Why We Need A Data Swaraj Resolution

Why We Need A Data Swaraj Resolution

by Tanuj Bhojwani - Tuesday, January 1, 2019 04:22 PM IST
Why We Need A Data Swaraj ResolutionRepresentative image (Peter Macdiarmid/Getty Images) 
  • India, not having the baggage of an existing data privacy law, can choose to go for a radical assertion of users’ rights over their own data.

Software is eating the world. This is an oft-repeated proclamation in Silicon Valley, originally coined by Marc Andreessen. The claim is that when you zoom into the technology space, it is neither computers nor mobile manufacturers, and not even Internet service providers that are capturing value.

The widespread existence of personal computing devices connected to the Internet means that the action now is all in the software. Software is the layer, which wills a computer or many computers connected over the Internet, including your handheld devices, to do an increasingly complex set of tasks.

This layer of software is able to replace entire value chains of traditional businesses at a very, very rapid pace. Take for example, the space of finance. In 2011, China sent almost no money over mobile payments. In 2016, its mobile money market was $5.5 trillion, 50 times that of the US.

Based on the success of its payments, Alibaba launched Yu’e Bao, which means ‘leftover treasure’. The app reminds users to move change from their mobile wallets into a money market fund for higher interest. Started in 2013, in just four years, it became the world’s largest money market fund.

Sceptics could argue that the act of moving money and moving bits have never been too different, so software may eat finance, but does it mean it is eating the world? One could keep listing examples from fields that are traditionally seen as non-software, but are being disrupted by software.

Take Netflix for example. Originally, in the business of shipping DVDs, Netflix today is arguably the largest channel of distribution of entertainment content in the world. It consumes 15 per cent of the global Internet bandwidth on average, and as much as 40 per cent during peak hours. It is very clear that software has ‘eaten’ how we consume content. Netflix chief executive officer Reed Hastings once commented that their competition isn’t the movies, “we actually compete with sleep”. “And we’re winning!” he added.

Netflix has gone from simply distributing content to making content. Netflix’s first original series was House of Cards in 2013. Fast forward to four years later, Netflix released an estimated 126 original series or films in 2017 for a total cost of $6 billion, more than any other single American network or cable channel. It was nominated for 91 Emmys, second only to HBO’s 110.

Not only did Netflix start making content, it became really good at making it too in just four years. Once Netflix owned the distribution, it could figure out exactly what its users liked and disliked from their behaviour of watching millions of hours of television.

So, finance and entertainment have been eaten by software. Does that mean every industry will follow? Well, once you start bringing artificial intelligence (AI) into the fold of software, things that we thought were inherently hard for a machine become possible too — from being a doctor to an artist. It is hard to deny that software is eating the world, and the sooner we see this as a forecast rather than a catch phrase, the sooner we can start reacting to the very real dangers of a world eaten by software — data colonisation.

To understand data colonisation, we must ask what is it about software that makes it simultaneously great at being a bank and at being a film producer. There are three critical things.

First, software is infinitely malleable — it can be written, rewritten, copied and deleted much more easily than any other structure built to govern a task.

Second, software tends to generate a much richer, more precise and seemingly infinite exhaust trail of user data. It lets businesses know, in the most direct manner, what their consumers do, what they like and dislike, what they are looking for and what they do when they find it.

Third, by using the data generated by its user, software companies improve their product offering to appeal to more users, who in turn generate more data, and a flywheel effect is generated. Once kick started, this data-driven machinery self-perpetuates, and is sometimes called the network effect. With AI in the mix, the improvements in the product are now dramatic, and the flywheel seems impossible to stop.

To feed this flywheel, tech companies are willing to service you sometimes even for free, as long as you kept giving them your valuable data. In a perverse way, while the product may have been ‘free’, the currency of exchange here really is your data. Further, they build a set of ‘convenient’ products around their core offering, but it only works well if you also use other products from the same company.

For example, your latest Apple product will play your customised music when you get home — but only from your iTunes library. It isn’t a coincidence that these companies are able to raise eye-popping amounts of capital, at sky-high valuations; the price premium is attributed on the near exclusive datasets that these companies have on their consumers. With a powerful mix of cheap, deep capital and large datasets, companies today are creating a barrier to entry unlike any other in history.

What is more perverse is the control of the narrative that these companies have had on their own progress thus far. Until the Cambridge Analytica scandal broke, this form of rapid capture was seen as ‘innovation’. Silicon Valley tech entrepreneurs were seen as missionaries out to “change the world”. They didn’t build empires, they built ‘products’. Data collected on users being used as barriers against them was seen as ‘core assets’ or ‘moats’.

Undercutting upstarts, as well as small and medium enterprise and driving them out of businesses is called, without the slightest hint of irony, “crushing it”. Sympathisers often call the usage of the term colonisation too harsh, and prefer the more positive sounding ‘disruption’ instead.

Regulators, who try to implement checks and balances, are seen as ‘anti-innovation’ or ‘regressive’. But it is precisely this control of language around the nature of business of these platforms that makes them even more dangerous. It’s happening right under our noses, and they’ve convinced us to look away.

Truth is, when the flywheel is in full motion, no longer can individuals negotiate their rights with these platforms fairly. Competition is ‘crushed’ or acquired before they become a meaningful threat. When it comes to privacy, the approach offered usually is “take it or leave it”.

Government interventions often cannot change the way they operate. Many of these companies have more free cash than the gross domestic product of the nations they are negotiating with. Many sympathisers argue that not all tech companies have been guilty of using user data against users themselves, so why should we be fear-mongering by calling it data colonisation?

Because we’ve heard this argument before, apologists of the empire would often point to the railways or the education system as gifts of the British Raj. But Maharishi Dayanand Saraswati pointed out, that good governance is no substitute for self-governance, and hence, swaraj. To be clear, in the context of data colonisation, we’re not asking for our foreign overlords to be replaced by Indian ones. We’re asking for our rights over our own data, to prevent having any masters at all.

Last year, a landmark judgement in the Supreme Court of India recognised privacy as a fundamental right. We can go further. India, not having the baggage of an existing data privacy law, can choose to recognise that user data belongs to the user, and not only to the platforms on which they are created. Recognising that ownership can lead to the affirmation of many rights that are not only necessary for protecting citizens but also empowering them to use their data for their own benefit, in a manner that they see fit.

The principle of data swaraj is not impossible nor is it too ambitious. If it sounds radical, it is because we’ve been lulled into believing that the only way data can be put to good use is if we let tech companies use it unabashedly and allow ‘innovation’ to happen.

There is no reason to believe this is true. Even the inventor of the world wide web, Tim Berners Lee, is creating a similar view of personal online data stores through his new startup, Solid.

In India, the fourth layer of the India Stack, known as the consent layer offers a way of asserting control over your data. In summary, the technology for data swaraj exists. The question we must ask ourselves is do we have the will to fight for the independence of our data?

Tanuj Bhojwani is a fellow-in-residence at iSPIRT Foundation. Most recently, he helped the government formulate and implement Digital Sky, a real-time low altitude notification and authorisation platform for commercial drones.

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