Data as a Currency

Jake Curreri
Sep 6 · 5 min read
Getty Images

Cambridge Analytica: Explained

A household name even to those unfamiliar with the big data world: Cambridge Analytica.

In 2014, Aleksandr Kogan, a professor at Cambridge University, programmed a Facebook survey application. The app paid users ($1‒$2) to take a personality quiz, requiring user consent to give the app access to their Facebook profiles and those of their friends. The paid task was advertised to remote freelance workers on Mechanical Turk, a crowdsourcing online marketplace controlled by Amazon. Only about 270,000 Facebook users actually took the survey.

Because of Facebook’s permissions at the time, the survey software was able to “scrape” data from the accounts of the Facebook friends of Facebook users who took the survey, finally collecting data on about 50 million Facebook users. This data was then sold to Cambridge Analytica for ~$7M.

Cambridge Analytica constructed personality profiles similar to IBM’s Watson AI, creating predictive analytics to control voter habits for the 2016 election.

What this meant for the Big Data world

GPDR, CCPA, and furthermore privacy acts quickly followed, boasting regulations that require businesses to protect the personal data and privacy of users. Non-compliance resulting in heavy company fines.

  • Google (January 2019, France, €50,000,000): Google was fined from France’s data regulator, citing a lack of transparency and consent in advertising personalization, including a pre-checked option to personalize ads.
  • British Airways (March 2019, £183,000,000): As a result of an attack on British Airways’ website, about 500,000 customer records were extracted by a malicious third party. The UK’s data protection agency claims BA’s website was compromised due to poor cybersecurity arrangements. This would represent the largest GDPR fine to date.
  • Haga Hospital (July 2019, Netherlands, €460,000): A Dutch hospital was fined over lax controls over logging and access to patient records. In one instance, 197 employees accessed one Dutch celebrity’s medical records.

Privacy & Security Futures for Big Data

Increases in data privacy and security stem from growths in social engineering. Most modern “hacking” is not done with a computer but with a simple phone call. Thereby, the crackdown continues.

  • Data Privacy: Controlling the flow of personal information. and
    the right to control how ones’ information is shared with
    others via digital channels.
  • Data security: Keeping customer data safe and also keeping company intellectual property, employee information, and many other data sets secure. This includes internal policies on how data is accessed.

Example Policy of GPDR: Clear, transparent consent practices and privacy policies. Under the regulation, companies can no longer hide behind murky and confusing privacy policies. Instead, consent policies must be easy to understand and “request for consent must be given in an intelligible and easily accessible form, with the purpose of data for processing attached to the consent.” In addition, companies must make it easy for consumers to either give or withdraw consent as desired.

Data has entered the state of an ownership battle. Does a consumer truly have a right to their data? If so, what extent beyond that right — if any — can companies leverage the data sets? By extension, what does it mean to have a “right to your data”?

Data has entered the state of an ownership battle.

Old iPhone Data Usage by Benjamin Dada

Data as a Currency

Aleksandr Kogan had part of the model right: pay consumers for their data and willingness to interact with services. Where he went wrong is by not allowing a public ledger of how consumer data is being utilized.

Blockchain providing Big Data transparency

A transparent, public ledger of interconnected data usage: Blockchain. By applying blockchain principles to the network of data arbitrage, you — the consumer — will regain access to your data usage as well as the anonymous data usage of your piers.

This leads to a global network of transparent data usage. Regulations can be easily applied to prevent voter manipulation crisis such as Cambridge Analytica long before the damage is done.

Your first data payment: $26.00

The true value of the survey submissions for Kogan’s app was $25.90 per entry.

Imagine an application in which you were paid $26 to take a 3-minute survey. In addition, where you were able to access the information and channeled network in which the data’s usage was transparently displayed. An app in which you were paid to use Facebook, Twitter, Instagram, Google (4 conglomerates buying and selling consumer data on the regular) as well as many other popular websites and mobile applications.

Imagine an application in which you were paid $26 to take a 3-minute survey…in which you were paid to use Facebook, Twitter, Instagram

The byproduct of this app is authentic data transparency. You know how your data is being used and by what societal influences this data’s impact reaches.

Gain true ownership over your data

Data ownership is decentralized. The concept of data as a series of bytes and bits connected by PIIs (Personally Identifiable Information) joins a person to their buying and internet habits. A PII includes your name, address, primary phone, email, and zip code, for example. This information is systematically updated (typically after being sold) through USPS (yes…), credit agencies, CPG (Consumer Packaged Goods) loyalty cards, and even through updating account information on a website.

MAIDs (Mobile Advertising IDs) connect a person’s mobile device to their PII. These are defined backdoor through popular apps such as Instagram, Twitter, or Facebook when you log in on a device.

Currently, you forfeit your PII any time you interact with an organization or their product — through any credit card purchase (high hopes for Apple Card’s data privacy) — or simply using service-at-convenience apps like Instacart. Some companies are fighting the trend. Netflix is a known anarchist of selling such information.

You will never own 100% of your data as related to your PII, yet you can be the majority owner. This is a forced model created from your habitual cookies and session storage from various websites and mobile applications.

The objective is to be the majority owner in your data, yielding the greatest return on investment for your consumer habits and turning that investment into a byproduct currency.

Revenue Dashboard | Photo by Austin Distel via Distel

Bits: Data as a Currency, Transparency as a Product

We’re actively developing a solution to this data pandemic, and it’s called Bits.

By signing in to your daily apps and e-Commerce sites with the Bits login, receive daily payouts for your data usage. Restrict organizational access and see the marketing pool your data connects.

Bits is the tool advancing civilization beyond a digital world “behind the curtain” and into a space of transparency and accountability amongst the large monopolies profiting on your information.


We inspire world-changing ideas and craft cutting-edge technologies through the development of meaningful brands, creative strategies, and innovative software.

Jake Curreri

Written by

ceo @, cto @, lover of functional programming, crafter of elixir, ruby, and react applications.


We inspire world-changing ideas and craft cutting-edge technologies through the development of meaningful brands, creative strategies, and innovative software.

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