Trends Identified
Nanotechnology
Beyond its role in plastics, nanotechnology can also help accelerate fuel efficiency trends, through a combination of lowering the weight of vehicles and thus increasing efficiency, improving tire efficiency, and nanocatalysts that make fuel consumption more efficient.
2018
The bigger picture- The impact of automation, AI, shared economy on oil demand
The 2° Investing Initiative
Genomics, nanotechnology and synthetic biology could all create prevention solutions
Beyond the predictive benefits of personalized medicine, nano-driven sensors are offering earlier detection (e.g., needing fewer cells to spot cancer). These sensors will be paired with therapeutics to support early intervention, such as theranostics. Nanotechnology and synthetic biology may alleviate concerns about growing antibiotic resistance through solutions_x000B_to reduce the spread of bacteria or, more effectively, destroy it. Viral outbreaks are already being successfully contained by analyzing an individual’s DNA to detect pathogens. In the future, sensors and electronic records will facilitate this tracking, while synthetic biology may have a role in formula ng just-in- me vaccines.
2013
Metascan 3 emerging technologies
Canada, Policy Horizons Canada
Growing pressure on local and regional authorities to better understand society, use of big data in areas such as e-health and e-education
Big data analytics is aimed at making governments and companies more effective. The rejuvenation of public services should continue through the rapid implementation of services such as e-government, e-health, e-invoicing and e-procurement. This will lead to more and better digital services for citizens and enterprises across the EU and free resources in the public sector for innovative use.
2014
Challenges at the horizon 2025
European Strategy and Policy Analysis System (ESPAS)
Design the organization of the future
Big data and deep learning have transformed our ability to learn, and the next generation of technologies will undoubtedly bring even more possibilities. History has shown, however, that applying new technologies to existing processes and structures generally yields only incremental gains. To unlock the learning potential of new technologies, leaders need to reinvent the enterprise as a next-generation learning organization.Merely applying AI to individual process steps is not enough: To increase the ability of organizations to learn in aggregate, they must build integrated learning loops that gather information from data ecosystems, continuously derive insights using machine learning, and act on those insights autonomously, all at the speed of algorithms rather than the speed of human hierarchies. But organizations must not learn only on algorithmic timescales—they must also better understand and position themselves for the slow-moving forces, such as social and political shifts, that are increasingly transforming business. To learn on multiple timescales, leaders will need to design organizations that synergistically combine humans and machines. Algorithms should be trusted to recognize patterns in data and act on them autonomously, while humans should focus on higher-order tasks like validating algorithms, imagining new possibilities, and designing and updating the hybrid “human + machine” organization itself. This division of labor also requires rethinking human–machine interfaces so that humans can trust and productively interact with machines. Collectively, these imperatives demand a massive evolution of organizational capabilities and the creation of new “learning contracts” between employees and enterprises. Many of these principles are already being implemented in isolated domains, such as the operations of digital marketplaces. But to win the ’20s, the same principles must be applied to all parts of the organization in order to create a “self-tuning enterprise” that constantly learns and adapts to the environment. Such organizations must be designed with flexible backbone systems, evolving business models, and, above all, a new model of management—one based on biological principles such as experimentation and co-evolution, rather than traditional top-down decision making and slow cycle planning. Management needs to shift its emphasis from designing hardwired structures and procedures to orchestrating flexible and dynamic systems.
2018
Winning the ’20s: A Leadership Agenda for the Next Decade
Boston Consulting Group (BCG)
Big data, the Internet of Things and artificial intelligence
Big data and IoT are new digital developments that make it possible to optimize business operations and facilitate the creation of new products, services and industries. The possibility of collecting unlimited amounts of data through Internet-connected sensors and monitoring of the web and social media allows prediction of demand, estimation of rural incomes (based on mobile phone activity) and anticipation of civil unrest. While such technologies add to the existing toolkit for development, the availability of fine-grained and increasingly personal data also introduces new risks (see section D.2). Such technologies therefore merit attention from policymakers. In the last few years, artificial intelligence has become a major focus of attention for technologists, investors, governments and futurists. Since it was first proposed more than 60 years ago, artificial intelligence has experienced periods of progress but also of stagnation, when it has been virtually sidetracked while other technologies advanced exponentially. However, recent breakthroughs have led to major advances, driven by machine learning and deep learning, facilitated by access to huge amounts of big data, cheap and massive cloud computing, and advanced microprocessors (Kelly, 2016:38–40).Artificial intelligence now includes image recognition that exceeds human capabilities and greatly improves language translation, including voice translation through natural language processing, and has proved more accurate than doctors at diagnosing some cancers.
2018
Technology and Innovation Report 2018
UNCTAD
Big data
Big Data' loosely describes a set of technologies that deal with very large volumes of fast changing information, usually from a variety of disparate sources with substantial economic, scientific or public value. Currently data value chains are emerging across almost all sectors of the economy and society, as information technologies increasingly accompany most aspects of our life and society in general.
2015
Preparing the Commission for future opportunities - Foresight network fiches 2030
European Strategy and Policy Analysis System (ESPAS)
The Death of Trade
Bilateral trade wars cascade and multilateral dispute resolution institutions are too weak to respond
2018
The Global Risks Report 2018
World Economic Forum (WEF)
Biodiversity
Biodiversity is likely to become prized as research into the extent and variability of different forms of life yield significant technological and health advances. On land, diversity will be reduced as a side-effect of mass agricultural production techniques, industrialisation, urbanisation and through continued erosion of natural habitats, especially tropical rainforests.
2010
Global strategic trends - out to 2040
UK, Ministry of Defence
Bio-electric interfaces
Bioelectronic interfaces make it possible to integrate electronic devices with biological tissues (often membranes of nerve cells) to carry out vital processes and bodily functions under various conditions and environments. From a medical viewpoint this is necessary to achieve connections between implantable chips, bionic prosthetic limbs, implanted artificial sensory organs, and the electrodes of various biotechnical systems and medical devices. Electronic sensory organs are likely to be developed, as well as prosthetics made from new materials with increased compatibility.
2016
Russia 2030: science and technology foresight
Russia, Ministry of Education and Science of the Russian Federation
Inequality Ingested
Bioengineering and cognition-enhancing drugs widen the gulf between haves and have-nots
2018
The Global Risks Report 2018
World Economic Forum (WEF)