Panchatantra21

Five Big Ideas for India in the 21st Century

The hurly-burly of the elections is over and a new government is in place in Delhi. Ministers and their officers must be drawing up lists of the many urgent things that need to be done in the next couple of months. But there is a difference between what is urgent and what is important and it is more often than not that the urgent displaces the important from our schedules. In this article we explore five important issues that India needs to address, not just for the immediate gratification of urgent needs but, to set the agenda for the 21st century. From garbage disposal through restructuring of our education infrastructure that will in turn transform India into an artificial intelligence based space faring civilisation that is rooted in our Vedic past, let us explore five new narratives of Panchatantra/21.

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Charity begins at home. The journey of a thousand miles begins with a single step. Before we set out to change the course of human civilisation, let us first clean up the garbage from our doorstep. Literally. India is drowning in garbage. Other than  metropolitan cities, no town or village has any mechanism to dispose of household garbage in any meaningful way -- except to dump it beyond sight. Households dump it on the streets and the municipality, if such a thing exists, takes it and dumps at the edge of the town. This creates huge and unsustainable garbage dumps that are not only an eyesore but also a health and ecological hazard. The situation is worse if the town has a lot of visitors, tourists or pilgrims. The devastation is compounded by the number of people creating garbage and the indifference of the transient visitors to the outcome of their actions.

Disposal of garbage is not rocket science and communities across the world have managed to solve the problem to a large extent. In fact, a systematic disposal of garbage is the leitmotif of a civilisation and the Sindhu-Saraswati civilisation was perhaps the first to realise this and implement it in their system of drains. But in the twenty-first century, we must do it better and differently. Swachchha Bharat and its focus on building toilets must be enlarged to encompass the creation of industrial grade garbage disposal units in each and every town and village in India. Methods and systems to collect, segregate, transport, recycle and dispose of garbage exist in many countries and India must adopt and adapt what is most appropriate for India and then create a mechanism to replicate it in a scalable manner across the land.

After garbage, the next area to be cleaned up -- and this time, metaphorically -- is the education sector where the infamous license-control raj is still alive and choking honest intent. Regulatory bodies like the AICTE and the UGC have all the authority to control educational institutes but not the responsibility of delivering anything useful. These have throttled and choked well meaning individuals from creating educational institutes of excellence. Instead, what we have are either tax-payer funded white elephants run by politically connected and government appointed directors or dubious private institutions run by crony capitalists. A majority of the former are handicapped by lack of three requirements - funds, efficiency and imagination. A majority of the latter aim to fool students and deliver dubious value in terms of employability.

What we need instead is a regulator, modelled on the Registrar of Companies. This should not not dictate which colleges are allowed to operate or what or how colleges teach. Instead it must ensure transparency -- in intent, execution and delivery --  by mandating disclosure norms that are based on principles that are similar to GAAP -- generally accepted accounting principles. More importantly, these disclosures must be validated through a statutory audit process. What this means is that students and their parents, who fund their education, would have a reasonably clear idea about the merits of an educational institute -- as equity investors have in the financials of companies that are listed on the stock exchange -- and take an informed decision on where to invest time and money to get a decent education. In short, let the market and not government babus decide the fate of educational institutes. This is explained in detail in an earlier article “Auditors, Not Regulators.” (https://bit.ly/2YNDWvk)

Continuing with this basic philosophy of minimum government, maximum governance and extrapolating from the gig economy --  Uber, Ola, AirBnB, Oyo  -- that allows individuals to sell their services directly to the customer, we could easily have good, but independent, teachers reaching out to students through platforms like Youtube. However, distance learning has its challenges. First, students want the sanctity of an accredited university degree that is a necessary condition for jobs. Second, they want the security of a placement service as the outcome of any education. Finally they want all of it to be either free or at a very low cost. Meeting all three conditions through a simple elearning platform is impossible. However, a recognised and accredited university, say IGNOU, can create a platform where individual, but non-employee teachers can teach, or deliver educational services and be paid based on a metric that is based on student ( “customer”) engagement and feedback. This metric should be multidimensional and should consist of (a) the number of actual student-hours views that the videos have, (b) the rating given by students. Such a platform supported by a distributed evaluation service, as in online exams in designated premises, and a Naukri.com style job-portal to facilitate placements can be put together as an alternative to the traditional campus oriented educational institute. This is explained in detail in “Distance Learning Reloaded.” (https://bit.ly/2VRPjk7)

These two new age educational initiatives -- auditing rather than regulating educational institutes and the ‘indie’ teacher based distance learning program -- form the second narrative for Panchatantra/21.

Education continues as the third of our five narratives but now the focus moves from platform to content. What is it that our students must learn? To begin with a large part of the curriculum will be drawn from the traditional BA, BSc, BCom and even BTech, BBA, MA, MTech, MBA courses. These are tried and tested curricula that have stood the test of time but of course each university or college should have the freedom to offer anything that they want without centralised bodies like AICTE or UGC trying to impose their point of view. In a market economy, “customers” -- that means both students and recruiters -- will signal their requirements in a manner that the education market must understand and respond to. This would mean that there will be more students -- and hence more colleges or independent, “indie” teachers -- for courses and subjects that are preferred by recruiters.  However, as Steve Jobs has put it, “customers do not really know what they want” and so it is up to policy makers to determine what would be important and useful for India in the current century and even the next.

Moving into the 21st century, mankind -- the carbon-based biologicals  --  will have to share this planet with what is virtually a new species, the silicon-based artificial intelligence powered systems as explained in “Intelligent Machines: Humans May Have To Contend With A Superior ‘Species’ Soon; Are We Prepared?” (https://bit.ly/2I2kMLk). This may sound like science fiction but automated and more importantly autonomous systems -- from self driving vehicles, through medical diagnostic tools right up to public safety and even juridical services -- will take over and run our society with little or virtually no human interference. We may not like it -- just as colonised people never really liked their new masters -- but we will have to learn to live with them. To begin with, we need to learn their language. Indians learned English when they were colonised -- say after the Battle of Plassey --  and then they made the best use of this skill to chart their own destiny in the 19th and 20th century. So should be the case with artificial intelligence in the 21st.

Every child in every school and college must learn the basics of artificial intelligence, of neural networks and of course, computer programming. Python, for example, would be the new English, a skill that is so eagerly sought after by parents who are so keen to send their children to English-medium schools. One could learn history, {human} languages, sociology, medicine, fine arts, engineering or whatever but one must also know AI and computer programming. Just as a knowledge of English equips a person to work his way through the world irrespective of the location or nature of work, so would a knowledge of robotics and AI be essential not just to live but to build new products and services for the coming age. Just as if you want to make money from a big economy like China you learn Chinese, so should there be no hesitation or embarrassment in learning Python and AI right from primary school all the way to college.

Machines and robots are “learning” about human languages, behaviours, attitudes and choices at an unprecedented rate but if we, biological sentients, have to keep up with them we need to know their language and behaviour as well. It is not just that computer programming should become “The Fourth Language” (https://bit.ly/2JFYKl4) in our schools  but AI and Robotics should be built into the warp and woof of our school and college curriculum. Products like Arduino and Raspberry Pi should be used not just for science projects but for every kind of project that is mandated in the curriculum. This is one area where a visionary  government and its policy makers must take the initiative to fund the design of innovative curriculum, the development of appropriate course material and the appointment of competent teachers.

But AI and robotics is the path, what is the destination?

This takes us to the fourth narrative of our Panchatantra/21 and to the next level of human endeavour -- Space! Europe was too small for the European civilisation and it flowered only when the bold and the brave among them, spread out, first to colonise America and then across Africa and Asia. Similarly, the world is not enough for humanity as biological and machine intelligence grows by leaps and bounds. The composite carbon-silicon civilisation must and will physically expand first  to the Moon and Mars, then to Titan, Enceladus and Europa and eventually to other solar systems in this galaxy.

In this grand adventure, it would be tragic indeed if  India were to be relegated to the position of a  passive observer clapping and cheering from the sidelines while the US, Europe and China establishes colonies in these distant realms. As described in this article, “A whole new space age”, (https://bit.ly/2MaeqPw)  India must take a definitive stand to become a space faring nation and invest the power of money, of mind and of machines to stake her claim beyond the frontier. Mangalyaan and Chandrayaan are two excellent initiatives and they must be viewed to be as important as say GST or Ayushman Bharat. This may not translate into votes in the 2024 elections but that is where the current government must demonstrate its passion for the big idea. “Go West young man” was once a part of the lexicon -- and the manifest destiny -- of the American civilisation that grew and prospered. Similarly, every young man and woman in tomorrow’s India must be encouraged to dream of going to space -- along with robots and other intelligent machines -- to set up homesteads, establish colonies and create opportunities for economic and social expansion.

Beyond the raw technology of ISRO, a national level Space Commission must be established to address the socio-economic issues of a space faring nation. Such a commission will encourage, and equip, schools and colleges with the tools and ideas that will allow their students to think beyond that next job in TCS or Hindustan Lever and incentivise private enterprise  to invest in space related ventures. Space travel and colonisation should be the fourth big idea that India must focus on in the next decade.

But in parallel with the exploration of outer space, India also needs to look within. We must use the rear-view mirror of history to look into the Indic heritage that stretches back in time longer than any other living civilisation that exists today. Egypt and Mesopotamia has been swallowed up in the march of time and even China that still preserves links to its past is in the process of forgetting the same. Only we in India can still trace our civilisation back through the Chandragupt’s Mauryan era to the tenuous links of the Harappan civilisation and even beyond. The evidence is tantalising. Remains of chariots from the Mahabharat era have been found in Sanauli, Baghpat in Uttar Pradesh. The sunken city of Dwaraka, Gujarat, is still visible under the ocean. Harappan era relics have been found along the dry bed of the Ghaggar river through which the Saraswati once flowed and this, as Michel Danino has shown in his book “The Lost River,  connects the Harappan civilisation with the Dwapar Yug of the Mahabharat.

It is time that the government puts together a formal mechanism that will initiate primary research into these areas, search for evidence, connect the dots and present a comprehensive picture that will transform our understanding of the  past. Legends must be codified as verifiable and documented history. Without compromising on academic rigour -- without claiming that ancient India had nuclear bombs and spaceships, for example --  honest historiography must be applied to elevate our myths from the fog of antiquity and bring them into the domain of history. This has happened in the past. The Asiatic Society of Bengal led by William Jones  had identified Chandragupt Maurya, named in ancient and mythical lists of Indian kings, as Sandrakottus, a contemporary of Alexander named in Greek records of his invasion of India. This monumental discovery had significantly extended the antiquity of Indian history. India as a nation owes it to itself to do this once again and reassert the continuity of the Indic civilisation right from the Vedic Age to the Age of Space and Intelligent Robots. This is the fifth and final narrative.

Man does not live by bread alone and nations too must look beyond the mere mechanics of administration and economics. Irrespective of who runs the government, the Indian economy will surely grow as issues related labour, land and capital markets are sorted out and technology is used to enhance efficiency of governance. But there is a far larger story that awaits India and it is time for us to gear up for a whole new role that India will play in the comity of nations.  India must prepare itself to be the tip of the arrow and not a mere lance bearer as humanity reaches out -- literally and metaphorically -- to touch the stars. Panchatantra/21 would be our road map in this quest.

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this article first appeared in Swarajya magazine

Is Inequality Inevitable ?

Maximilien Robespierre might have fired the imagination of the world with his call for Liberty, Equality and Fraternity during the French revolution but the concept has been rather elusive in practice. Equality, in particular, has proved to be a bridge too far.

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Let us begin with the Internet and the world wide web that was supposed to liberate the individual from the clutches of the powerful media barons. As one of the early pioneers and evangelists for this new technology, this author had created a portal -- Yantrajaal, a Bengali word that he had coined to define a network of devices -- in the same year that Google was born and seven years before Facebook. The general idea was to serve as a platform to share information on technology from an India perspective. In principle it could reach out to every corner of the world -- something that his earlier journalistic efforts in school and college had failed to do. But of course that would never be. Hardly anyone, other than the author’s immediate circle of physical friends, visits Yantrajaal. Unfortunately, that is true, not for Yantrajaal but for many other websites as well. While millions of websites exist and continue to be built, the really popular websites -- at least, the ones that make some money  --  are still the ones owned and operated by big media houses like Times of India and the New York Times. But even this is an illusion because the real flow of news and views across the globe is actually governed, not by these media houses but by technology firms like Google, Facebook and Twitter, or, where they are banned, as in China, buy their local equivalents. In fact, these so-called tech companies have actually morphed into full fledged, advertisement driven media companies and it is they who rule the roost when it comes to the dissemination of information.

This concentration of power is an outcome of the network effect. The value of a network is proportional to the square of the number of its participants. As more and more people join a network its value as perceived by its members goes up very fast, compelling others to join it in a virtuous, or vicious, cycle. You may build a search engine or a social media platform that is better, say more private and secure, but you would never be able to catch up with the leaders.  It is not quite the first mover advantage, but anyone who breaks away from the pack becomes unreachable and hence unbeatable, irrespective of its quality.

Very similar is the case with cryptocurrency. Just as the internet was designed to democratise the distribution of information, Bitcoin was designed by the mysterious libertarian Satoshi Nakamoto as a way to create and distribute monetary value in a decentralised manner. Thanks to the magic of mathematics, it was now possible for a private citizen to do what was earlier the prerogative of Central Banks, namely create a cross-border, tradeable currency. It is a different matter that many governments and central banks have gone hammer and tongs to break the backbone of this remarkable technology. The methods being used are obviously inappropriate -- similar to the case of censors in Iran and China blocking the internet -- but the fact remains that “Tiger Zinda Hai”. Cryptocurrencies have weathered most regulatory storms and despite some current setbacks will certainly comeback when the establishment finally gives up and falls in line. But the dream of citizen empowerment is a myth. Even though anyone can, in principle, create Bitcoins, and similar cryptocurrency, the ownership of such wealth is hugely skewed. 87% of all Bitcoins that have been mined are owned by 0.5% owners or wallets, 61% are owned by just 0.07% wallets. Of the 23 million Bitcoin wallets, 13 million own a fraction, less than one, Bitcoin.  1500 wallets have between 1000 and 10,000 coins while 111 wallets own more than 10,000. [ March 2018 data ] For a system that is barely a decade old, that is a huge inequality that has emerged from what was supposed to be purely technology based egalitarian platform.

This inequality of wealth in Bitcoin is very similar to the inequality of wealth seen across the world and more so in the mature economies. In the United States, that is seen by many as a leitmotif for the modern economy, wealth inequality is enormous. Those who view this as an inevitable fallout of ‘evil’ capitalism should look back at what Communist Russia once was and read Orwell’s Animal Farm where all animals were equal but some animals, the pigs, were more equal than others. Today there is no visible and viable to alternative because what happens in China is not clearly visible and socialist countries like Venezuela have either collapsed or like Italy and France are tottering as they try to redistribute their shrinking wealth. Some diehards like Bernie Sanders may hark back to a Scandinavian utopia but that story may not really be as attractive as it is portrayed to be and moreover it is certainly not scalable beyond the socio-economic demographics of Northern Europe.

Which begs the question, is inequality inevitable?

One way to look at it is to note the difference between opportunity and outcome. Equality of opportunity is essential but it may or may not lead to an equality of outcome. Google may have bowed to political correctness by sacking James Damore for daring to suggest that women may be different from men, but facts do bear him out. As Jordan Peterson, that arch nemesis for page three feminists and their ilk, has pointed out, the eventual outcome is a function of a complex series of inputs, not just the obvious differences of say gender or race. It is well known that women are underrepresented in STEM -- science, technology, engineering and mathematics. What is less well known that societies that have a higher degree of gender equality have, paradoxically, a lesser percentage of women in STEM than those societies that offer lower opportunities to women. [ The Atlantic, Olga Khazan, April 2018] This has been explained by arguing that women in societies that marginalize them see STEM as a way to climb their way out into better opportunities in life, which is something that their sisters in more equitable societies do not have to struggle so much for. In a similar vein, while women may be underrepresented in engineering colleges and in IT companies,  the percentage of seats occupied by women in medical colleges is more than 51% in India but in neighbouring Pakistan and Bangladesh, the numbers are as high as 70% and 60% respectively. Clearly, inequality is not something that can be explained very easily.

In India, social inequality is frequently equated with caste. This has led us to build a huge edifice of largely ineffective and useless hubris around caste based reservations to pander to our politicians craving for votebanks. While caste is something thing that has existed in India, our politically tainted educational system has been instrumental in making us believe that it is the ONLY cause of economic inequality and misery in India. In the process we have only succeeded in sharpening the inequality with indiscriminate reservations. Caste is the unfortunate fall guy where the real reason could be something far different.

In fact, in a study reported in Vox, researchers Barone and Mocetti were the first to establish that in Florence, Italy -- where there is no caste system -- the highest paying taxpayers from the 15th century to the present have been from the same set of families. Similar studies have shown remarkably similar results in a wide range of cultures -- “This is true in Sweden, a social welfare state; England, where industrial capitalism was born; the United States, one of the most heterogeneous societies in history; and India, a fairly new democracy hobbled by the legacy of caste.” [ New York Times, Your Ancestors, Your Fate, Gregory Clark, Feb 2014] What could explain this phenomenon? The authors suggest that “the compulsion to strive, the talent to prosper and the ability to overcome failure” that are all strongly correlated to success and hence eventual wealth are inherited qualities. Hence, as heretical as it may seem, genetics plays a role and “Alternative explanations that are in vogue — cultural traits, family economic resources, social networks — don’t hold up to scrutiny.”

A more politically palatable, or charitable, explanation could be the network effect that we have seen in the case of the world wide web. On the web, companies like Google and Facebook use their pre-eminence in the number of clients and customers to prolong and propagate their pre-eminence. Similarly, in human society, those who are, let us say, eminent -- in money, power, education, intelligence, contacts -- will use their eminence to make sure that their progeny get access to all that is required to become eminent in the next generation. There may be individual exceptions but by and large, that will be the desire in almost all cases. In the long run, this desire will translate into a self propagating mechanism that will ensure that inequalities inherent to society cannot be erased simply by desire or dictat.

If the inequality is somehow removed, it will always find ways to creep in. In India, we recognise this in the replacement of an exploitative foreign coloniser by an equally exploitative but local political class that has taken over the trappings of the foreigner. Subhayan Mukerjee, a researcher in Computational Social Science at the University of Pennsylvania explains this by saying that equality is an unsustainable, unstable equilibrium and cannot last very long. Sooner or later, this equilibrium will be broken and the collective will move towards a stable but hierarchical structure. The resultant inequality will pave the way for even more inequality.  If we view the collective as a set of marbles lying on an elastic membrane that is stretched flat where each marble makes an identical depression, then a single slightly larger marble will create a little larger depression. This will draw in other marbles making the depression deeper. Now the unstable equilibrium will be broken as the deeper depression pulls in more and more marbles making it deeper and deeper until most of the marbles have moved into it.

Both the world wide web and world of cryptocurrency began as a flat world of equals without any hierarchy but it did not take long to for inequality to creep in and a hierarchy to establish itself. Even in the animal world, for example, among apes, there is inequality in the form of size, strength, potency and skill. Even if humans inherited these inequalities the world might still have been more egalitarian and equitable simply because there were too few opportunities for enrichment. But the potential was always there and the moment economic opportunities presented themselves -- with the advent first, of agriculture, then industry and currently the digital age -- the natural tendency towards the equilibrium of a new and sharper inequality began until we have what we have today. At best, humans may recognise the inequality, and unlike a pack of animals may try to mitigate it with, say, mechanisms like social security. But in the long run, the outcome is rarely what we desire -- the rich remain rich or become richer while the common man stays where he was, at the bottom of a hierarchy.

We may ardently believe and proclaim that all men (and women) are equal but that is simply not enough. Egalitarians, if not actual practicing socialists, may work out a myriad rules and regulations that seek to curb inequality but nature is such that people and organisations will always find loopholes and ways to beat the system. In the end we will always tend towards the stability of an unequal world!

Perhaps that is how it is meant to be. Could it be that equality is against nature? Take a look at the palm of your hand -- are all the fingers identical or equal? And would we be where we are if they all were the same?

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This article first appeared in Swarajya magazine

AI://games.wargames:war

In popular perception, skill in cerebral games board, like chess, are assumed to be a proxy for or measure of intelligence. This perception has motivated people to build computer programs that can play these games in an effort to make programs look intelligent or behave intelligently. But the reality is different. The complexity of decision making that a child, or even a dog, demonstrates while crossing a busy road is several orders of magnitude higher than what a grandmaster uses to win a game of chess. But because the act of crossing a road is something that we do every day we feel that it is somewhat trivial when compared to playing chess. Nevertheless  Artificial Intelligence (AI) research has enthusiastically used games as a testbed to try out more and more complex tasks that they would like computers to perform.

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Programming a computer to play chess has been an obsession with many of the key personalities from the world of theoretical computer science. Norbert Wiener, who coined the word cybernetics, the science of information and control in both humans and machines, was the first to design a program that should be able to play chess way back in 1948. Claude Shannon  and Alan Turing, the so-called ‘father’s of information theory and computer science respectively, were both very actively involved in designing and building chess programs though their initial efforts were not very successful. With the passage of time, these programs became more sophisticated until in 1997, the Deep Blue program from IBM managed to beat Gary Kasparov, the World (Human) Champion. Since then, these programs have improved constantly and the current World (Computer) Champion is a program called Komodo that has an ELO ranking of ~ 3300 which is more than 450 points higher than the current World (Human) Champion Magnus Carlsen.

Bridge, on the other hand, is a game where computer programs have had rather limited success. While bridge playing programs do exist and can indeed defeat most amateur players, they are yet to win against the world champions. The reason for this lack of success vis-a-vis chess can be explained in two ways. First, unlike chess where the entire board is visible, bridge is played with incomplete information because any player can see the cards in only two hands, his own and that of the dummy. But the second and perhaps more important reason is that unlike the rigorous and near brute force approach of “looking ahead” into many possible moves, bridge involves a lot of intangible psychology - of feinting, of deception and the need to anticipate the same in an intuitive manner. To put it bluntly, it is possible to determine nearly all possible moves and countermoves in chess and choose the one that works best but there is no easy way to enumerate, and hence evaluate, all possible future moves in bridge.

Game playing programs were stuck in this rut for a very long time until the arrival of the artificial neural network (ANN) based programs like Google DeepMind. ANNs are not really programmed in the classical sense of computer programming where a human programmer specifies what all needs to be done and when. Instead, ANNs are designed to “learn” on their own by taking certain actions and then detecting whether that action leads to success or failure of the overall goal. The “learning” process involves changing -- either increasing or decreasing -- the numerical values of certain parameters, called weights and biases, over successive iterations in a way that gradually increases the the possibility of a success. What is interesting in all such cases is that there is no clear explanation about why a particular value of a specific parameter results in success. It is just that a certain set of values leads to success while any deviation leads to failure. This is very similar to the intuitive approach that many humans take while making decisions that they otherwise cannot explain. Success of course can be defined in many ways -- from recognising an image of a person, navigating a car around an obstacle, or in our case, winning a game of chess. This technology -- based on the backpropagation algorithm and the gradient descent method --  was an astonishing force multiplier that propelled computer programs to new heights. While bridge was somehow never quite in the radar of the ANN enthusiasts, games like Go, which are orders of magnitude more complex than chess, have been cracked. Google DeepMind’s AlphaGo program beats the best human challengers on a consistent basis. But what is really startling is that the best players have admitted that AlphaGo’s style of play is so unusual that it seems to have developed strategies that no human has ever used or even thought of before. So it is not that it has been taught by, or has learnt from, any human being. It is in fact creating new knowledge or strategies on its own without human assistance.

Traditional ANN technology is based on feeding past data and expecting the computer to learn from successes and failures. This is possible when you have lots of past data and the computing power to crunch through the same. A variation to this strategy is to make the machine observe actual human behaviour -- as in driving a car or playing a game -- and from there ‘magically’ learn how to behave in a manner that leads to success. But AlphaGo and similar programs use a variation of the standard ANN called Generative Adversarial Networks (GAN) where the program fights, or competes, with its own “brother”, a clone or copy of itself, and by recording the success or failure, learns by itself when it has been successful or has failed. By challenging it’s own copy, it builds up its own training data and learns from this at a speed that is humanly impossible. This allows the program to venture into more and more interesting tasks. Just as in the case of new styles for playing Go, GAN based machines have trained themselves to create artificial images of human faces that are indistinguishable from actual photographs of real people.

As we have noted earlier, the ability to play a board game, however complex may be viewed as a proxy for human intelligence but in reality, true intelligence lies in doing apparently simple daily tasks like crossing a busy street or in haggling with a roadside hawker. Here success lies in reaching the other side of the road within a reasonable time without being hit by a car or to convince another person to part with a product at a lower price. Here again, we can have ANN/GANs being trained for success but the difficulty lies in creating a learning environment where the system can train itself. Unlike board games, we cannot have half trained machines running amok on real roads or bargain with real shopkeepers. But if we cannot have real environments, can we look for virtual ones?

Enter strategy games! Arcade style video games have been around since the 1970s when the first such game, Computer Space, was launched in 1971. This was followed by the commercial release of Atari’s Pong. From these humble beginnings, the computer gaming industry has now become a US$ 140 billion business that is far larger than the global movie business. In fact the top selling game Call of Duty : Black Ops collected an incredible US$ 650 million in five days after its launch, which is a record for any book, movie or game. In all these games, the human player has a quest, or a challenge that increase in complexity like acquiring resources -- firewood, gold, weapons, land, territory, soldiers -- and this quest is obstructed or sought to be foiled by other human players or by specifically designed computer programs that put hurdles in the way. Since these games are generally played online, hundreds of players log in and participate through avatars -- realistic or fantasy representations of themselves -- that they control. These Massively Multi-user Online Role Playing Games ( MMORPG) could be very realistic representations of actual reality, as in World War II battlefields or well known urban locations, or can be played out in fantasy sci-fi locations in deep space or in ancient Jurassic parks. But irrespective of the location where these games are set, what really matters is that players, or combatants, are humans who use every possible trick, guile and deception to beat other players so as to achieve success in their respective goals. In fact, most games allow players to create teams, build coalitions and join guilds to improve their chances of success. Playing these games brings one quite close to operating within a community of intelligent individuals, because as explained by James Vincent in the Verge “Although video games lack the intellectual reputation of Go and chess, they’re actually much harder for computers to play. They withhold information from players; take place in complex, ever-changing environments; and require the sort of strategic thinking that can’t be easily simulated. In other words, they’re closer to the sorts of problems we want AI to tackle in real life.”

After chewing through human champions in  chess and Go, and ignoring bridge for the time being, computer AI has now set its targets on these online games and the results are just as startling. Dota 2 is an online multiplayer battle arena, a derivative of the wildly successful Warcraft, where players form five member teams to occupy and defend territory on a map. Elon Musk’s OpenAI team has been working to build AI systems that can play -- or rather simulate a human player -- against the usual human teams and on more occasions than one have successfully beaten humans. In January 2019, AI crossed another milestone when Google’s DeepMind learnt how to play Starcraft II and beat two very highly ranked professional human gamers. Starcraft II is a science fiction, real-time strategy game where three species -- humans and two others with many kinds of natural and supernatural powers -- battle it out to create bases, build teams, invade other’s territory and eventually establish their dominion across the galaxy. AlphaStar, the AI program that ‘plays’ Starcraft is based on the principles of Reinforcement Learning where it begins as a novice playing randomly and then builds up expertise by observing the outcome. Since no human would ever have the physical stamina to play with an AI, AlphaStar generally plays with multiple copies of itself and hence can learn and build expertise at a speed that is impossible for humans.

Games like Dota 2, Starcraft II, Call of Duty and the current favourite shooter game PUBG are, at the end of the day, harmless. You can shoot, maim and kill your enemy as much as you like in the game but when you shutdown the game, you are back to your mundane world of home and work that was temporarily suspended while you battled with hostile adversaries. There is no physical touch point between your actions on the keyboard and the world of brick and mortar. But what if there was? What if you were a drone operator sitting in front of a computer screen and controlling, not just a fantastical beast in a fantasy terrain, but an armed drone flying across Afghanistan or even along the LoC in Kashmir? Or what if you were controlling a team of armed semi-autonomous vehicles that are tasked to cross the LoC and perform a surgical strike on terrorist camps in PoK? Operating an armed drone or autonomous vehicle on the ground is not really different, conceptually and qualitatively,  from what human players are  do, both tactically and strategically, in combat games like Dota and StarCraft. So after AlphaGo and AlphaStar -- the AI programs that beat humans in Go and StarCraft -- will there be an AlphaWar that can beat any human operator in a real war that spills real blood and blows up real buildings? Why not? We could have  a fleet of AI controlled armed drones relentless flying over the LoC in Kashmir, observing the terrain and remorselessly killing anyone that looks or behaves like a terrorist while ignoring civilians -- just as it is done in so many popular first person shooter games like Doom or PUBG. And of course we could live with some collateral damage!

Much as society would like it to, science and technology never waits for ethics to catch up with its own progress -- as in the case of He Jiankui, the Chinese scientist who broke state laws to create genetically edited human babies with the CRISPR. Asimov’s First Law of Robotics that mandates that robots will not harm humans, is good science fiction but will not stand the test of ground reality. Given the proliferation of war and conflict themed games and the ability for AI systems to learn from them, it is matter of time before they acquire the capability to wage real war. We may argue that the actual instruments of war, for example armed drones, are not connected to the AI systems but that is obviously a transient problem. Access to and connectivity across multiple computers -- from gaming consoles to armed drones -- is a matter of policy and behaviour and not just technology. Given time patience  and computing power any computer can be hacked. In principle, one could hack into any military computers that control the war machines and since hacking is essentially a matter of strategy and guile, there is no reason why an AI system cannot be taught to do so or, as is more likely, learn on its own -- if that is a goal that “it” is directed to achieve.

Now that AI systems will have the ability to wage war, who will direct them to actually do so? And against whom?  Or, and this could be ominous, will “they” decide whether they will do so or not? That is where the programmer stops and the psychologist, the philosopher and the politician must take over to first understand this technology and then to divine or to define the trajectory that it would follow in the near future.

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this article first appeared in Swarajya magazine

Kailash Manasarovar 2018 Slide Show

The Vedantin looks at Cloud Robotics

In 2006-2007, in the early years of the Web 2.0 that emerged phoenix like from the ashes of the dotcom bust of 2000, Michael Wesch, Professor of Digital Ethnography at Kansas State University produced a video called “The Machine is Us/ing Us”. Prior to the emergence of Web 2.0, the world wide web was primarily a read-only medium to publish news and information to a passive audience. Web 2.0, with its focus on user generated content and a personal network of trust, created a read-write platform that allowed individuals to feed information easily into the system or “The Machine”. In the process The Machine learnt stuff that it never knew before. Wikipedia, one of the first Web 2.0 platforms, became the biggest repository of information, if not knowledge. This in turn allowed it influence a whole generation of students, journalists and web user, and shape the way they view the world. For example, this author who has studied in a Catholic missionary school, had had a great regard for Francis Xavier. But this was completely reversed after he read the Wikipedia article about the murderous Inquisition that Xavier had unleashed on the Hindus of Goa. Obviously, no one at school had ever talked about such unsavoury matters.

image from https://blogs.oracle.com/

The thrust of the Wesch video was that every action that a person takes in the digital world is used as an input by “The digital Machine” to increase its own knowledge of both the physical world and recursively, about the digital world. Every “like” of a post on social media or a click on hyperlink on a web page or a mobile app is like a drop of information that individually and collectively adds to the pool of knowledge about what humans know and think. This in turn is used to shape our own world view by returning recommendations of what next to view, “like” and click again. Unless you are like Richard Stallman, an advocate of extreme privacy who hardly uses anything digital -- like Google search, cellphones or credit cards -- you have no escape from this tight embrace of The Machine. Fortunately, The Machine is not yet one monolithic device. It’s world of has been broken up into fragments -- Google, Baidu, Amazon, Alibaba, Facebook --  by high commercial walls. But in its tireless striving it certainly does stretch its arms into every nook and corner of human activity and through that, the human mind.

In parallel with the growth of the web, there has been the emergence of data science. This began as an extension of statistics and has evolved into machine learning. Then again there was classical, 1960s style artificial intelligence that, after lying dormant for nearly 30 years, suddenly woke up and  adopted the neural network structure of the brain as a new model of machine learning. This neural network model, often referred to as deep learning is the new age AI and it is racing forward with some truly stunning applications in the area of voice and image recognition, language translation, guidance and control of autonomous vehicles and in decision making as in loan disbursement and hiring of employees.

Data science has moved through three distinct stages of being descriptive -- reporting data, inferential --  drawing conclusions from data through the acceptance or rejection of hypotheses and finally predictive -- as in the new age AI. What has really accelerated the adoption and usage of this new AI has been the availability of data and hardware. The backpropagation algorithm that lies at the heart of all neural network based AI systems that are popular today was developed in the 1960s and 1970s but it has become useful only in the last decade. It is driven by the availability of (a) huge amounts of data, collectable and collected through the web by The Machine described in the Wesch video and (b) enormous yet inexpensive computing power that is available on rentable virtual machines from cloud service providers like Amazon Web Services, Google Compute Engine and Microsoft Azure.

The key driver in this field is cloud computing. Instead of purchasing and installing physical hardware, companies rent virtual machines in the cloud to both store and process data. The simplest and most ubiquitous example of this is Gmail where both our mail and the mail server are located somewhere in the internet cloud that we can access with a browser. But this same model has been used for many mission-critical, corporate applications ranging from e-commerce through enterprise resource planning to supply chain and customer relationship management systems. Though there has been some resistance to cloud computing because of the insecurity of  placing sensitive company data on a vendor machine, the price performance is so advantageous that most new software services are all deployed in the cloud -- and that includes machine learning and AI applications.

Cloud service vendors have aggressively marketed their services by not only offering high end hardware -- as virtual machines -- at very low prices but also by offering incredibly powerful software applications. Complex machine learning software for, say, image recognition, language translation that are ordinarily very difficult to develop are now available and accessible almost as easily as email or social media. Cloud computing services are categorised into Platform-as-a-Service (PaaS) or Software-as-a-Service (SaaS). The first category provides a general purpose computing platform with a virtual machine, an operating system, programming languages and database services where developers can build and deploy applications without purchasing any hardware. The second category is even simpler to use because the software -- like email as in the case of Gmail -- is already there. One needs to subscribe (or purchase) the service, obtain the access credentials, like userid and password, connect and start using the services right away. Nothing to build or deploy. It is already there waiting to be used.

In an earlier article in Swarajya ( March 2017), we had seen how machine learning and now, the new age AI, uses huge, terabyte size, sets of training data to create software models than can be used for predictive analytics. This is an expensive exercise that lies beyond the ability of individuals and most corporates. But with AI or machine learning available as SaaS at a fraction of the cost, new software application that use these services can be built easily. For example it would be possible to enhance a widely used accounting software by replacing the userid/password based login process with a face recognition based login process. Similarly, the enormous difficulty of building the software for a self driving car, or for a voice activated IVR telephony, can be drastically reduced by using AI-as-a-Service from a cloud services vendor. Obviously, all cloud services including SaaS assume the existence of rugged, reliable and high speed data connectivity between the service provider and the device on which the service is being used.

Robot-as-a-Service (RaaS) can be seen as logical extension of this model but a closer examination may yield a far deeper, or intriguing, insight.

Cloud Robotics, a new service from Google is scheduled to go live in 2019 and allow people to build smart robots very easily. It is inevitable that other cloud service vendors will follow suit. While many of us view robots as humanoids -- with arms, legs, glowing eyes, a squeaky voice or a stiff gait -- the reality is generally different. Depending on the intended use, a robot could be a vehicle, a drone, an arm in an automated assembly line or a device that controls valves, switches and levers in an industrial environment. In fact, a robot is anything that can sense its environment and take steps to do whatever it takes to achieve its goals. This is precisely the definition of intelligence or more specifically artificial intelligence (AI). So a robot is an intelligent machine that can operate autonomously to meet its goals.

Traditional robots have this intelligence baked, or hard coded, into its “brain” -- the physical computer that senses and responds to the stimuli that it receives from its environment. This is no different from its immediate role model -- humans. Human beings, and even most animals, learn how to react and respond to external stimuli ranging from a physical attack to a gentle question and we estimate this intelligence by the quality of their response. In both cases, the knowledge of the external world as encoded in a model along with the ability to respond is stored locally -- either in the human brain or in the local computer. Cloud robotics replaces the local computer that controls a single robot with a shared computer -- located at the cloud services provider’s premises -- that controls  thousands of robots. Just as GMail servers store, serve and otherwise control the mailboxes for millions of users each sitting at home, the cloud robotics servers sitting in some unknown corner of the internet would be able to control millions of intelligent robots that are driving vehicles, flying drones, controlling devices and operating machines in farms, factories, mines and construction sites across the digitally connected physical world.

Circling back to the Wesch video, with which we began this article, these RaaS servers would not just be controlling machinery across the globe but would also be learning from the robots that it controls by using the robots to collect and build up its own pool of training data. This is an extension of the original Web 2.0 idea -- perhaps we could call it Web 3.0. Here The Machine has not only made a successful transition from the digital to the physical world but also does not need humans anymore to teach it. It can become a self sustaining, self learning physical device.

Privacy would be an immediate issue and like all other cloud services, cloud robotics would be protected with access control and data encryption. But then as we have seen in the past, convenience trumps privacy. We all know that Google can read our GMail but nevertheless, we still use Gmail simply because it is convenient and free! So would be the case with cloud robotics. We also know that the different RaaS vendors would try to isolate their own robots from interacting with the servers of other vendors or even from each other. But this could be a temporary reprieve. Collaboration among various vendors and pooling of data could happen either through mergers and acquisitions or because it is mandated by governments that are not concerned about privacy issues.

The need for privacy arises because each sentient human sees itself as a unique identity -- I, me and mine -- that is surely distinct from the collective crowd. My data becomes private because it needs to be protected, or shielded, from the collective crowd. But if we go back to the philosophical roots of the Indic sanatan dharma and explore the perspectives of Advaita Vedanta, we see that that this sense of “I” ness is erroneous. Each apparently unique individual is actually a part of a transcendent and collective consciousness referred to as the Brahman. The Brahman is the only reality and everything else is an error of perception. The world is Maya, an illusion that perpetuates this sense of separateness, and creates this distinction between the individual and the universal. The correct practice of Yoga can lead to the removal of this veil of illusion and initiates the process of realisation. That is when the Yogic adept sees the unbroken continuity between his own identity and that of the Brahman and experiences the ecstasy of enlightenment.

We know that many renowned Yogis have actually experienced this enlightenment. AI products have now gone well past image and voice recognition and are now known to have the sophistication necessary to create their own private, non-human languages and original strategies in multi-user, role playing games. What we need to know is what happens when robots start emulating yogis and eventually realise their  identity with the cloud robotics server of which they are a part!

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this article was originally published in Swarajya

Social Credit : What China does today ...

Credit rating is a big business. Thanks to companies like CRISIL and  ICRA and the research they do into the finances of companies, bond investors get an independent view of a company’s financial status. Then they can take a call on whether they should invest or not. At a personal level, the CIBIL score is a relatively new product in India and its value is used as a benchmark by financial institutions to determine whether an individual qualifies for a personal loan and if so for what amount. In all cases, the financial credit score, whether personal or institutional, is the primary determinant for access to loans or financial credit and by extension, to goods and services that are available on credit. In India, these extensions may not be evident but in the US and other financially mature societies, the financial credit score is used to allow or deny telephone connections or even rental of residential apartments. The utility of the financial credit score is well understood and it is generally accepted as a useful tool to ensure safety and stability in a financial ecosystem.

China has taken this concept and is planning to extend it to the social domain. By defining a metric called social credit and determining it’s numeric value for each citizen, it seeks to create a new tool that will ensure a safe and stable social and political system. Or will it create a high tech, low life, cyberpunk dystopia? This article explores this idea and speculates on how it may or may not be used in other countries, including India.

The financial credit score for an individual is calculated, or built up, with information about the individual that is available with the participants in the financial ecosystem and which they are willing to share without compromising the privacy of the individual. Generally, assets like income stream, home value, bank balance are private but information on liabilities like loans -- secured, as in car and home loans and unsecured, as in personal or credit card -- that are sanctioned along with a history of utilisation and repayment are available with credit rating agencies. The key determinant in this case is behaviour. While ability to repay a loan is certainly important, what is perhaps more important is the willingness to repay. This behavioural trait is measured and quantified by keeping track of actions that can be used as a proxy for the corresponding behavioural traits. For example, if a person has taken loans in the past, there is a behavioural pattern -- of repayment, or lack thereof -- that can be used as a proxy. Not having taken a loan means that there is no observable behavioural pattern to go with.

In 2014, the Chinese government operating through the State Council defined the architecture of a new national social credit system. Designed as an extension of the well known financial credit system, it will begin as any normal credit scoring system that will assess the creditworthiness of businesses operating in China but then it will go far beyond recording just financial behaviour. Though it is not very clear how non-financial behaviour will actually be recorded, there are pointers that some very sophisticated tools from the world of data science and artificial intelligence will be used to collect, collate and interpret digital data that may exist with one or more government agencies and private companies.

“Big Data” techniques are already used by search engines like Google, Baidu, social media firms like Twitter, Weibo, and eCommerce sites like Amazon, Alibaba to gather vast amount of data on what people search for, talk about and purchase. In western societies, concerns about privacy and legislation limit the amount of that can be collected or the way that this can be used by government agencies. In China, where national security and the need to maintain social order overrides any concerns about privacy, this kind of data will be readily -- if not compulsorily -- available. Hence the Chinese government will have a fairly detailed view, not just into the buying patterns of its citizens, but also into what they are thinking and talking about. This obviously means that any kind of behaviour that threatens national security or social order -- an euphemism for anti-government behaviour -- will be detected with relative ease.

But even this is not enough. Anyone who has been to China would have noticed the large number of CCTV cameras that are deployed not just in public and private buildings but also on roads. Using facial recognition and vehicle number plate reading technology it is very much possible to track the actual physical movement of individuals and the vehicles registered in their name across any part of the country. All it needs is to collect the digital imagery from thousands of cameras and run them through a centralized system, neither of which is difficult with the technology that is readily available today.

Some of the data that is gathered and the use to which it is put is sometimes funny, though occasionally useful. For example, time spent on online gaming ( and perhaps on pornography, though this is not stated as such) is tracked and if it is excessive then the social credit score gets reduced. People on matrimonial or dating sites are encouraged to display their social credit score, along with their other characteristics, as this is expected to ensure social compatibility of partners! Similarly hospitals are being encouraged to ask patients for their social credit score and offer preferential services to those whose scores are high.

The financial credit score, like CIBIL, determines  access to loans. So a bad financial credit score means that one cannot get loans or the interest charged on loans is high. China’s social credit score mechanism takes this to the next level by placing similar restrictions on access to other services. Some of these restrictions could seem logical, as in denying access to the best schools and colleges to children of parents who have low social credit. What is more troublesome is the restriction on travel implemented by creating a no-fly no-train ( or no-travel)  list of people who are not allowed to purchase train or airline tickets for themselves. This means that in one shot, people whom the government deem to be troublemakers are now physically restrained from leaving their residential neighbourhood and participate in any troublesome activity. Forget about guns and bombs, the person cannot even travel to the capital and meet with fellow activists there. This is like a house arrest, or in this case, a neighbourhood arrest.

This no-travel scenario is not from a hypothetical cyberpunk novel. The system has become operational from March 2018 when and by May 2018 the process of denial of air and train tickets has been implemented. It is reported that nearly 10 million people were not allowed to buy airline or high-speed train tickets. The reason for denial of tickets is not very clear and it seems that at the moment,  most of the people on the no-travel list are debtors with bad history of repayment. But as is evident, it would be very easy to extend the same no-travel list to include people with low social credit as well.

One challenge with the current Chinese system is that unlike financial credit, the basis of determining social credit is not clearly known. The definition of good and bad behaviour is still ill-defined and there is no clear explanation about which all entities are contributing data. Nor is there any mechanism to question the validity of a social credit score or appeal against a low score.

Is such pervasive surveillance possible? Certainly yes.  We -- not just China but every country -- have the technology to make it happen. A combination of data science and artificial intelligence along with free and open source tools to use them is readily available to anyone who wants to do so.

Is such pervasive surveillance permissible? This is where the issues become murky and questions become difficult to answer. If you subscribe to the Western ideals of liberalism, individualism and social contract articulated by philosophers like Locke and Rousseau, then such surveillance and the subsequent restrictions are unacceptable. But if you were to subscribe to the philosophy of Confucius who believed that disorder and chaos is the biggest hindrance to peace, prosperity and happiness and that the average person does not have ability to make important decisions, then the surveillance and restrictions suddenly make a lot of sense. In China, obviously, they believe more in Confucius than in Rousseau and hence there is little known objection to this new concept of social credit. But then what happens behind the Bamboo Curtain is something that is difficult for us to know.

Where does India figure in all this?

Unfortunately, or perhaps fortunately, India is a country of inertia and momentum. Nothing changes easily and if anyone tries to change anything, there is always a tremendous opposition. Plus we have politicians who will oppose anything that is proposed by the government. We have three ways to tag, and track, individuals, namely, the Voter Card issued by the Election Commission, the PAN  issued by the Income Tax department and finally Aadhar from UIDAI. The Voter Card number is of little use in tracking anything beyond the polling booth because it is neither standardised nor is there a central searchable repository. The PAN is somewhat more useful because its disclosure is now mandatory in all high value monetary transactions and so it is possible to link large movements of money to specific individuals. Recently, the income tax department has mooted a proposal in which regular tax-payers, that is those with the correct tax related behaviour, would be eligible for special privileges at toll roads, airports and government offices. In a sense, this is like the reported usage of social credit in Chinese hospitals.  Aadhar -- as a unique identity -- could have been used to track a person’s behaviour across different types of platforms and processes but the Supreme Court has ruled that it can only be used for its original purpose, namely, to track disbursal of government subsidies to specific targets. Hence it appears that such pervasive surveillance may seem to be difficult in India. However with the rapid advancement of technology that can connect individuals to their actions as recorded in their digital footprint,  the possibility of perpetual and pervasive surveillance will never go away -- even if we were restrict or eliminate Aadhar. In the digital world, you can run -- or click --  but you can never ever hide!

What China is overtly doing today with their social credit mechanism is something that, in a sense, is already being done covertly by companies and governments in many other countries. Going forward, such surveillance may become as common and as acceptable as body searches at airports and car searches at hotels that we have agreed to submit to in the interests of personal safety. A powerful convergence of commercial and political interests will ensure that privacy will eventually become a myth and any attempt to push back against the use of surveillance technology and the consequent the loss of privacy will be as futile as trying to hold back the tide on the seashore. The best that we can hope for is that this loss of privacy does not lead to an automatic degradation in the quality of personal and social life.

This kind of a dystopian future is frequently envisaged cyberpunk scenarios. The NeonDystopia website describes “Cyberpunk [as] both a culture and a genre. Cyberpunk is a sub-genre of science fiction that features advanced science and technology in an urban, dystopian future.  On one side you have powerful mega-corporations and private security forces, and on the other you have the dark and gritty underworld of illegal trade, gangs, drugs, and vice.  In between all of this is politics, corruption, and social upheaval.”

Human society today is caught on the horns of a dilemma. Technology, economics and politics has created a powerful vortex that makes it very difficult to steer a course away from this cyberpunk dystopia without abandoning technology and regressing into primitive medievalism. While scientists, both physical and social, grapple with these issues, the anodyne perhaps could lie, not in Rousseau or Confucius, but in the Non-Dual Advaita of Sankara that sees a primordial unity across all sentience. Perhaps this utopian scenario would blur the borders between individual identities and lead to the irrelevance of the idea of privacy.

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this article first appeared in Swarajya

Corporate Management Practices in Public Sector Institutes

The policy of the Government to identify and support Institutes of Eminence has generated controversy because of the inclusion of the green field Jio Institute in a group that includes the IITs. Whether the inclusion of Jio is correct or not may be debated elsewhere but let us first ask whether the IITs themselves -- and similar public sector Institutes like the IIMs, IISc, IISER and others -- deserve the “eminent” tag. Within India of course, their stature and allure is beyond question but one wonders if in the land of the blind the a one-eyed man has become the king!

copyright free image from https://pxhere.com/en/photo/1448079

University rankings can of course be subjective and one may argue that our institutes serve a social purpose. However that is a fig-leaf that cannot hide the grim reality that shows up in the Times Higher Education Ranking of Engineering Schools, where IIT Bombay at rank 350+ is the highest ranked Indian school. Another, reasonably well-regarded, QS World Universities Rankings, is a little less embarrassing for India because we open our account there with IIT Delhi at 172. Let us admit that irrespective of  how much we quibble and wave our hands, our Institutes of Eminence are nowhere the top of the global pecking order.

Which is not only unfortunate but very strange as well. People from India, whether graduates from these IITs or not, are found in significant numbers in almost every school that has a rank higher than the Indian schools. This means that it is not the quality of people that is at fault but something else.

An obvious cause could be lack of money. Most top ranking schools have access to funds that are far higher than what is available to IITs, but again this is a red-herring that is often used to divert attention from deeper issues. Money is not really an issue because of two reasons. First, the primary use of money, is and should be payment to faculty and in India faculty pay is calibrated with the local economy. So faculty does not need a dollar denominated salary just as no corporate manager in India expects anything like what their equivalents get in wealthier economies. The second need for money is in laboratories and equipment. This is true for only certain areas like, say physics, astronomy or quantum computing. But today, a vast range of research in say, computer science or biotechnology can be done with investments that are almost within the affordability of individual “hackers” and certainly within the budget of most Indian universities. So lack of money is a really bad excuse for our poor rankings.

Outside academia, the situation in the corporate sector is not so pathetic. While we certainly do not have a Google, Tesla or Arm (that makes chips for most of the smartphones on the planet)  as yet, our corporates like TCS, Tata Steel, HUL, ITC, Airtel, HDFC are quite comparable to global companies that are in the same line of business. Not perhaps in absolute revenue but certainly in the kind of work they do -- excluding R&D of course -- and with the efficiency with which they operate. Which is why many of them can compete and win in global markets against global brands.

Management Structures & Systems

This means that the weakness is in the management process. Family owned Lala-ji companies cannot compete in the global market even though they may have the cheapest labour or raw materials. What we need is a professional management structures and processes and this is what is sorely missing in our Indian institutes that, despite protestations to the contrary, are lala-ji operations led by a Director and his favourite Deans. Even if we leave aside the process of appointment of a Director, which is nowhere as objective as it should be, the fact that he operates with all authority and little accountability -- except at an aggregate financial level -- means that management processes are absent. The institutes are run in an ad-hoc manner, but being a government agency, this ad-hocism is tied up in the longest and messiest red-tape of sarkari bureaucracy. So the real problem is the poor state of the underlying management and administrative mechanism. Given the rigid, anachronistic and inefficient processes under which they operate,  it is no wonder that these institutes have no chance of competing with world class institutions in other countries.

But instead of simply criticizing the administration, let us see which areas need improvement and how we could about rectifying it -

1. Human resources : We take it for granted that competent people will leave lucrative corporate careers and join public sector institutes at government salaries but in reality this never happens. As a result we have a majority of employees -- both faculty and staff -- who are there as a necessity and not out of choice! This is tragic because we would want the best people to be here. Obviously salaries cannot be hiked across the board. Instead we must have a well designed HR mechanism that seeks out competent people, induces them to join our institutes, help them manage both their careers and their personal life ( especially spouse employment in remote locations)  and ensure that they are well looked after in terms of accommodation and other perks. In parallel there must be an annual performance appraisal that rewards good work and punishes the laggards. In short we need an active HR function and a corporate style Compensation and Benefits policy that is significantly different from the take-it-or-leave-it, one-size-fits-all salary structure that is doled out by the latest Pay Commission.

2. Financial Accounting : Most public sector institutes have very weak financial management systems and there is no clarity on where the money is being spent. There is clearly no shortage of money and while there may not be blatant theft, a lot of money is diverted to unnecessary uses like civil construction that benefits contractors, not students or faculty. The large granularity at which expenses are tracked results in a lack of transparency in the usage of funds. A simple enforcement of the generally accepted accounting principles that mandate a highly granular set of cost codes and charge accounts followed by a thorough statutory audit would easily unearth vast amounts of ill-spent money that can be diverted for useful activities.

3. Procurement : While tracking money is difficult, spending money is even more so. Being government organisations, these institutes have to follow the rigid L1 tender process and there is the perpetual fear of investigations by the CAG, the CBI and the Vigilance Commission. This does not deter unscrupulous deals -- any vendor is ready to provide the three mandatory quotations -- but it introduces an intolerable delay and difficulty in any genuine procurement process. For example, attempts to buy low value products and services over the web using credit cards and then seeking reimbursements are blocked by the three quotation rule. A simplified procure-to-pay cycle that will reduce costs and yet ensure compliance with appropriate approval procedures will introduce a great deal of flexibility and efficiency in the system.

4. Asset Management : Public sector institutes sit on vast assets but most of these are ill managed. Civil and electrical infrastructure is maintained poorly as there is no clear cut demarcation of authority or accountability. Equipment is bought and not used because of lack of training or compatibility. Non functioning equipment is not repaired or cannot be repaired because of procedural issues. Junk piles up in dusty store rooms but cannot be disposed easily because of outdated audit mechanisms. A smart and modern asset management policy will ensure that the public funds are used much more effectively.

5. Enterprise Information Architecture & Culture : It is indeed a paradox that even though these institutes are supposed to be thought leaders in technology their own usage of the same is woefully low. Other than email systems, none of the collaborative tools and practices that are used in corporates are available here. Email is for broadcast of information, not for interactive discussion. Peons still carry paper documents, through proper channel, to people across the floor and get acknowledgements of receipt in “peon books”. Tele  and video conferences are unthinkable, social media is a private matter for individuals and mail based approvals -- for even mundane matters -- are not acceptable.

Technology, or its cost, is not the bottleneck. People are simply not willing to experiment with new ways to manage accounts, handle procurement, manage assets and adopt best practices from the corporate world. This leads us back to the first point, the HR issue,  because there is no incentive to improve anything nor is there any disincentive for staying with the status quo. As long as you are in the good books of the Director and as long as the Director is in the good books of the current bureaucrats at the HRD Ministry everyone can keep milking the mammaries of the state.

Mergers and Acquisitions ?

The final need is for these institutes to scale up but thanks to Rajiv Gandhi’s ill-conceived decision to “gift” an IIT “for” Assam, we have opened the floodgates to regionalism. This has caused massive fragmentation of scarce resources -- both money and people.  By opening IITs to pander to regional sentiments we ignore the fundamental mandate of IITs to source both students and faculty at a national level. Institutes are built by accumulating talented people and not making grand buildings that only benefit contractors.  To put it simplistically, twenty professors with a thousand students in one institute is far better than to have two professors at ten institutes with a hundred students each. Even though the teacher-student ratio in both situations is 1:50, in the first case, each student gets access to all twenty specialist professors but in the second case, each students get access to only two professors who teach ten subjects each. Obviously, quality will suffer. Plus twenty professors networking with each other can achieve far better research results than two lonely professors at each location. This is the fatal flaw in our IIT system. Instead of allowing them to scale to the level of the global organisations like MIT or Oxford, our academic “world has been broken up into fragments by narrow domestic walls”. 

Since the multitude of IITs (or IIMs) cannot be shutdown we need to explore the equivalent of a Merger-and-Acquisition mechanism used in the corporate sector. Many, if not all of the new IITs, can be merged with the nearest of the “Original Five” and this will cause an immediate scale up. With collaborative technology and some travel, faculty and facilities can be readily  shared across multiple locations as in multi-location corporates. Only administrative staff would be rendered redundant and many of our Directors, and their Deans, will have go back to teaching and research jobs, which what they were supposed to be doing anyway. The program on data analytics conducted jointly by IIT-KGP, IIM-C and ISI could be a template for a more comprehensive and formal merger of, say, the IITs at Kharagpur, Bhubaneswar, Dhanbad, Patna and Guwahati into the first mega IIT. Even NIT Durgapur can be thrown into this mix.

There is a wealth of talent that is available in India but unfortunately, it is managed very poorly. That is why this talent seeks opportunities outside India or just withers away. Adoption of modern management processes will radically change the way our institutes operate and allow them to compete with global universities on equal terms.
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originally published in Swarajya