Apathy, cynicism of babus hurt welfare - Hindustan Times

Apathy, cynicism of babus hurt welfare

Feb 23, 2022 08:35 PM IST

To reform the system, bureaucrats have to start believing in welfare. Only then they will be able to find the right algorithm

Anyone who has encountered the Indian welfare State will testify that, but for a cluster of activist bureaucrats, most view the State’s welfare function with apathy and cynicism, as no more than a corrupt cesspool imposed on them by politicians driven by electoral incentives. The widely held view is that, at best, the welfare State needs to be “reformed” and limited to “target beneficiaries”.

The bureaucracy is constantly worried about ‘identifying’ the poor. It is this belief system that caused the bureaucracy at the peak of the lockdown crisis to actively resist cash transfers to migrant workers (Himanshu Vyas/ HT Photo) PREMIUM
The bureaucracy is constantly worried about ‘identifying’ the poor. It is this belief system that caused the bureaucracy at the peak of the lockdown crisis to actively resist cash transfers to migrant workers (Himanshu Vyas/ HT Photo)

Development scholars have long analysed about the roots of this apathy but recent conversations I’ve had with retired bureaucrats have added to the puzzle by pointing to the changing profile of the Indian Administrative Service (IAS).

The IAS today is predominantly populated with officers trained in the sciences, especially engineering. Data collected by the Trivedi Centre for Political Data on the Indian bureaucracy attests to this. In 2020, 80% of new recruits into the IAS came from science, technology, engineering and maths (STEM) backgrounds, compared to 18% in 1980. Simultaneously, the social base from which the IAS is recruited has become more democratised and, therefore, more representative of India’s social realities. A survey conducted by former IAS officer and public policy scholar Anirudh Krishna on the 2009 cohort of the IAS revealed that as many as 85% came from small towns and villages. A total of 24% were educated in government schools and 23% completed their education in rural settings.

How does this relate to the bureaucrats’ perception of welfare? On further probing, an interesting hypothesis emerged. First, at the risk of some generalisation, STEM training privileges a mental model which, to borrow from a former IAS officer, interprets the world through algorithms. It reduces real world complexities into neatly defined problems that require technical (usually technological) fixes. But the real world and, in particular, the deeply structural challenge of poverty is shaped by multiple layers of unique and often unpredictable interactions of policy with people and institutions, and the underlying power dynamics that govern these.

When welfare is approached as a technical fix, it correctly identifies all that is broken — the corruption, the absent, inefficient, apathetic bureaucrats, the greedy elite seeking to grab welfare largesse. But the fixes do not address the complexity that caused the break. Aided by technological advancement, failures of welfare are reduced to technical failures, to be fixed with data platforms, GPS monitoring trackers, command-and-control centres. Of the many challenges with this mental model, of critical relevance is the fact that it reinforces a worldview that sees the welfare State as corrupt and inefficient, caught in distortionary networks that feed electoral cycles.

This perspective has legitimised a deep disenchantment with the possibilities of welfare. This is why the bureaucracy is constantly worried about “identifying” the poor, lest money be wasted. Thus direct benefit transfers (DBTs), which cut through layers of people and are predictable (money moves from the bank to the beneficiary), have greater salience than investment in public goods and safety nets such as food subsidy and the Mahatma Gandhi National Rural Employment Guarantee Scheme. But for DBTs to work, they have to be built on data platforms that require citizens’ to be “verified” and “authenticated” to prove their legitimacy as “beneficiaries”. The welfare function of the State is thus reduced to a limited palliative available only for those who can be “verified” by the State. It is this belief system that caused the bureaucracy at the peak of the lockdown crisis to actively resist cash transfers to migrant workers. How can we give cash when workers can’t be identified, the argument went. Inevitably, the focus shifted to creating a new database.

The second hypothesis is linked to the changing social base of the IAS. The IAS today is far more representative of India’s social realities. But does succeeding, against the odds, influence perceptions of what it takes to “move out of poverty”? And, does this shape perceptions of welfare? After all, the IAS exam is designed to identify the cream of the crop. For those who make it, does success lend itself to a belief system that privileges individual capacity and entrepreneurship over the limits set by structural inequality, which underlies the rationale for the welfare State? And, is this one reason why “growth” and “welfare” are positioned as trade-offs?

I offer these hypotheses not as definitive conclusions, but as provocations to better understand why the welfare State routinely fails. Bureaucracy, as political scientist James Wilson argued in his classic study of the American bureaucracy, is not a black box. Rather, bureaucratic behaviour is shaped by belief systems, attitudes, and professional norms of individuals that people the system. Yet our debates on the civil service and welfare reforms rarely address this. Much of the reform debate focuses on technical skill sets, technology, better monitoring, and performance incentives. But no amount of reform can succeed if those charged with delivering welfare simply do not believe in it. The Indian State urgently needs new frameworks to address norms, values and build a collective sense of purpose.. Reforming the welfare State will first require bureaucrats to start believing in welfare. Only then will it be able to find the right algorithm.

Yamini Aiyar is president and chief executive, Centre for Policy Research The views expressed are personal

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