Future Scenario: National Data Funds

As part of our Our Data Future series, we explore a dark future where governments have all the control over our data

Case Study
identity in the future

Illustrations by Cuántika Studio (Juliana López - Art Director and Illustrator, Sebastián Martínez - Creative Director)

In this third leap to 2030, Amtis sees that people have created national data funds where citizens and governments together own the data that is being generated by sensors or by the services people use.

Here’s how Amtis lives this time:

Smart commuto-mobile

In the busiest parts of the city there are no more cars. There are only special lanes for drones, houndopacks – fast robots that run like dogs to deliver packages, and smart commuto-mobiles – slim electric booths where you can sit on your way to work and look at your phone without being worried about the traffic. It’s pretty cool – you can check your emails, take phone calls, schedule meetings, listen to a podcast on the best route to work. The commuto-mobiles drive themselves and are connected to high resolution cameras installed all over the city, so they have 360 degree eyes of the road. This also means that every conversation you have while in the smart commuto-mobile is recorded and processed in real time by an AI Traffic Grid. This measure was introduced in order to ensure a high level of empathy in society. For example, if you get angry and raise your voice while talking in your commuto-mobile, the vehicle pulls over and gives you a 20 minute time out to cool off, while it plays music and guided meditation practices. I bet you wouldn’t like to have this happening before an important meeting  you don’t want to be late for! There is no way you can hop back in and make it run until you have calmed yourself down. And it gets registered into your 'good behaviour' record too! The AI Traffic Grid also has sensors that analyse your facial expression to determine emotions, your gestures to determine thought processes and intentionality, and your breathing patterns to determine your heart rate and anxiety level.

Employer knows if you worked during your commute

With the commuto-mobile, traffic is much faster and the risk of accidents is very low. Basically, while you are in your smart booth, you don’t need to worry about anything besides boosting your productivity. People started asking for this time to be included in their working hours. And why not? They jump from bed straight into their smart commuto-mobiles and get to work – who wants to lose time in traffic? This is precisely why the commuto-mobiles were brought to the market. The commuto-mobiles are connected to the Internet, and work reports are sent to employers to show exactly how you spent your time on your way to work. Everything gets recorded in the journey log anyway.

Data as a service for the private sector

All the information that is generated from the city and the services we use is amassed into a big database that is managed by the government and citizens. This fund makes it easier for new companies that want to enter the market and need a lot of data. The idea is that if you want to use any of the datasets, you have to pay to get access. We’re calling this Data as a Service because it turns companies into the customers of our city. Access to these datasets is highly regulated and the more datasets you want to use, the more expensive it becomes. Also, depending on the sensitivity of the information, the price goes way up. For example, driving information is less expensive than health data. The money that the government receives from companies gets redistributed back to the people. This redistribution will be exactly the reason why the government will always seek new ways to collect more data, because they can use it to generate the revenue they need to maintain the 'smart' cities they have created.

The data is anonymised, so everything is safe and nothing can go wrong. Except re-identification of individuals from anonymised datasets can happen more easily than you think.

Individuals and researchers can also apply to get the data they need. If the project benefits the entire community, your idea can be subsidized by the government. Through these subsidies, smaller, independent companies started to run good services, and it became harder to maintain a monopoly position on the market.

We can build our own services

If there is a gap in the market, we can build the services that are missing ourselves. We have all the data at our disposal, and I think gradually this is what we are moving towards. However, for the moment these so-called 'collective services' are not that great. Most of them are not easy to use and look really, really 2000.

Here’s what I make out of this story on a more objective and critical level. If you’re excited to move to Scenario 4 click here.

Reflections on Scenario 3

Besides National Data Funds, there are many more models to explore. Data ownership can be addressed in a lot of ways. National Data Funds don't sound like a perfect solution, but they’re not destructive, either.

Governments will have more control

In the National Data Fund model, the government gets all the data we are generating. This means governments will also have more control. They will basically have every individual’s data and can infer patterns for masses, as well as behaviours and intentions. Will people still dare to protest when abuses happen? We all know how fragile democracies are and the risk of this turning into a techno-dictatorship is high. Around the world there are corrupt, oppressive and ruthless governmental regimes. And if they aren’t now, they could become one very easily.

We will need super advanced security measures to ensure that these databases are not leaked, hacked, or manipulated by foreign or domestic agents. Personal data will have to be anonymised, but research already shows we need to do a lot more to improve anonymisation techniques. And even so, handling anonymised data still can have a huge impact on individual lives because you can look at trends and control masses based on those insights.

Moreover, National Data Funds based on access permission implies a type of infrastructure that will potentially take a significant amount of time to build and will involve a lot of resources.

Trusting governments with all our data

It would be very complicated to put all the necessary checks and balances in place, and to make sure decisions are transparent, without hidden agendas or secret deals between governments and companies. Even if there are no bad intentions in the middle, government structures will still have to change drastically. Entire teams of technical specialists will have to assess proposals coming from companies and take steps to ensure that security measures are in place for preventing abuse. Proposals would also need ethical, sustainability and environmental checks – so a lot of talent needs to be added to government. The public sector needs to get way more attractive in terms of financial rewards for its specialists. Where would this money come from? Would the government be tempted to allow more companies access to data in order to build its budget? Or outsource core services? These are hard operational and strategic decisions to take. Will governments have the backbone to make the correct decisions? What if government interests are aligned with a company’s interests? Exploitative services should not be allowed in the first place, but preventing this from happening will require a total transformation of the mindset we operate in - more than just an independent body under civilian oversight.

Security for databases

Needless to say, having a centralised database as a single point of failure is a very bad idea. The database could potentially be decentralised to eliminate the central point of vulnerability, but technical challenges around decentralisation and data integrity are significant. When it comes to centralised databases, the Adhaar system in India shows us the massive implications around managing such a database.

No incentives for companies

One of the ideas for the National Data Funds is to ask companies to pay a share of their profit. Of course, there could be other models such as subscription fees, subsidised access, completely free access, access based on income, or a mix of these. Companies may be required to pay twice: once for getting access to the data and again for the profit that data generates. But we already see business models that deliberately run on losses (Uber, Amazon) in order to consolidate their position, kill competition and promote the regulatory framework that’s best for them. Will the National Data Fund model solve this problem? You don’t want to maximize the revenue of the companies using the fund, but at the same time, where are governments going to get the money from for all the costs involved with technical management, deliberation and social benefit analysis?

A lot of uncertainties

There are many more questions to think about. For example, by default will everybody’s data be captured? Is there a possibility not to contribute to the fund? And if I don’t contribute, will I be able to freely operate and participate in society without major negative consequences? There is also a lot to discuss about how this data pool is managed and how decisions are made by both governments and citizens. Will every point of view have the same weight? How can we make sure citizens will not be threatened, pressured or forced to vouch for certain decisions? Also, what happens if a company gets access to a database, but then misbehaves? Even if you cut their access to the database, the damage is already done, potentially harming millions. What will be the measures to ensure that the risks of abuses are mitigated?


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