Artificial Intelligence and the Job Conundrum

Updated: Feb 21

Why in the news?

Tata Sons’ chairman N. Chandrasekaran, adding that AI should be deployed for purposes that raise productivity but do not displace workers in the country. However it is increasingly being witnessed that production has been highly capital intensive despite the abundant availability of labour. In far too many cases, businesses find machines cheaper than putting people to work, and this often has to do with our labour restrictions..


The quandary of AI and jobless

  • By 2030, up to 12 million women in India could risk losing their jobs to automation, according to a new study by the McKinsey Global Institute.

  • The study on the future of women at work mapped the impact of automation on occupation among women in 10 countries

  • Men could lose roughly up to 44 million jobs to automation in the same period in India, McKinsey noted. The report comes even as joblessness touches a 45-year high and female labour force participation rate remains a low 27%.

  • According to a new data analysis based on the Reserve bank of India, within manufacturing, there were job losses. The textile and leather sectors lost around 12 lakh workers and the wood and furniture sector has lost around 9 lakh workers during these five years. Much of the employment has happened in the electronic and optical equipment industries. The food and beverages sector attracted just 1 lakh new entrants a year.

How and why AI are taking jobs?

  • The repetitive nature of jobs are increasingly being overtaken by AI. for example recently Zomato and Swiggy replaced their customer service representative by bots to make customer experience more predictable. The increasing case of automation in manufacturing and service sector industry points towards cost-cutting and maximisation of profits.

  • The above illustration has created a condition of Robotic dystopias,:where robots replace humans or even rise up against humans, are a recurrent topic in popular culture and innumerable science fiction movies.


But did calculator replaced mathematics ?

  • Tasks within jobs typically show considerable variability in 'suitability for machine learning' while few -- if any -- jobs can be fully automated using machine learning," they continue.

  • Machine learning technology can transform many jobs in the economy, but full automation will be less significant than the re-engineering of processes and the reorganization of tasks."

  • Humans are still the key to success. AI affects change and empowers individuals in a way that is only possible with technology. Globality’s Smart Sourcing Platform multiplies the capabilities of sourcing in immediate timeframes, matching companies in need with the best quality service provider at the right price for every project. That creates broader opportunity while also enabling each individual to reap the payoff of the compounded efforts our platform delivers.

The augmentation of skills


Human skills in three broad categories depending on their readiness for automation:

Process-oriented skills include physical or repetitive activities in highly structured and predictable settings. These skills account for approximately half of the activities that people do today. Building houses or manufacturing objects, filing documents, following procurement or accounting processes are all examples of process-oriented skills.


Quantitative reasoning skills require intelligence. Some examples are linguistic knowledge, problem-solving, logical and numeric reasoning, understanding analytics, and programming.


Cross-functional reasoning skills are mainly related to social abilities and creativity. Some examples are making sense of things, defining a strategy, managing people, design mindset, emotional intelligence, and conflict resolution.

In this areas AI can create more task thus increasing the number of jobs by the way of

  • AI interaction designers will be able to communicate with personnel to translate requirements into machine functions.Simplicity consultants will simplify and streamline processes, technologies, and communication in an organization.

  • Wellbeing coaches will be in charge of change management to enhance the collaborative relationship between humans and machines then maintain wellness among employees.

  • Analytic HRs will use analytics to spot talent trends and to create and implement business, innovation and talent management strategies.

But what about the manufacturing jobs in a labor surplus country like India?


It is widely known fact that in India's manufacturing sector the number of small scale industry is much more as compared to that of big industry. In case of such industry the restriction of labor acts as a deterrent.

  • For firms below a threshold intrinsic productivity level, the small-scale technology will be more profitable, that is, it might not pay for them to incur the additional fixed costs of the more efficient large-scale technology. Restrictive labour laws might throw more firms into that category.

  • There is imperfect enforcement of labour regulations. Firms may then cross labour law thresholds but not follow applicable laws.

policy suggestion

There is urgent need of labor reforms in India particularly in term of labor restriction.

  • the exclusion of non-confirmation of a worker on probation and downsizing in response to demand and technology shocks from Industrial Disputes Act definition of retrenchment.

  • Also, more flexibility in task reassignment should be allowed within the Standing Orders Act.

Both these changes will provide Indian producers more flexibility in response to shocks. Also, no more than a single union should be allowed within any firm. And, finally, more labour laws should be covered within the newly installed self-reporting web portal.


way forward & conclusion

The advent of the unemployable and the risk of increased income inequality might result in social and political tensions. Delaying or blocking the adoption of AI will not help to address these challenges. Business and government alike should embrace AI to benefit from improved productivity and other societal advantages. Instead, the focus should be on facilitating workforce transitions through the following four avenues:


Invest in human capital: governments, education providers and employers should improve school systems and on-the-job training in areas related to science, technology, engineering, and mathematics or associated to AI, such as programming and data science. Additionally, a new focus is required on creativity, critical thinking, as well as social and emotional skills. Through tax benefits and other incentives, governments can influence businesses to invest in human capital, to develop innovative ways of life-long learning and to institutionalize training opportunities


Assure strong economic growth: economic growth is a prerequisite for job creation and wealth. Governments will need to invest in projects that contribute to employment (such as services, infrastructure or climate-change). Additionally, entrepreneurship and rapid new business formation are required. Building a more energetic ecosystem for small businesses and a competitive environment for corporations might require simpler and more advanced regulations, taxes, and incentives.


Increase the dynamism of the labor market: research studies have proven than wages rise when more people change jobs more often. Governments should make labor markets flexible to allow people to change jobs more easily.


Rethinking social policies: Many workers will need assistance and safety nets to adjust to the changes AI is bringing in and to find new jobs. Some voices even advocate for more comprehensive approaches such as a universal basic income. Additionally, as new varieties of work arise, such as the gig economy, issues such as income inequality and portability of benefits or insurance will need to be addressed.

The following article is based on the editorial How to defang AI which appeared in “livemint” on 14th of feb.


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