“Torture the data, and it will confess to anything.”
– Ronald Coase
 
The mystery behind the unprecedentedly foolish decision of demonetisation of 86.4 percent currency may never be fully unravelled but by now it is clear enough that it was taken by none other than der Führer of the Indian Reich, Narenda Modi. In a style, characteristic of his mother organisation, Rashtriya Swayansevak Sangh (RSS), Modi kept shifting the goal posts every time the foolishness of the November 8 decision unfolded.

When the system failed miserably to provide cash to people, he swiftly asked them to go digital; to make India a cashless economy, later moderated to a less-cash economy.

While launching an Aadhar-based e-transaction biometric app abbreviated as BHIM (Bharat Interface money) on December 30, he did not forget to score a political point saying it was named after Babasaheb Ambedkar. However, it failed to cut ice with people, scores of whom were driven to starvation and literal deaths by then.

The foolish expectation that a significant amount of old currency in black money would never come back, when over Rs. 15 lakh crores amounting to 97 percent of demonetised currency was already back into the banking system, spelt another slap in the face of the government.

Modi then swiftly shifted his goal post by saying that the data generated by the process of demonetisation would be mined using analytics tools to catch the black money culprits. Scores of Modiphiles eager to uphold his irrational move rushed to pontificate on how big data analytics can help eliminate black money, not realizing that the data lacked the crucial bit.  

Alchemy of Analytics
Big data is typically defined by three Vs, Volume (hugeness of data), Variety (multifariousness of data- audio, video, text, signals), and Velocity (rapidity with which data swells). Analytics is the combination of statistical modelling and machine learning. Big data analytics examines large and complex datasets to uncover hidden patterns, unknown correlations, trends and myriad other useful information.

But while this is all true, it is not a magic wand to produce something out of nothing. True, Currency notes have a country identifier, denomination, unique serial number, and a mechanism for counterfeit prevention. This data can be captured easily and in real time by cash counting machines provided they are equipped with sensors to detect and store serial numbers of currency notes that are run through them. With these data the notes can then be traced to the end user or account holder. The algorithms can be built to indicate the rough location of hoarded money once the collected data is run through them.

But as for the demonetisation process data, the fact remains that the counting machine in banks did not have the requisite sensors to collect the serial number of currency notes. In the absence of this crucial data, there is no way to construe deposits of money as illegitimate, least, to trace them to some person.

The ways in which the old currency was exchanged with new ones are: (1) Ordinary people exchanging their hard earned money standing in queues, (2) Exchanging through agents paying commission ranging from 20-40 percent and (3) Deposit by paying penal tax at 50 percent.

Of these three, only the middle one is illegitimate as it converted black money into white. It happened in two ways: One, through the connivance with bank officials, and two, by engaging a battery of poor people to exchange old currency at a commission of around 10 percent. Crores of rupees have been exchanged by these methods.

What could analytics make out of these data? Expectedly, there will obviously be a big surge in bank deposits but can it be construed as illegitimate money? The only thing demonetisation has done is to convert the black money of criminals into white, thus rewarding them.

Fooling the People
As explained in my earlier column (December 3, 2016) the black money in cash (that includes jewellery) is just about 5 percent. Therefore, if the intension was to trace black money, the currency was an unlikely candidate.

The fountainhead of black money is corporate with its patronage network in politicians and bureaucrats. Interestingly, this very source has Modi’s personal protection. He has given tax exemption to donations to political parties to the extent of Rs 20,000 per donor. The political parties thus became a conduit to make black money white for criminals.

None other than Nasim Zaidi, chief election commissioner has termed these political parties, numbering today over 1900, “as conduits for siphoning off black money”. Of course, the main beneficiary is the BJP. Pretending to catch suspect cases by sifting big data of currency deposit is like trying to catch the fish after letting bulk of them escape through a big hole in the proverbial net.

Is Modi going to flag the peaks in deposits before the declaration of demonetisation? After all, his claim of secrecy of the decision is exploded by the media reports that there were huge transactions in previous quarters. There is no intelligence needed to know that they all belonged to the inner circle of the BJP.

Do you really require BDA tools to identify pickpockets in the crowd when there are robber gangs roaming around in broad daylight? They verily belong to Modi’s own political class.

If the rise in assets were a proxy for corruption, BJP clearly scored over the Congress. Whereas the assets of BJP’s re-elected MPs jumped from Rs 5.11 crore to Rs 12.6 crore in 2014, an increase of 146 percent, that for the Congress saw an increase of 104 percent, rising from Rs 5.66 crore in 2009 to Rs 5.90 crore in 2014.

According to report compiled by Association for Democratic Reforms (ADR) based on the election affidavits of the candidates, the assets of 165 MPs re-elected to the 16th Lok Sabha (of the total 168, the affidavits of three MPs being not clearly available on the ECI website as per ADR), had on an average risen by a whopping 137 percent between 2009 and 2014.

Modi’s own party topped the list in both assets as well as criminal cases. In Uttar Pradesh, where the BJP won 71 out of the 80 seats, Varun Gandhi saw his assets grow by 625 percent. In 2009, according to Varun's affidavit, his assets stood at Rs 4.93 crore. In 2014 it shot up to Rs 35.73 crore, an increase of Rs 30.81 crore. His mother Maneka Gandhi’s assets saw a rise of 105 percent. If the rise in assets were a proxy for corruption, BJP clearly scored over the Congress. Whereas the assets of BJP’s re-elected MPs jumped from Rs 5.11 crore to Rs 12.6 crore in 2014, an increase of 146 percent, that for the Congress saw an increase of 104 percent, rising from Rs 5.66 crore in 2009 to Rs 5.90 crore in 2014.

How come these politicians claiming to do public service are transformed into financial wizards is a question that Modi needs to answer. Varun Gandhi, who had never been to a college, could beat the best of the MBAs! Similar wizardry may be observable in the cases of bureaucrats, without whom politicians’ wizardry may not be possible.

It is an open case that bureaucrats, particularly those controlling administration, police, and in regulatory posts, etc. all have huge assets disproportionate to their source of income. How many of them are ever investigated, least, convicted? The vulgar inequality that brings India a dubious distinction as the most unequal country in the world, with its 57 billionaires owning up 58 percent of its wealth[i] is after all not produced by honest money. 

Issues with Analytics
BDA’s new paradigm of data driven decision has enormous implications, both positive as well as negative. Philosophically, it spells the ‘end of theory’.[ii] Big data looks for the correlation rather than the causation–the "what" rather than the "why”. To those who are enamoured by this new paradigm, a recent White House report “Big Data: A Report on Algorithmic Systems, Opportunity, and Civil Rights” may serve as caution about its risks. 

It states, “[t]he algorithmic systems that turn data into information are not infallible–they rely on the imperfect inputs, logic, probability, and people who design them.”

An earlier White House report had warned of the potential of encoding discrimination in automated and secretive decisions that analytics entail through its complex algorithms. The benefits of big data are seriously tempered by concerns over privacy and data protection. Advances of the data ecosystem upends the power relationships between government, business, and individuals, and can lead to racial or other profiling, discrimination, over-criminalization, and other restricted freedoms.

While the entire world is concerned with these issues the Indian government is pushing its digital juggernaut oblivious of its harms. It is upbeat about Aadhar data which it wants to leverage for digitising every transaction with biometrics as identifier.

Despite experts’ demonstrations that biometrics are unreliable for financial transactions, Modi flaunted BHIM as “your thumb as your bank”. Contrary to its stated objective to create a unique identity, soon after Aadhar was launched in 2009, an Aadhar-authentication Application Programming Interface (API) was created, making it available for businesses.

BDA’s new paradigm of data driven decision has enormous implications, both positive as well as negative. Philosophically, it spells the ‘end of theory’. Big data looks for the correlation rather than the causation–the "what" rather than the "why”. To those who are enamoured by this new paradigm, a recent White House report “Big Data: A Report on Algorithmic Systems, Opportunity, and Civil Rights” may serve as caution about its risks. 

As Nilekani, its architect recently averred, just an “Aadhaar-enabled biometric smartphone” is estimated to create a $ 600 billion opportunity.[iii] There is of course not an iota of consideration to what happens to the privacy of Indians or security of their crucial data.

When this issue came up in the Supreme Court in August 2015, the Attorney General had settled it saying that the people of this country do not have a right to privacy. Interestingly, in the case to strike down defamation as a crime, around the same time, the government pleaded exactly opposite that they had to protect the privacy rights of the people.

The Supreme Court had rightly restricted the use of Aadhar card to only six areas – rations in the public distribution system, liquefied petroleum gas, the Jan Dhan Yojana, the National Rural Employment Guarantee Act, and pensions – and that too, voluntarily. But in utter contempt of it, the government has been bull-dozing it to make it mandatory all over. Obviously, it wants to take complete control of our lives in contravention of the Constitutional guarantees and reduce us to be the guinea pigs, the subservient automatons, with application of Big Data Analytics.

When people could quietly endure the disaster of demonetisation, this malfeasance perhaps may be a minor irritant!