in proximity to humans and operating in and near the built environment to perform a multitude of tasks.
- Drones are essentially robots operating in three, rather than two, dimensions; advances in next-generation robotics technology will accelerate this trend.
- Flying vehicles will never be risk-free, whether operated by humans or as intelligent machines. For widespread adoption, sense-and-avoid drones must be able to operate reliably in the most difficult conditions: at night, in blizzards or dust storms.
Even today’s best supercomputers cannot rival the sophistication of the human brain. Computers are linear, moving data back and forth between memory chips and a central processor over a high-speed backbone. The brain, on the other hand, is fully interconnected, with logic and memory intimately cross-linked at billions of times the density and diversity of that found in a modern computer.
- Neuromorphic chips aim to process information in a fundamentally different way from traditional hardware, mimicking the brain’s architecture to deliver a huge increase in a computer’s thinking and responding power.
- Miniaturization has delivered massive increases in conventional computing power over the years, but the bottleneck of shifting data continuously between stored memory and central processors uses large amounts of energy and creates unwanted heat, limiting further improvements.
- In contrast, neuromorphic chips can be more energy efficient and powerful, combining data-storage and data-processing components into the same interconnected modules.
- Neuromorphic technology will be the next stage in powerful computing, enabling vastly more rapid processing of data and a better capacity for machine learning.
- IBM’s million-neuron TrueNorth chip, revealed in prototype in August 2014, has a power efficiency for certain tasks that is hundreds of times superior to a conventional CPU (central processing unit), and more comparable for the first time to the human cortex.
- With vastly more computing power available for far less energy and volume, neuromorphic chips should allow more intelligent small-scale machines to drive the next stage in miniaturization and artificial intelligence.
- Potential applications include: drones better able to process and respond to visual cues, much more powerful and intelligent cameras and smartphones, and data-crunching on a scale that may help unlock the secrets of financial markets or climate forecasting.
The first sequencing of the 3.2 billion base pairs of DNA that make up the human genome took many years and cost tens of millions of dollars, today your genome can be sequenced and digitized in minutes and at the cost of only a few hundred dollars.
- The results can be delivered to your laptop on a USB stick and easily shared via the Internet. This ability to rapidly and cheaply determine our individual and unique genetic makeups promises a revolution in more personalized and effective health care.
- Many of our most intractable health challenges, from heart disease to cancer, have a genetic component. Cancer is best described as a disease of the genome. With digitization, doctors will be able to make decisions about a patient’s cancer treatment informed by a tumour’s genetic makeup.
- This new knowledge is also making precision medicine a reality by enabling the development of highly targeted therapies that offer the potential for improved treatment outcomes, especially for patients battling cancer.
- Like all personal information, a person’s digital genome will need to be safeguarded for privacy reasons. Personal genomic profiling has already raised challenges, with regard to how people respond to a clearer understanding of their risk of genetic disease as well as how others—such as employers or insurance companies—might want to access and use the information.
- The benefits, however, are likely to outweigh the risks because individualized treatments and targeted therapies can be developed with the potential to be applied across the many diseases that are driven or assisted by changes in DNA.