Envisioning the future of education and jobs
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Revolution. Contained within that often-frightening word is another, less-destabilising one: evolution. If we look at this fourth Industrial Revolution as the end result of a series of advances propelled by the force of global trends, then we have a better chance of meeting the challenges it presents, rather than being ambushed by it. We will also be better equipped to help our children prepare for their future. This report, the product of a collaboration between the Organisation for Economic Co-operation and Development (OECD) and the UK-based charity, Education and Employers, offers a glimpse of how children see their future, and the forces that, if properly understood and harnessed, will drive them forward to realise their dreams. Through concerted actions by educators and business leaders, we can help our children develop the kinds of skills needed not only to weather, but to take advantage of this revolution. The future will be about pairing the artificial intelligence of computers with the cognitive, social and emotional capabilities of humans, so that we educate first-class humans, not second-class robots. It is our responsibility, as concerned adults, to acknowledge and understand the trends that are shaping this industrial revolution, and to impart that understanding to our children as early as possible. It is our responsibility, in other words, to help our children get ready for their future. Download the paper at http://www.oecd.org/education/Envisioning-the-future-of-education-and-jobs.pdf
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Envisioning the future of education and jobs
- 1. STARTING STRONG Wollongong Andreas Schleicher Envisioning the future of education and jobs Trends and Drawings
- 2. Andreas Schleicher Director for Education and Skills Drawing the future
- 3. The rise of the global middle class 0 1 2 3 4 5 6 7 8 9 0 10 20 30 40 50 60 70 80 90 100 1951 1957 1963 1969 1975 1981 1987 1993 1999 2005 2011 2017 2023 2029 Headcount(billions) %ofworldpopulation World middle class share of world population World middle class World population Within the next decade the majority of the world population will consist of the middle class Estimates of the size of the global middle class, percentage of the world population (left axis) and headcount (right axis), 1950-2030 Source: Kharas, H. (2017), The unprecedented expansion of the global middle class, an update, https://www.brookings.edu/wp-content/uploads/2017/02/global_20170228_global-middle-class.pdf. Kharas, H. (2010), The emerging middle class in developing countries, https://www.oecd.org/dev/44457738.pdf. Figure 1.2
- 4. Growing unequal Income gaps continues to grow Trends in real household incomes by percentile, OECD average, 1985-2015 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1985 1990 1995 2000 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Bottom 10% Mean Median Top 10% Source: OECD (2018), A Broken Social Elevator? How to Promote Social Mobility, https://doi.org/10.1787/9789264301085-en. Figure 2.1 Index 1985 = 1
- 5. More people on the move -30 20 70 120 170 220 270 1990 1995 2000 2005 2010 2015 2017 Millionsofpeople Africa Asia Europe Latin America and the Caribbean Northern America Oceania Estimates of international migrant stock by region of destination, 1990-2017 Source: United Nations (2017), "International migrant stock: The 2017 revision" (database), www.un.org/en/development/desa/population/migration/data/. Figure 1.5
- 8. Security in a risky world Household savings and debt Household savings (% of disposable income, left axis) and household debt (% of disposable income, right axis), OECD average, 1970-2016 Source: OECD (2018), OECD National Accounts Statistics (database), https://stats.oecd.org/. 0 20 40 60 80 100 120 140 160 0 2 4 6 8 10 12 14 16 18 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 Debtas%ofdisposableincome Savingsas%ofdisposableincome Savings (left axis) Debt (right axis) Figure 3.9
- 9. Access to Access Number of mobile broadband subscriptions per 100 inhabitants, OECD average, 2009-2017 Source: OECD (2018), "Mobile broadband subscriptions" (indicator), https://doi.org/10.1787/1277ddc6-en. Figure 5.1 0 20 40 60 80 100 120 2009 2010 2011 2012 2013 2014 2015 2016 2017 Numberofsubscriptions
- 10. 10 Digitalisation Democratizing Concentrating Particularizing Homogenizing Empowering Disempowering
- 11. 11 Digitalisation Democratizing Concentrating Particularizing Homogenizing Empowering Disempowering The post-truth world where reality becomes fungible • Virality seems privileged over quality in the distribution of information • Truth and fact are losing currency Scarcity of attention and abundance of information • Algorithms sort us into groups of like-minded individuals create echo chambers that amplify our views, leave us uninformed of opposing arguments, and polarise our societies
- 12. 15-year-olds feeling bad if not connected to the Internet (PISA) 0 10 20 30 40 50 60 70 80 90 100 ChineseTaipei-2 Sweden-9 France-5 Portugal Greece Singapore-2 Thailand Macao(China)-7 Brazil-2 Spain UnitedKingdom Bulgaria HongKong(China) Korea-7 Belgium-4 Denmark-4 Croatia-5 Israel-10 NewZealand-4 Netherlands-3 Uruguay Hungary4 Australia OECDaverage-3 DominicanRepublic Ireland-7 Poland-3 CostaRica3 Lithuania Japan-5 Mexico Russia-8 CzechRepublic Italy Peru Colombia4 Finland-6 Chile Latvia SlovakRepublic B-S-J-G(China)11 Switzerland Austria-3 Luxembourg Iceland Germany Estonia Slovenia % Boys Girls
- 13. Students are using more time online outside school on a typical school day (PISA) 0 20 40 60 80 100 120 140 160 180 200 Chile39 Sweden56 Uruguay33 CostaRica31 Spain44 Italy40 Australia52 Estonia50 NewZealand51 Hungary43 Russia42 Netherlands48 Denmark55 SlovakRepublic40 CzechRepublic43 Austria42 Latvia46 Singapore45 Belgium44 Poland46 Iceland51 ECDaverage-2743 Ireland48 Croatia40 Portugal42 Finland48 Israel34 Macao(China)45 Switzerland40 Greece41 ongKong(China)39 Mexico30 Slovenia37 Japan31 Korea20 Minutes per day 2015 2012 Percentage of High Internet Users (spending 2 to 6 hours on line per day), during weekdays
- 14. Public matters Reading the news online: Is this for real? Individuals using the Internet (last 3 months) for reading/downloading the news online, 2005 and 2017 Source: OECD (2018), ICT Access and Usage by Households and Individuals (database). https://stats.oecd.org/. 0 10 20 30 40 50 60 70 80 90 100 Iceland Norway Korea Luxembourg Sweden Finland Denmark Estonia CzechRepublic Netherlands Switzerland Lithuania UnitedKingdom Latvia Germany Spain Hungary OECDaverage SlovakRepublic Austria Canada Greece Slovenia Poland Portugal Belgium Japan Ireland France Turkey Italy NewZealand Mexico %ofInternetusers 2005 2017 Figure 2.4
- 17. The kind of things that are easy to teach are now easy to automate, digitize or outsource 35 40 45 50 55 60 65 70 1960 1970 1980 1990 2000 2006 2009 Routine manual Nonroutine manual Routine cognitive Nonroutine analytic Nonroutine interpersonal Mean task input in percentiles of 1960 task distribution
- 18. Combined registered users of Upwork and Freelancer Freeing up work? Sources: OECD (2017), OECD Employment Outlook 2017, https://doi.org/10.1787/empl_outlook-2017-en. Figure 5.2 0 5 10 15 20 25 30 35 40 45 50 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Millionusers
- 19. Mass self-communication and creative expression Individuals using the Internet (last 3 months) for uploading self-created content on sharing websites, 2008 and 2017 Source: OECD (2018), ICT Access and Usage by Households and Individuals (database), https://stats.oecd.org/. Figure 5.7 0 10 20 30 40 50 60 70 16-24 25-55 55-74 %ofinternetusers Age group 2008 2017
- 20. 100 80 60 40 20 0 20 40 Turkey Greece Chile Lithuania Israel United States Poland Russian Federation Ireland Slovak Republic England (UK) Northern Ireland (UK) Japan OECD average Slovenia Estonia Denmark Austria Australia Canada New Zealand Germany Czech Republic Norway Flanders (Belgium) Netherlands Sweden Finland Korea Singapore Level 2 Level 3 Level 2 Level 3 Skills to manage complex digital information Young adults (16-24 year-olds) Older adults (55-65 year-olds)
- 21. Education won the race with technology throughout history, but there is no automaticity it will do so in the future Inspired by “The race between te chnology and education” Pr. Goldin & Katz (Harvard) Industrial revolution Digital revolution Social pain Universal public schooling Technology Education Prosperity Social pain Prosperity The future will be about pairing the artificial intelligence of computers with the cognitive, social and emotional skills and values of humans
- 22. The growth in AI technologies 0 2 000 4 000 6 000 8 000 10 000 12 000 14 000 16 000 18 000 20 000 1991 1994 1997 2000 2003 2006 2009 2012 2015 Numberofpatents Number of patents in artificial intelligence technologies, 1991-2015 Source: OECD (2017), OECD Science, Technology and Industry Scoreboard 2017: The digital transformation, http://dx.doi.org/10.1787/9789264268821-en. Figure 1.10
- 26. % Yes No If I am more innovative in my teaching I will be rewarded (country average) What do teachers say about innovation in schools?
- 27. Public matters Declining voter turnout in OECD countries Change in average voting rates per decade in OECD countries, 1990s and 2010s Source: International IDEA (2018), International Voter Turnout Database, www.idea.int. 40 50 60 70 80 90 100 Australia Luxembourg Belgium Denmark Sweden Turkey Iceland Norway Austria Netherlands NewZealand Italy Germany Spain Israel OECDaverage Ireland Finland UnitedKingdom Hungary Canada Estonia Greece Latvia CzechRepublic SlovakRepublic Slovenia Portugal Korea Japan UnitedStates Mexico Lithuania Poland France Switzerland Chile %ofvotingturnout 1990s 2010s Figure 2.3
- 28. Public matters Para-diplomacy on the rise in cities Cumulative number of city networks, 1885-2017 Source: Acuto, M., et al. (2017), “City Networks: New Frontiers for City Leaders”, Summary report for the 9th session of the World Urban Forum, Connected Cities Lab, University of Melbourne, Melbourne. 0 20 40 60 80 100 120 140 160 180 1885 1890 1895 1900 1905 1910 1915 1920 1925 1930 1935 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2017 Numberofcitynetworks Figure 2.6
- 29. Living longer, living better 70 is the new 60 Total gains in life expectancy at birth, OECD countries, 2000-2016 Source: WHO (2018), Global Health Observatory (database), http://www.who.int/gho/en/. Figure 4.2 0 1 2 3 4 5 6 7 Estonia Korea Turkey Ireland Slovenia Latvia Portugal CzechRepublic SlovakRepublic Denmark Hungary Poland Israel Luxembourg France OECDaverage Norway Spain Finland Austria Canada Switzerland UnitedKingdom NewZealand Netherlands Australia Belgium Italy Lithuania Germany Greece Japan Iceland Sweden Chile Mexico UnitedStates Years Gains in healthy life expectancy Additional gains in life expectancy
- 30. Working later in life Senior and older (50-74 years) labour participation rates (% of the age group), 2006 and 2016 Source: OECD (2016), “OECD Older Worker Scoreboard 2016”, http://www.oecd.org/els/emp/older-workers- scoreboard-2016.xlsx. Figure 4.6 0 10 20 30 40 50 60 70 80 50-54 55-64 65-69 70-74 Labourparticipation(%) Age group 2006 2016
- 31. Participation in lifelong education and training by literacy level (Adults aged 25-65 years) 0 20 40 60 80 100 High literacy skills (4/5) Low literacy skills (1)%
- 33. Aspirations and realities 0% 5% 10% 15% 20% 25% 30% 35% 40% Protective service occupations Leisure, travel and related personal service occupations Textiles, printing and other skilled trades Process, plant and machine operatives Culture, media and sports occupations Skilled metal, electrical and electronic trades Transport and mobile machine drivers and operatives Other managers and proprietors Skilled construction and building trades Health professionals Teaching and educational professionals Sales occupations Science, research, engineering and technology professionals Business, media and public service professionals Corporate managers and directors Administrative occupations Business and public service associate professionals Caring personal service occupations Elementary administration and service occupations % 7-11-year-old children choosing career % Net needed 2024
- 34. Aspirations and realities 0% 5% 10% 15% 20% 25% 30% 35% 40% Protective service occupations Leisure, travel and related personal service occupations Textiles, printing and other skilled trades Process, plant and machine operatives Culture, media and sports occupations Skilled metal, electrical and electronic trades Transport and mobile machine drivers and operatives Other managers and proprietors Skilled construction and building trades Health professionals Teaching and educational professionals Sales occupations Science, research, engineering and technology professionals Business, media and public service professionals Corporate managers and directors Administrative occupations Business and public service associate professionals Caring personal service occupations Elementary administration and service occupations % 17-18-year-old children choosing career % Net needed 2024
- 35. Andreas Schleicher Director for Education and Skills Find out more about our work at www.oecd.org –All publications –The complete micro-level database Email: Andreas.Schleicher@OECD.org Twitter: SchleicherOECD Wechat: AndreasSchleicher
Editor's Notes
- Note: Income refers to real household disposable income. OECD average refers to the unweighted average of the 17 OECD countries for which data are available: Canada, Denmark, Finland, France, Germany, Greece, Israel, Italy, Japan, Luxembourg, Mexico, the Netherlands, New Zealand, Norway, Sweden, the United Kingdom and the United States. Some data points have been interpolated or use the value from the closest available year.
- Note: Northern America includes Bermuda, Canada, Greenland, Saint Pierre and Miquelon, USA and Mexico.
- Note: OECD average refers to the average of 32 countries: Australia, Austria, Belgium, Canada, Chile, Czech Republic, Germany, Denmark, Spain, Estonia, Finland, France, United Kingdom, Greece, Hungary, Ireland, Italy, Japan, Korea, Luxemburg, Latvia, Mexico, Netherlands, Norway, New Zealand, Poland, Portugal, Slovak Republic, Slovenia, Sweden and the United States
- Note: Where the data for countries were not consistently available in the same years, figures from the closest year are used.
- Half of the jobs in the industrialised world are potentially automatable, because the things that are easy to teach and easy to test are also the things that are easy to automate, digitize and outsource.
- Notes: Includes extrapolated figures for Upwork based on most recent annual growth rates. Registered number of users for the two platforms combined.
- Note: The figure is based on average data for 26 OECD countries. These include Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovak Republic, Slovenia, Spain, Sweden, Turkey, United Kingdom
- Goldin and Katz call this the race between technology and education.
- Note: Data refer to the number of IP5 patent families in artificial intelligence (AI), by filing date and inventor's country, using fractional counts. AI refers to the "Human interface" and "Cognition and meaning understanding" categories in the ICT patent taxonomy as described in Inaba and Squicciarini (2017). 2014 and 2015 figures are estimated based on available data for those years.
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- When we looked at this more closely in 2008, many teachers talked about schools as rather innovation-hostile environments. For example, just a quarter of teachers said that if they were more innovative in their teaching, they would be rewarded, and this is not just about money, we looked at any form of recognition. The figures are particularly low in Belgium, Ireland, Denmark and Australia. A higher percentage of teachers, though, said that innovative practices would be considered in appraisal and feedback, though you would really want to see this figure to be closer to 100%.
- Note: Countries are ranked in descending order by the average voting rates for the period 2010-18, covering national parliamentary elections from 2010 to the latest year with data available. Voting in Australia, Belgium and Luxembourg is compulsory. Vote was also compulsory in Chile until 2012 (the two elections comprised in this graph for the 2010s period, 2013 and 2017, were thus held under voluntary suffrage.
- Notes: Countries are ranked in descending order of life expectancy gains.
- I want to conclude with what we have learned about successful reform trajectories In the past when you only needed a small slice of well-educated people it was efficient for governments to invest a large sum in a small elite to lead the country. But the social and economic cost of low educational performance has risen substantially and all young people now need to leave school with strong foundation skills. When you could still assume that what you learn in school will last for a lifetime, teaching content and routine cognitive skills was at the centre of education. Today, where you can access content on Google, where routine cognitive skills are being digitised or outsourced, and where jobs are changing rapidly, the focus is on enabling people to become lifelong learners, to manage complex ways of thinking and complex ways of working that computers cannot take over easily. In the past, teachers had sometimes only a few years more education than the students they taught. When teacher quality is so low, governments tend to tell their teachers exactly what to do and exactly how they want it done and they tend to use Tayloristic methods of administrative control and accountability to get the results they want. Today the challenge is to make teaching a profession of high-level knowledge workers. But such people will not work in schools organised as Tayloristic workplaces using administrative forms of accountability and bureaucratic command and control systems to direct their work. To attract the people they need, successful education systems have transformed the form of work organisation in their schools to a professional form of work organisation in which professional norms of control complement bureaucratic and administrative forms of control.