Data is Money

When I use Google Search, I don’t pay anything. I get a great service but I don’t pay them cash for it.

There’s a popular expression now: “if you’re not paying for it you are not the customer. You are the product.”  I like this expression, because it captures the way I feel about the Google and Facebook (GAF) business model. But while I like it, I no longer agree with it, because it’s not an accurate picture of my relationship with GAF. I am a customer, and I do pay for their services. I just happen to pay in data, instead of dollars.

Data Is Money

Data is now a currency. With data I can buy thousands of apps on the Apple App Store. I can search the web, the world’s academic journals, and millions of photos of cats doing funny things. I can send and receive email. It’s the business model of the Internet, and it has its limitations, but nevertheless it is here.

Data is money. In exchange for creating, and then transferring data to GAF, they give me a web service. Both companies specialise in aggregating all that data and selling it for dollars to advertisers. In effect, there is a data to dollars exchange rate (and, you’ll note, a dollar to data one too).

Data is Money. Not like money, or as good as money. It is money.

Anthony, Brazen Thoughts, 2012

It is money because it is a medium of exchange, a unit of account, and a store of value. Currently, organisations that have a lot of it either “mine” it for information that can be used to design better products or services, or package it directly for sale in another form of currency (eg dollars).

Where it might get interesting is when we start asking to be paid in data directly, instead of in dollars first. There’s an example of a musician, asking to be paid in data, instead of the measly fractions of cents she gets as a cut from iTunes. It’s not that big a stretch to imagine a supermarket where I pay for my groceries in personal data (making Woolworths an advertising platform, as well as a supermarket. They’re halfway there already).

This doesn’t necessarily lead to a world where “everyone is an advertiser” however. The advertising business model exists because we haven’t yet thought of any other way to convert data to dollars, which we want to do, because we need dollars for food. But if we had even one farmer who was willing to supply food in exchange for data…

Now, all we need is a trusted record of exchange of data. I wonder if anyone is working on that?

First Data Bank

Here’s an idea I’d like to see: a data bank.

You “deposit” your data in a bank. You can withdraw it, which means it’s deleted. You can add to it at any time. You can deposit any kind of data you want, and transfer it to other accounts if you choose. The data is yours, in the same sense that money in a bank is “yours”.

The bank “loans” data to borrowers, under strict terms (in essence, the bank doesn’t need to physically transfer anything, or even give direct access to the data… but I digress). The borrowers have that data on loan, and must pay “interest.” The interest takes the form of the insights that they gain from analysing that data. The insights flow back to the data bank, and ultimately the data depositors.

This is a very different business model to GAF.

Money is Data

Money, by the way, is data. This is where I actually started, but I decided to lead this blog post with the conclusion rather than the introduction.

Money is an act of collective imagination. A mass, mutual suspension of disbelief. Money has value because we all believe it has value. This is easy for us, because our government says it’s true, and everyone is acting as if it is. Fairly catastrophic things happen to societies when people stop believing that their money still holds value (or that it will in the future). We call these catastrophic things hyper-inflation, and the collapse of civilisation.

While we have physical manifestations that represent money (coins, notes, bearer bonds, etc), most of our money these days exists purely as data recorded on bank computers. I rarely think about it, but I go about my day secure in the belief that the money in my account is “real.” But it’s not physically real. There’s no vault, no physical ledger, no gold or cash. It’s just flipped bits on a platter in a private cloud.

To access our money, we often use “money avatars”, such as credit & debit cards, gift cards, or cheques. They are avatars in the sense that they are physical manifestations that represent something imaginary, an intangible value. The bank note is not the thing, it just represents the thing. Its value is based on a promise we all beleive will be kept. The item itself is near-worthless paper.

Modern avatars pop up in other places too. Service avatars are physical manifestations of intangible service value. My iPhone is a service avatar. The true value of the iPhone is in the intangible apps. My Kindle is a service avatar (“The Kindle is not a product. It is a service” – Bezos).

Maybe I’m just a data avatar. 🙂

TL;DR: Conclusion

Money is data, but more interestingly, data is money. In exactly the same way as a fiat currency, data has an irrational but reliable intangible value and is used in exchange for services.

Could be really interesting times ahead.



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My 6 Coursera (& MOOC) Study Tips

Calculus I at The Ohio State UniversitySince I’ve been really quite slack in contributing to this blog I thought I should try and re-boot.

I’ve studied a few courses now on Coursera and completed about half of them. So from my rich well of both success & failure, here are Hisso’s Tips for Actually Completing Courses Online (if you’re just mucking about, these tips won’t apply):

  1. Study one course at a time, no matter how tempting it might be to add “just one more” because it sounds really interesting. As cheap as it is to sign up, the extra courses only serve to distract and overwhelm.
  2. Use the estimated hours. If the course convener has said the course will need 8-10 hours per week they mean it. I’ve found those effort estimates pretty reliable. You might look at the video lectures and think it’s only 1-2 hours a week — but the lecturers have run this before and know that the exercises, peer-assessments and reading actually make up the bulk of the time commitment. So go with their estimate.
  3. Study what’s interesting to you, not your employer. Because presumably you’re having to do this study in your own time, so you’re going to need to rely on intrinsic motivation to finish.
  4. Keep up with the lectures and quizzes. Once you start to fall behind it can be almost impossible to catch-up, because the cumulative study time required will easily exceed your spare time available. Which leads me to…
  5. Schedule in the Study Time. Ideally this is a regular time (I schedule 7-8 am weekdays) which not only helps keep you on track but also gives you a good idea of the maximum course load you can take on. If you know you only have 5 hours a week then you know not to bother trying to complete an 8-10 hour a week course (without scheduling in additional time).
  6. Find a Friend. If you can find a friend or colleague who will do the course at the same time then your chances of completing are greatly improved.

So there you go. Guaranteed Coursera Course Completion or your money back (har har).

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