Only 1% of the data that we have with us has been analyzed, and the whole new level of personalized services and products that we experience today is, to a large extent, is a result of that. The economic value that data can unlock is only limited by our imagination. And, the dazzling speed of computing coupled with plummeting storage costs, is pushing the frontiers every day. The UN has identified 17 developmental areas that need to be addressed by developing countries to drive equitable growth. Policy-making is a critical aspect, and unless governments get it right, the digital divide will only increase further. If 4 billion people do not have access to the internet then we could potentially be looking at a situation that may even be termed as AI divide. To address this, we must solve the last-mile connectivity challenge. It will become an ethical issue if we have continued with yawning gaps in prosperity levels because technology’s access is limited. 

Skill plays a major role, and nations like India with a steady flow of STEM talent is doing very well in this area. The government’s Digital India initiative has worked, and young people today are aligning themselves to the future of work. At significant risk are workers who are at the lower end of the value chain and for them reskilling may be very challenging. In Singapore, the government encourages companies to invest in reskilling people who are at high risk. Unlike AI, the internet had its early beginnings with DARPA and was backed by the government. AI today is driven by private sector investments, and they have a massive role in skill-building as well. 

Policy-making for frontier technologies is a tricky affair. While regulations are important, but there’s always a risk of stymying innovation, and one never has the perfect answer. The pace at which things happen there’s always a catch-up that policymakers must contend with. Policies have to be well thought-through.

Companies must believe that it’s possible to be profitable and good (society’s standpoint) at the same time, and the two aren’t mutually exclusive. A collaborative mindset should be at the heart of everything that we do while engaging with the industry, government, individuals, and academia. Essentially, building an AI-led ecosystem is about harnessing technology to reset the future, provide fuel to the engine – data, think social good by humanizing the idea backed up by robust governance. A special mention needs to be made about the quality of data. GIGO is not going anywhere. 

AI Infrastructure is really about the ecosystem as one of the speakers highlighted. Today it may not be possible to replicate the Silicon Valley model, but we need the layer to be interoperable, connective, and data-rich. Such a layer would provide an opportunity to get people together and exchange diverse ideas. It’s also about creating TRUST-based rules. 

Almost all nations which are part of the AI revolution have national AI strategies in place – it’s a WIP document of course. The document alone will serve little purpose, and it’s about execution, execution, and execution! Big, bold steps are required, and many countries are at it silently. Perhaps, they are readying to spring a mighty surprise.    

Based on the RAISE 2020 Session Infrastructure for AI-led Innovation.

Speakers: Mr. Jonathan Wong, UNESCAP, Ms. Deepali Khanna, Rockefeller Foundation, Mr. Ravi Narayan, T-Hub, Telangana, Mr. Marco-Alexander-Breit, Federal Ministry for Economic Affairs and Energy, Germany, Mr. Christopher Fabian, UNICEF Innovation Unit,  Mr. Rahul Sharma, AISPL Public Sector, India & South Asia, Mr. Keith Strier, Worldwide AI Initiative, NVIDIA, Dr. Rajat Moona, IIT-Bhillai, Mr. Saurabh Gaur, Joint Secretary, MeitY.