The effect of Automation and Artificial intelligence on the future of employment has always been a subject of substantial interest. As we progress into the fourth industrial revolution, which will fundamentally alter our livelihood and work, the pace of changes is unprecedented or as the interviewee, Dr. Rohith Jyothish would say, “the first era of technology, where technology itself is running faster than culture.”
To elucidate the effects of automation and artificial intelligence on labour markets of different economies and policy measures that the government can implement to provide a safety net for those who are at risk of losing their jobs, we sat down with Professor Dr. Rohith Jyotish, assistant professor at the Jindal School of International Affairs is a political economist with a PhD from JNU, specializing in the understanding the organization of work under contemporary capitalism in the Global South.
Is Automation different in the Information Age?
Often referred to as a labour-saving technology, automation has been about minimizing human effort in the production of goods and services. Automation has been around for decades since the industrial revolution. The industrial revolution revolutionized societies and their ways of life. Shifting society from working in agriculture to production jobs and as time went on and automation became more widespread humans shifted to service sector jobs.
One of the key developments during the initial stages of the industrial revolution was the mechanized loom famously known as the power loom. While this did affect the demand for skilled handweavers in the short run. However, due to automation, the process of producing cloth became more affordable thus increasing foreign demand and stimulating exports. This increased industrial employment and opened opportunities for women to work in mills. Another such example of labour-saving technology was in the form of railroads. Prior to the invention of railroads, the most common modes of transportation of people and goods were by horseback or on the rivers. Fast forward to when railroads were introduced, they improved the efficiency of transportation which had a domino effect. The improved efficiency of transportation of people and goods created made it easier for sellers to find new markets to sell their goods and this, in turn, gave individuals more access to goods that would have otherwise been more difficult to obtain.
If one were to look at a common trend in these examples of automation of certain jobs a common theme that can be seen is that these happened over a long period of time and their effects took time to create an impact. While these automated machines did take over individuals' jobs and created a temporary situation of unemployment, over time it created better and more efficient jobs which catered for growing populations. However, in this Information age, Professor Jyotish argues that “technological advancement now is...too fast for us to cope without any kind of public policy intervention.” This technological advancement takes but does not create jobs to cater to the growing population. There are many estimates by academics and professionals that estimate that around the world, millions of jobs are at risk due to automation, David A. Spencer in his paper ‘Fear and hope in an age of mass automation: debating the future of work’ writes that “estimates for the UK suggest that 15 million 12 jobs are at risk of automation – this approximates to half of the current workforce. In developing countries, the estimates of potential job losses are even higher – for example, more than two-thirds of jobs in India and over three-quarters of jobs in China are seen to be vulnerable to automation.”
Technological advancement creates labour displacement thus unemployment is a concern the government should be working with through the implementation of forward-looking policies.
Inequalities in the system
The labour displacement alone is a grave issue that needs to be addressed but we live in a divided world, and there is greater divergence among regions, countries, and people, making it even more divided every day. We ask Professor Jyotish about the same, to understand how these inequalities in society among people and countries interact with automation and how it could impact different countries and people in different ways.
To understand the impact of inequality, Professor Jyotish point us to a survey done by Jean Drèze and Reetika Khera, wherein they survey 1,400 school children in underprivileged households and find that, “only 8% of rural children were able to take advantage of online classes regularly, while 37% did not attend any such classes.” He draws from these conclusions and adds that “when our systems become more and more dependent on advanced technology, which is capital intensive, countries which are traditionally lower in capital endowments will experience a disproportionate impact, and we're kind of seeing that today.” He continues from this and points out that, despite the fact that automation discourse and theorists proposing the “upskilling” of labour, but fail to realize the gap in education in the developing world, where an adverse event such as the pandemic can set children 18 months behind on their school education, which will have serious impact in the future of a child’s education. It is variables like these that impact different countries, regions, and people of income brackets differently. Therefore, he emphasizes that “ignoring inequalities will have adverse outcomes.” Professor Jyotish highlights that “there has to be more of a systematic thinking into how automation and its related effects are impacting differently in different countries,” especially the workers in the Global South.
Defining Digital Labour
We then moved the conversation to the idea of digital labour. Fumagalli, Lucarelli et. al. (2018) defined digital labour as “the labour-force of independent contractors who work on their own account and at their own risk for low wages and without social security, as in the case of many platform-based business models” such as Uber, Zomato, Swiggy, Dunzo and other platforms. They expanded on the same by adding to the definition that digital labour also entails the “human activity...that rely on a new composition of capital capable of capturing personal information and transforming it into big data.”
Professor Jyotish suggested that “the term digital labour itself is larger than the gig economy,” right from click-work, call centre jobs that moved to developing countries like ours from the global north, and even the gig economy, digital labour can describe an array of activities. With the advent of the internet and waves of globalization, came the concept of BPO - Business Process Outsourcing, which allowed companies and organizations to outsource jobs to low-income countries. This has created opportunities such as - translations, transcriptions, lead generation, marketing, customer service and personal assistance in the developing world, with India being one of the biggest benefactors in the same. The smartphone revolution and high-speed internet connectivity have unlocked another form of digital labour - the ‘gig economy.’
An interesting aspect that Professor points us to is how “all of these classes of workers are fragmented, so even within what you refer to as a digital labour.” In IT/Services/Tech companies of today, we have a group of people on the backend, where employees have the luxury to stay at home or work in luxury offices while there is another class of labour in the same organization that is, for example, is delivering food or groceries from one place to another travelling on their 2-wheelers with delivery targets, with little to no social security or insurance, where even the smallest failures, would lead to a substantial loss of income due to the “gamified,” incentive-based income that is offered to such employees. This, according to Professor Jyotish, is important in highlighting the prevalence of “class difference in labour organizations.”
Digital labour, although popular in contemporary India, due to lack of regulation and social security, are not protected by the state from exploitation. Cases of exploitative regimes operating in digital labour have become a common sight. Professor Jyotish points out that it was only after the pandemic that there have been some “comprehensive labour organizations and efforts” to protect them from exploitation among the gig economy. In the most recent budget announcement, Finance Minister Nirmala Sitharaman announced that Code on Social Security Code 2020 has made provision for universalization of social security for the entire workforce including gig and platform workers.
Policy Interventions for Unemployment or Technology?
Mark Graham et. al. in their paper, ‘Digital labour and development: impacts of global digital labour platforms and the gig economy on worker livelihoods’ argue that “the rise of digital labour has come about at a confluence of two trends,” the first being that in much of the world, unemployment and underemployment is a major social and economic concern for policy-makers, especially considering the fact that ILO “estimates that between 2014 and 2019 there will be 213 million new labour market entrants.” The second trend is the ‘rapidly changing connectivity’ wherein in 10 years, we have gone from 15% of population having internet access to 40% of world’s population with internet, and more recent estimates, put the number a little over 50% as connected to the internet. These changing global trends are critical in policy making for the future.
One of the biggest points of conversation around automation and the ‘4th industrial revolution’ is that of the job losses to be caused by automation, where human labour processes are replaced with a machine or a computer. One of the most advocated policies to soften the blow of automation to labour is to create a safety net in the form of the Universal Basic Income, where those who are at risk of losing jobs or have lost jobs are able to be reskilled as well as be paid in this period. Upon asking about the feasibility of a UBI, Professor Jyotish interestingly points out that one of the reasons for the popularity of UBI is because it is “a politically feasible solution” which according to him, “is one of the few policy issues where the left and right, broadly speaking, tend to sort of agree, or they think that there are merits to this policy.”
He also adds key issues that need to be addressed in the UBI discourse. First, we need to make sure that Universal Basic Income “does not come, possibly at the cost of some of the other structures that we have built over the years.” Secondly, along with this, he raises macroeconomic concerns with UBI such as the negative inflationary effects that UBI can create which, upon not having enough economic growth, may lead to economic pressure. Thirdly and most importantly, Professor Jyotish points out that many suggest that there exists a ‘technological unemployment,’ but “we definitely see the existing data doesn't suggest that technological unemployment is the problem but rather it is that (of) a structural unemployment.” He argues that Universal Basic Income as a solution can be explored beyond the realms of technological unemployment but “might be a good solution for this larger job insecurity that exists.”
According to Professor Jyotish, policy interventions such as Right to work programs or employment guarantee programs such as National Rural Employment Guarantee Act are also particularly important policy interventions that can provide work to people who are unemployed. But the current NREGA caters to the rural populace that are at the “lower end of the skill spectrum and possibly not very appealing to a section of the population who already have achieved a certain level of education.” This, along with long term programs that aim to educate and skill the Indian populace with the right tools to sustain employment.
“I'm interested in what exactly is a politically infeasible solution which we are reluctant to look at, that's what I want to see” he says. While we look at UBI, reskilling programs, right to work programs as those that are feasible politically, he mentions that there is a need to look at alternate policy solutions while understanding the consequences of technology. “We have entered an epoch of technological advancement whereby we might accept technological change to such a level that we may not be able to cope...an example of this Elon Musk himself actually made this statement about how he may have made a mistake when he went and over robotized a lot of his factories because he felt that a lot of that work could be done by human beings much better.” Professor Jyotish ends this conversation by asking us to explore alternate solutions “industry by industry at a decentralized level by looking at the political class, coalitions and various political formulations that result on the basis of this and then we'll get a better idea of what alternative policy proposals are possible.”
References
Spencer, D. A. (2018). Fear and hope in an age of mass automation: debating the future of work. New Technology, Work and Employment, 33(1), 1–12. https://doi.org/10.1111/ntwe.12105
Shashi Shekhar. (2021, October 3). The marginalized bear the brunt of the pandemic. Mint. https://www.livemint.com/opinion/columns/the-marginalized-bear-the-brunt-of-the-pandemic-11633289391331.html
Fumagalli, A., Lucarelli, S., Musolino, E., & Rocchi, G. (2018). Digital Labour in the Platform Economy: The Case of Facebook. Sustainability, 10(6), 1757. MDPI AG. Retrieved from http://dx.doi.org/10.3390/su10061757
Isis Hjorth, Vili Lehdonvirta, & Mark Graham. (n.d.). Digital Labour and development: Impacts of global digital labour platforms and the gig economy on worker livelihoods - Mark Graham, Isis Hjorth, Vili Lehdonvirta, 2017. SAGE Journals. Retrieved October 20, 2021, from https://journals.sagepub.com/doi/10.1177/1024258916687250.
Comments