Will digitalisation of work worsen caste inequalities in India?

22 April 2024

The tasks carried out by workers are valuable indicators of the direction and impact of technological advancements. Routine, repetitive tasks have been identified as actions that can be automated and performed more efficiently through technological innovation, while non-routine tasks (tasks that do not follow a fixed set of procedures) are considered to be less impacted.

As a result, people working in jobs with high levels of routine task content are more likely to find some of their tasks being replaced by technological innovations. This potentially puts their jobs at risk.

This concern is particularly alarming in the context of India, where societal structures are more complex and segregated with less opportunity for social mobility. In India, technological innovation presents a significant job security risk for large swathes of (lower class/caste) workers, with little likelihood that they will be able to reskill and retrain their way into other, better work opportunities.

Digitalisation and India’s caste system

In our Digit sponsored research study, we look at the task contents of occupations in India and compare them for workers belonging to different social groups or castes. The caste system is a social and hierarchical stratification system that has existed for centuries in India. In ancient India, the population was divided initially into four, later five, distinct groups based on heredity, occupation, and endogamy (the practice of marrying within one’s own clan). These were the Brahmins (priests and teachers); Ksatriyas (warriors and royals); Vaishyas (merchant and business class); Shudras (those doing menial work); and Ati Shudras (untouchables, doing the lowest of the menial jobs such as cleaning toilets, pit latrines, drain, burial/cremation ground work etc.).

In modern India, four caste groups are used administratively for the purpose of affirmative action policies. These four groups are Scheduled Tribes consisting of indigenous tribes, Scheduled Castes, Other Backward Class and General/Upper Castes. Scheduled Tribes and Scheduled Casts are considered as the most disadvantaged socio-economically, followed by Other Backward Class. General or Upper Castes are considered as the privilege castes. As the caste system is rooted in the historical assignment of specific occupations, use of advanced technology in work has the potential to affect individuals from different castes in varying ways.

The existing literature on caste based inequality has focused on inequalities in resources and opportunities, leading to poor socio-economic outcomes for people from disadvantaged castes. It highlights inter-caste disparity in earnings, food expenditure, clothing expenditure, land-holding, and education levels of heads of household. However, there is currently little knowledge about the possible impact of the technological change on the existing caste inequality. Our research sought to address this.

Digitalisation of work may deepen existing inequalities

Our study shows that individuals belonging to disadvantaged castes, including tribal and untouchable communities (Scheduled Tribes and Scheduled Castes), are disproportionately engaged in occupations characterised by significantly higher routine task intensity (RTI) (Figure 1). Using Labour Force Data from multiple years, combined with O*NET task data, we see an overall decline in routine task intensive occupations, and an overall growth in cognitive and interpersonal task intensive occupations for all castes.

However, this change has been less pronounced for most disadvantaged castes (namely, Scheduled Caste and Scheduled Tribe) followed by Other Backward Class. Individuals from Scheduled Caste and Scheduled Tribe groups continue to work on occupations with high routine task intensity; these occupations are more vulnerable to advanced technological adoption.

The earnings gap is also more pronounced in low RTI jobs as opposed to high RTI jobs. This suggests that individuals from upper castes tend to earn higher wages in occupations with low routine task content. They are also less susceptible to the impact of advanced technology adoption, compared to their counterparts from disadvantaged castes.

These findings lead us to two key conclusions: first, individuals from disadvantaged castes are disproportionately concentrated in occupations highly vulnerable to automation and technological advancements, characterised by high routine task intensity. Second, workers from more privileged castes seem to have reaped greater benefits from digitalisation, increasingly occupying roles with non-routine interpersonal and analytical tasks, accompanied by a wage premium.

Consequently, individuals from disadvantaged castes are more exposed to the transformative impact of advanced technological changes in the labour market compared to their counterparts from higher castes.

The ongoing technology revolution in India has the potential to exacerbate existing inequality and disadvantage, particularly for those already situated in the lower strata of society. This may result in the emergence of a new group of workers at risk of becoming jobless. However, historical evidence suggests that technological advancements often create job opportunities, which could help mitigate disruptions for this group of workers, as they adapt to emerging roles. On the other hand, while automation primarily affects those in high routine-intensive jobs, the impact of AI advancement could extend to other groups, prompting anticipation and uncertainty about its impact on social inequality until its effects become clearer over time.

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