4. Limitations

Understanding limitations is the first step towards solving them. Here are few of the limitations we currently foresee and we will overcome them with research and creativity.

Potential duplicates

There is a 1 in a trillion chance of two people being the same based on 8 facial features [32]. Since we are using more sophisticated methods, we can safely say that the chance of duplicates will be less than 1 in a trillion. Furthermore, we will use government IDs as well as other data points about the two users as a differentiator on top of this.

Data quality

The applications built on top of Human Chain are going to be as good as the data that drives them. While we will do everything we can to improve the data quality, ultimately it is limited by the data Human Chain can source.

People data

To begin with, we are focusing on people data. This means that the applications built on top of Human Chain are going to be limited to ones that are empowered by people data.

Government identity systems

For some applications, our identity layer is partly dependent on government IDs and integrating with government systems. Such a dependence on an external system can potentially limit the usage of HumanChain by powers outside of our control. For example, if a user cannot verify their government IDs, they will not be able to use applications that require KYC verification.

Wallet loss

If a user loses their self-custodial wallet that stores their identity information (Human ID), then they lose access to their Human Chain account. This means they also lose the power to control their data and their Human Chain tokens that may still be in that wallet.

False rejections

Rejections may happen at the signup and identity verification stage due to infrastructure issues faced by the user such as camera quality, video quality, inadequate quality of government ID proof, etc.