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Facebook’s imminent IPO raises an interesting issue for many of its users. The company’s value is based on its ability to exploit the online behaviours and interests of its users. 

To justify its sky-high valuation, Facebook will have to increase its profit per user at rates that seem unlikely, even by the most generous predictions. Last year, we looked at just how unlikely this is

The issue that concerns many Facebook users is this. The company is set profit from selling user data but the users whose data is being traded do not get paid at all. That seems unfair.

Today, Bernardo Huberman and Christina Aperjis at HP Labs in Palo Alto, say there is an alternative. Why not  pay individuals for their data? TR looked at this idea earlier this week.

Setting up a market for private data won’t be easy. Chief among the problems is that buyers will want unbiased samples–selections chosen at random from a certain subgroup of individuals. That’s crucial for many kinds of statistical tests.

However, individuals will have different ideas about the value of their data. For example, one person might be willing to accept a few cents for their data while another might want several dollars.

If buyers choose only the cheapest data, the sample will be biased in favour of those who price their data cheaply. And if buyers pay everyone the highest price, they will be overpaying. 

So how to get an unbiased sample without overpaying? 

Huberman and Aperjis have an interesting straightforward solution. Their idea is that a middle man, such as Facebook or a healthcare provider, asks everyone in the database how much they want for their data. The middle man then chooses an unbiased sample and works out how much these individuals want in total, adding a service fee. 

The buyer pays this price without knowing the breakdown of how much each individual will receive. The middle man then pays each individual what he or she asked, keeping the fee for the service provided. 

The clever bit is in how the middle man structures the payment to individuals. The trick here is to give each individual a choice. Something like this:

Option A: With probability 0.2, a buyer will get access to your data and you will receive a payment of $10. Otherwise, you’ll receive no payment.
Option B: With probability 0.2, a buyer will get access to your data. You’ll receive a payment of $1 irrespectively of whether or not a buyer gets access

So each time a selection of data is sold, individuals can choose to receive the higher amount if their data is selected or the lower amount whether or not it is selected.

The choice that individuals make will depend on their attitude to risk, say Huberman and Aperjis. Risk averse individuals are more likely to choose the second option, they say, so there will always be a mix of people expecting high and low prices. 

The result is that the buyer gets an unbiased sample but doesn’t have to pay the highest price to all individuals.

That’s an interesting model which solves some of the problems that other data markets suffer from.

But not all of them. One problem is that individuals will quickly realise how the market works and work together to demand ever increasing returns.  

Another problem is that the idea fails if a significant fraction of individuals choose to opt out altogether because the samples will then be biased towards those willing to sell their data. Huberman and Aperjis say this can be prevent by offering a high enough base price. Perhaps.

Such a market has an obvious downside for companies like Facebook which exploit individual’s private data for profit. If they have to share their profit with the owners of the data, there is less for themselves.

And since Facebook will struggle to achieve the kind of profits per user it needs to justify its valuation, there is clearly trouble afoot.

Of course, Facebook may decide on an obvious way out of this conundrum–to not pay individuals for their data.

But that creates an interesting gap in the market for a social network that does pay a fair share to its users (perhaps using a different model to Huberman and Aperjis’). 

Is it possible that such a company could take a significant fraction of the market? You betcha!

Either way, Facebook loses out–it’s only a question of when.  

This kind of thinking must eventually filter through to the people who intend to buy and sell Facebook shares. 

For the moment, however, the thinking is dominated by the greater fool theory of economics–buyers knowingly overpay on the basis that some other fool will pay even more. And there’s only one outcome in that game.

Ref: arxiv.org/abs/1205.0030: A Market for Unbiased Private Data: Paying Individuals According to their Privacy Attitudes

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