Technology

This report proposes an innovative focus on cybersecurity incentives for the investment community. Investors in innovation and technology-driven companies have a responsibility to ensure that cybersecurity is given priority in the early stages of product development. By ensuring cybersecurity from the outset – including features like security-by-design and security-by-default – investors can increase the likelihood of company success in the long term, promote more durable technology and improve overall cyber resilience. This report proposes principles for investors that will raise their internal cybersecurity awareness and offers a complete framework enabling investors to assess the cybersecurity preparedness of their target company.

The technologies on the list, which is curated by members of the Forum’s Expert Network, are selected against a number of criteria. In addition to promising major benefits to societies and economies, they must also be disruptive, attractive to investors and researchers, and expected to have achieved considerable scale within five years. “From income inequality to climate change, technology will play a critical role in finding solutions to many of the challenges our world faces today. This year’s emerging technologies demonstrate the rapid pace of human innovation and offer a glimpse into what a sustainable, inclusive future will look like,” said Jeremy Jurgens, Chief Technology Officer at the World Economic Forum. “Technologies that are emerging today will soon be shaping the world tomorrow and well into the future – with impacts to economies and to society at large. Now that we are well into the Fourth Industrial Revolution, it’s critical that we discuss and ensure that humanity is served by these new innovations so that we can continue to prosper,” said Mariette DiChristina, Editor-in-Chief of Scientific American, and chair of the Emerging Technologies Steering Committee.

This report, done in collaboration with McKinsey and Company, represents a year-long effort with business, government, civil society leaders, experts and practitioners to advance public-private data collaboration to address some of the world’s most pressing humanitarian and sustainable development challenges.
The report provides a holistic governance framework designed to strengthen trust, balance competing interests and deliver impact. It offers insights to balance both the need to innovate in the use of data and the mandate to protect vulnerable populations against known and emerging harms.

The Advanced Drone Operations Toolkit provides a modular approach for governments to enable societally important and safe drone projects. Each recommendation is based upon lessons learned from the latest successful pilot projects in Switzerland, Rwanda, and Malawi – saving lives and creating new forms of aerial logistics. This toolkit is the first multi-stakeholder publication to collect and share vital lessons from across the planet as an enabler for new drone programs that can save lives safely. By leveraging the formative work of innovative governments and supported by those private companies leading the technological revolution, the toolkit accelerates access to airspace and begins to promote a unified vision for autonomous flight.

This paper addresses the present state of play and future trends, uncertainties and possible disruptions of Artificial Intelligence (AI) and Big Data in the following areas:
Political: AI is biased, difficult to scrutinise and to estimate its power, and – more so when embodied in autonomous systems – potentially dangerous. Policy responses are accountability, transparency, safety and control, and public debate. These should be based on ethics. AI will lead to better governance, more debate, new policy actors and processes, a contest over centralisation, and the EU catching up. AI might progress in a revolutionary or evolutionary mode, lead to new political divisions, and change democracy. AI might be misused as a “superior orders” defence. What if data analysis changes or replaces democracy?
Socio-economic: Big Data is changing the role of data, is often dependent on sensitive information, is handicapped in the short term but better in the long term due to data protection, and its industry is in danger of monopolisation. AI lowers the cost of prediction, replaces human prediction and human labour and causes social problems, increased nudging and misuse of the term AI. AI will lead to more data, economic growth and more job market distortions. AI might lead to new industry giants, a request for more privacy, new state solutions, yet unknown jobs, AI taxes and increased state ownership. What if new economic ideologies emerge, singularity strikes or AI monopolies are broken up?
Geopolitical: AI is increasing the power competition between the US and China and gives both more power. Europe tries to create businesses and find its strengths. All are investing in military solutions and the west has a slight disadvantage here. AI will lead to a shakeup of the international system, hierarchies and networks becoming more powerful, and real-life deception being more difficult. AI might lead to China becoming the most powerful power overall and in AI. The future of AI R&D and the success of Europe’s broad approach is uncertain. What if there are two digital worlds, China becomes a data-privacy defender, and AI become targets?
Technological: Superintelligent AI is invested in and researched, challenged by philosophy, and possible this century. It might imitate the brain, be assembled together or be designed by other AIs. An intelligence explosion or a conscious AI could be possible, and might be the last invention of humanity. It would require long term funding, need to overcome many technical hurdles, be dangerous due to its intellect, possibly be contained with collective intelligence, and maybe have humans lose their jobs, safety or purpose.
Key questions for policy-makers: What makes European AI distinctive? What areas can and should we prioritise, if any? What should be regulated? How could and should the EU foster AI development, avoid monopolisation, provide data pools, use high data standards, link researchers and corporations, balance fundamental with applied AI research and private with state funding, boost applications, compensate for job loss, keep AIs away from dangerous actors, support EU foreign policy (neighbourhood, FPI, democracy and human rights, aid and development, economic freedom), improve our lives with AI, change the geopolitical AI race, deal with autonomous weapons and superintelligent AI and organise Foresight?

Notwithstanding the emergence of artificial intelligence (AI), robotics, and the Internet of Things (IOT), European productivity growth has slowed, and continues to lag U.S. growth.1 Since the financial crisis, labor productivity in the 28 EU member states has grown just 0.7 percent annually. At this rate, it will take a century for Europe’s per capita incomes to double. No wonder there is political unrest across the continent. And while Europe decreased the productivity gap with the United States before 1995, since then, the gap has only widened. Reversing that trend is critical if Europe is going to be able to effectively cope with its demographic challenges, particularly a rapidly aging population, and be able to more effectively compete in global markets. To do that it needs more ubiquitous use—as distinct from production—of information and communication technologies (ICTs) by all organizations (for-profit, nonprofit, and government) throughout all of Europe.

Data-driven innovation is unlocking new opportunities for Europe to grow its economy and address pressing social challenges. While Europe has achieved some early successes in data-driven innovation, including in areas such as education, energy, environmental management, health care, open data, smart cities, and smart manufacturing, it has not yet come close to reaching its full potential. The primary obstacle is that Europe’s policymakers, both in its capital cities and in Brussels, have not yet fully embraced data-driven innovation as a core driver of economic and social progress. To inject new leadership into this debate, Member States should appoint national chief data officers to not only champion data innovation domestically, but also serve on a new, independent advisory panel charged with counseling the European Commission on how to seize opportunities to innovate with data.

Data-driven innovations have the power to address some of the most pressing social challenges in Europe. While many government and non-governmental organizations (NGOs) are using data in their attempts to tackle a range of social issues from high unemployment to the refugee crisis, more can be done. To accelerate progress, public and private-sector leaders should take steps to collect data on disadvantaged populations, facilitate cross-sector collaboration on data projects for social good, and implement policies that encourage data use, reuse, and sharing in support of social goals.