Our Data Future

In 2030 Amtis finds a future where property rights for data were adopted. Here’s how this future plays out:

My data, my turf. This was the first graffiti I saw as I was walking down the street and I said to myself, “Yeah, big corp, we’re going to get you good!”. I am fed up with companies making insane amounts of money from my data. If this is the game we’re playing, I want my fair share.

I was not the only one thinking like this. A few years back there was a strong push towards adopting property rights for data.

I was on my way to see a data property consultant. I just got fired from my job and I desperately needed a way to survive in this city. There was a big queue in front of the consultancy firm, in a tall glass building with a huge advertisement on it: 'Sell Your Data'. The first meeting was free.

OK, I have property rights over data. Where do I start?

I decided to see a consultancy because I didn’t know what data property actually means. For example, can I rent my data? Can people now buy and sell data like on the stock market? Do I need a data broker to bid for me? How much money can I make from giving data to my day-to-day services? How much will my data be worth in the future? Can I leave it as an inheritance to my children?

What I am most interested in now is what’s the fastest way to profit. At the same time, I don’t want to be fooled like in the past with 'free services'. I may have lost my job, but I still have dignity left. I wouldn’t want my data to be used in any way companies please. Would I be able to set my own conditions?

Little money for a lot of data

While I was waiting for my turn at the consultancy, I received a notification that I had unlocked a special data payment feature on my social media platform. I was receiving this offer based on my location. The offer was valid only for people on the waiting list for this particular consultancy firm. They must be a hotshot company to have such personalised deals. I’m sure they receive a commission for this. They offered 0.50 units for every social interaction I made: post, uploaded photos, tagging people and objects, clicking on links. I just used the app as I normally do and in about 10 minutes I got close to earning 5 units – that’s about the price of a public transportation ticket. Not exactly a fortune, but in my situation, anything helps. I’m not sure if this is a one-off promotion or if they would offer the same reward tomorrow.

Credit backed by data

The social media company was also advertising data credits. They recently started operating like a bank. Their new product is a financial credit package which could be backed by data as collateral. Because data is seen as property, instead of guaranteeing to pay back the credit with my apartment or goods, I could vouch for it with my data. The company knew my exact identity, my financial transactions, but more importantly they knew my social behaviour, how trustworthy I was and how much my data could be worth. This sounds like a fast solution for my situation, but let’s see how the meeting with the consultant goes.

Full data scan for price simulations

It was almost dark when I finally entered the consultant’s office. The company had an entire floor of 'data officers'. They were basically sales people with programming skills. I was escorted to one of the data officers. She welcomed me and explained the first steps. In order to receive a full analysis of how much my data is worth, I needed to hand in my devices and wearables for data scanning. I was storing all my data locally for privacy reasons, but if I wanted to learn the entire worth of my data, I had to hand in the data.

Can’t get rid of 'free' services

She also explained the privacy policy for this simulation. The data that’s extracted from my devices would be shared with my social media company and partners. This is why the first consultancy session is free. Without a job, I didn’t really have a choice. I would have to give in, even though I felt used. Despite the bitterness of compromise, I decided to continue.

While my data was scanned, she ran a virtual reality programme. She said the programme would walk me through the basics of data property and that I could ask all my questions in real time, receive feedback and get simulations based on the data analysis that was running in the background on my devices.

The question that bugged me the most was whether there was any way to know where my data travels and which partner companies and affiliates get their hands on it. Is there some kind of body where I can report data property abuses? And what will they do? In the case of physical property, I can imagine that if my bike is missing, I can report it to the police and maybe they will try to find it. If they don't find it, nobody will give me a new bike. The maximum that can happen is to receive compensation for the bike from an insurance company for example. But it's unlikely that I will ever get the same bike that I lost. Does the same apply for data property?

Tailor-made AI assistant for data transactions

At the end of the virtual programme, I could decide if I wanted her to programme a tailor-made AI assistant for my data transactions. For example, I could set up price alerts to see the best deals that companies offer for data batches, and I could also rent my data to different companies as a sort of subscription. The simulation explained everything for me:

Real-time bidding for selling data

To start, I learned how real-time bidding architectures for data work. First, you select which devices will join the bidding platform. Your devices are linked to your identity and everything generated from them is considered your property. And all the data generated from those devices feeds straight into a centralised platform. There are a number of companies registered with this bidding platform that will have access to your data after the transaction is completed. Once your data gets on the bidding platform, you can immediately auction it.

The AI assistant would help me set price ranges and tell me how others sold similar data points historically, what types of data transactions are trending, and which data are likely to be more profitable.

Time-locked subscriptions for data

As an alternative model, I could put my data in subscription offers to companies. I can ask my AI assistant to set the subscription price. Companies can buy the data subscription from me for a limited period of time. Start-ups in particular like this model because it ensures them a continuous stream of data. However, the downside is that as companies grow bigger or diversify their services, if my data becomes irrelevant to them, they can simply stop the subscription without explanation or notice.

Managing data transactions is overwhelming

The AI assistant was subscription-based. It wasn’t cheap, but not super expensive either. Given my condition, I couldn’t afford it. The consultant said they are partners with the social media company I frequently use, so she suggested that I apply for a credit for the assistant.

Of course, I could personally manage my data transactions without the assistant, but that would mean I have to do it full-time, read all the conditions and fine prints, make sure I am not being scammed and spend a lot of time hunting for the best deals. I am not even sure I would be able to understand all the terms.

In the end I made the credit and got the AI assistant. I added only a few parameters, so the data officer didn’t have much to programme and customise in my case. I desperately needed money, so my bar was really low. I hope the assistant will help me maximize the value of my data so that I can pay my credit in data in half the time.

As I was leaving the consultancy, I started listening to the World Data News Channel. There was an interview with a girl named Lucy. She was talking about how inspired she was by Jennifer Lyn Morone which came up with the concept of People Inc. Jennifer Lyn Morone was an art student when she incorporated herself as a business to protest against extreme capitalism. She believed that it was the only way to stop corporate exploitation. Jennifer Lyn Morone started the trend of Incorporated Persons and apparently she's been getting more and more followers. Lucy herself became a copycat. From individuals to Incorporated Persons The concept of Incorporated Persons basically assures that your identity, name, IP address and every bit of data you create is your company’s property. If others abuse your data or touch it without your permission, theoretically, you can sue them. People Inc. claim it’s an effective way to put a fence around your data. Human Corporations have leverage on data greedy companies. Also, if you want to make a profit, you can market all sorts of data services and products. For example, if someone wants a picture taken with their friends in a pub or asks for advice where to eat in town, Jennifer Lyn Morone Inc. can offer this for a fee. And she can increase her efficiency in life too. She says: “If my friends and family became corporations I knew exactly who I would use and for what and I know who I would invest in, not only because of what they can do but because of who they are.”

It wasn’t exactly easy to start Your Name, Inc. You needed legal, entrepreneurial and technical skills to run your company. So this model was more popular with middle-class, educated people that were able to sustain this effort. In that part of the world, Human Corporations function in a totally different type of social dynamic.

I don’t know how you feel, but for me reading Amtis diary on data property was unsettling.

Here’s what I make out of this story on a more objective and legal level. If you're eager to read Scenario 2, click here.

Reflections on Scenario 1

Data property does not mean more or better control

Creating a new law that attaches property rights to data is problematic. Due to the nature of data and how it's used in practice, it is very doubtful whether you can have exclusive property rights over it. It’s not as simple as with material goods, where you either have them or you don’t. Data can be here and everywhere and can be copied and transmitted at almost zero cost. Therefore, there are limited barriers that can be exercised with property rights and exclusivity.

The general idea around property rights is for you to keep and enjoy that particular possession. Property usually comes from an approach of non-disclosure, not one where you want to disclose by default. If you decide to lease your property, the tenant is entitled to use and possess the property until the end of the agreement. In this case, there will be limited claims you can make as property owner during the renting period.

Also, consider homeowners’ associations. You may be able to buy a house, but you might need to get permission if you want to redesign your garden or change the paint colour. You can’t always do what you want, even if you do have property rights; they don’t automatically imply that you have absolute supremacy over what you possess. The same would mean for data property. Even if you have property rights over data, this will not necessarily mean you will have unlimited powers over it.

One-off transaction

Once you sell data, it’s a one-time transaction that can’t be simply reversed. Moreover, once you sell, the company can do whatever it wants with the data. There could be some conditions for selling, but do we expect people to have real negotiation power with companies? Privacy is also a time-shifted risk. What you might be fine revealing today might not be a good idea to share tomorrow. If you transfer your property rights over data to others, there is no real way to assure that the data won’t be abused. This argument is valid for all data property or data monetization scenarios and will come back in some sections of the Reflections below.

Data monopolies don’t die

Property rights don’t change the fact that companies can amass large batches of user data. Nor does it undo the fact that certain companies today have already done that - take for example companies like Facebook, Amazon, Netflix and Google.

Accomplices to the same broken model

We don’t know what the main digital revenue model will be in the future, but we know now that some of the biggest companies today rely on advertising. This means that every click or purchase that I make translates into money for them. The more clicks and products I buy, the more money they get from advertisers. In a system where I get paid for data, this means the more profitable companies are, the better paid I am. In other words, it’s actually in my interest for them to make more money, so that I get more in return. This feeds the same old game; it makes us accomplices to a broken system, one that we’re trying to move away from. Do we want to legitimise questionable market practices and data abuses for a few pennies?

What is it exactly that I own?

Amtis only briefly hinted at it, but I don’t think there is an easy consensus on what exactly I can own. Is it my bank and credit statement, my smart meter reading, my GPS coordinates? How about my picture with my friends and family? If they are in the picture, do they own it too? What happens with genetic data? It contains information about my family, so if I reveal it, will my family also have property rights over it? What about my future children and grandchildren, too? Data about me is also data about other people.

And what happens to the data about me that is generated without my knowledge? Would this be covered too?

Designing a system of data property rights would require a classification and inventory of all possible data types that can be owned, along with their state (e.g., data in transit, data in storage). Questions would include: What data do we assign property rights to? Is it data that is collected, or analysed, or aggregated, or data that is being profiled? Would data in transit be owned as well, or only data that is already stored somewhere? Could the same data have multiple owners?

Property is not compatible with the nature of data

Here’s a legal argument to keep in mind. Intellectual property rights may at first seem akin to data ownership, but there is a fundamental difference. For example, copyright law protects the original expression of an idea, not the idea or information itself. The colours that make a painting are not protected, but the original way in which they have been expressed can be. In the case of a Facebook post, the way I express myself can be protected by copyright, but I do not own each individual word that makes that post. However, in the case of data gathered by sensors there is no creative effort involved, it's raw data. When we are talking about data, we can’t say that we have intellectual property rights over it, because data is not protected per se, especially if there is no intellectual work behind it.

But let’s say we are doing something with the data. Let’s say we are collecting it in a database and this takes quite a lot of effort and resources. In the case of EU database law, the protection applies to the creation of the database, not the data entries themselves. More specifically, the resources invested in making the database are the object of protection, not the creation of a database in itself.

Similarly, if we discuss compilations (such as an anthology for example), which are generally protected under copyright law, the protection lies with the originality of selection and arrangement of information – it does not protect the individual elements that make the compilation.

Aside from this, there is more critique that can be addressed to intellectual property law. Authors are usually part of a long tail and receive only a small compensation for their work. There is a lot of power asymmetry between authors and the beneficiaries. Think for example of the music industry. Record labels generally get all the money and authors get paid last. Few authors have real negotiation power, good legal representation and the possibility to enforce their rights. That is why they earn more money through concerts than from their records.

On a more fundamental level, property rights are alienable, which means you can essentially transfer them from one person to the next. Human rights such as the right to privacy and data protection are inalienable. If you transfer them, they lose any meaning. What's the point of freedom if you renounce it? And what is more: if you sell data but want to keep some basic rights about the uses of that data, you are actually thinking about a rights-based approach, not a property one.

Data markets in practical terms

Let’s imagine we somehow figured out all the questions related to property. Then we still need to consider the practical aspects of a data market. Let’s say in a property system, some individuals would sell their data. Who is going to set the price? Based on what criteria? Am I going to have negotiation power in relationship to companies? How would the money actually be transferred in practice? Will I need to spend time brokering or auctioning data? Where would I go if I am not satisfied? Will I spend my time monitoring companies to make sure they actually respect the contractual agreement? Will I go to court if they don’t, and spend years awaiting a resolution (since court decision generally take a long time)? Also, how would consent be managed without producing decision exhaustion? Will we need to give instructions to our own bidding bots? Data property puts a lot of burden and responsibility on the individual to manage all data exchanges. Does this really mean more control?

Additionally, if I start selling data, companies would have little incentive to promote data transfers or portability from one service to the other, as they will be heavily invested in buying data. If we aren’t able to pull data from one company and move it to another in an easy way, we will just get trapped in the same corporate walled gardens of today. We won’t be able to complain to companies if we are dissatisfied. What’s more, start-ups and small companies would still rely on large investments to compete with big companies when buying data. Regulating licensing of data would be extremely difficult and start-ups would be loyal to their investors, not to innovation and/or social good.

And in the end, how many companies can actually afford to pay me money? Aside from a few well-known big tech companies, there are a zillion small companies that won’t have the resources to pay me. How would a property rights or data monetization system stop them from getting my data? And how will I know if they have my data or not? Who will enforce this? Will I be able to ask them if they have my data, like in Europe with the GDPR?

SCENARIO 2 – DATA LABOUR

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