The network effects of HUMAN Protocol
Blockchains are networks; and so is HUMAN Protocol. The Protocol is a software infrastructure that orchestrates the communication and collaboration of different agents in the work cycle; from the requester who launches a specific piece of work, to the workers who attempt the work, to the oracles responsible for verifying and paying out that work. It is a network that enables work.
The network participants are primarily the requesters and workers. However, in this article we look at the network established and enabled by the applications running on the Protocol: the job exchanges.
Communication is key to value in any network. Whether the network is Ethereum, Facebook, or Google, it is communication between network participants – the ability to transfer information from A to B – that gives the network its value.
Metcalfe’s law states that a linear increase in network participants increases the utility of the network exponentially. How can that be so?
As one application comes onto HUMAN, it increases the kinds of work that can be fulfilled beyond the immediate and obvious kind of work fulfilled by that application.
The exchanges on HUMAN Protocol are the applications through which work is completed. hCaptcha is one already running on HUMAN Protocol, while other, more granular image labeling tools such as Intel CVAT are in development. The addition of a textual annotation tool, such as INCEpTION, would add a vast scope of work within the field of text annotation itself, but also expand the kinds of task accomplishable by the network more generally.
As per the diagram above, two applications can only speak to each other. Three applications can each speak to the other; so each application that comes on signals a higher-proportional increase in network utility.
The key is to find a way to intelligently dissect a large job into composite tasks, and to distribute those accordingly to the correct applications.
The addition of a textual annotation tool, for example, would mean that the exchanges could benefit from their independently held information. That INCEpTION can accurately label syntax means that suddenly a larger job could be a page from a textbook, or a medical report; anything that contains both images and text.
Another example of work, beyond data labeling, could be that of a company report. If one application is for writing text as opposed to labeling it, the utility is brilliant for articles, blog posts, journals, but limited to only those; the addition of a design application means that, not only could design tasks such as logo creation be solved, but, by combining both tools, an entire website could be executed.
The applications on HUMAN are only as good as they are reliable. The above example would rely on an intelligent role played by HUMAN to govern the dissection, distribution, and assimilation of tasks. This example, however, of quality assurance, requires direct communication between exchanges. If hCaptcha wants to know if an image is really of a car, it can send that image to Intel CVAT to be checked; thereby increasing hCaptcha’s quality assurance, while also benefiting CVAT with greater quality data, as well as pre-labeled images to use itself.
We built HUMAN Protocol with the aim of unlocking the next generation of knowledge workers. The nature of the network means that: an increase in applications will benefit the other applications already on the Protocol, and those looking to join. It starts with small steps; and that is why we are constantly working to bring on new applications, knowing that a small increase has large network implications for the future.
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The HUMAN Protocol Foundation makes no representation, warranty, or undertaking, express or implied, as to the accuracy, reliability, completeness, or reasonableness of the information contained here. Any assumptions, opinions, and estimations expressed constitute the HUMAN Protocol Foundation’s judgment as of the time of publishing and are subject to change without notice. Any projection contained within the information presented here is based on a number of assumptions, and there can be no guarantee that any projected outcomes will be achieved.