AI and the Phantom Worker: The Story That They Never Told You
The popular idea that Artificial Intelligence (AI) and robotization leads to unemployment is simply not supported by data. Data for the last 10-20 years shows a different trend altogether – human development, skilling, and education are the key determinants of low unemployment rates. Moreover, the anecdotal evidence increasingly suggests that new technology creates, rather than destroys, jobs.
Over the last 5 years, there has been endless talk about how machines and AI will continue to kill jobs thus increasing unemployment. Prominent newspapers often publish articles to this effect. One particular survey from 2013 by Benedikt Frey & Michael Osborne stated that “47% of workers in America had jobs at high risk of potential automation. In particular, they warned that most workers in transport and logistics (such as taxi and delivery drivers) and office support (such as receptionists and security guards) “are likely to be substituted by computer capital” (see more here).
The most famous alarm bell ringer on AI is Martin Ford, a futurist and an entrepreneur. In his book ‘Rise of the Robots: Technology and the Threat of a Jobless Future’ (2015), Ford paints very grim picture of the situation, with statements like “what if robots can do anything humans can do? Would there then be long-term technological unemployment?” (see more here) and “middle-class jobs will vanish, economic mobility will cease and a wealthy plutocracy could ‘shut itself away in gated communities or in elite cities, perhaps guarded by autonomous military robots and drones’. The unemployed masses will subsist on a universal basic income” (see more here).
Interestingly, anecdotes and alarmist quotes aside, there is very little data to substantiate these claims. In fact, according to Maximiliano Dvorkin, the number of non-routine cognitive jobs has increased steeply in the last 30 years, whereas the number of routine manual jobs remain more or less flat (Source: Federal Reserve of St. Louis, 2016 - see more here). Critics of the AI doomsday prophets often point to Amazon as an example of automation leading to creation, rather than destruction, of jobs. The Seattle Times had reported “The world’s largest e-commerce retailer said it has 45,000 robots in some 20 fulfilment centers. But most importantly, Amazon also reported a 12 months 46 percent increase in the number of staff. (see more here).
The Amazon experience is not an isolated example. In the world of accountancy, despite significant advancements in software (both in terms of specialized accounting software and in terms of widespread availability of spreadsheets), the number of Chartered Accountants has risen in most countries. According to the Association of International Certified Professional Accountants (AICPA), their enrolment figures swelled on an average per annum by 1.4% from 1995-96 to 2015-16. Furthermore, in the home of accounting software, the US, the number of new hires by CPA (Certified Professional Accountants) firms in the US rose by about and average of 3% per annum from 1996 to 2016 (see more here). Another more prosaic example of automation being accompanied by rising, rather than falling, employment is the Bombay Stock Exchange (BSE). The total number of employees of the BSE rose by about 1% on average per annum between 2013-14 and 2019-20.
If the evidence that automation leads to job losses is ambiguous at best, and non-existent at worst:
1) What explains the rising concern regarding unemployment in both the developing and developed world?
2) What can be done to improve and enhance the job creation engines which drive economies across the world?
Looking at time-series data for four major Advanced Economies (AE) of the world (Exhibit 1), unemployment as a % of the total workforce has declined, especially in the last 4-5 years. In fact, barring the fallout of the Global Financial Crisis, unemployment has been stable over the last 20 years in these economies.
More generally, the picture for the OECD countries generally is very similar – over the last 20 years there has been no discernible upward trend in unemployment.
If we look at the prominent Emerging Markets, barring Brazil, there does not seem to be any structural shift in the unemployment rate either upwards or downwards over the last 20 years.
To understand why there is so much talk on unemployment, we need to look at skilling and education, more precisely the links between skilful education, human development and unemployment. To this effect we have analysed PISA scores (The OECD Programme for International Student Assessment examines what students know in reading, mathematics and science in 15 year olds (read more here), HDI (the human development index constructed by the UNDP), and unemployment rates. The PISA data and HDI data and corresponding unemployment data has been taken for the year 2018. A relatively new index, the Global Index of Economic Mentality (GIEM)) (read more here) developed by Carlos Newland, Pal Czegledi, and Brad Lips measures economic freedom with respect to minimal government intervention and maximum private initiative, personal responsibility, and free competition.
The results of our analysis, which itself is shown in Exhibit 4, highlights three key results:
1. Better levels of education (as measured by the PISA scores), better levels of human development (as measured by the HDI index), and better levels of economic freedom (as measured by the GIEM index), are correlated with significantly lower levels of unemployment. This finding is especially true for OECD countries but it also applies to the developing economies.
2. These findings hold true regardless of the size of countries (measured in terms of the population).
3. Putting all the three factors (PISA scores, HDI, and GIEM) together, it turns out that unemployment on an average reduces when these factors improve, in almost all countries. The result is starker and stronger for the developed economies (than for the developing) which could be possibly due to the better starting points these countries have had vis a vis the EM’s and developing countries.
Dlving deeper into the EM’s and the developing nations, we look at HDI and unemployment rates in Bangladesh, Vietnam, and India. Interestingly, all three countries have shown improvement in HDI over the last 20 years and at broadly the same rate.
Exhibits 5 and 6 point out the trends that HDI growth and unemployment rates follow in these 3 countries – as HDI increases in all 3 countries, unemployment rates stay level or even reduce. This is also reflected in the 10-year Compound Annual Growth Rate (CAGR) for HDI (0.04%, 0.06%, 0.08%) and unemployment rates (-0.30%, -0.17%, -0.21%) for Vietnam, India, and Bangladesh, respectively.
This is true for AE’s and developed countries as well. We saw in Exhibits 1 & 2 that unemployment in the developed countries has been stable for the past two decades. Looking at the data for US, Germany and Japan we find that not only have their unemployment rates fallen (10 year CAGR of -1.45%, -10.08%, -5.21% respectively), this has been backed up by steady improvement in HDI scores (10-year CAGR of 0.40%, 0.97%, 0.78% respectively).
Logically, this makes sense. According to a widely quoted report from James Bessen of the Brookings Institute & his colleagues: “rising automation represents an increase in a challenge that society already faces, not a challenge of an entirely new sort” and that “evidence suggests that there is a role for governments to facilitate these transitions following automation episodes” (source: Automation – A Guide for Policymakers, 2020; read more here). In that sense, the role of the government is no different to what it was in the preceding century.
In fact, the rise of automation in the context of the gig economy is seems to be fostering employment, rather than unemployment, in emerging markets like India, Vietnam and Bangladesh. For example, the rise of cab rental services like Uber and Ola may have put traditional some taxi drivers out of business but has substantially increased the number of contractual drivers working for these services. There were around 63,000 black & yellow taxicabs running on the streets of Mumbai approximately 20 years ago. In 2018, that number had fallen to 18,000. However, the number of Uber and Ola cabs in 2018 was around 75,000, raising the total number of cabs on street to 93,000, implying an average annual growth rate of ~2% (see more here).
Much like the point we made in our preceding piece about de-globalization being fake news (click here for our preceding piece), it appears that the fears created around AI and mechanization are of a similar sort. As Joel Mokyr, and economic historian at the Northwestern University put it “Imagine trying to tell someone a century ago that her great-grandchildren would be video-game designers or cybersecurity specialists. These are jobs that nobody in the past would have predicted”(source: The Centre for Innovation Studies, 2019 – read more here). New technologies and advancements will bring new types of employment opportunities – the key is to be able and skilled enough to grab those opportunities.
Mark Mobius is the Founder of Mobius Capital Partners LLP. Saurabh Mukherjea is the Founder of Marcellus Investment Managers. The authors thank Nandita Rajhansa for her help with this piece.
Photo by Possessed Photography on Unsplash