How to Read Crowdsourced Knowledge

Wikipedia has a mixed reception when it comes to the academic world; creating an interesting conversation about the utility of crowdsourced information and its current iteration in the form of AI. This post will explore the current state of Wikipedia and ChatGPT alike, hopefully coming to a satisfactory conclusion about how we can view them moving forward.


I want to use the Wikipedia page on Digital Humanities as a basis for analysis (linked directly above this paragraph). This page has an interesting history; being created all the way back in 2006! This was during the earlier days of the formalized Digital Humanities field, which is reflected in several different places, including this page. For those unaware, the “Talk” page on Wikipedia articles (located directly under the article title) contains user discussion surrounding the page; highlighting anything from potential additions to the page, places where things should be revised or removed, and other general discussion about the future of the article. On the page for the Digital Humanities, users have discussed a lot of revisions, but the most striking detail that stood out to me is the lack of a clear definition for the Digital Humanities, as one user addresses during earlier iterations of the page, shown in the image below this paragraph.

Although in 2023, the page is quite thorough in highlighting criticisms, definitions, examples of visuals and projects generated by scholars in the Digital Humanities, and so on, it was not always like this! The contributors of this page over the years addressed the vagueness of the Digital Humanities just as the field did within over several decades and iterations. One can see every version of the page by exploring the “View History” tab, located on the right side of the same bar as the “Talk” page. Every edit and reason for editing appears, which can be filtered by user, date, type of edit, and so on. This shows a very precise evolution of the page one is looking at, and one can start to pinpoint where changes occur if one is inclined. Pictured below is the general “View History” page layout, and an example of the DH page when it was first established by user “Elijahmeeks:”

All of this is to showcase the progression and utility of crowdsourcing information, and the level of investment core users and casual editors collectively put into a page over the span of over a decade! I personally use Wikipedia as a starting point for casual or academic questions I may have, looking into the source material they utilize first and foremost! I think that depending on how one utilizes crowdsourced material, there can be a lot of benefits for users across the Internet!

This brings us to AI, which is essentially automating crowdsourced information that the user can interact with in different forms. In the case of ChatGPT, a free service that is only growing in popularity, one cannot see what exactly it is pulling from. When inquiring about this, the bot will say something along the lines of pulling information from a database that includes textbooks, reputable sources, and other such places. It is vague, and there is no clear way to check its work. With Wikipedia, it is all there for the user; one can even see which user made how many edits during specific timeframes! What is interesting is that when asked questions about the Digital Humanities, ChatGPT gave decent answers when compared to Wikipedia and other source material that I have read up on. It really protects its corpus, and results generated by AI are starting to pop up everywhere, with varying degrees of accuracy. Just because there is a decent success rate with this experiment I conducted with it, I am not sure where that leaves its impact throughout the rest of the Internet.

To summarize my feelings concisely, I am skeptical at best, but there is potential if it is developed ethically. I see it being inevitable regardless of my feelings on the matter, so time will only tell where this new age of crowdsourcing takes us, and if we will be begging for the days and uncertainty of Wikipedia ten years from now. It is an interesting thought experiment though, and I cautiously encourage you to try it for yourself on topics that you are passionate and/or well-read in.

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