Friday, November 22, 2024

If India wants to build infrastructure, AI-driven labor data-dashboard is a must

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It is great that we have learnt from China (and early days of USA) that building infrastructure is a smart way to grow rapidly, as it pumps money into the economy and facilitates growth. But, as I stare at the auspicious number of 1,11,111 crore allocated in the union budget for building “infrastructure” this year, I get tempted to ask a question that I am yet to get a clear answer of.

Where is the construction labor that can do this?

Where are the unskilled men who will move the material, or the skilled bricklayers, the mesons, the men who will fix the shuttering, the men who can cut the reinforce steel bars and place them, the plumbers, and electricians?

We (sadly) know where our doctors are (i.e., mostly in USA) or IIT-ians (again, even more mostly in USA), our remaining engineers (who carry a piece of paper that claims thus) or architects (who carry nothing but conformation from CoA that even Supreme Court does not care about) and so and so forth because they all come from a system. But we have no idea about the men who are expected to build the 1,11,111-crore infrastructure, as most of them, even today seasonally come out of the woodwork of rural India and go back.

My thirty years spent in construction industry has taught me that our construction labor force is the most mysterious human resource we have, as finding them has no formal process.

In case of Gujarat, the local labor is sourced by a labor contractor (who is mostly a tout) going to a village and meeting the village-head and “bulk buy” or rather reserve the men-power the head will claim to have by paying a lumpsum amount. The lot thus acquired will have all kind of riffraff along with a few skilled and experienced men. It will have women, teenagers and old and the frail too. I suspect that same is the case across India with local variations in the process.

As there is no certificate to claim that one is a meson or a RCC worker, the entire human resource pool that comes to a construction site via this lumpsum deals has no uniformity of skill. But this is what is building most of India, even now. This organic system has worked, but probably because we were not really aspiring to build ultra-large projects that we are envisioning now. 

These are nameless people with a range of skills that a contractor is forced to use to constructed anything ranging from an atomic power station to EWS housing.

With arrival of mobile phones reaching deep into rural India, this process has evolved to calling instead of going to the villages and a few rural entrepreneurs have matured into labor-suppliers with networks, but the overall mess remains the same for a simple reason.

We do not know our labor.
We do not know where many of them vanish during festivals and harvesting time.
We do not know their skills.

And most importantly, we do not clearly know how many of them are out there.

So, when the finance minister earmarks X amount for a project in a region, it is a hopeful shot in the dark as there is no certainty if required labor is available there or not.

This information gap may not be visible, but its effect clearly is.

Most of the government contracts are delayed, and the reason is not always slow-paced payments. The delay is mainly caused because no contractor can find required number of laborers from any formal information system.

This has been the reality of the construction industry; but I am not sure we have to accept it and carry on.

Today we have a completely new tool to close this information gap, and that is data analytics driven by AI.

Registration of labor is now taking place in each state, directly or indirectly.

In a progressive state like Gujarat, labor welfare is seriously driven by the state by offering benefits linked with healthcare, food and shelter, and hence almost all labor gets “touched” by a data gathering system at some point.

All that is now required is to work on this data using AI and build a transnational information system to catch the missing and weed out the duplications, to list and verify the skills; in short, know our nation-builders and deploy them efficiently.

This task was clearly an impossible one in past but now completely doable.

If we want to build infrastructure in a timebound manner, labor availability is the primary dataset based on which budgetary allocations and developmental proposals should be made.

Each state must start with having a dashboard (hopefully linked with a national portal as soon as possible) to know where each laborer is deployed, what is he doing and if his wellbeing is taken care of or not.

This will not only improve the infrastructure sector management, but it will also help in taking care of the most hardworking, but the neglected and the voiceless segment of our society.



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Disclaimer

Views expressed above are the author’s own.



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