Could Artificial intelligence help bridge India’s societal divide?

The Personal Data Protection Bill 2019, tabled in December 2019 by the Union Cabinet of India is keeping rights activists and big corporations at the edge. The Bill aims to protect and govern the processing of personal data by the government, companies incorporated in India and foreign companies dealing with personal data of individuals in India. In its current form, the bill gives the Indian government ultimate rights over accessing user’s data. It also grants authority to corporations by relaxing the provisions on data localization (that is, by allowing companies to take personal data out of the country with minimal oversight). Critics say the government is missing out on an opportunity to formulate a progressive policy that could set the benchmark for data policies around the word. 

But why is India so concerned about this bill? Well, for one, there is the Government flagship programme called Digital India, which aims to transform India into a digital empowered society and knowledge economy. And the apparent manifestations can be seen in other flagship schemes like Make in India (giving boost to manufacturing sector and entrepreneurship) and booming e-commerce space. And then, there is “National Strategy for Artificial Intelligence”, a discussion paper by NITI Aayog, Government of India’s Think Tank. The strategy strives for positioning India among leaders on the global AI map – with a unique brand of “#AIforAll and becoming technology leaders for achieving the greater good”. The paper lays out sectors such as healthcare, education, agriculture, smart mobility and smart cities for the initial rollout.  

All this has data as its backbone. The data is needed for creating algorithms for machine learning and for building technology for artificial intelligence (AI) applications which would, in turn, power the digital transformation.  And if India is to harness the good of digital transformation, it would need to weed out the wicked that come with data and technology, its availability, its accessibility and its governance.  

While the NITI Aayog’s paper naively suggests AI intervention in the given sectors, a lot has already transpired. For instance, in the agriculture sector, large-scale data is being harvested for soil quality, weather conditions, crop maturity, seed properties etc., using GPS sensors and drones. Food is being grown in controlled environments or indoor farms, robots are taking over manual tasks such as sowing and harvesting. Innovative and smart warehouse management or food packaging is adding to the agro-industrial value chain. All these efforts may mean increased farm productivity; however, this doesn’t guarantee sustainability in the sector. The farmers are still missing crucial market linkages. Their earnings haven’t increased. Farms practices are becoming more and more extractive and ecologically exploitative to reach economies of scale.  

This also raises the concern about data collection and ownership. In the agriculture sector, data is getting consolidated with agro giants such as Bayer-Monsanto or Walmart-Flipkart, giving them full access and control over these data sets, and endangering livelihoods of small-scale farmers in the long run. Data monopolization is another key concern that comes with AI, and regulation of new data oligopolies is not addressed sufficiently in the proposed Bill either. This gives them the freedom to monetise data for profit motives, knowingly or unknowingly set in data biases and create digital profiles that could perpetuate existing inequalities and jeopardise public harmony. And with government getting the ‘no-questions-asked’ kind of control over these data sets, there is increasing surveillance and profiling, curbing civil rights and invasion of privacy by the State itself.  

While the progressive actors across the world challenge these new hegemonies, public engagement and accountable plans for AI and data governance are the only way forward.  AI and tech-innovations should be geared towards creating equal and inclusive societies. And for this, public and private actors would need to build trust and avenues for cooperation. The proverbial “greater good” of AI and tech-solutions can only be achieved if it is affordable, accessible and economical for all strata of the society.