India Insights with Geetha Nandikotkur

Artificial Intelligence & Machine Learning , Next-Generation Technologies & Secure Development

Analysis: India's Artificial Intelligence Push

Much Needs to Be Done to Reach Maturity
Analysis: India's Artificial Intelligence Push

As India gears up to use artificial intelligence to boost its defense capabilities and improve security in various sectors, it inevitably will face challenges.

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Some serious measures are being considered to use AI to boost the operational preparedness of India's armed forces.

Ajay Kumar, defense secretary, articulated his plan: "AI is India's preparation for next-generation warfare. This is where the future lies. We must prepare ourselves for next-generation warfare, which will be more and more technology-driven, more and more automated and robotized."

Therefore, after much hype, the government has formed a 17-member task force to work on the AI project. Members include National Cyber Security Coordinator Gulshan Rai; M.V. Gowtama, chairman and CEO of Bharat Electronics Ltd; plus representatives from the Indian Army, Navy, Air Force, Indian Space Research Organization, Atomic Energy Commission, Defense Ministry, Indian Institute of Science-Bengaluru, and Indian Institutes of Technology at Mumbai and Chennai.

The task force will work toward building AI capabilities across various sectors, not just defense, with the objective of revolutionizing security systems with AI and associated technologies.

It's encouraging to hear IT Minister Ravi Shankar Prasad say that India is working toward applying AI in security, finance, manufacturing, commerce, voice recognition and transportation. In a recent blog, he wrote: "The application of AI in governance provides an opportunity for India to apply information and communications technology tools and leapfrog over developmental and infrastructural constraints."

The National Informatics Center already has developed a pilot project to monitor implementation of the toilet construction program under Swachh Bharat Abhiyan by analyzing photographs taken with GPS-enabled smartphones. AI software can detect the location, the identity of the beneficiary through face-recognition technology, and the physical state of the toilet using an algorithm that infers its condition from the photos.

AI's Role in Security

Many security practitioners say that AI can help mitigate the threat of cyberattacks by automating the more complex processes for detecting attacks. But so far, only a handful of companies are working to apply AI for security.

Globally, some aviation companies are deploying AI applications integrated with big data analytics to help secure valuable information on human behavioral patterns that can track vulnerabilities that could lead to attacks.

The financial sector has also started applying AI techniques to boost business operations. "There's a dire need for AI today, as 99 percent of the breaches are due to known vulnerabilities," says Sridhar Sidhu, head of information security services at Wells Fargo.

It would be helpful if the National Informatics Center develops ways to apply AI embedded with security by design to enable businesses to map their security risks and take action against hackers misusing data.

Collaboration between industries and government departments will prove essential to building a unique AI framework with a built-in security model, which can detect vulnerabilities in the initial stages and gather intel early.

Stages of Development

The task force is expected to submit its recommendations in the next couple of weeks.

It will prove critical to create standards for mapping security risks during the innovation stage, and not as an afterthought. The concerns of data privacy and data security must be balanced against data availability and innovation in the context of AI.

The AI maturity model calls for several stages of development, including:

  • Initial: Primarily deals with automated alerting, with little or no routine data collection;
  • Minimal: Incorporates threat intelligence indicator searches and a moderate level of routine data collections;
  • Procedural: Follows data analysis procedures created by others and a high level of routine data collection;
  • Innovative: Creates new data analysis procedures with very high level of routine data collection.

With the right approach, Indian organizations can move forward toward mature implementation of AI.

About the Author

Geetha Nandikotkur

Geetha Nandikotkur

Vice President - Conferences, Asia, Middle East and Africa, ISMG

Nandikotkur is an award-winning journalist with over 20 years of experience in newspapers, audiovisual media, magazines and research. She has an understanding of technology and business journalism and has moderated several roundtables and conferences, in addition to leading mentoring programs for the IT community. Prior to joining ISMG, Nandikotkur worked for 9.9 Media as a group editor for CIO & Leader, IT Next and CSO Forum.

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