“The amazing thing about technology is that it is a great leveller; it recognizes no caste, creed or religion”: so said Mukesh Ambani in the India Today Conclave in April 2017. The reality is that the inequality in the distribution of income and wealth has peaked in present-day society. UN Development Programme declares that Income distribution is “more unequal today than at any point since World War II”. The top 10 per cent now claims 48 per cent of national income; the top 1 per cent makes almost 20 per cent, and the top 0.1 makes nearly 9 per cent.
Technology driving inequality is as old as human society. Income disparity in a community driven by technology started about 10,000 years ago when nomadic people settled down and became agriculturists. Ancient farming societies saw income differentiation when some people acquired livestock to aid agriculture and grew richer than those who did not. Since livestock increases productivity, it can be called an ancient equivalent of technology.
A series of industrial revolutions with increasing knowledge content has been happening. As economist Robin Hanson (Hanson 2000) has noted, each of these epochs has been marked by a transition to substantially higher rates of economic growth. Each epoch has also become progressively shorter, suggesting that even faster changes to a more prosperous future may be in the offing.
Silicon Valley is a glaring advertisement for technology-driven inequality. News reports show that on a typical morning in Palo Alto city centre, homeless people and their meagre belongings lie scattered on every available public bench. In San Jose, a camp of homeless people named Jungle has sprung up. David Rotman (Rotman 2014), writing in MIT Technology Review reports that Silicon Valley reached a median income of $94,000 in 2013, far above the national median of around $53,000. Yet an estimated 31 per cent of jobs pay $16 per hour or less, below that needed to support a family.
Although inequality is an essential consequence of Capitalism, uncontrolled growth of income inequality began in the 1970s with the ICT revolution (robotics, the Internet of Things, “big data”, and artificial intelligence). This introduced technologies that complemented the labour of high-skilled workers. Those who had access to them experienced a productivity and wage increase relative to less-skilled workers.
Automation and digital technologies have reduced the opportunities in jobs related to production, sales, administrative, and clerical functions, abetting inequality growth. At the same time, low-paying jobs difficult to automate (cleaning, cooking etc.) has increased. This creates a double-humped job market, with demand peaking at the high and low ends. In the lower-end jobs, supply outrun demand and hence wages dropped throughout much of the 2000s, further worsening income inequality.
Brynjolfsson [et.al](https://et.al). wrote about a “New World Order” in Foreign Affairs (Brynjolfsson 2014), presenting a perspective that the economy will increasingly be dominated by high-tech entrepreneur-elite that “innovate and create.” Their ideas and products can be created and widely distributed thanks to digital technologies. An example is Instagram, which is growing rich at a staggering rate.
Robots are on the path of cognification, acquiring self-learning capability and becoming “smarter” over time. Further advances in artificial intelligence will only enhance this trend. Consequently, robots are preferable to humans for routine, difficult/dangerous, or menial jobs. Robots are charged around US$4.32 per hour, less than the average hourly wage of US$23.32 paid to humans in US manufacturing (Naude 2016). Robots are already performing 80% of the world’s automobile manufacturing. This trend is also affecting emerging economies: up to 66% of all jobs in developing countries are at risk. This is because they are increasingly taking part in robotics production. The International Federation of Robotics estimates that the robot population in China will exceed that in the US or Europe by 2017. India is approaching the top ten in the robotic market.
New skills are in demand though supply is not catching up. Education and training have lost out to technology. Workers with skills appropriate to new technologies tend to gravitate to firms at the technological frontier. Across industries, skills mismatches have increased: in OECD countries, a quarter of the workforce reports a mismatch between their skills and those needed for the job.
The lack of a corrective policy has been a significant cause of the rise of inequalities. The policies must be proactive and responsive to stem the increase in inequality. All over the world, and especially in countries affected by globalization, public alienation is rising. So have populism and ultra-nationalism. A significant cause of this upheaval is the rising income inequality.
The recent tendency of high compensation for top executives promotes inequality. Progressive tax policies must be adopted to find ways to redistribute those gains. It is believed that the tax cuts made by Margaret Thatcher in Britain in the late 1970s and Ronald Reagan in the US in the early 1980s were one of the prime causes of income inequality growth in these countries.
Weak anti-competition policies reinforce the technology-driven dynamics producing more asymmetric market structures. Flaws in patent systems inhibit a wider diffusion of innovations. Deregulation without safeguards and regulations that actively restrict competition also cause unbalanced growth. Other factors include large institutional investors buying out competing companies, and firms becoming more and more adept at erecting barriers to entry through product differentiation and other means.
Competition policies should be updated to be relevant to the digital age. They should ensure that markets continue to provide a level playing field for firms and check the growth of monopolistic structures. Those who gained in the open, competitive system often try to close the system and kill competition. Competition policy needs to acquire a global character to address issues posed by multinational tech giants causing market concentration and competition in many countries.
Proprietary agglomeration of data provides a competitive advantage. As a result, regulations on digital platforms, ownership of data, how user data is handled, and privacy protections matter increasingly for competition. There has been more action on this in Europe than in the United States, an example being the General Data Protection Regulation (GDPR) introduced in Europe in 2018.
New ideas are needed in areas such as competition policy, the innovation ecosystem, digital infrastructure development, and skill updating of workers. Promoting the wide dissemination of new technologies among firms and re-skilling the workforce can promote inclusive economic growth.
The conclusion from all of these is that while technological innovation may have contributed to rising inequality, much of the blame lies with the weakness of institutional governance. This has resulted in reductions in taxation and lower regulations on globalization and multinational enterprises. Policies to reduce inequality are often confused with those for redistribution. A broader “ pre-distribution ” policy plan that can make the growth process more inclusive is preferable. Reforms intended to bring more inclusive outcomes from the technological change also help achieve more robust growth.
The most apparent policy recommendations point to education. Differences in educational achievement are now associated more with family income than with race and ethnicity. Research shows that the differences in achievement levels are already set by the time children enter kindergarten. Education reform alone can lead to merit-based differentiation where everyone has a fair chance to compete.
Technological advances drive inequality because the economically advantaged are more likely to exploit these advances and benefit from them. There is a fundamental difference between material resources and knowledge resources. Material resources are zero-sum. On the other hand, knowledge resources are open in principle to an infinite number of people. Knowledge does not diminish with the number of people using it. Ideas can be shared equally in a way that material goods cannot. An increasingly knowledge-based society should have increasing levels of economic equality.
However, this forgets the fact that access to knowledge needs an initial resource of knowledge which comes out of education and training. Without these, the field is no longer level.
Technologist Ray Kurzweil has dubbed this phenomenon of ever-faster technological and social change “the law of accelerating returns.” However, he has also suggested that the period between extraordinary advances — major spikes in the knowledge that come from great scientific discoveries and technological inventions — has decreased.
1. Wim Naudé and Paula Nagler (2016), [https://unu.edu/publications/articles/is-technological-innovation-making-society-more-unequal.html](https://unu.edu/publications/articles/is-technological-innovation-making-society-more-unequal.html) 1. Rotman David (2014) Technology and Inequality, [https://www.technologyreview.com/2014/10/21/170679/technology-and-inequality/](https://www.technologyreview.com/2014/10/21/170679/technology-and-inequality/) 1. Brynjolfsson, McAfee, and Spence (2014), New World Order: Labor, Capital, and Ideas in the Power Law Economy, Foreign Affairs (2014, July/August 1. Robin Hanson (2000) Long-Term Growth as a sequence of Exponential Modes, [https://mason.gmu.edu/~rhanson/longgrow.pdf](https://mason.gmu.edu/~rhanson/longgrow.pdf)