India's largest platform for AI & Analytics leaders, professionals & aspirants

Sign in

India's largest platform for AI & Analytics leaders, professionals & aspirants

3AI Digital Library

How India can augment AI Research

October 11, 2018

AI Embedding Patents And IP In Indian Industry-Academia Ecosystem

In the academic, industry forums and conferences, India is being positioned as a potential superpower in the field of AI on the world stage. It is our collective vision to see India as the premier destination of AI in the foreseeable future. There is seemingly a lot of work to be done if we are to overtake our formidable competitors and eventually the current leaders in the space of AI – the US and China. But no intervention is perhaps as urgent as the need to promote natively developed AI research and intellectual property within our academic institutions, universities and corporate enterprises. 

China spends 2.07% of its GDP on core research and development. In India, that number is a meagre 0.6%. Given this, it should not be surprising that China produced 4.5 times the number of citable research documents in the field of AI between 2010 and 2016. In terms of citations, the H-index of papers published in India (100) lags well behind China (195) and the US (413) – for the same period. At this juncture, it is evident that India’s contribution to the overall body of knowledge of Artificial Intelligence has been both quantitatively and qualitatively disappointing.

The contribution from Indian corporate enterprises has also been found to be wanting. For the period between 2001 and 2016, corporates contributed to merely 14.42% of the AI research done in India, with almost 70% of that being done by foreign multinationals doing business in India – the likes of Microsoft, Google,  IBM and others. 

There is a definite need for both academia and Indian industry to step up and contribute to India’s vibrancy in the domain of artificial intelligence. Here are 5 critical interventions needed urgently to take our research capabilities to the next level: 

Foster a collaborative approach to IP development

There is often a pattern of multiple research projects happening in silos – through collaboration between like-minded researchers from the same field of science. Artificial Intelligence on the other is an interdisciplinary subject. It essentially requires researchers from different walks of life – data engineers, machine learning scientists and those conversant with real-life challenges that AI can solve – to come together to solve common problems and add to the overall body of knowledge.

Universities need to quickly recognize that and build research capabilities in AI in an interdisciplinary, collaborative manner. The good thing is, universities by their very nature tend to host brilliant minds from multiple fields, but it is imperative that these minds be brought together for real, cutting-edge research to be published in the field of AI

Boost Funding for Research at Universities

Whilst India does not lag in the number of STEM graduates, our research capability is still inadequate. This is partly because of a lack of funding for research. For millennials, the allure of a corporate job or opting for entrepreneurship is far too high due to the compensation and benefits on offer.

It is critical that local and national governments intervene to help academic research in the field of AI be a viable career option for those who are interested in research. By expanding the budget allocated towards research and development, more researchers would be able to tap into public grants to expand the research in AI. 

Promote Corporate Funding and Empanelment

The onus of funding AI research cannot only fall on public institutions. Private Indian corporations would also be a huge beneficiary of locally developed AI competency. It is critical that we continue the work in building the bridge between academia and corporations to fund and promote AI research.

Several large companies, as well as startups, recognize the need for indigenously developed research in Artificial Intelligence. Corporate empanelment programs take multiple forms – from the low touch speaker arrangements to corporations helping setup topical centers of excellence at universities in a technology area that is key to their business success. More arrangements of the latter form are necessary, in addition to individual research grants and scholarships that corporations provide.

Release government datasets for AI algorithm development

Activating the development and learning for AI algorithms requires access to a lot of data. Here again, the government should step in to provide the relevant data sets to researchers working on complex, India-specific problems. 

In multiple circumstances, the government holds a treasure trove of data which can be hugely beneficial for the learning cycle of algorithms and promoting their development. The government should take a positive stand on sharing data sets, all the while keeping in mind data security measures and privacy rights of citizens.

Two-Pronged Approach – Core AI as well as Applications-Led IP Development

Research in AI needs to be supported at two levels. First, the development of patented core AI algorithms that will have broad, cross-industry applicability. The second is the development of intellectual property that is topical to industry or sector-specific problems.

India suffers from numerous topical problems that need an AI-led solution – from providing health care services to our burgeoning population, support for those engaged in the agricultural sector and provision of basic public infrastructure – roads, hospitals, schools and sanitation facilities. In addition to developing core mathematical capability, significant value can be unlocked through by developing expertise around these large, complex problems in AI, with solutions that can be applied to help countries facing similar problems.

Building core R&D capabilities and more IPs in Artificial Intelligence is key to cementing India’s position and competitiveness in this space. Building strong capabilities in AI is now a mandate for most of the world’s most powerful countries and it is imperative that India does not fall by the wayside. The good news is that NITI Aayog, MEITY, NASSCOM and others are already taking concrete steps to engage the stakeholder community – researchers, educational and corporate institutions – for AI research. The foundational aspects – an inclination towards STEM streams and an orientation towards key subject areas among the current students is there as well. It is time we harness their wisdom and knowledge to catapult India to the forefront in the field of AI. 

Related Posts


    3AI Trending Articles

  • Fintech startup Volopay raises $2.1M in seed round

    Singapore-based fintech startup Volopay has raised $2.1 million in seed funding to provide businesses and startups in the Asia Pacific region a powerful control center for all their financial needs. Singapore-based fintech startup Volopay has raised $2.1 million in seed funding. The company said it wants to use the funding to provide businesses and startups […]

  • Major Cybersecurity Incidents of 2020

    From ransomware schemes to supply chain attacks, this year melded classic hacks with extraordinary circumstances. WHAT A WAY to kick off a new decade. 2020 showcased all of the digital risks and cybersecurity woes you’ve come to expect in the modern era, but this year was unique in the ways Covid-19 radically and tragically transformed life around the […]

  • Mental Health Startup Wysa backed by Google In Series A Round

    Wysa is artificial intelligence (AI)-driven virtual coach that combines empathetic listening with evidence-based therapeutic techniques Bengaluru-based mental health startup Wysa is looking to raise funds from Google, the company’s filings with the ministry of corporate affairs (MCA) confirm.  The filings, which contain Wysa parent Touchkin Eservices Private Limited’s articles of association (AOA), read, ‘“Series A1 […]

  • ML & Data Science Solutions: Build, Buy or Outsource?

    Data and analytics leaders increasingly believe that data science is a critical component of their analytics and business intelligence (BI) modernization plans, and are clamoring to incorporate new. Technologies such as predictive analytics, machine learning and deep neural nets sit at the Peak of Inflated Expectations on related Gartner Hype Cycle. While some degree of backlash […]