Computer scientists are working on reproducing all human skills using artificial intelligence, machine learning and robotics. Unsurprisingly then, many people worry that these advances will dramatically change work skills in the years ahead and perhaps leave many workers unemployable.

Artificial intelligence (AI) and robotics are major breakthrough technologies that are transforming the economy and society. The OECD’s Artificial Intelligence and the Future of Skills (AIFS) project is developing a programme to assess the capabilities of AI and robotics, and their impact on education and work.

This volume describes the second phase of the project: exploring three different approaches to assessing AI.

Inspired by the ground-breaking 2001 Schooling for Tomorrow scenarios, this book provides a set of scenarios on the future of schooling, showing not a single path into the future, but many. Using these scenarios can help us identify the opportunities and challenges that these futures could hold for schooling and education more broadly. We can then use those ideas to help us better prepare and act now.

Computer scientists are working on reproducing all human skills using artificial intelligence, machine learning and robotics. Unsurprisingly then, many people worry that these advances will dramatically change work skills in the years ahead and perhaps leave many workers unemployable. This report develops a new approach to understanding these computer capabilities by using a test based on the OECD's Survey of Adult Skills (PIAAC) to compare computers with human workers. The test assesses three skills that are widely used at work and are an important focus of education: literacy, numeracy and problem solving with computers. Most workers in OECD countries use the three skills every day. However, computers are close to reproducing these skills at the proficiency level of most adults in the workforce. Only 13% of workers now use these skills on a daily basis with a proficiency that is clearly higher than computers. The findings raise troubling questions about whether most workers will be able to acquire the skills they need as these new computer capabilities are increasingly used over the next few decades. To answer those questions, the report's approach could be extended across the full range of work skills. We need to know how computers and people compare across all skills to develop successful policies for work and education for the future.

Advances in artificial intelligence (AI) are ushering in a large and rapid technological transformation. Understanding how AI capabilities relate to human skills and how they develop over time is crucial for understanding this process.

Since the 1950s, under congressional mandate, the U.S. National Science Foundation (NSF) - through its National Center for Science and Engineering Statistics (NCSES) and predecessor agencies - has produced regularly updated measures of research and development expenditures, employment and training in science and engineering, and other indicators of the state of U.S. science and technology. A more recent focus has been on measuring innovation in the corporate sector. NCSES collects its own data on science, technology, and innovation (STI) activities and also incorporates data from other agencies to produce indicators that are used for monitoring purposes - including comparisons among sectors, regions, and with other countries - and for identifying trends that may require policy attention and generate research needs. NCSES also provides extensive tabulations and microdata files for in-depth analysis. Capturing Change in Science, Technology, and Innovation assesses and provides recommendations regarding the need for revised, refocused, and newly developed indicators of STI activities that would enable NCSES to respond to changing policy concerns. This report also identifies and assesses both existing and potential data resources and tools that NCSES could exploit to further develop its indicators program. Finally, the report considers strategic pathways for NCSES to move forward with an improved STI indicators program. The recommendations offered in Capturing Change in Science, Technology, and Innovation are intended to serve as the basis for a strategic program of work that will enhance NCSES's ability to produce indicators that capture change in science, technology, and innovation to inform policy and optimally meet the needs of its user community.

The Austrian higher education system has consistently recognised the need to become more entrepreneurial and innovative with a view to supporting the economic, social and cultural development of the country and its regions. Over the past decades, the government has been implementing a broad reform agenda to provide strategic funding, diversify higher education institutions (HEIs) and promote an allocation of students that improves the quality of services and empowers them vis à vis the future of work and society. This review illustrates policy actions promoting the development of entrepreneurial and innovative activities in the Higher Education System and individual HEIs.

Over the past five years, business and education groups have issued a series of reports indicating that the skill demands of work are rising, due to rapid technological change and increasing global competition. Researchers have begun to study changing workplace skill demands. Some economists have found that technological change is "skill-biased," increasing demand for highly skilled workers and contributing to the growing gap in wages between college-educated workers and those with less education. However, other studies of workplace skill demands have reached different conclusions. These differences result partly from differences in disciplinary perspective, research methods, and datasets. The findings of all of these strands of research on changing skill demands are limited by available methods and data sources. Because case study research focuses on individual work sites or occupations, its results may not be representative of larger industry or national trends. At a more basic level, there is some disagreement in the literature about how to define "skill". In part because of such disagreements, researchers have used a variety of measures of skill, making it difficult to compare findings from different studies or to accumulate knowledge of skill trends over time. In the context of this increasing discussion, the National Research Council held a workshop to explore the available research evidence related to two important guiding questions: What are the strengths and weaknesses of different research methods and data sources for providing insights about current and future changes in skill demands? What support does the available evidence (given the strengths and weaknesses of the methods and data sources) provide for the proposition that the skills required for the 21st century workplace will be meaningfully different from earlier eras and will require corresponding changes in educational preparation?