Foresight and Optimisation in Horizon 2020

Horizon over the water, sunrise or sunset

Photo by Evan Leeson/CC BY-NC-SA 2.0

Background

As digital technology becomes more relevant in diverse aspects of our economy and society, it is important to anticipate changes in technology and how we use it. This understanding is particularly important for Horizon 2020, the European Union’s 7-year research and innovation funding programme.

Goals

RAND Europe explored how aspects of Horizon 2020 could be shaped to support development of European research and innovation capacity in ten key areas related to digital technology. The ten areas, listed in the interactive carousel below, emerged from a crowdsourcing exercise carried out by the European Commission's Digital Foresight team in 2014.

The central question addressed in this project was: What type of research should be funded by the public purse?

Methods

Given that the world in which Horizon 2020 will operate will not be the same as that in which it was conceived, the study focused on bringing together critical uncertainties and policy implications. It used a foresight approach to explore trends, opportunities and future scenarios focused on those ten key areas.

The project had three main parts:

  1. A trend analysis of significant current and emergent developments along the ten themes;
  2. A SWOT (strengths, weaknesses, opportunities and threats) analysis from the perspective of European innovation system stakeholders in the context of societal grand challenges; and
  3. Scenario development, taking into account the critical uncertainties and policy implications associated with these themes.

Ten Themes and Trends

  • Digital agriculture and food

    We are facing climate change, a growing world population, food safety scares and scandals, and rising bureaucratic burdens for EU farms. ‘Precision agriculture’ is emerging as sensors, satellite navigation, drones and robotics find applications in farming, though data on uptake in Europe are patchy.

    Trends

    • Precision agriculture via sensors, robots, drones
    • Big Data

    Drivers

    • Costs (labour, fuel), financial risk
    • Need for environmental sustainability
    • Climate change – need to adapt fast
    • EU bureaucracy burden for farming
    • Galileo satellite navigation
    • Public concerns: safety, transparency, local, organic

    Barriers

    • Data concerns
    • Poor interoperability
    • Unclear benefits for some farmers
    • Low rural connectivity

    Uncertainties

    • Impact on small farmers?
    • Would a few data companies dominate?
    • Is it risky for the food supply to depend on digital infrastructure?

  • The emerging consumer Internet economy

    Connected technologies are creating new ways for consumers and businesses to interact, transforming the context where goods and services are produced and purchased. These developments can create economic opportunities, competitiveness challenges and empower consumers. They may also make consumers more vulnerable and raise questions about market regulation and consumer protection.

    Trends

    • Creating and innovating with consumers
    • Big Data
    • Hyperconnectivity and e-commerce

    Drivers

    • Digital native consumers
    • Consumers creating content

    Barriers

    • Uneven digital connectivity across EU
    • Lack of digital skills
    • Limitations in big Data analytics

    Uncertainties

    • How can European companies be supported in the global consumer Internet economy?
    • Are new taxation frameworks needed for new forms of value creation?

  • The path towards singularity

    Technological singularity, or often referred to simply as the singularity, is the idea that artificial intelligence could one day eclipse human intelligence. The singularity, as a concept, is misleading since the term refers to different ideas and scenarios, including the intelligence explosion and Whole Brain Emulation (WBE). It is unclear when or if the singularity will occur, and whether the outcome will be good or bad.

    Trends

    • Machines designing machines
    • Machine learning
    • Exponential increases in computational speed.

    However, their combined consequences are unpredictable.

    Drivers

    • More hardware
    • Better algorithms
    • Massive datasets
    • Progress in psychology and neuroscience
    • Economic incentives

    Uncertainties

    • How quickly will we accumulate the scientific knowledge necessary for the singularity to happen?
    • Will there be active resistance to obstruct the path toward singularity?

  • The evolution of learning and education

    As societies move towards knowledge-based economies, access to and quality of education will become crucial predictors of growth and prosperity. Meanwhile, the need for digital skills is becoming increasingly urgent.

    Trends

    • Gamification
    • MOOCs and distance learning
    • Big Data and learning analytics
    • Blurring between formal vs. informal learning

    Drivers

    • Need for digital skills
    • Expanding broadband coverage and mobile computing

    Barriers

    • Lack of uptake in classrooms
    • Limited usefulness of learning data
    • Lack of evidence of technology impact on learning outcomes
    • Limited availability of materials in languages other than English

    Uncertainties

    • What is the role of data privacy in personalised learning?
    • How much should education be personalised?
    • What should be the main focus of technology: aiding critical and in-depth assessment of information or expanding ubiquitous learning opportunities?
    • Can technology deliver 21st century skills and values?

  • The evolution of the web's architecture

    The Internet of Things (IoT) is one of the fastest growing technology segments and many countries view it as a vehicle for economic growth. With several billion connected devices around the world today, the IoT is enabling industrial and information economies to merge.

    Trends

    • Explosion in number of connected devices
    • Cheaper, smaller, smarter devices
    • Advances in wireless communication technologies
    • Global IoT investments

    Drivers

    • Advances in processing power and storage
    • Cheap hardware and bandwidth
    • New protocol eliminates concerns about shortage of IP addresses
    • Synergies between IoT, cloud computing and big data

    Barriers

    • Scalability and systems engineering issues
    • Immature standards environment
    • Security, privacy and ethics concerns
    • Shortage of IoT-specific skills
    • Limited battery life
    • Limited availability of spectrum

    Uncertainties

    • What business model will IoT adopt?
    • Who 'owns' the IoT and IoT-generated data?
    • Who is liable for the actions of automated IoT systems?

  • New economic models

    Digital technologies are giving rise to modes of production, distribution and consumption that put individuals at the centre. This shift requires economic models to focus on ‘me’ as a unique economic agent, use large amounts of granular data and explore how technology can decouple growth from resource consumption and CO2 emissions.

    Trends

    • Sustainability
    • 'Me' economy
    • 'Peer-to-peer' economy
    • Distributed innovation

    Drivers

    • Massive use of (personal & open) data
    • Entrepreneurship

    Barriers

    • Entrepreneur-unfriendly business environment in EU
    • Skills mismatch
    • Growing income inequality
    • IP regimes, rules and regulations block uptake of many technologies

    Uncertainties

    • How will global insecurity and economic instability impact new models of value creation?
    • Could major security or privacy breaches undermine trust and reverse current trends?

  • Do-It-Yourself Innovation

    Digital fabrication, through 3D printing or additive manufacturing, has been hyped as a 'new digital revolution' that would give consumers as well as industry unprecedented freedom to design and create whatever they wanted. This technology has been used within 'Maker' communities but wider adoption may be held back by practical and legal considerations, and lack of interest.

    Trends

    • Democratisation of manufacturing
    • Transition from mass production to mass customisation
    • Local manufacturing
    • Freedom to create or obtain 'whatever, wherever, whenever'

    Drivers

    • Ease of use
    • Low costs
    • Ubiquitous distribution

    Barriers

    • Inferior quality and reliability
    • Slow production speed
    • Few materials can be used
    • Tax burdens for some entrepreneurs
    • Lack of sustainability

    Uncertainties

    • Who is liable for potential malfunction?
    • Are there new intellectual property issues to consider?
    • Will it lead to more waste?

  • The societal and economic impacts of robotics

    As drones and driverless cars move from science fiction to reality, governments are looking to robotics as a key disruptive technology. Robotics applications now include medicine and healthcare; transport; space technology; agriculture; and environmental remediation. As robotics can increase efficiency and reduce labour costs, such applications can offer significant economic potential.

    Trends

    • More adoption of industrial robots
    • Wider use of robotics outside manufacturing and more human-robot interaction
    • More robotics investment globally
    • More robotics patents, prizes and crowd-funded projects globally

    Drivers

    • Progress in artificial intelligence and machine vision
    • Increasing levels of performance of computers and software
    • Falling costs of sensors and actuators
    • Economic potential
    • Need to preserve human safety in danger zones

    Barriers

    • Safety and reliability concerns
    • No tested laws on liability for errors
    • Ethical and cultural challenges for robotics legislation
    • Skills shortage in engineering and computer science

    Uncertainties

    • Employment impact
    • Could robotics dependency lead to loss of human knowledge and skills?
    • Impact of more human-robot interaction

  • Digital art and science

    Digital tools are widening access to art and science as pressure builds for artists and scientists to show their value for society to justify their funding. Collaborative, data-intensive projects are becoming more feasible. Art can influence technology and how it is perceived; some say artists should do more to question and shape technology.

    Trends

    • Open access to scientific publications, data
    • Crowdfunding, citizen science, co-creation
    • Large, collaborative art and science projects

    Drivers

    • Big Data
    • Social media
    • Digital art tools

    Barriers

    • Research culture discourages online engagement and sharing
    • Limited interaction between art and science/technology

    Uncertainties

    • Do online science platforms encourage multi-disciplinary work?
    • Could online engagement improve scientists’ communication with each other and the public?

  • Governance & policymaking

    Technological advances have changed how governments interact with citizens, and share and use information, but the impact of these changes remains uncertain.

    Trends

    • eGovernment: user-centric and user-driven public services
    • More open, collaborative governance
    • More co-regulation in design and provision of services

    Drivers

    • Connectivity and digital tools
    • Digital natives
    • Growing middle class endorsing democratic values, media plurality
    • Digitisation of personal information
    • Public dissatisfaction with government and need for more accountability
    • Austerity pressure to reduce government spending

    Barriers

    • Lack of interoperability
    • Privacy, trust concerns
    • Digital literacy gap
    • Questionable credibility of new stakeholders

    Uncertainties

    • Will other actors challenge the role of governments and inliiduals as data owners?
    • Will political participation change, and how?
    • What is the role of digital skills in political participation?
    • Will the Internet remain open?

Scenarios

In addition to the trends we detected in our ten themes (above), we developed a set of four scenarios, each with a slightly different character:

  • ‘Easy riders’ – after a painful period of economic recovery, the world attains steady growth and progresses towards societal objectives. Helping to feed this growth are digital enhancements and a vibrant set of new, agile companies and business models.
  • ‘Stately procession’ – economic growth is maintained, but the development of business and societal ecosystems has slowed to a crawl, ruled by large, powerful and stable organisations that produce a steady stream of modest advances in the most critical areas.
  • ‘Riders on the storm’ – the hoped-for recovery has faltered and a succession of crises has seen power returned to contending countries and increasing fragmentation and protectionism and the emergence of new networks based more on shared interest than national identity.
  • ‘Riding the waves’ – the emerging economies have been slowly overtaking today’s major powers, and inequality has declined. The economic shocks of 2007–2008 have given way to problems involving rare earths, terrorist states and climate change, strengthening international cooperation.

These scenarios help explore connections among the themes and test the robustness of specific recommendations to critical uncertainties. Robust policy options, which work well across all scenarios, can be implemented early; other options may need to be delayed until more is known, made more flexible, or monitored closely.

Findings

Using a foresight approach to explore trends, strengths, weaknesses, opportunities and threats as well as future scenarios for ten themes, the research offers a framework for assessing and reflecting on funding priorities. The study proposes guiding principles to help guide funding strategies, including:

  • Social, legal and policy implications of technology need to be integrated into technology research programmes
  • Inflexibilities in the legal and policy environment create barriers for the uptake of research outputs and must be addressed
  • It is important to consider whether traditional innovation support mechanisms are likely to engage key players in particular areas. E.g. Do-It-Yourself innovation is tightly linked to the sharing economy, but the sharing economy is disaggregated and likely to be dominated by actors other than traditional firms. Failing to find ways to engage these actors could result in the loss of their contributions.

Project Team

Helen Rebecca Schindler
Jonathan Cave
Salil Gunashekar
Veronika Horvath
Catherine Lichten
Enora Robin
Sonia Sousa
Nicole Van der Meulen