Nonetheless, I doubt this is quite what Keynes had in mind as the economic possibilities for our grandchildren. If lower hours are not a full answer, retraining workers in line with their comparative advantage might be. One important dimension of this is education. School education has tended to focus on developing the core cognitive competences – for example, reading, writing and arithmetic. Smart machines have long since surpassed humans in their ability to do the first and third of these. And they are fast catching-up on the second. That begs the question of whether there are other skills where humans’ comparative advantage is greater. For example, humans are known to possess an equally-important class of non-cognitive skills – self-confidence, self-esteem, relationship-building, negotiation skills, empathy. In studies of children, these non-cognitive attributes have been found to be as, if not more, important than cognitive competences in enhancing jobs, incomes and well-being (Heckman (2007)). In a world in which machines came to dominate tasks involving core cognitive processing, the importance of, and skill premium attached to, non-cognitive skills is likely to rise. The high skill – high pay jobs of the future may involve skills better measured by EQs than IQs, by jobs creating social as much as financial value. Yet our education system, at present, has a strongly cognitive slant. Perhaps in future that will need to change, with as much effort put into cultivating social CVs as academic ones.

Chart 18: Percentage of workforce by job type Agricultural Labourers  Telephonists and Telegraph Operators  Percentage of workforce  8  Percentage of workforce  0.6  7  0.5  6  0.4  5 4  0.3  3  0.2  2  0.1  1 -  Accountants Percentage of workforce  -  Hairdressers 0.8  Percentage of workforce  0.7  0.7  0.6  0.6  0.5  0.5  0.4  0.4  0.3  0.3  0.2  0.2  0.1  0.1  -  -  Source: Deloitte (2015)  22  0.8  BIS central bankers’ speeches  Chart 19: Share of unskilled workers in the UK, 1550–1849 Percent  Chart 20: Employment shares in US manufacturing, 1850–1910 45  Percentage point change in relative to 1850  White collar Skilled blue collar  40  15.0  Operative/unskilled  35  10.0  30  5.0  25  0.0  20  -5.0  15  -10.0  10  -15.0  5 155-Q99 1600-49 1650-99 1700-49 1750-99 1800-49  0  Source: de Pleijt and Weisdorf (2014)  1850  1860  1870  1880  1900  -20.0  1910  Source: Katz and Margo (2013)  Chart 21: Average real wages of unskilled building workers and GDP per capita, since 1270 Log scale, mean of 1270-1870=100  Allen Real Wages (Allen) Clark Real Wages (Clark)  320  GDP/cap GDP/cap 160  80  40  1270  1320  1370  1420  1470  1520  1570  1620  1670  1720  1770  1820  20 1870  Source: Broadberry, Campbell, Klein and van Leeuwen (2015); Clark (2005); Allen (2001)  BIS central bankers’ speeches  23  Chart 22: Change in employment shares, 2004 – 2014 Percent change in employment  5 4 3 2 1 0 -1  Managers, Professional Associate Skilled Process, Directors and Occupations Professional Trades Plant and Senior and Technical Occupations Machine Officials Occupations Operatives  Administrative Caring, Elementary Sales and and Leisure and Occupations Customer Secretarial Other Service Service Occupations Occupations Occupations  -2  Decreasing median pay  Source: ONS Notes: This chart shows the percentage point change in employment as a share of total employment.