The prolonged period of lockdowns has changed the way we work, view productivity, and manage our well-being. In this pandemic, work from home, earlier construed a privilege for some employees, has become the new norm.
This has led to newer beliefs among firms, many of whom are now considering to have remote work for specific roles permanently. Employees are learning to navigate through their work demands while fulfilling domestic responsibilities under a lockdown. This has led to new paradigms of the well-being of the mind and body, and work-life balance.
A survey of approx. 3,100 individuals employed in diverse occupations across India was conducted during June-December 2019 to assess the suitability of machine learning (SML) and, in turn, the resultant susceptibility of 106 Indian occupations, as defined by the National Classification of Occupations (NCO 2004).
The survey instrument, which was based on Brynjolfsson & Mitchell (2017), had a task evaluation rubric that comprised 23 questions pertaining to SML.
Occupations such as painters, building structure cleaners, administrative associate professionals among others have high SML scores whereas occupations involving mining, construction, potters, glass makers, domestic and related helpers, cleaners among others score low on the SML Index.
Refer Fig. 1
The sectoral SML index shows high scores for creative, arts, entertainment, architecture and engineering activities, computer programming, among others. Similar to occupations, sectors such as mining, quarrying, building construction, among others score low on the SML sectoral Index scale.
Refer Fig. 2
We estimate an occupational index for feasibility of remote work (RWI) using seven questions that capture the occupational need for physical presence on the job, the data-intensive nature of the job, and the need to explain decisions during job execution. Responses are recorded on a five-point scale that reflects increasing feasibility of remote work.
The 𝑅𝑊𝐼𝑜 for occupation o is estimated as follows:
The index for need for human proximity (NHP) is estimated using two survey questions that assess whether it is important that the underlying task outputs are perceived to come from a human and whether task execution requires detailed, wide-ranging or conversational interactions with a human. Responses are again recorded on a five-point scale that reflects increasing need for human proximity in task execution.
The 𝐻𝑃𝐼𝑜 for occupation o is estimated as follows:
The outbreak of the novel coronavirus (COVID-19) and the subsequent work-from-home imperatives and lockdowns have led to significant economic disruptions around the world. As several millions of workers across diverse sectors are asked to self-quarantine, an understanding of the impact of this shift and mitigation strategies becomes critical. The insights from prior studies on the impact of work from home arrangements do not extend to the current context since these arrangements were mostly limited to a select group of workers and/or organizations and were often self-selected.
Two indices (Work From Home and Human Proximity) were mapped, district-wise and industry-wise, to determine the impact of the current lockdown. In this district-level measure, researchers find that cities had a higher potential for work from home, with many services based from here. Also, some urban districts were found more amenable to work from home. This study also found interesting variations within a district. In the case of Delhi, northeast Delhi was found to be facing much higher disruption compared to south Delhi.
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