Crowd-Sourcing and Impact in the Humanities

I read the article “More than a business model: crowd-sourcing and impact in the humanities” by Stuart Dunn, a lecturer in Digital Humanities at King’s College London.

Crowd-Sourcing –  “the practice of obtaining needed services, ideas, or content by soliciting contributions from a large group of people and especially from the online community rather than from traditional employees or suppliers”, as explained by Merriam Webster.

In the early days of crowd-sourcing, it was focused on furthering the aims of for-profit businesses. So anyone that had access to the internet, who had a lot of time and enthusiasm, were able to participate in design competitions, micro- tasks and distributed production. The aim of this was to build on the company’s status and help them out a little bit.

Dunn wrote that  “Crowd-sourcing was about the public having impact, and reaping whatever reward the project offered – money, or the prospect of winning it, prestige, seeing your design on the mass-produced t-shirt – and not the public being impacted.” The people who are who are helping to crowd-source projects, want the companies to collaborate with them, so both parties are impacted. A survey was done for this article, and the “Super-Contributors” to these projects answered that they want to be part of the conversation, not just the process. They mostly have a desire to be useful, and see what happens on the inside, rather than being limited to just providing info and getting a fancy prize for it. They wish to learn about the content and see how the projects are organised.

Dunn gives some advice to ensure a “reciprocated impact of a humanities crowd-sourcing activity”.

  1. Not every question or problem you come across will  be susceptible to crowd-sourcing as a solution.
  2. Small groups of people have done the most valuable amount of work by sustaining their intellectual engagement throughout the project.
  3. It would be a good idea to have a contributor’s forum so that mutual problem solving is an option, by having support discussions put in place throughout the forum for particular projects. This helps to create a space full of non-institutional people working on your project, and also creates more exposure for the discussions about your project on a social media platform.

Google have recently open-sourced TensorFlow, a software library for machine learning. They hope people will contribute to the code to make their software even better, giving people a chance to make a change in machine learning.

You can find Stuart Dunn’s article “More than a business model: crowd-sourcing and impact in the humanities” Here.

Here is the TensorFlow website, where you can find more info on the project itself and why Google chose to open source it.


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