The Rise of the Machines, and its Effect on Employment (SDG-8)

Automation - Its impact on jobs in India

The debate on technological upgradation and human employment has been raging for a while now, and is set to get more heated as advancements in technology continue to shake up the workplace. SDG 8 advocates a focus on labour-intensive sectors with diversification, technological upgrading and innovation, in order to make a more efficient, productive and satisfied workforce. 

The inclusion of technological upgradation in making a more satisfied workforce may, at first sight, seem counterproductive, since technology has always been seen as a threat to human employment. For instance, the International Labour Organization has estimated that 70% of jobs in Vietnam have a high probability of being replaced by machinery, and occupations with the highest risk of disappearing in the future include shop sales assistants (2.1m), garden laborers (1m) and sewing-machine operators in garment manufacturing (770,000). Technology is also affecting the local workforce’s desirability – Cal Newport, in his book “Deep Work” argues that the local workforce is being affected by the development of remote working technologies like high-speed data networks and collaboration tools like e-mail and virtual meeting software, with it becoming easier for firms to hire those they deem to be more technically and intellectually superior at the work that the organization needs to perform, even though they may be living in a different country, thus putting local talent on the backburner. 

However, multiple thinkers beg to differ – Guy Ryder, ILO Director-General explains that though technology may cause turbulence and disrupt the workforce in the short run, it has historically only contributed to employment. Similarly, Newport himself brings up the conflict between technology and the workforce in interesting ways. He says that as intelligent machines improve, the gap between man and machine is shrinking, with employers more likely to hire new machines than new humans. He thus says though this will happen for many, many others who can adapt to these machines and work around them to “tease results out of these machines” will survive in this technology-dependent world. He drives the compelling argument that it is only humans that can extract truly meaningful observations out of the complex conclusions of machines, and such a skill will only become more valuable. 

Add to this the continued problems that have arisen out of attempts to circumvent manpower instead of embedding it into the workforce, through automation and artificial intelligence, and the need for human employment becomes clearer, as explained by this article by Bright Simons on the WEF website – studies have repeatedly shown that, for example, robot-checkout contraptions in supermarkets are causing supermarkets to lose money since they are unknowingly triggering aggressive consumer behaviour and increasing shoplifting. And with reports of frequent AI and robot glitching and technical problems becoming clearer, the human frequently emerges as a much more reliable source of productivity. It is thus argued that technology could instead go hand-in-hand with human talent, provided the ‘human’ knows how to make use of it (for example, with superior virtual reality and machine-iteration systems, average food technologists can carry out a more varied range of biochemical explorations). This is, again, similar to Newport’s conclusion in his book as explained above. In a similar vein, another article estimates that technological advancements could create 2.1 million new jobs, most of these being in specialized areas such as computing, architecture, mathematics and engineering. It is also clear that jobs which may involve questions of morality, ethics, etc. like law or policy-making, are less likely to allow the complete overtaking of artificial intelligence due to inherent trust issues. 

To combat the rise of automation, it is imperative to develop interpersonal/soft skills like sharing, negotiating, etc. in combination with mathematical or analytical skills, and a person only having either of these skills is likely to suffer. This preparedness must start from the grassroots level – education – where children must be educated on the importance of both skills, in a market where the focus in education has predominantly been solely on technical skills. Ultimately, it does look like machines will not, after all, take over the world. But whether they take over the lives of millions of future workers will depend on the education system that prepares them, and their own fire to survive and thrive. 


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