Proactive social services on the blockchain
Blockchain is still regularly used as a buzzword, but the use cases for which the technology actually delivers value are starting to take shape. From Novum, we therefore set up an experiment in collaboration with Ledger Leopard to explore the extent to which we can use the technology behind blockchain within the social domain for both government and citizens.
2 use cases
We have taken two use cases in which we can test a proactive approach to our social services by means of a digital identity card, also known as a self-sovereign identity wallet and claim structure.
The Uber driver
In the first use case, we focused on a citizen who became a Uber driver due to disability and who has a monthly variable income. As a result, he is entitled to an income supplement in one month and not in another month. With the dynamic claim structure in his digital identity card, he receives a monthly income statement from his employer, who then communicates (via a smart contract) with the government about the income supplement. Is his income of that month below the social minimum? Then his income is automatically supplemented. For example, the citizen gets every month to which he is entitled and does not come into contact with claims on debts due to incorrect preliminary calculations or changes in his living situation.
The asbestos patient
In the second use case, we focused on a citizen who has been diagnosed with asbestosis. The citizen receives a medical statement from the pulmonologist in his digital identity card, which communicates with (smart contracts from) other (government) bodies. In this case, the citizen will automatically receive a message that he is eligible for a contribution from the SVB under the astbestos scheme and can easily apply for this via his digital identity card. This way, citizens do not have to look for what they are entitled to in certain vulnerable situations.
The technology behind blockchain
From a technical point of view, we were particularly curious whether:
- Data exchange on an open blockchain can take place GDPR-proof;
- Smart contracts on the blockchain can trigger each other across chains (for example, different government agencies);
- The concept is scalable to millions of citizens.
Open vs closed blockchain
Setting up blockchain can be done in various ways, open and closed. In the open variant, all digital ledgers are spread over private computers. Everyone can make his or her computer available as a station in the blockchain.
To form a closed blockchain, it is possible to name the stations in the blockchain itself, for example data centers of the national government. Another form of a closed blockchain is by encrypting the ledger (encryption) to limit access. A combination of both closed blockchain forms is a third possibility.
Which form is chosen differs per blockchain and underlying case.
We can summarize the results in 3 points.
- Yes it is AVG-proof: this is made possible by a mixer service and ZKsnarks. Zk-SNARKs is a “zero-knowledge proof” technology. Most blockchains are open and transparent, while zk-SNARKs allow the same information to be verified without revealing exactly what that information is. Mixer service: you create a lot of accounts (public and private keys) and the credits are sent divided to different accounts, which then send it back to the user so that you cannot trace back that someone receives money from the SVB.
- Smart contracts can indeed trigger each other, whereby after detection of a certain situation (eg low income or a certain illness), an amount is automatically deposited from the government.
- Performance: At the moment it is in a closed blockchain, where transactions can take place within a second. When placed on an open blockchain, it will take 4-14 seconds depending on how busy the network is.
Together with Ledger Leopard, Proof of Concept made the use cases. Curious how we did that? Watch the video with detailed explanation.
Do you want to know more about this experiment?
Listen to our podcast that explores the blockchain challenges of identity, privacy, governance, performance and impact on government based on our experiment.
We are also very curious about your opinion! Do you see other use cases for which our acquired knowledge can be used?
Let us know!
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