Is Data Immutability Always Favorable On The Blockchain

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15 January 2018  |  3430 views  |  2

One of the most appealing aspects of Blockchain and DLT technology is the ability to synchronize data of multiple parties from a variety of industries. This ability has the potential to solve huge industry-wide problems by locking in data or making it immutable meaning that the data would be kept “real” by all participants. This however, would depend on the proper governance to ensure that parties cannot update data on their own but rather have a consensus on the type and quality of data.


It’s very obvious that there are big benefits to data synchronization and immutability, but can data synchronization and immutability be a bad thing?


Well, I think that data synchronization and immutability could indeed have a negative effect and those types of scenarios can be found across many industries.  For example, in the financial industry, hedge funds or other proprietary traders (brokers as well) might encounter a situation where they want to appear differently, perhaps some may want to hide certain intentions, or there might be a case of arbitrage markets using different profiles. In the cryptocurrency environment, anonymity is one of the basic foundations of the distributed world. This means that we have to find mechanisms to cloak the legitimate user or firm for its own benefits.


Another area that might benefit from data synchronization is the Healthcare industry. No more filling out forms in different doctors’ offices. All of your data would be potentially synchronized across different physicians and care providers. However, is that ideal?  I would argue that there are instances where it isn’t the best practice for so many people to know where your data profile and history are stored and have access to it. The confidentiality of personal procedures and sensitive information would not be safeguarded as it once had been, leaving the patient feeling exposed and unprotected.  Smokers would be destroyed on insurance applications and some pre-existing conditions or types of disorders are not the info one would choose to share across all disciplines. 


What might be the solution is “Data Filters”; similar to photo filters or avatars. DLT users should be able to mask their data as they please within the right data governance set by the node operators. Fundamental data such as verifying locations or regulatory data needed when in a regulated senario should not be masked. However, that depends on governance. The need for data masking also assumes that all disparate Blockchains are also interoperated and synced which is now not the case. We somehow need to maintain the allure of distributed applications including DLT but at the same time provide functional and dramatic improvements in productivity.


I see this clash continuing with the adoption of distributed computer networks such as Ethereum. 


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