Intelligence Assistance and India’s approach to AI

Artificial Intelligence, most commonly known as AI, is at the forefront of the current technological revolution. AI offers a wide range of opportunities to improve human lives but at the same time provokes valid fears all around the world about job losses and increasing inequality. 

Korinek and  Stiglitz  in their recent paper, ‘Artificial Intelligence (AI), Globalization and Strategies for Economic Development’ talk about how developing countries and emerging economies have reasons to worry as AI, being a resource-saving and labour-saving technology, is likely to erode their comparative advantage resulting from abundance of labour and natural resources.  However, the authors also highlight a unique concept called  Intelligence Assistance (IA), a type of innovation that could be labour-using rather than labour-saving.  Simply put, IA are those technologies that complement human intelligence. Examples of past innovations that fall in this category of IA as highlighted by the authors include telescopes and microscopes that enabled humans to see what the naked eye could not; thermometers that enabled humans to measure temperature precisely, and tests developed to detect the coronavirus (Korinek and Stiglitz, 2021). These examples show that IA technologies complement human capabilities. 

In a similar way, there is scope for AI technologies to be used as Intelligence Assistance technologies to improve labour productivity and address societal challenges. It is in this context that we explore the approach of India’s policymakers to AI. Although India does not have a national AI policy as yet, there exists a ‘National Strategy on AI’ released by NITI Aayog in 2018. The main theme of this strategy document is #AIforAll: Technology Leadership for Inclusive Growth. According to this strategy document, the guiding principle of India’s approach towards AI will be “optimisation of social goods, rather than maximisation of topline growth”. The document further outlines five key sectors, Healthcare, Agriculture, Education, Smart Cities and Infrastructure, Smart Mobility and Transportation, where AI would be applied to solve current challenges. It thus appears that India’s approach to AI is currently positioned more in the IA space. 

Some interesting examples of startups that are already operating on the principles of IA include Niramai, a Bangalore based healthcare analytics startup, that has developed a novel software-based medical device (using machine learning algorithms) to detect breast cancer at a much earlier stage than traditional methods and works for women of all ages. The technology can be used for regular preventive health checkups and large scale screening in remote areas creating jobs to operate the setup. Another example is that of Intello Labs, an agri-tech startup, that uses image recognition to detect crop health and gives predictive analytics on the crop’s final grade to help farmers scale their business effectively. 

India being an IT powerhouse should harness the opportunities that IA technologies offer to tackle societal challenges. However, these advanced Intelligence Assistance (IA) technologies are eventually a form of Artificial Intelligence (AI), and thus will come with the usual concerns that surround issues of data privacy, data security, etc.  As India seeks to increase its presence in the IA space, it would be important for all necessary policies related to the use of data to be in place to ensure that these technologies achieve their full potential.


References: 

  1. Korinek A. and Stiglitz J. (2021), Artificial Intelligence, Globalization, and Strategies for  Economic Development, Working Paper No. 146, Institute of New Economic Thinking, available at https://www.ineteconomics.org/research/research-papers/artificial-intelligence-globalization-and-strategies-for-economic-development 
  2. NITI (2018), National Strategy for Artificial Intelligence NITI Aayog, Government  of India, available at http://niti.gov.in/sites/default/files/2019-01/NationalStrategy-for-AI-Discussion-Paper.pdf 
  3. Niramai, https://www.niramai.com/ 
  4. Intello Labs, https://www.intellolabs.com/ 

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