Why India needs an AI policy6 min read . Updated: 23 Jan 2017, 05:55 AM IST
With China making rapid progress in artificial intelligence (AI)-based research, it is imperative that India view AI as a critical element of its national security strategy
With China making rapid progress in artificial intelligence (AI)-based research, it is imperative that India view AI as a critical element of its national security strategy, recommends an August 2016 report titled India and the Artificial Intelligence Revolution. Authored by Shashi Shekhar Vempati of Carnegie Endowment for International Peace, the report advocates spurring AI-based innovation and establishing AI-ready infrastructure as prerequisites for preparing India’s jobs and skills markets for an AI-based future and securing its strategic interests.
Here are highlights from the report:
AI’s potential in India
Thanks to the increasingly digital economy, fuelled by improving education and globalization, the Indian consumer is unknowingly the country’s biggest beneficiary of recent advances in AI, notes the report.
From utilizing various applications powered by AI to using a range of online services such as Amazon Marketplace and Netflix that learn from consumers’ online behaviour to make intelligent product and service recommendations, consumers are readily engaged with the proliferation of AI in India, whether they appreciate it or not.
Policymakers, however, lag behind, not exploiting AI for national security, public services, or other priorities.
Indian academics, public researchers, labs, and entrepreneurs face a different challenge than the corporations that dominate the space—the infrastructure necessary for an AI revolution in India has been neglected by policymakers.
Why China is stealing a march in AI research
While lack of physical infrastructure is certainly a major impediment, India’s AI development also suffers from the paucity of the necessary cultural infrastructure, which is key for recent advances from lab to marketplace in AI.
Fostering a culture of innovation and a commitment to research and, most important, nurturing an ecosystem beyond the four walls of the organization are all common to Google’s DeepMind, IBM’s Watson, and Baidu’s Institute of Deep Learning, the most successful AI projects of the past half decade.
While it must come as no surprise that Google, IBM, Microsoft, Facebook, and other global technology giants have invested significantly over the decades in machine intelligence, it is the story of Baidu that holds the most pertinent lessons for India.
The story of AI at Baidu is the story of Andrew Ng—an associate professor at Stanford University who teaches a popular course on machine learning (also available via Coursera, an online learning platform that he co-founded). Ng was hired away from the Google Brain project in 2014, following which Baidu invested heavily in physical infrastructure.
Baidu is investing in deep speech for voice-based searches that leverage speech recognition.
This intelligence is being built for understanding and interpreting queries in Mandarin rather than English; as such, Baidu is constructing a uniquely Chinese platform, independent of that which is used ubiquitously in the English-speaking West.
This version of AI thus offers the possibility for the development of AI in India, as an example of AI technology successfully developed in and employed by a non-Western nation.
Baidu’s investment in AI research exposes the relative backwardness of India’s technological infrastructure: China has recognized the importance of bridging the gap between the lab and the market while nurturing a research and innovation ecosystem unbounded by national borders and corporate firewalls. India, in contrast, boasts neither the material nor the cultural institutions required for such innovation.
Prime Minister Narendra Modi often challenges Indian IT entrepreneurs, asking when India will give birth to the next Google or Microsoft. But until India attains the infrastructure omnipresent in the US, and increasingly existent in China, the deep-learning capabilities necessary to address the vast linguistic diversity across India using machine intelligence may prove elusive.
AI’s impact on Indian jobs
While India dreams of its own manufacturing revolution through Modi’s Make in India programme, it is important for policymakers to closely examine how the advent of industrial robots and their impact on manufacturing transformed companies in other developing nations.
Consider the case of Foxconn—one of the world’s largest contract manufacturers for electronics. In 2015, Foxconn made news when its chief executive, Terry Gou, predicted that 70% of all manufacturing in Foxconn’s assembly lines would be automated with robots displacing humans. Some back-pedalling later, his estimate was scaled down to 30%. Foxconn is among the top owners of robotics patents filed with the United States Patent and Trademark Office and produces thousands of industrial robots a year that in aggregate are capable of performing more than ten types of manufacturing tasks. This is expected to have a significant impact on the workforce: as many as 60,000 workers have been displaced by robots in one Foxconn factory alone in the Kunshan region of China.
China was projected to have more installed industrial robots by the end of 2016 than any other country, with more than 30 robots for every 10,000 industrial workers. If China were to increase that density, employment would be further damaged.
While the dire predictions of a robot takeover of manufacturing have not come to pass, the reality of automation is that manufacturing is unlikely to create jobs at the scale that it did in the past. Quoting the US Bureau of Labor Statistics in 2013 on future employment projections, Darrell M. West of the Center for Technology Innovation at Brookings highlights how jobs will decline over the next decade in manufacturing and information technology among other sectors.
Writing in Pacific Standard magazine, Frank Levy, professor emeritus at the Massachusetts Institute of Technology, places jobs dislocation on account of AI in perspective when he dismisses the dire projections of a robot takeover.
According to Levy, the greatest area of concern for policymakers ought to be the impact of AI on jobs in the middle-skill category—assembly line workers, clerical workers, and the like. Levy also warns of significant dislocation caused by automation leading to a reduction in an individual’s potential for upward mobility. He emphasizes that a good education will be critical to acquire the necessary skills and to be competitive in this evolved labour market.
In their book The Second Machine Age, Erik Brynjolfsson and Andrew McAfee make several specific policy recommendations for coping with the job crisis likely to be spurred by AI. A key recommendation of particular importance for India, given Modi’s Startup India initiative, is the need to “restart startups". Brynjolfsson and McAfee view creative destruction inherent within the start-up economy as the best bet for experimenting with the new jobs and industries that can thrive in an AI-driven economy.
The authors provide examples of start-ups such as TaskRabbit and Airbnb that contrive previously non-existent economic opportunities for ordinary people with spare time and assets, thus creating economically productive work.
Skill development for future jobs
Not everyone is as sanguine as Brynjolfsson and McAfee about the coming AI revolution. The recent victory of AlphaGo (a computer program developed by Google DeepMind) over the world champion in Go has prompted fears of the threat posed by intelligent machines that are capable of superhuman tasks.
The direst warning comes from noted physicist Stephen Hawking, who apocalyptically predicts the end of the human race with the development of “full artificial intelligence".
In the provocative book Humans Need Not Apply, Jerry Kaplan, an American computer scientist and futurist, explores this and several other questions while attempting to paint a picture of an apocalyptic future and what it might look like if and when machines take over. Specifically, Kaplan raises two issues that should be of interest to policymakers in India. The first is the education system and the second involves skills and jobs. While discussing the likely impact of AI on labour markets, Kaplan poses the radical question: Is the current system of sequential education and work outdated, and does it require an overhaul?
In his book, Kaplan also proposes a so-called “job mortgage" as a new type of financial instrument through which employers, vocational schools and colleges would have an incentive to collaborate in a new way. In this proposed job mortgage market, Kaplan attempts to use free market mechanisms to match current skills acquisition to future job opportunities. He proposes to accomplish this by compelling employers to commit to an intent to employ an individual in the future if that person commits to acquire a specific set of skills over a certain time frame.
India will have to experiment with the kind of innovative instruments that Kaplan proposes if it is to prepare itself for the challenges from a machine intelligence-driven economy in the near future.