The growing necessity of applying technology more ethically and responsibly has forced powerful nations like the US, as well as developing nations like India to layout strategies for the coming years. Since the field of artificial intelligence has the potential of producing something remarkable overnight, measures are ought to be taken to guarantee growth without any unwanted impediments.
The US Department of Defense recently released a report on AI strategies, funds allocation and areas of focus. In a document titled Harnessing AI to Advance Our Security and Prosperity, US Department of Defense stated that AI was poised to transform every industry and is expected to impact every corner of their Department, spanning operations, training, sustainment, force protection, recruiting, healthcare, and many others.
Whereas, in mid-2018, Indian Government’s think tank NITI Aayog released a survey or a roadmap to the adoption of AI in various sectors of the country. A Task Force was assigned to study the strategic implementation of AI for National Security and Defence was set up by MoD/DDP in February 2018.
According to NITI Aayog’s AI report, India’s plan is to pursue “moonshot” projects ambitious explorations that aim to push the technology frontier and that would require the pursuit of world-class technology development and leadership in applying AI technologies to solve some of the biggest challenges.
Here is a comparison of AI strategies of the US and India:
Role Of Academia & Enhancing Partnership With Industry
US plans to make longer-term, stable funding available to attract the best academics to invest in long-term research relevant to critical DoD areas and remain in the business of educating the next generation of AI talent.
This entails increasing investment through existing channels, such as DARPA/IARPA and the Military Service Research Laboratories, and sponsoring long-term discoveries relevant to the Department.
It also involves stimulating the development of geographic concentrations of interconnected companies and institutions in AI. Strong and stable academic partnerships clustered in this manner will provide benefits to the Department, industry, and national competitiveness.
In India, institutes like IIT Hyderabad are already offering an MTech program in AI and ML, and an MTech in Data Science since 2015-16.
And, research giants like DRDO has its own AI wing where it has brought out impressive products in the form of CAIR
Recently, NITI Aayog, Intel, and Tata Institute of Fundamental Research (TIFR) joined hands together to set up a Model International Center for Transformative Artificial Intelligence (ICTAI) towards developing and deploying AI-led application-based research projects. This initiative is part of NITI Aayog’s ‘National Strategy for Artificial Intelligence’
ICTAI aims to conduct advanced research to incubate AI-led solutions in three important areas – healthcare, agriculture and smart mobility – by bringing together the expertise of Intel and TIFR.
It aims to experiment, discover and establish best practices in the domains of ICTAI governance, fundamental research, physical infrastructure, compute and service infrastructure needs, and talent acquisition.
Through this collaborative effort, the model ICTAI is chartered to develop AI foundational frameworks, tools and assets, including curated datasets and unique AI algorithms.
The Role Of Open Source Community
Financial incentives for private companies could include payroll taxes which are dedicated to subsidising training opportunities, income tax deductions for companies participating in reskilling initiatives, special taxes to be paid if a minimum training budget is not disbursed, as well as public grants for subsidising training, especially for smaller sized firms.
And, help create a pipeline of AI research projects for through initiatives like those of ICTAIs through grand challenges to be given by the government and PSUs. And incentivise public agencies to adopt and employ AI in delivering service through financial support; extra budgets for R&D; tax incentives and awards.
The open-source community serves as a vibrant global incubator of talented individuals and transformative ideas. To contribute data, challenges, research, and technologies to this community and engage with the open-source ecosystem as a vehicle for attracting talent, identifying and advancing new AI technologies that can transform defence, and broadening the accessible technology base.
The intent is to develop standards and support policy development related to information technology such as data storage, information security, privacy, and ethics for data capture and use. And to develop AI foundational technologies to promote applied research that can scale for national impact and will lead to the creation of a vibrant and self-sustaining ecosystem.
Read the detailed report here.
Budget
The ultimate goal of this research is to produce new AI knowledge and technologies that provide a range of positive benefits to the society while minimising the negative impacts.
The Trump Administration has prioritised funding for fundamental AI research and computing infrastructure, machine learning, and autonomous systems.
The Federal Government’s investment in unclassified R&D for AI and related technologies has grown by over 40% since 2015, in addition to substantial classified investments across the defence and intelligence communities.
On September 7, 2018, the U.S. Department of Defense announced it will invest up to $2 billion over the next five years towards the advancement of AI.
This will be in addition to existing government spending on AI R&D, which totalled more than $2 billion in 2017 alone, just from unclassified programs and not including Pentagon and intelligence budgets.
Existing funding has already propelled more than 20 active programs under the Defense Advanced Research Projects Agency (DARPA) exploring different aspects and uses of AI.
To pave the way for greater advancements in digital technologies, the Indian government has doubled its allocation to the ‘Digital India’ programme to $480 Mn (₹3,073 crore) in 2018-19.
During India’s Budget 2018 session, it was announced that the government will be investing extensively in research, training and skill development in robotics, AI, digital manufacturing, Big Data intelligence and Quantum communications, among others.
Challenges Faced In Large Scale Adoption
Indian AI taskforce and their US counterparts identify few areas of challenges and the way to address them:
In the Indian scenario, the challenges are concentrated across common themes of:
- Lack of enabling data ecosystems:
- Low intensity of AI research
- Core research in fundamental technologies
- Transforming core research into market applications
- Inadequate availability of AI expertise, manpower and skilling opportunities
- High resource cost and low awareness for adopting AI in business processes
- Unclear privacy, security and ethical regulations
- Unattractive Intellectual Property regime to incentivise research and adoption of AI.
Whereas, the US seems to be well ahead of India in terms of the advancements in this space. They had a good head start by at least more than a decade. This puts them in a comfortable position with respect to the infrastructure available.
The main challenge that the US faces is the adoption of AI at the ethical level. The growing scepticism surrounding the eavesdropping of watchdogs like NSA has put it under a tight spot with respect to its accelerated approach in adopting AI.
AI For Social Good and Open Mission Initiatives
The US plans to form open AI missions with academia and industry that will contribute to addressing global challenges of significant societal importance, such as operationalising AI for humanitarian assistance and disaster relief for wildfires, hurricanes, And Earthquakes.
And combine efforts with a wide range of actors to produce inspiring AI technology that benefits society. These open missions will challenge a broad community to advance the state of AI and learn how to operationalise the technologies on an integrated basis across domestic and international organisations.
Today’s world creates and has access to an unthinkably large amount of data, which can be harnessed to gain new insights. This is the time where the usage of data analytics powered by machine learning has gained traction on a large scale. The sudden surge in applied artificial intelligence presents the innovators with endless possibilities.
Non-profit organisations have historically been suffering from the lack of tools to tackle this amount of data. But things are changing now, even in India.
For instance, UK-based Data Kind conducts events which are volunteered by the data scientists who not only address the impending issues but also offer solutions. Their Bengaluru chapter had recently come up with ideas like using Anganwadi data along with NASER data to develop a thematic map for achievement across all the districts in Karnataka, and the correlation of availability of drinking water and toilets to the dropout rate among students.
The US believes that the insertion of new technologies into complex work systems changes the nature of the work, including new forms of brittleness and error, and uncovers new at the same time as it improves the work in other respects.
The infrastructure, the resources and the talent pool are there but for a large scale adoption, the government needs the belief of the commoner.
Though the challenges faced at the resources level in the Indian scenario is quite different from the US, they both seem to agree upon the ethical and privacy part of adopting this technology.
What India lacks is the rich talent pool that pioneers like the US and China flaunt. India has its handful in terms of manpower but falls short at the skilled section.
But this also happens to be the reason why the world takes India seriously; skills can be learned but building a population both dense and young will take more than a generation. So, it is high time India puts their initiatives into motion more aggressively.
