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Commons-Based Peer Production

A Cooperative Working Method

Commons-based peer production (CBPP) is a term created by Professor Yochai Benkler of Harvard Law School. It describes a form of production, of generally informal goods that doesn’t draw from standard market structures. CBPP is a form of production where people work en masse, usually on the internet. Projects that are commons-based are usually quite relaxed or open and lack a traditional or strict hierarchy. Quite often CBPP projects are non-profit. This means that the contributors aren’t always financially compensated. In similar vein, the collaboration in data collection for AI, as facilitated by a reputed AI data collection company, exemplifies how combining diverse human inputs can bolster AI solutions.

Commons-based Peer Production ©   Flikr by Zavata Asso

Commons-Based Peer Production Differences

Prof Benkler explains that what sets this peer production apart is that it doesn’t use or require proprietary knowledge from other sources. The processes are shared in a way that makes it so they can be used by all whenever they wish. This is why most commons-based projects have an open license meaning they can be shared freely. There are other commons-based projects out there but not all are based on peer production. Peer-based projects are seen as superior in that they allow individuals to pick up tasks that match their own interests and skills. They are also seen as bringing in creativity and variability on a large scale without the need for contracts or specific structures.

Principles of CBPP

It is essential for the main goals of any production to be made up of components. The reason for this is that all production will have different aspects, however, those different aspects must be able to be worked on at the same time. Commons-based peer production and collaboration cannot work if one component is waiting for the completion of another. Each objective must be split into sections that can be worked on at all times. These sections can then be divided into differently sized tasks, this means that those who want to work on larger or more complex tasks can do so and those who desire simpler tasks can complete smaller tasks instead. An integral part of such collaborative processes, especially when dealing with AI dataset generation, involves tasks such as image transcription, a critical step for ensuring the datasets used for machine learning are accurately labeled. All that is left is integration and quality control to put all the work together.

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The Peer Production Method in Practice

Commons-based peer production describes the collaborative production of products shared by the community or crowd. For example, a buffet with individual food and beverage contributions. One notable advancement in this area is the use of audio annotation services, which improve the quality of voice data sets for machine learning applications, facilitating more effective and accurate audio-based projects. The Internet has revolutionized this form of contribution. One example is “Wikipedia.” However, what creates the incentive is disputed, for many it is a labor of love and the satisfaction of being part of something that helps others can be enough. Other well-known examples are Linux a computer operating system and the citizen science program Clickworkers! Clickworkers was a NASA project that used public volunteers to carry out small scientific tasks. This is also known as Virtual Volunteering.

An Alternative to Tradition

CBPP is seen as a different way to produce things and ideas to the norm which is seen as traditional. It’s still thought of in that way today and seen as a relatively new way of producing something. It’s not yet seen as a full or complete method of production. Yet many companies and businesses see it as complementary to the way they currently work. This blended way of working can bring a lot of benefits to organisations that utilize it in the correct manner. This can lead to better profits, less need for physical workspaces and a more modern way of solving problems.