Cryptocurrency for Direct Benefit Transfer

The astonishing rise, and fall, in the price of Bitcoin has suddenly made everyone -- other than geeks who have been at it since 2009 -- sit up and take notice of an extraordinary new phenomenon called cryptocurrency. We call it a phenomenon because while it certainly carries value, it is not linked to any traditional investment product like equity, debt, commodity or real estate. What is even more mysterious is that the value is recorded in a database called the blockchain, a shared ledger that resides simultaneously across multiple computers that are operated by unknown, unregulated entities.

image from techbullion.com

Bitcoin is to the transfer of value what the internet is to the transfer of information - made it possible to effect transfers easily, anonymously and most importantly without the intermediation of any central authority. This makes both technologies a favourite with libertarians and an anathema to despotic and autocratic governments. But while most governments, barring a few, have reluctantly reconciled themselves to the free flow of information, the transfer of value is, in general, being opposed tooth and nail by central bankers who see themselves becoming as irrelevant as the telegraph and postal service. Hence a barrage of FUD -- fear, uncertainty and doubt -- has been unleashed stating that Bitcoin is being used by criminals, terrorists and tax-dodgers to undermine social order and so must be stamped out ruthlessly! Adding to this general hostility is of course the unstated jealousy of all those who are rueing the fact that they did not acquire Bitcoins when the price was only a few dollars!

The Government is on record, through the Finance Minister’s budget speech, with its view that crypto-assets must be ruthlessly blocked. This is grossly erroneous. All technology -- from nuclear power through genetic engineering to artificial intelligence -- is inherently double-edged and can be used for good or evil. Just as the commercial benefits of the internet far outweigh the nuisance of its misuse by criminals and terrorist, cryptocurrency can be used very beneficially in social and governmental work and in this article we show how it can be used for direct benefit transfer (DBT).

The public distribution system in India is riddled with inefficiency that results in a massive leakage of both money and goods. Government spends money but the poor people do not benefit. A DBT mechanism is perhaps the only way to control the problem but implementing this is not easy. The current mechanism of using bank accounts linked to biometric based Aadhaar cards is of course one way but tokens based on cryptocurrency technology could be an alternative that is a cheaper, simpler and more transparent.

But first, what is Bitcoin?

A Bitcoin is a unit of value, like an equity share of a company, that can be owned and transferred. It resides in an account in a ledger, like a dematerialised share in a demat account with NSDL. The account number, the public key of the account, is known to all and so anyone can send or deposit demat shares into this account. However to sell or transfer shares out of this account, the anonymous account holder must use a password, a private key that only he knows, to create and publish an outbound transaction pointing to another account identified by its public key. In cryptocurrency jargon, an account is called a wallet and the ledger is called the blockchain. A wallet is defined by a {public-key : private-key} pair consisting of two very large numbers that have special cryptographic properties. But what is really novel is that the blockchain ledger, the record of all transactions, is not maintained by or at any one institution, like the NSDL for equity shares, but jointly by all participants in the network. Everyone has a copy of the blockchain-ledger that has a record of all coin transfers and so everyone can both verify and confirm each transaction before they accept it in their own copy. An invalid transaction can pass into the blockchain-ledger if and only if, it is accepted by more than 50% of the network and this has never happened since 2009.

Verification means that a payment transaction is valid -- the total value of all inbound or credit transactions to a wallet less value of all outbound or debit transactions is more than or equal to the current outbound debit transaction. Confirmation means that there is no double spend and the same set of unspent, inbound, credit transactions (“UTXO” or unspent transactions outputs) are not being used to create more than one outbound payment transactions. Since everyone has access to all transactions, anyone can perform the verification and confirmation. This leads to a problem of sequencing. If A has Rs 1000 in his account but writes two cheques of Rs 800 and Rs 900 to B and C, either -- but not both -- cheques will be honoured by the bank, depending on which is presented first. However when there are multiple agencies that are verifying and confirming transactions, there is distinct possibility of an inconsistency in the shared ledger depending upon the transaction that each agency sees first. To overcome this, all cryptocurrencies implement a consensus process. In a zero-trust environment, the consensus is achieved through a proof-of-work algorithm that is based on brute computing power -- it is as if the first banker who completes a 10 km run will be allowed to update the shared ledger! But since this consensus is essential for the success of the process there is a reward for demonstrating that power. “Miners”, that is those who verify and confirm transaction  by running full node blockchain software on a powerful computer, are rewarded with newly created coins that are added to their wallet when they have verified and confirmed a new block of transactions -- that is then added to the blockchain. However the reward is not given to any miner who performs the verification and confirmation but to the one specific miner who, in addition to the verification and confirmation, also solves a difficult mathematical puzzle first, like the first banker who runs 10 km!

The payment, or output  transaction that deposits a newly created coin into a successful miner’s wallet is called a coinbase transaction. It is different from all other transactions because it is not backed by any previous input transaction. Hence the analogy of mining, as if a coin was dug out of the ground and not received from anyone else, whereas all other coins would have to be received from someone before they can be sent to someone else. However a better analogy would be to view Bitcoin, as sweat equity that is given, in lieu of salary, to the accountants in a bank for checking and approving all transactions. The brilliance of “Satoshi Nakamoto”, who designed bitcoin, was in equating the sweat equity of the bank to the assets that are managed by the bank and initiating a self-sustaining network that is working flawlessly since 2009. The magic mathematics of cryptography ensures that this decentralised autonomous organisation (DAO) runs without any formal management and yet has achieved a market capitalisation of over US$ 70 billion.

But why should these “sweat equity” shares of a non-existent bank, the actual Bitcoins, be each worth thousands of dollars today? Many people, who are not miners, buy these coins from the miners for investment or payment purposes and this demand is pushing up the market price.  Bitcoin can be purchased at many cryptocurrency exchanges with fiat currency like US$ or INR ₹. After KYC compliance, these exchanges will convert fiat currency into cryptocurrency and vice versa at market driven prices. Hence, Bitcoin is both a currency that is extremely useful as a payment mechanism because transfers are simple, fast and anonymous and is also a commodity that has appreciated in value and hence worth investing in.

For DBT let us define a new blockchain based cryptocurrency token ( lets call it the cowrie) and peg it to the Indian rupee. So anyone can use a cowrie in lieu of a rupee to pay for goods and services provided the seller is willing to accept the same. This is neither illegal, nor anything new because we already have loyalty points from retailers, credit cards and even meal-companies like Sodexho, that are freely tradeable in lieu of cash at selected stores. Moreover, since the value of the cowrie is pegged to the rupee, there is no question of trading, capital gains and taxation.

Cowries, like any other cryptocurrencies, can easily be stored in mobile wallets and freely transmitted from one wallet to another without the fear of double-spend. They can also be freely exchanged for fiat currency like rupee through cryptocurrency exchanges that follow normal KYC guidelines applicable to banks or at banks themselves.

As an example, let us focus on the public distribution of rice at ₹ 2/kg. Assuming that the government gives 2 kg per week per person when the prevailing market price for similar quality of rice is ₹ 25, the subsidy works out to ₹ (25-2) x 2 x 4 = ₹ 184 per person per month. Let us assume that the government selects 1 crore people who will get this ₹ 2/kg subsidised rice. This means that the government intends to spend ₹184 crores every month for this subsidy. A government agency, say the NPCI,  builds a cowrie wallet and floats an Initial Coin Offering (ICO) that is subscribed to by the government. Government pays ₹184 crores to NCPI and NPCI “pre-mines” ( or creates) 184 crore cowries and transfers them to the Government’s cowrie wallet.

The cowrie wallet is available as a free and open-source software that anyone can download and install on their mobile phones. However those who are entitled to receive the subsidy will have to register their cowrie wallet public addresses with the government disbursement agency with proper identification as would be the case if they were to apply for a ration card. Any shopkeeper who wants to sell rice must also install a cowrie wallet on their phones or computers.

At the beginning of the month, government will transmit 184 cowries to each registered wallet. Recipients, who are entitled to the subsidy, can now go to any rice shop and buy rice by transferring cowries to the shopkeepers wallet and paying the rest in cash at ₹ 2/kg. The shopkeeper can either keep the cowries for future use or exchange them for rupees at a cryptocurrency exchange. The exchange operator can also either keep the cowries for future use or trade them with NPCI in exchange for rupees and NPCI will extinguish them by dumping them into a one-way, black-hole wallet from where they cannot be spent any more.

The cowries are freely transferable. Recipients who are not interested in buying rice can use the same cowries to buy wheat, or daal or school exercise books from the same store using the cowries. Or they might transfer it to the wallets of their friends and relatives and even perfect strangers as gifts or in lieu of other goods and services. Transfer of cowries is governed by the same verification / confirmation mechanism common to all cryptocurrencies and those who validate transactions could be rewarded with newly “mined” cowries as an incentive. However if miners are registered and hence trustworthy, then the computationally expensive proof of work processes can be replaced with simpler consensus mechanisms.

All this can be done using standard cryptocurrency software except that instead of using anonymous public addresses, we can ensure that all public addresses are tagged to a government identity document so that there is perfect transparency on the blockchain about who is getting how many cowries and how these are flowing through the system. However, private addresses are secret to the wallet owner so that only he can spend from the wallet. In principle, even a liquor store can accept cowries, but the blockchain database can be used to track this if it happens too regularly and we wish to question the spender!

One of the attractive benefits of this mechanism is that multiple subsidies can be routed through this mechanism. For example, subsidies on diverse goods and services, like kerosene oil and school tuition, that are delivered through different channels, can be routed through the same wallet. Family wallets can hold cowries for all members. Multi-signature wallets can be coded so that the male member cannot spend the cowries without the consent of the female member and vice versa. Smart contracts can be developed so that not all the cowries can be spent immediately and there will be “timed release”. Smart contracts can also be created to make sure that cowries are spent only at specified points or on specified goods and services. All this is technically possible but initially it may be prudent to keep matters simple so that people first understand how cryptocurrency works.

To continue with the subsidy, Government must continue pay ₹184 crore to NPCI every month to buy 184 crore cowries that NPCI must “mine” and push them into the respective wallets. The exact amount will of course change depending on the kind and level of subsidy that government wants to disburse in each specific month.

Cryptocurrency is an amazing technology that could revolutionise payment systems. Instead of trying to throttle it, it is better that government finds creative ways to use it to discharge its obligations towards its citizens. DBT could be the first of many applications. Who ever has advised the Government that “blockchain is good but cryptocurrency is bad” fails to understand that cryptocurrency is the most natural and popular use of blockchain technology. It is as if we are saying that TCP/IP technology that runs the Internet is good but we should not use it for http applications like websites because websites can peddle pornography. Instead we must use TCP/IP only for FTP, SMTP, NNTP, ICMP, SIP and other “useful” things … Without websites, the benefit of the internet will be restricted to laboratories and not be accessible on our laptops, phones and in our lives. So is the case of cryptocurrency and the blockchain.

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This article originally published in Swarajya, the magazine that reads India right.

Aadhaar - way forward

Like demonetisation and GST, Aadhaar has been in the news for both good and bad reasons. On one hand we have heard how crores of rupees in non-entitled subsidy have been saved by the government but then on the other hand we have had horror stories of destitutes being deprived of entitlements because of the lack of an Aadhaar identity. In general, those who believe in the current prime minister are bullish about Aadhaar but they forget that many of them had opposed the same on the grounds of privacy when it was proposed by the previous government. What is missing in all such discourse is a clear understanding of how Aadhaar operates and how it could fail.

image from techniknow

Ever since it was freely and finally admitted that 90% of all money that the Central government transmits to citizens as subsidies is stolen by middlemen there has been a demand for a direct benefit transfer (DBT) mechanism. One obvious mechanism is through bank accounts : Instead of selling 3 kg of rice to Ram once a week at Rs 2/kg, make him buy the same rice at Rs 20/kg from the market but send the difference, Rs (20-2) x 3 x 4 = Rs 216, to Ram’s bank account every month so that he does not have to spend any more than Rs 2/kg. But since there are a thousands of people who call themselves as Ram, we would need to connect “our” Ram’s bank account to “our” Ram’s hungry body using a marker that is unique to “our” Ram, namely his fingerprints and iris scan. This is the genesis of the Aadhaar database and the Aadhaar number.

But this simple concept has been criticised for three major reasons - namely privacy, potential for misuse and operational inefficiency. Before we examine these in greater detail, let us look at how the database is created and used.

To create a new Aadhaar number for a new registrant, we need the (a) biometrics - iris scan and all 10 fingerprints (b) name, gender, date of birth, address and (c)  optionally a cellphone number and email address. Since the biometrics is the only data that is guaranteed to be unique for each person, a de-duplication exercise is carried out to check if another Aadhaar number has already been generated for the same set of biometrics, to ensure that no one body gets attached to two or more Aadhaar numbers.

To confirm a person’s identity using Aadhaar before he is allowed to avail of any benefit or service, a verifier has to transmit the person’s Aadhaar number to UIDAI along with either biometric data ( as in the case of banks or phone companies) or name and date of birth (as is the case of some mutual funds). In either case, UIDAI replies either with (a) a binary YES / NO that confirms or denies the association of the Aadhaar number with the accompanying data or with (b) a more detailed extract from the Aadhaar database that includes photograph but specifically excludes the “core” biometric information. In some less critical situations, for example, where a physical copy of Aadhaar needs to be downloaded, the optional phone number or email address is used to send a one-time-password to establish an association between the Aadhaar number and the phone/email and hence by extension to the name of the person. In this must be clearly understood, and communicated to all, that the physical possession of Aadhaar card -- that can be manufactured by anyone with a computer and a printer -- is no proof of anything at all and should never  be used for any kind of verification.

Now let us look at privacy and potential for misuse, the two major concerns.

The basic data that is stored is quite primitive. Name, gender, date of birth and address is already available with the government in Voter cards and Election rolls but the optional phone number and email is an addition. Frankly, phone/email is a better way of contacting a person in the 21st century so there is no ideological difficulty in storing that information. The real, new addition is the biometric but that is a part of the original design to prevent duplication. So prima facie, there is no real privacy concern unless there is misuse and this misuse can be of two types -  first deliberate misuse by the government and second, illegitimate misuse by hackers.

By requiring individuals to link Aadhaar numbers to bank accounts and cellphones, government gets an easy way to discover who owns and operates which bank accounts and telephone numbers. But this demand is nothing new? Under anti money laundering schemes, the banks are in any case required to use stringent KYC processes to know their customers. Similarly, because of terrorist and other security concerns, telephone companies are forced to use similar stringent KYC processes. Whether such intrusive knowledge is necessary is irrelevant to the Aadhaar debate. If we have accepted KYC processes in banks and telephones, then there is no additional loss of privacy in linking bank accounts and telephone numbers to Aadhaar and thus simplify traceability. Hence the claim that Aadhaar represents a new mechanism to misuse private information is baseless.

Moreover, insinuations that Aadhaar can be used by the government to surreptitiously know bank balances from linked accounts or to surreptitiously listen in to private telephone conversations on linked phones are so ludicrous and absurd that there are not even worth contradicting.

However, this does not mean that any government agency -- from the municipality crematorium to the motor vehicles department -- or even private agencies like hospitals and airlines should start demanding Aadhaar for rendering services. Rules framed under the Aadhaar Act 2016 should stipulate which all public services require Aadhaar and this information must be made available on the UIDAI website.

What happens when things go wrong? There is no point in claiming that the Aadhaar database is “totally secure and hacker proof”. No computer system ever is. So what we should plan for is to estimate the damage to the registrant if the data is compromised. Let us examine what could happen if the Aadhaar database is hacked and the information falls into the hands of unauthorised people, or if the government goes rogue and starts using the information in a manner not envisaged under the Aadhaar act? Consider various scenarios …

What all can a criminal do with the text information about a person that is stolen from the Aadhaar database? Neither can he open a new bank account, nor get a new telephone SIM as both require a biometric validation. At best he can attempt to get phone-banking access to a bank account by quoting the date of birth, but knowing this, no sensible bank should ever accept DoB as a verification question.

Can he take a loan and wreck the Aadhaar registrants credit rating? This is unlikely unless there is collusion with the employees of the bank to which the registrants loan is linked, but they have the number anyway - so there is no incremental exposure. Can the phone number be used to access bank accounts through UPI apps or digital wallets? This is theoretically possible if someone clones your SIM but if we want to guard against this then we should not share our phone numbers with anyone at all. In fact, the worst case scenario is a barrage of spam or crank calls. But then again, this is already an issue with many of us and not really an Aadhaar specific abomination.

Can the picture of the registrant can be misused? The government, or a criminal, can use a public image of an individual, say in a newspaper or on social media, and use face recognition technology to identify him. This may, in principle,  be used to identify either real criminals or persons hostile to the government but the possibility of its effective use is pretty low. Hence the threat is quite far fetched.

Finally, the biometrics. In principle, this should never reach anyone outside UIDAI but what if it does? There do exist locks and access control devices that use biometrics like fingerprint and iris scans to grant access to assets that could range from nuclear weapons to even iPhones and these may, in principle, get compromised. But the process of transferring the data from digital format to the access control device is, to say the least, very complicated. Readers may recall the movie Angels and Demons where a dead scientist’s eye was gouged out and used to open a vault protected by a retinal scanner to understand how complex the process is and even then, it has been proven that this is simply impossible. Retinal scanners need a living eye to focus on a point and hence cannot be fooled by a static image of the iris pattern. Similarly, while it may be possible in-principle, to steal one’s fingerprint images and use them at a crime site to implicate the owner, the physical challenges of actually doing so are very high that the probability of its occurrence is quite low.

So net-net, a hack of the Aadhaar database could of course result in a flood of spam on your phone and email box but all the other scenarios described have a very low probability of causing actual damage. In fact, many of the conveniences that we use -- passport, air travel, cellphone, online banking, Gmail -- have greater probability of causing damage to our privacy and in a throwback to Heisenberg's Uncertainty Principle, let us accept that it is impossible to maximise both privacy and convenience at the same time. One must always trade-off any one against the other. Unless  you are like Richard Stallman -- the open source guru and privacy fanatic, who does not use cellphones, credit cards, hotel wifi, Google search engine, Facebook and many other conveniences of daily life in his quest for total privacy -- a lot information about you is already in the public domain and Aadhaar will hardly add anything more to that. Hence Aadhaar being a threat to privacy is more of a urban myth or an attempt at scare mongering. The recent hack or unauthorised access of the Aadhaar database, as reported in The Tribune must be seen in this context.

But even if the threat of privacy recedes, Aadhaar faces the one big challenge that hobbles and frustrates all bold policy initiatives in India -- the threat of a poor implementation. Like demonetisation, GST or even more prosaic projects like building roads and highways, the Aadhaar project is full of operational pitfalls. First there was an immense shortage of biometric equipment and trained staff and it was quite difficult to get an Aadhaar number to begin with. Then there were significant process issues that were not thought through adequately. For example, what to do about people with age, medical or disability related problems that do not allow biometrics to be captured easily? Some of these problems have been highlighted both in mainstream media as well as on social media and remedial action has been taken as an afterthought but much more detailed level planning needs to be done to handle genuine exceptions to the regular processes.

What is immediately needed however is to flood the country with low-cost, but high-reliability biometric devices that can communicate seamlessly with the Aadhaar database and allow instant confirmation of a person’s Aadhaar number and hence his identity. Unless the Supreme Court puts a roadblock to many of the ambitious Aadhaar based projects that the government has in mind -- particularly in the area of digital payments and smartphone wallets --  we will see an exponential increase in the number of verifications. Without a quick and reliable verification mechanism, these projects will falter and Aadhaar will be blamed for this.

Finally, the Aadhaar database should not become a single point of failure for the nation. What this means is that even if the database is hacked-into and corrupted, no critical operations like banking, stock market or PDS should come to halt and cripple the nation. Critical systems should be loosely coupled to the central database and there should be adequate workarounds that allows bypass but with clear audit trails.

In 1985, when the author arrived in the United States for his PhD program, he realised to his chagrin there was no way that he could register at the university or open a bank account without a Social Security Number (SSN), that he as a foreign national did not have. But this scenario had been anticipated and the University had been authorised to allot a temporary SSN to new foreign students that could be used in lieu of the actual one for upto six weeks. The real SSN was of course allotted by the social security administration after a thorough verification of immigration credentials which took about four weeks and all that the author had to do after that was to go back to each organisation and have his temporary SSN replaced by the real one.

The Aadhaar implementation should focus on processes, not technology that keeps changing by the hour. If the various processes that use Aadhaar are thought through and planned as beautifully as the example given above, Aadhaar will surely become a very useful tool for governance in India. While it is far from being fault free, a lot of “criticism” of Aadhaar is due to the fact that, as reported in the Economic Times (January 5, 2018),  it is killing lakhs of non-existent, ghost teachers, ration card holders, students and other beneficiaries in whose name tax-payer’s money was being stolen from the public exchequer. That is why Aadhaar must continue.

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this article originally appeared in Swarajya

Time, Gödel & Mahākāl

In the evolutionary ascent of man, the idea of time is perhaps the first concept that differentiates him from his animal past. Unlike a human being, an animal, say a cow, has no -- or very rudimentary -- memories of the past, and certainly no hopes and plans for the future. It lives in the perennial present and is motivated only by the current state of its environment and its own current state of hunger, fear, libido or discomfort. Time is also an enigmatic concept that defies definition. Trapped in a peculiar case of circular logic, where “the snake swallows its tail”, we say that “Time is what is measured by clocks and a clock is what measures time”.  We obviously sense the passage of time but this flow is another mystery because if it indeed flows, like the water of a river, then what exactly are the banks of the river that it flows through? Then again, do we sit still while time flows past us? Or do we move along through stagnant time? There have been questions galore but hardly any convincing answers.

It was Albert Einstein who, in a sense, caught time by its ears and dragged it into the same cage that holds the other three dimensions of length that define what is traditionally known as space. Time in Einstein’s Theory of Relativity is just another dimension that creates a platform for the manifestation of physical phenomena and helps us model the physical world in the language of mathematics. Multiplied by ‘c’ the speed of light, time becomes dimensionally equivalent to a measure of  length and can be treated as such to calculate the Euclidean distance between two events in space-time as opposed to the mere physical distance between two points in pure space. In fact, light -- or rather its speed -- is the magic knot that ties space and time together with measurements along either of these dimensions being affected as the observer travels at a speed close to that of light. Clocks slow down, increasing the time elapsed between events and distances shorten as we increase the speed of the observer.

But just as we thought that we have caught up with time, it gives us the slip and speeds away again. How? Because unlike in the other three dimensions, we cannot stand still in time - we must keep moving, or as we said earlier, time moves past us. But whether we are moving through time or time is moving past us, what is the speed with which time moves? Speed is by definition change of position ( or at a stretch, any other physical quantity like temperature or illumination ) per unit of time, but when it is time that is changing, then the change of time per unit of time is a phrase that is drained of all meaning! Can we extract some meaning from this apparent meaninglessness?

If you are travelling in a train, you cannot make out whether it is moving or not (assuming that there is no sound or vibrations) unless you look out of the window and see the scenery moving “backward”. So if you are moving along in time, you should not be able to determine whether you are moving in time unless you looked out of the “window” and saw something that is not moving through, or with, time. But like a tree that is stuck to the ground and against which you can determine that your train is moving ( though the tree might argue, if it could, that you are stuck and it is moving - and relatively speaking both would be right) is there something that is stuck in time and against which you could measure the quantum of movement that you have made through time?

This is tough. If everything is moving through time at the same “speed” then we cannot determine the “speed” of this movement by looking outside the window. But if looking out of the window does not help, can we look inside? Inside of what? Let us begin by looking into our minds and what do we see there? Memories -- and these are stuck in time, like trees in the landscape outside our speeding train. Memories are artefacts stuck in the past but they are mental objects that lie outside the reach of physical sciences. The corresponding physical objects are events, of which we have memories, and a collection or rather a sequence of events is what gives us our sense of motion or movement through time.

If the relativistic concept of dimension was the first handle that physics had on the elusive nature of time, then the sequence of events is the second handle it could grip it with. This second handle, or perspective, also leads to the key concept of a direction, the Arrow of Time. Unlike a dimension of space in which we can move forward or backward, to and fro, the time dimension is a one way street. You can move from Nagpur to Kanpur and back  to Nagpur again but while you can, and will, move from childhood to old age, you cannot go back to your childhood again. Physics liberates this concept of sequence from its ties to human memory, by formalising it in terms of the Second Law of Thermodynamics that states that entropy, generally understood as the level of disorder in a system, increases with time. Or as Omar Khayyam puts it “The moving finger writes and having writ, moves on; nor all your piety nor wit shall lure it back to cancel half a line, nor all your tears blot out a word of it.”

The fabric of physics now seems all set to wrap up time between the warp of relativistic dimensions and the weft of a thermodynamic direction but even this elegant gift wrap fails to cover this oddity quite completely.  Under the relativistic interpretation, the world is symmetric under time-reversal. This is because the laws of physics must have the same form regardless of any smooth coordinate transformation whatsoever -- and time-reversal is just such a smooth coordinate transformation. We know that when a body moves at high speed through space, a clock attached to it slows down. While moving faster through space it moves slower through time, and so by extension, in principle, when the speed of the body goes past the speed of light -- that mysterious knot that ties up space and time -- time should stop and then go backward. From old age back to childhood? But that is an intolerable state of affairs that is blocked, not only by the Second Law of Thermodynamics but also by our intuitive understanding of time and this is a blemish on the fair face of science.

Relativity tries to do plastic, or cosmetic surgery, to erase this scar by stating that as the spatial speed of a body reaches the speed of light, its mass would become infinite and so it would take an infinite force, and infinite energy, to accelerate it past that magic figure and back into the temporal past. Hence while it may be theoretically possible to travel back into the past, it will never be practically possible.

But even in the realm of massless objects, like photons of light, that travel, obviously, at the speed of light, we run into the problem of establishing the state of simultaneity. To determine the sequence of events along the arrow of time, we need to map these events to corresponding simultaneous ticks of a universal clock. But since relativity puts an upper limit on the speed at which information can be transmitted through light beams, there is no guaranteed way to determine if two events that are separated in space are, or were, simultaneous in time! The blemish on the face becomes a scar!

Enter Gödel, to deliver the coup de grâce.

Who is Gödel? Gödel was an Austrian mathematician and logician, and close friend and confidant of Einstein during his last days at Princeton. In his youth, Gödel had driven a stake through the heart of mathematics by using mathematics to prove that mathematics was incomplete in the sense that there will exist facts that are true but not provable by mathematics. This was the Theorem of Incompleteness, where, as his biographer Paul Yourgrau puts it, “Gödel had used the letter of a false doctrine to demolish its spirit”. Gödel’s Theorem is very well known and respected in the mathematical community but what is not known is the way he demolished the concept of time as it is understood by the Theory of Relativity! Gödel’s genius lay in demonstrating that time as it is captured by the laws of physics cannot be the same as the time that is intuitively understood as flowing through a sequence of ordered events. He did this by showing that under certain circumstances -- and admittedly these are extreme circumstances, comparable in extremity associated with black holes -- relativistic time can bend back on itself. Just as by going around a spherical world surface you can be back where you started without turning around, you could also come, or go, back to the past if the universe was expanding and spinning at the same time.  Time travel is possible, but only if we agree that this scientific time is not the intuitive time that we generally understand as time. Physics claims to have a caught a bird and put it in a relativistic cage only to realise that what it has caught is only a clay image of the bird. The real bird -- time as it is intuitively understood -- is still flying free in the sky, unfettered by the logical bars that define the cage of science.

Einstein admitted that Gödel was correct in his analysis but defended the relevance of his own work by stating that Gödel’s requirements were unlikely to be met with in the real world. But then many of Einstein’s own reservations about the real world, like the possibility of black holes and the expanding universe, were later overturned by physical evidence. For more detailed explanation of how Gödel demolishes time, the reader can look up Yourgrau’s book, “The Forgotten Legacy of Gödel and Einstein”.

But if time cannot be talked about logically and scientifically, how should one go about trying to describe or articulate the idea? Or in that case, is it something not worth discussing at all?

Ludwig Wittgenstein, one of the most influential philosophers of the western world in the 20th century, had originally stated in his Tractatus Logico-Philosophicus that  “Whereof one cannot speak, thereof one must be silent.” But with the passage of time, this stark utterance has been beautifully re-interpreted by Doxiadis in his famous graphic novel Logicomix as “The things that cannot be talked about logically are the only ones that are truly important”. This, in a sense, is also echoed in the Sanatana Dharma where the principle of  neti neti (नेति नेति) or “not this, not this” --  an expression of something inexpressible -- has been used to arrive at an approximate description of the Atman. Then again we have Gödel, who was a great fan of fairy tales, stating that  “Only fables present the world as it should be and as if it had meaning.”

So our search for the meaning of time must now explore the legends, fables and the divinity associated with time. In the Indic worldview, the world is viewed as moving cyclically with the Kālchakra and rotating recursively through a sequence of solar-years, yugas, mānavantars, kalpas and Brahma varshas  whose cumulative span is longer than the scientifically dated age of the universe.

Our universe obviously exists in space and in time. But for space to exist it must first acquire and demonstrate the quality of persistence and persistence by its very definition is a property that can only be manifested in the flow of time. Hence time must precede space -- it cannot be at the same level of significance as just another dimension of a hybrid space-time. This makes time the most fundamental component,  the primordial matrix of the manifest universe.

The iconic imagery of Kāli and Mahākāl --that which is time or even beyond time,  is an excellent expression of this perspective.

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This article originally appeared in Swarajya, the magazine that reads India right.

Saraswati 2018

Astrology - an application of Data Science

Every morning, when the sun rises, birds wake up and start chirping. We are not surprised because we see a very clear connection between a cause, the increase in ambient light, and the effect it has in waking up the birds. But when the sun rises, the Ispat Express moves out from Howrah station as well. Even in this case we are not surprised even though there is no obvious connection between the ambient light and behaviour of the engine. We explain the first phenomenon through causation and the second through correlation. Perhaps if we look very hard we might find a causative mechanism that explains why the Ispat Express departs at the crack of dawn and not at any other time, but frankly that is of little interest to the passenger. We are happy with the correlation, we are not really bothered about the causation. That is the crux of this article where we explore astrology from the perspective of data science and machine learning.

Traditional scientists would of course hesitate to view astrology as a science because they are trained to interpret phenomena through the prism of cause and effect. Naive astrologers also fall into the trap of trying to justify astrology by invoking gravitational, electromagnetic and even undiscovered, unheard of “rays” that emanate from astronomical bodies and influence human destiny. Both are wrong because they are searching for causation whereas the underlying principle is one of correlation. Astrology is interested in predicting an outcome based on some correlation -- an event, say an accident, happens not because a certain planet was at a particular location and caused the event but because it has been historically observed that the presence of a planet at a particular position is associated or strongly correlated with the occurrence of that specific event.

Is correlation an acceptable way to analyse situations and predict outcomes? Certainly, if we consider ...

The world of data science, of which artificial intelligence (AI) is a specific example, is largely based on the study of correlations. Most well known AI systems -- for example those that control autonomous, self-driving cars, recognise people and objects in photographs, react to voice commands, play board games like GO or perform other tasks that eerily mimic human behaviour -- are based on the technology of Artificial Neural Networks (ANN). In all such cases, the system is presented with a set, or pattern, of input data, that in the case of face recognition, would be the colour and brightness of light at every point of an image. If the system has been “trained” adequately, it should predict the identity of the person in the image even though this particular image has never been encountered before. A similar ANN software, if “trained” differently, and presented with an appropriate set of input data, should also be able to predict the best possible move in a competitive board game, the possible motion of a pedestrian in the vicinity of an autonomous car, or the intention and ability of a bank customer to repay a loan. In all such cases,  “training” consists of feeding the system with thousands of pieces of historical data and identifying which of the corresponding predictions were correct and which were not. Initially, most predictions will be erroneous but after a few thousand errors, the system will “learn” or get “trained” and from then on, the number of correct predictions would improve dramatically.

What happens inside the system, that is almost like a black  box, is not very clear. Some parameters, also known as weights, are assigned numeric values, but it is not possible to explain why specific values were chosen. All that is known is that changing these values leads to a change in the accuracy of the prediction. Once the values have been set correctly -- the system has been “trained” -- the subsequent predictions are almost always correct. This situation, where the system works well but we cannot explain why it works well,  is described in “The Dark Secret at the Heart of AI” [ MIT Technology Review, April 2017, see ]. This article describes a new kind of autonomous car from NVidia that is not explicitly programmed to drive through traffic.  Instead, it learns driving by observing the environment and recording the actions of a human driver who is navigating through the environment.

“Getting a car to drive this way was an impressive feat. But ... it isn’t completely clear how the car makes its decisions. Information from the vehicle’s sensors goes straight into a huge network of artificial neurons that process the data and then deliver the commands required to operate the steering wheel, the brakes, and other systems. But .. if .. it did something unexpected ... it might be difficult to find out why. The system is so complicated that even the engineers who designed it [cannot] isolate the reason for any single action. And ... there is no obvious way to design such a system so that it could always explain why it did what it did.”

This inability to explain the reason for a behaviour is not because the system has supernatural or magical properties. This is a purely deterministic machine, that follows the laws of cause and effect at the micro level. But the situation is so complex -- in terms of the the number of micro-operations and the way they are related to each other --  that the connection between cause and eventual effect is impossible to establish at the macro level. But this does not detract from the fact that these and many other similar systems are being successfully used in situations where there is a need to predict outcomes based on (a) a set, or pattern, of current input data  and (b) historical, or “training”, data that maps thousands of  similar patterns observed earlier  to corresponding outcomes that have actually occurred.

Since this approach is “scientifically” acceptable in the case of AI research, we can extend the same to astrology! But before we do so, there are two difficult challenges to overcome.

The first challenge is the question whether the world is indeed deterministic, and hence predictable?  -- are all events pre-determined? -- or do events happen because of free will or pure chance? This profound question cannot be answered in this short article. So we will seek an acceptable answer that skirts the quicksands of philosophy and yet helps us move ahead without being facetious.

We accept that at the micro level the world is indeed completely deterministic but not so at the macro level. For example, a man dies in a plane crash because he boarded the aircraft to attend a meeting that was called by his boss and the mechanic who repaired the aircraft engine did not tighten a nut on an engine because he was thinking about his wife. The meeting was called by the boss because {of some reason} and the mechanic was thinking of his wife because { of some other reason } and this chain of events or reasons can stretch backward through millions of interrelated links that hide the eventual effect from the possible causes. Conceptually, this is no different from the behaviour of ANN systems, where despite the existence of deterministic causality at the micro level, we are not in a position to explain the full chain of causality.

A simple demonstration of such a mechanism is the 2003 Honda advertisement ( https://www.youtube.com/watch?v=_ve4M4UsJQo ) that shows how interrelated the world could be. A tiny gear rolls across the table, pushes a lever, that in turn causes some liquid to spill, that in turn causes a table to tilt, that in turn causes a spring to snap … and so on and on … until a Honda Car rolls out of the store. This video demonstrates how precisely Honda technology works and so one can see how a small change in any of the actions will result in the final car not moving. But unless this was explicitly shown, one would never know how the movement of a small ball or the flow of a liquid can in any way affect the final outcome. A similar video is available in the Facebook Japanese Community page ( http://bit.ly/2eUXAks ) that shows an even more complicated piece of mechanism where apparently unrelated movements of many objects finally end with a desired result.

To the profound question of whether the world is deterministic, a simple answer would be that while the world must indeed be deterministic, it may not be possible to establish a clear and unambiguous cause-and-effect linkage between two events that are widely separated in space and time.

The second and more difficult challenge is to explain how the position of astronomical bodies could in any way be a part of this huge chain of inexplicable causality. This is where we completely discard causality as the operating principle and instead, introduce correlations into our description of astrology.

The universe as we know it is a long and complex chain, or web, of interconnected events, that have a location in space and time. From this universal set of all events, a certain subset is related to human beings and of which an even smaller sub-subset is related to a specific individual. So the life of every individual can be represented by a unique set of events, many of which he shares with others. Indian astrology considers  ten astronomical objects, namely, the Sun, the Moon, five actual planets, the Lagna or ascendant horizon and Rahu and Ketu, the two points in space where the lunar orbit intersects the ecliptic plane.  For every person, the presence of these ten notional “planets” at specific locations on the Zodiac at the moment of birth are also events that are a part of the huge collection of events that define the life of the person.

Each event in a person’s life, including these ten planetary events, can be interpreted as a piece of data. Some of this data is binary - the event happened or did not happen; others can be interpreted as ordinal -- for example, favourable, neutral or unfavourable; categorical -- for example career in medicine, law etc; or even numeric -- for example, age at marriage or at death. With this interpretation, the life of a person becomes, what mathematicans refers to as, a vector in a multi-dimensional space, with the number of dimensions being equal to the number of events used to represent his life. Pictorially, every person can now be viewed as a point in multi-dimensional space and a group of persons looks like a random scattering of dots in this multi-dimensional space.

But are these points scattered randomly? Or do they form clumps and clusters?

Data science tools -- that is software programs based on algorithms like K-Means, K-Nearest-Neighbour, Decision Trees, Logistic Regression and of course the very popular ANN --  are quite efficient in detecting and isolating clusters by identifying points that are “similar” to others. This is routinely used in recommendation systems used by websites like Amazon and Netflix to identify individuals who have similar preferences -- individuals in a cluster would tend to display similar buying preferences -- and show them advertisements of products that they are likely to buy. In fact these recommendation systems try to predict who is likely to buy what.

For example, consider the attached figure, based on representative, simulated data, that shows the kinds of movies that people prefer. If the data of many people are plotted as points in  three-dimensional space where the three dimensions are represented by gender (shown as colour, blue or red), preference for action movies ( position on Y axis) and preference for romantic comedies (position on X axis), then there will be two clear clusters of points along with a few outliers. From the diagram, or actually the data, we can clearly see that men prefer action movies and women prefer romantic comedies.

Can we explain why men prefer action movies and women prefer romcoms? No, the diagram offers no explanations, and we do not care. But we do know that there is a clear correlation between gender and movie preferences. So by knowing a preferences of movies we could, in principle, predict whether a person is a man or a woman. Obviously with more data and more dimensions our prediction would be more accurate but there is nothing magical or supernatural about this prediction that is based on data and data alone. This ability to predict events without being concerned about the cause of the event is the basis of all forms of astrology.

But of all the events that define a person’s life, why is it that these ten planetary positions are the ones that considered in our search for correlations with other life events?

In principle, many mathematical techniques can be used to cluster people defined through their hundreds of dimensions. In practice this becomes difficult when the number of dimension becomes very large. Data scientists call this “The Curse of Dimensionality” where the number of dimensions is high compared to the number of data points available. Fortunately, there exist sophisticated mathematical tools, like Principal Component Analysis (PCA) and Factor Analysis (FA) that help identify key or important dimensions and allow the scientist to ignore others. Not everybody needs to understand the complex mathematics of PCA and FA but everyone uses it to reduce the number of dimensions to a manageable number.

Dimensions are also reduced through mathematical projections. Civil and mechanical engineers regularly project a three dimensional structure, say a building or a machine component, into two dimensional images called plan and elevation. This process can be generalised by projecting an n-dimensional structure into an m-dimensional surface where m is less than n. Representing high dimensional data pictorially and making it visible or understandable to a lay person is difficult, but for mathematicians, this is a very routine matter because these are standard mathematical operations.

From the thousands of potential dimensions that could be used to describe a person’s life, astrology chooses a smaller subset --  the positions of the ten astronomical bodies, or “planets”, on the various charts -- and this is used to identify clusters. Why do we choose the dimensions that are based on planetary positions at birth? The most likely reason would be that, thanks to astronomy that is closely associated with astrology, these are dimensions that are guaranteed to have numerical values that can be accurately determined if the date, time and place of birth is known. Other dimensions, associated with event, like omens, may not have valid data for everyone. If we choose these planetary dimensions -- and of course their derivatives like, aspects, conjuncts, combinations, Navamsha positions etc -- we are assured of a standardised structure that can be used to create a lower dimension surface, a  projection, of a person’s life that is otherwise defined as a point in a space of far higher dimensionality. So the choice of the planetary positions as key variables is an exercise in reduction of dimensionality -- a process that is, again, quite common in data science.

Once we plot the lives of individuals on this lower, ten-dimensional surface, then the search for clusters becomes a tractable problem. For example, mangaliks -- those with Mars  at the 4th, 8th or 12th position from the Ascendant or the Moon -- are likely to have marital problems unless they are married to fellow mangaliks. More specific events require far more complex patterns to be identified. For example, the birth of a child is associated with a fairly complex pattern in the charts of both parents that involves the dashas of planets associated with the Ascendant, the 5th and 9th houses and of Jupiter. The specific birth event is associated with another complex pattern that involves Jupiter, Saturn, Mars and Moon casting their aspects on the 5th and 9th house. Similarly, if a person is in the medical profession, it is very likely that the chart will show an afflicted Moon, a strong Jupiter associated with Ketu and Sun and an association of the 5th Lord with the Lords of 6th, 8th  and 12th houses. These are examples of positive correlations, where the patterns and events happen together, but there are also cases of negative correlations, the “limiting” patterns, that do not occur with certain events and seem to inhibit, rather than cause these events.

Such complex patterns are not easy to spot by manual means and the failure to do so leads to errors in prediction. Competent astrologers, like good chess and card players, are adept at spotting patterns and the inablity to do so is the reason why many astrologers end up with wrong predictions. However, the usage of data analytics tools, particularly software tools, can eliminate the possibility of missing patterns and improve accuracy of predictions.

Can we explain why these specific patterns are associated with specific events? No, and we do not need to. This is similar to the correlation between the gender and movie preferences that we have encountered earlier. Since we observe a correlations between patterns in the horoscope and events like marital bliss, childbirth and professions, we can use the existence of these correlations to  predict the occurrence of events on the basis of the existence of the patterns in the chart. As in the earlier case, there is nothing magical or supernatural about these predictions -- it is based on data and data alone. This ability to predict events without being concerned about the cause of the event is the basis of all forms of astrology.

These examples are taken from the area of natal astrology where the date and time of the person’s birth is the key variable but there are other types of astrology as well. For example, in horary astrology it is the date and time when a question is being asked and in mundane astrology or “Medini Jyotish”, it is the date and time of the creation or Independence of a country that is used to predict it’s destiny. In all such cases, the position of the planets at a point in time are the principal dimensions on which prediction models are built.

We have now overcome two major hurdles in our attempt to show the similarity between the predictive powers of astrology and data science. First, we have addressed the question of determinism and second, the importance or necessity of planetary positions. Let us now look at the next big hurdle -- the availability of data, or the lack thereof!

Data science begins with large sets of training data that has been collected in the past. It then uses mathematical techniques to deduce the rules of correlation that associate patterns of data with corresponding outcomes. In astrology, the history of this training data is lost in the mists of antiquity but the rules have survived. Are these rules perfect? Are they always correct? Most of them are, but possibly some are not,  but that is equally true for data science as well. Errors and wrong predictions are quite common in  data science but these can only be reduced if we have more and better data.

Physics as we know it today got a head-start over life sciences and social sciences because it was data driven. Tycho Brahe was the first European scientist who collected and collated a huge amount of data on the movement of planets. This data was subsequently used, first by Johannes Kepler to identify the correlations between duration and size of planetary orbits and then by  Isaac Newton who formulated the laws of gravitation. As an aside, it is interesting to note that Newton never really explained the cause of attraction, why bodies attract, but only identified the circumstances under which the attraction was observed. Eventually it was left to Albert Einstein to explain gravitation as arising out of the curvature of space-time but that is another story.

Like Kepler and Newton in the world of European physics, India has had sages like Bhrigu, Parashara and Jaimini who identified the laws of correlation that we have inherited today as the principles of astrology. But the the training data that might have been used to deduce these laws is not available any more. We can only speculate that Indian astronomers like Aryabhatta might have collected data like Tycho Brahe did, but unfortunately, there is no hard evidence for this. It has also been suggested that sages like Bhrigu had divine insight and rules of astrology were revealed to them through a direct and transcendent vision similar to the knowledge of the Vedas. We can respectfully consider such possibilities, but the exploration of such divine origins is beyond the scope of the current article. In fact it is best to keep religion and faith away from this discussion because astrology is not restricted to people of Indic origin or beliefs but is something that is found across many cultures in Asia and Europe. In fact, Tajik jyotish, one of the systems of Indian astrology -- like Parashari, Jaimini and others -- is supposed to have originated in the Middle East.

Data science validates its predictive models by testing them against a part of the historical data but astrology cannot validate its predictive models because there is no historical data to validate its models with. This is why classical scientists are reluctant to accept astrological predictions while being quite comfortable with the predictive abilities of data science. This can be addressed by creating a pool of training and test data from the personal information of thousands of real people. We need data on the  date, time and place of birth followed by data on key life events like dates of college admission, marriage, birth of children, entry into job, change of job, change of residence, major illness, loss of job, loss in business, death and illness of parents, spouse, siblings or children plus qualitative data like profession, level of wealth, happiness, spirituality, place of residence, relationship with spouse, siblings, parents children and so on. Coincidentally, a similar data collection is already happening every day in the world of internet and social media! Companies like Google, Facebook, Amazon, Uber and many others are already collecting personal data, often at the cost of privacy. Many of these companies have made it their business to collect personal data and then either use it to build their own predictive models or sell it to those who do. With a little bit of imagination, a similar data collection initiative could devise mechanisms that will incentivise people to voluntarily contribute data about events in their life, in return, perhaps, for a detailed astrological reading or other benefits.

Once sufficient data is collected it must be codified and stored with modern database technology so that it can be accessed from computer programs. Standard relational database technology can be used but since the data is of high dimensionality with many missing values, sparse matrix techniques or columnar databases can be used for efficient storage. Once the data is accessible to programs, then the same data science tools that are used by companies like Google to build predictive tools for, say, voice or image recognition,  can be used to either validate traditional predictive models of astrology or create a new rules of prediction. In fact, these new models may contradict traditional models and generate more accurate predictions. Going further, once we associate astrology with data science, then it can be included in the curriculum in universities. This will not only result in more structured research and better models but will also drive hundreds of fraudulent astrologers -- who sell fake remedies to gullible people, out of business. Astrology, like data science, can make predictions but cannot change destiny. There are some who claim that it could -- but that is another debate that is beyond the scope of this article.

Isaac Newton had said that he could see further because he was standing on the shoulders of giants. Astrology today is based on traditions of scholarship whose origins are long lost in the swirling mists of myths, legends and history. This traditional wisdom is an excellent foundation, a starting point, on which we could build the edifice of a new science of astrology that will be powered by tools and techniques that are commonly used in the corporate world today. Pattern recognition and machine learning techniques can be used to build predictive models with data  about key life events of thousands of interested volunteers connected through social media platforms. Such models will help identify natal planetary patterns, recorded at birth, and their degree of correlation with subsequent life events. This will either confirm, or contradict, ancient astrological aphorisms or even lead to new clues about what could lie in the womb of futurity.

As a data driven science, astrology must move from the Age of Parashara to the Age of Google.

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Acknowledgment : The astrological patterns alluded to in this article have been identified by eminent astrologer K N Rao and explained to the author by his IIT Kharagpur batch mate, Raghuram Hebbar, consultant engineer and amateur astrologer extraordinaire. Any misunderstanding or misrepresentation of astrological rules is obviously the fault of the author.

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This article originally appeared in Swarajya, the magazine that read India right

The fourth R : Computer Programming in Schools

The three ‘R’s -- Reading, wRiting and aRithmetic -- are the three fundamental skills that are compulsory in the curriculum of all primary schools. Should another R --  computer progRamming --  be also included as the fourth fundamental skill?  Computer programming -- as in Java or C++ -- is already being taught as an optional subject in many schools in classes  IX and X as  and Computer Science is generally available as the “fourth” subject in classes XI and XII. Then why do we need to make it compulsory and burden our already stressed out kids with one more subject?

Before we address this question, we must first stop viewing computers as just another career option, a vocational skill, on par with, say, medicine, accounting, music or sports.  Instead, we need to see it as an enabling tool that impacts all aspects of life. Programming teaches students to think logically, solve problems in a systematic manner and stimulates creativity. Eventually it will become a prerequisite to be able to share our world with artificial intelligence and even new forms of life! In this article, we explain why this is so.

A quick Google search on “why should schools teach computer programming” will throw up many pages that support the premise of this article and we will base our arguments on some of them. But before that, the very first step in our quest, namely searching in Google, reveals how entangled we are with computers. From the phone, through banks, e-commerce, GPS controlled app-cabs all the way to cars, aircraft and hospitals, nothing moves without a computer and each and every computer is controlled with a program. So at the very least, being able to write  computer programs ensures a degree of relevance in the employment market. But however powerful that may be as a reason to learn coding, the real reasons are significantly different and far more powerful.

In the past, managers would have secretaries who would, on their behalf, manage their “paperwork” consisting of physical “files” and postal mail. But today it is almost entirely a do-it-yourself scenario and people, including the most senior managers, have learnt how to perform these tasks themselves. A manager who needs a secretary today, to dictate memos to or to type, send and receive letters, would be a misfit in the corporate hierarchy. Replace the word “secretary” with an “IT professional” and the same would continue to be true for many corporate tasks. The ability to build a company website, to set up a system to accept customer feedback or carry out market research, to register members for an event and many other similar tasks, which in the past would have needed a staff from the IT department, are being done, or have to be done, by “non-computer” professionals. Just as knowledge of MS-Office and GMail have made secretaries almost obsolete, so has a whole range of free and easy-to-use tools, like Blogger and Google Docs, have made it almost essential for “non-computer” people to be able do what was earlier being done earlier by the “computer-people”. Similarly, students in schools need to learn computer programming not just to master Java and C++  but to facilitate their understanding of traditional subjects like history, geography, physics and chemistry. A certain fluency with computers is essential to explore new topics, through Google Maps and Youtube and software based science laboratories. A computer, like the English language, is no more an end by itself but a means, or medium, to reach out to and touch a vast realm of knowledge. Clearly, computers hold the keys to the new kingdom that is ruled by knowledge and information.

But does one need to learn computer programming to be able to use computers? Does one need to learn computer programming to be able to, say, use Blogger to create a website?  Or use Google Docs to create a workflow that routes an expense reimbursement request through an authoriser to the cashier who makes an authorised payment? Many of these tasks can be accomplished without writing a line of code as is the case when we use MS-Word to create a report.  But there is no doubt that having a fluency with coding gives a tremendous advantage, and more importantly the confidence, to be able to configure and implement these apparently codeless systems.

Programming, teaches one how to break up a big task into a set of smaller tasks, define the sequence in which these smaller tasks need to be done, or, under which circumstances some of these tasks need to be replaced by other similar tasks ( IF - THEN - ELSE ) and how many times each of these tasks need to be performed ( in a LOOP ) to achieve the final goal. The ability to think in such a structured manner is the key to the successful execution of any complex activity. This includes domestic chores, like cooking, where a recipe is actually a non-digital program, through corporate tasks, like manufacturing goods in a factory, to society wide programs like implementing Swachh Bharat or GST. Hence teaching a student how to write a computer program will in fact equip her with a crucial set of skills that is essential for the successful execution of a whole range human activities. This is where computer programming becomes as essential a skill as language and mathematics. Just as language and maths skills are useful even if the student does not become an author or an accountant, computer programming is a skill that remains important and useful even if the student has no intention of becoming a professional programmer.

How easy is it to learn computer programming? Many kids pursue a liberal arts education perhaps because they are so inclined but also possibly because they are mortally afraid of science and mathematics. Would it not be an unnecessary overload if computer programming is imposed on them? Not really. While the rules of  languages like Java and Python, so beloved of professional programmers, may deter those with a disposition towards the liberal arts, there exist many languages that use graphical metaphors to accurately represent complex programming constructs in a way that almost any child will be able to use with a ease and pleasure. Scratch, created at MIT Lifelong Kindergarten Lab in 2003 and subsequently adapted by Google and released as Blockly, is one such language. Components of this language are represented by coloured blocks that students have to collect, arrange and “stick” together, to create programs that perform desired tasks like leading a butterfly to a flower while avoiding a cat. Hidden in all these playful constructs are hard core programming concepts that can be revealed, if the child so desires, as actual Python or JavaScript code that will run on a real computer. Blockly is available at many portals like Code.org where it is used to create delightful modules that teach computer programming through self-driven exercises. These modules can be used not just by students of different ages but also by adults who have never written programs.

But the greatest value of teaching computer programming is the sense of empowerment that it fosters in students by allowing them to actually create something tangible. While many programs perform the same task or look similar, each program is in fact an original creation of the person who has coded it and there is no joy as overpowering as that that is felt when a program executes and does what the programmer wanted it to do. One of the unfortunate drawbacks of India’s school education is its emphasis on rote learning, on memorising, and its utter inability to incentivise students to create something original. Programming allows every student to virtually create something original and with a little effort, this can be hooked to or extended into the physical world.  For example, products like Mindstorm from Lego allow students to build and control robots that move while others allow the creation of apps that run on phones and tablets. As an aside, products like Twine allow those who wish to be authors, journalists or movie makers to create structured storyboards that help them put together storylines and presentations that do not follow a linear structure.

Creativity, whether strong or weak, is inherent in every student and teaching computer programming from a young age is perhaps the best, or easiest, way to nurture this precious asset. By being able to create something unique, each and every student gets the confidence that she too can build the kind of toys and gadgets that she sees in the market and in people’s hands. Sixteen year old Kavya Koparapu, originally from India and currently studying in a high school in the US, has built a lens-and-app contraption that helps diagnose critical eye diseases. Stories like this can emerge from India only when our own kids get the confidence to be able to build products from an early age.

Can schools in India afford to teach computer programming? Let alone teachers, do we have the infrastructure? When schools do not have books and blackboards should they even think of acquiring computers where students will learn programming? Good questions. For private schools this is a non-issue because most of them have infrastructure far in excess of what is required to teach programming but for government schools, this could be a dilemma. This is a different problem and the answer lies elsewhere. The real problem in government schools is not the lack of money but it’s rampant misuse. If this can be curtailed and if some of the sops that are handed out during elections can be diverted towards schools and not stolen, then there will be no shortage of computers anywhere. Management of money, not money itself, is what our schools lack.

The evolution of natural languages has shown that the ability to communicate is an essential driver of the evolutionary ascent of man. Without being able to communicate, the solo ape could never have come together to form flocks and packs which eventually became clans, tribes, nations and finally the civil society that we see today.  But in the last thirty years there has been the far more rapid evolution of a parallel intelligence in digital computers. This began with machines beating humans in chess and it now threatens to replace humans in many business and industrial activities. The social impact of the rapid rise of this artificial intelligence [see author’s article in Swarajya, March 2017] is still not very clear but there is no doubt that it represents a new kind of species, a non-biological, perhaps non-physical species, with which traditional biological species will have to share space in the future. Also, the rise of genetic engineering and biohacking [see author’s article in Swarajya, April 2017] is leading to the creation of man-machine hybrid cyborgs.  Machines with artificial intelligence are rapidly acquiring natural human language capabilities so as to be able to work better with humans. In some cases, as in the case of the famous Facebook example, “they” are learning to create their own languages. In this context, it is equally important for human beings to be as just adept with computer languages so as not to lose the advantage when interacting with this digital species.

In the past, people would learn foreign languages to benefit from commercial and cultural ties with foreign nationals with whom they share the world. In the future, people will need to learn the language of this new digital species with which they will share an ecosystem that consists of both man and machine. That is the real reason why we need to teach computer programming in schools, not just because it is a skill that helps one get a job in the IT industry.

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This article was originally published in Swarajya, the magazine that reads India right.

Managing GST efficiently with Blockchain and GSTCoin (⇞)

Bitcoin is the rage! With an unbelievable appreciation in prices, many people want to invest in this red-hot cryptocurrency but whether the current valuation is a bubble that will burst is an open question. What is indisputable however is the immense versatility of the blockchain technology that is used in bitcoin -- and all cryptocurrencies. GST too is the rage, or rather the cause of rage because of the inefficiency of the software implementation. This article explains how a decentralised blockchain application could solve GST problems. But what is bitcoin?

image borrowed from financeminutes

A bitcoin is a unit of value, like an equity share of a company, that can be owned and transferred. It resides in an account in a ledger, like a dematerialised share in a demat account with NSDL. The account number, the public key of the account, is known to all and so anyone can send or deposit demat shares into this account. However to sell or transfer shares out of this account, the anonymous account holder must use a password, a private key that only he knows, to create and publish an outbound transaction pointing to another account identified by its public key. In cryptocurrency jargon, an account is called a wallet and the ledger is called the blockchain. A wallet is defined by a {public-key : private-key} pair consisting of two very large numbers that have special cryptographic properties. But what is really novel is that the blockchain ledger, the record of all transactions, is not maintained by or at any one institution, like the NSDL for equity shares, but jointly by all participants in the network. Everyone has a copy of the blockchain-ledger that has a record of all coin transfers and so everyone can both verify and confirm each transaction before they accept it in their own copy. An invalid transaction can pass into the blockchain-ledger if and only if, it is accepted by more than 50% of the network and this has never happened since 2009.

Verification means that a payment transaction is valid -- the total value of all inbound or credit transactions to a wallet less value of all outbound or debit transactions is more than or equal to the current outbound debit transaction. Confirmation means that there is no double spend and the same set of unspent, inbound, credit transactions (“UTXO” or unspent transactions outputs) are not being used to create more than one outbound payment transactions. Since everyone has access to all transactions, anyone can perform the verification and confirmation. But because this needs a lot of computational power, this task is voluntarily done by a group of miners. As a reward for doing this public service, miners who run a full node blockchain software on a powerful computer, are rewarded with newly created coins that are added to their wallet when they have verified and confirmed a new block of transactions -- that is then added to the blockchain. However the reward is not given to any miner who performs the verification and confirmation but to the one specific miner who, in addition to the verification and confirmation, also solves a difficult mathematical puzzle first.

The payment, or output  transaction that deposits a newly created coin into a successful miner’s wallet is called a coinbase transaction. It is different from all other transactions because it is not backed by any previous input transaction. Hence the analogy of mining, as if a coin was dug out of the ground and not received from anyone else, whereas all other coins would have to be received from someone before they can be sent to someone else. However a better analogy would be to view bitcoin, as sweat equity that is given, in lieu of salary, to the accountants in a bank for checking and approving all transactions. The brilliance of “Satoshi Nakamoto”, who designed bitcoin, was in equating the sweat equity of the bank to the assets that are managed by the bank and initiating a self-sustaining network that is working flawlessly since 2009. The magic mathematics of cryptography ensures that this decentralised autonomous organisation (DAO) runs without any formal management and yet has achieved a market capitalisation of over US$ 70 billion.

But why should these “sweat equity” shares of a non-existent bank, the actual bitcoins, be each worth thousands of dollars today? Many people, who are not miners, buy these coins from the miners for investment or payment purposes and this demand is pushing up the market price.  Bitcoin can be purchased at many cryptocurrency exchanges with fiat currency like US$ or INR ₹. After KYC compliance, these exchanges will convert fiat currency into cryptocurrency and vice versa at market driven prices. Bitcoin is both a currency that is extremely useful as a payment mechanism because transfers are simple, fast and anonymous and is also a commodity that has appreciated in value and hence worth investing in.

How can GST use this technology?

Bitcoin is the most popular and valuable coin but there are many others. The software to create similar coins is freely available and anyone can do so. But these alternate coins do not have any value in the bitcoin network because transactions with these coins lack the cryptographic signatures of past owners that are necessary for verification and confirmation. However these coins can have value in other networks where they are recognised and traded.

Let us consider a scenario where where we have 4 companies identified as A, B, C and D. C buys ₹1000 worth of goods from A and ₹ 2000 worth of goods from B. Assuming GST @ 18%, C pays ₹ 1180 to A and ₹ 2360 to B. D buys ₹ 5000 worth of goods from C and pays ₹  5900 to C. Under GST rules, A, B, C are required to deposit ₹ 180, ₹ 360 and ₹ 900 respectively to the GST Authority (GSTA). However C can claim ₹ 540 as GST Input Tax Credit and deposit only ₹ 360 provided GSTA has evidence, that A and B have made the corresponding deposits on behalf of C.

The idea is simple but the process is very complex and laborious. There are millions and millions of GST transactions and all this data accumulates in the central GSTA database. GSTA needs to run a  matching exercise within this huge and ever expanding pool of data and identify the two deposits from A and B that benefit C. This is a big bottleneck, a possible single point of failure and so cause of delay before C gets credit for ₹540.

Instead, let the GSTA define a new cryptocurrency called GSTCoin identified by the symbol ⇞ and through an Initial Coin Offering (ICO), release, say,  ⇞100 crore into its own GSTCoin wallet. To deposit GST, one has to purchase GSTCoins of equivalent value.  GSTCoins (⇞) can be purchased at one of many GST Exchanges (GSTX) operated by, say, banks. Every GST registered company will need a GSTCoin wallet whose public key is, for example, the GST registration number. This GSTCoin wallet will be hosted by the same GSTX where the GST registered company becomes a member and this will hold balances in two currencies namely, Rupee (₹ ) and GSTCoin (⇞). As in any currency exchange, the fiat currency Rupee (₹ ) may be deposited from and withdrawn into a traditional bank account using NEFT or credit card. GSTA too will have a wallet in each GSTX.

A GSTX would differ from a normal cryptocurrency exchange in two ways. First, members can only trade with GSTA, not with other members. When a member deposits GST, he actually buys GSTCoins(⇞) from GSTA, using either his Rupee (₹ ) balance or his GSTCoin (⇞) balance. The second key difference is that the purchased GSTCoins (⇞) are not delivered to the purchaser’s, wallet but to a public key associated with the wallet of the beneficiary that may be on a different GSTX. This is quite easily done in any cryptocurrency network. If the identity of the beneficiary for whom GST being paid is not known, or if the beneficiary does not have GST registration, then the GSTCoins are delivered to a special terminus wallet of the GSTA.

All transactions are recorded in the GSTCoin blockchain ledger and a full copy of which is maintained by all those who runs a full node on the GSTCoin network. Any organisation with an interest in the GST network, including large GST payers, may run these full nodes.

In our case, A and B will first deposit Rupees into their respective GSTX wallets and then buy GSTCoins worth ⇞180 and ⇞360, respectively from GSTA using their Rupee balances.  These will be delivered to the wallet of C which will now show a credit balance of ⇞540. Since GSTCoins could not have been transferred from the GSTA wallet to C’s wallet without a corresponding GST payment in either Rupee or GSTCoin, there is no further need for any matching. The GSTCoins in a beneficiary’s wallet must have been received against some GST deposit somewhere. Hence credit is automatic and instantaneous. For the GST deposit that C needs to make on his sales to D, he will purchase a total of ⇞ 900 GSTCoins through two transactions :  a ⇞540 transaction from his GSTCoin balance and a ₹360 transaction from his Rupee balance. This fulfills his obligation to deposit ₹ 900 as GST while actually spending only ₹360. In case D is registered for GST, the ⇞900 GSTCoins that have been purchased by C will go to D’s wallet. If D is not registered, ⇞900 GSTCoins will be delivered to GSTA’s own terminus wallet where it will be accounted for as nett GST received.

As in any cryptocurrency network, all transactions will be verified and confirmed by miners who operate full nodes and who, on finding a block of valid transactions, will be rewarded with a certain number of GSTCoins through a coinbase transaction. Like any other GSTCoin, these too can be used for GST deposits.

How is this blockchain based architecture any different from the current architecture of the GST software application that runs on a centralised database? Can we not modify this centralised software to make automatic NEFT or UPI payments to beneficiaries when GST is received? Functionally the two architectures are no different. But by physically distributing the processing requirements across multiple GSTXs we eliminate bottlenecks caused by the limitations in the computing power of a single central machine. Such a distributed system is inherently scalable and will not get choked by high transaction volumes. So delays associated with uploading data and transferring credit will be significantly reduced. Moreover, as a distributed system it will be almost immune to any form of hacking or disruption at any single point of failure. Finally, there is total transparency because the blockchain database is immutable and visible to the network of full node operators.

One challenge is privacy. Since all transactions are visible to everyone, all GST deposits and hence corresponding purchase prices are in the public domain. Fortunately all cryptocurrency wallets allow the creation and management of any number of public keys and it would not be difficult for the depositor’s wallet to pick up a new public key from the beneficiary’s wallet before initiating a GSTCoin purchase transaction, and use that to deliver the GSTCoins. This will make all blockchain transactions anonymous while leaving a clear audit trail within the wallet of the depositor that can be used in case of any subsequent disputes. In fact the wallet itself could automatically generate the GST return on a daily basis.

Another challenge is that GST consists of Central, State and Interstate GST and dues in one category cannot be offset with credits in the other. This problem can also be easily addressed by creating three different GSTCoins, say of three “colours”. The wallets will become a little more complex, but the same underlying principles can be used to meet the requirements of three different, but similar, taxes.

With the RBI apparently exploring the possibility of its own cryptocurrency, the GSTCoin could be a good way to test Blockchain technology as well as improving the efficiency of the current GST system.

This article has been written with help from Bhartendu Tilak, a Chartered Accountant and a colleague of the author. Any inaccuracy or inconsistency is of course the responsibility of the author.

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This article originally appeared in Swarajya, the magazine that reads India right