My Views on The Second Machine Age

With ‘The Second Machine Age‘, Erik Brynjolfsson and Andrew McAfee have written a fascinating book, which deservedly parks in many’s books of the year lists.  Written by two MIT scientists, it tracks the impact so far of the digital age and looks at the future.  The authors claim the impact of digital technology will be as big, or bigger than that of the first machine age, and will reinvent our lives and economy.

Some key points from the book:

  1. Although the PC was Time’s ‘Person’ of the year in 1982, the full impact of digital technologies has only recently reached full force.  There are different reasons for this:
    • Moore’s Law. First formulated in 1962, it roughly stated that the amount of computer power you can buy for one dollar would double each year.   This ‘law’ has proven remarkably correct for over 40 decades.  It has even proven to be correct for many digital technologies.  That continuous doubling has brought us in the ‘second half of the chessboard’ where the absolute amounts increase phenomenally.
    • Digitization of information.  More information is available in digital format.  With the ‘internet of things’ massive amounts of digital data are created.
    • Network effects.  The more people are online and using an particular platform, the stronger the benefits.
    • Organisational capital.  Companies investing in IT, typically spend about 10 times that amount on changes in the organisation of the company.  Using IT to do existing things faster does not increase productivity much.  It’s using IT to do things fundamentally different what makes the difference (a comment often formulated about using computers in classrooms as well).  Such fundamental rethinking of production processes usually takes several decades, as existing managers retire and are replaced by ‘digital natives’.
  2. Digital goods are fundamentally different from physical goods
    • They have a high cost to create, but are almost free to replicate unlimitedly;
    • They are not exhaustive, you can not ‘use up’ a digital good.
  3. These characteristics have profound effects on our economy
    • Job (and wage) polarisation.  Demand for routine manual and cognitive jobs has been falling, depressing wages.  Demand has been rising for skills that complement digital technologies (pattern recognition, assessing complex situations…).
    • “Winner takes all” markets.  We have been moving from markets with absolute advantages to markets where a small relative advantage leads to absolute dominance.  Being a slightly better writer 50 years ago would give you slightly higher scales, as the extent you could market and sell your writings would be limited.   There was a market for many writers, some slightly better or worse than others.  Today, a writer as JK Rowling can sell her books worldwide, dominating the market for fiction writing.
    • GDP as a measure of economic activity becomes less useful. GDP is based on physical reproduction of items.  When digital items are copied, people enjoy from ‘free’ digital services or produce intangibles such as intellectual property and human capital, these are not captured in GDP.
    • Traditionally, productivity growth has been linked to rising living standards.  The share of labour in GDP growth has fallen in recent years (to the expense of the share of capital).  This, together with the job polarisation, implies that rises in productivity do not longer automatically translate into broadly shared rises in welfare.  This explains the jobless recoveries after recent crises.

Whereas the authors are inherently optimistic about the digital age, they do see risks of high unemployment:

  • Job polarisation and “winner takes all” markets reduce demand for certain jobs.
  • Inelastic demand. Demand for goods may rise slower than prices fall as a result of technological progress.
  • Technological progress may be faster than the ‘adjustment time’ to re-skill workers for jobs that are in demand.

For the solutions, the authors look mainly at education.  This chapter is one of the weakest.  The authors advocate a re-think of the curriculum towards ’21st century skills’ and a stronger focus on entrepreneurship.  The authors put high hopes in MOOCs (only xMOOCs in fact, not the much more interesting cMOOCs), brushing aside the fact that they offer a sub-standard experience of what on-line learning can be.  They have a point that, as on-line learning becomes more mainstream, the characteristics of digital goods markets will impact education, such as job polarisation and ‘winner takes all’ markets. In South Korea, for example, lectures from ‘superstar’ teachers with  astronomical salaries are broadcast on-line, reducing the role of traditional teachers.

But nevertheless a great book on the analysis of how digital technologies have been affecting our lives, and are likely to disrupt it even a lot more.  For the part on how education could (and needs to) respond to our changing society, I would recommend other articles, books and blog posts.

 

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Income Inequality in the Developing World

Science recently published a theme issue on income inequality in the developing world (free access, with registration).  It includes contributions from, among others, Thomas Piketty, Martin Ravallion and Angus Deaton.

The main idea from Piketty’s bestseller, Capital, is that inequality has been rising since the 19th century because yields on wealth are higher than those on income.  This trend was only interrupted by the 2 world wars.  Piketty’s thesis rests on historical data from the US and Europe.  This theme issue looks whether the conclusions are valid for developing countries as well.

Has the strong economic growth in developing countries since 2000 resulted in falling levels of inequality?  And what has been the effect on poverty?  The main findings from the article of Ravallion:

Science 2014 May 344(6186) 851-5, Fig. 1

Science 2014 May 344(6186) 851-5, Fig. 4

 

 

 

 

 

 

Inequality has fallen between 1981 and 2010.  However, the period between 2005 and 2010 shows an increase.  The variance over time is mainly attributable to inequality between countries.  Again, most recent data indicate that the component between countries has fallen, whereas the component within countries has risen.

  • Economic growth has lead to increasing inequality between countries, but to falling inequality within countries (although the latter trend has weakened in recent years).
  • The effect of economic growth on poverty depends on the initial level of inequality.  The higher that level, the lower the share of economic growth that flows to the poor and the lower the poverty reduction resulting from that growth.
  • Even if inequality has not been rising overall, there are still worries about high levels on inequality in developing countries:
    • capital tends to have diminishing returns, implying it’s more ‘useful’ when more equally spread;
    • high inequality means that many poor, talented people cannot reach their full potential;
    • high inequality tends to erode democracy, as a small group of people may hijack the democratic process and turn ‘inclusive institutions’ into ‘extractive ones’ (see Acemoglu’s and Anderson’s work);
    • low inequality and a strong middle class tend to create a more diversified and robust economy, as a result of a stronger focus on consumption goods and support for pro-growth policies.
  • Three cautionary remarks on the data:
    • The data, using the Gini or related MLD indicators, represent relative inequality. This means that inequality is the same whether incomes are 1$ and 2$ or 1000$ and 2000$.  This implies that even with constant relative inequality, the absolute differences in income and wealth can grow much larger.
    • Data on inequality in developing countries are notoriously unreliable.  The main data sources are the national accounts (household consumption item) and household surveys.  In the latter, the rich either don’t participate or tend to under-report their income and wealth.
    • Developing countries are a mixed bag.  Countries with rising inequality from a low base (India, China), countries with rising inequalities from a high base (South Africa, with Gini = 0.7!!!) and countries with decreasing inequality (most countries in Latin America).
  • Falling inequality is not something which happens ‘automatically’ as countries grow rich, as was postulated by Simon Kuznets.  It’s the result of pro-equity policies, such as investments in health and education (Bolsa Familia in Brazil) and job creation.