Editing Online Communities (UW COM481 Fall 2024)/Wikipedia Advising Report

Like many others, member of the Wikipedia community and the Wikimedia Foundation (WMF) are interested in brainstorming a set of approaches for the usef of generative AI and large language models in Wikipedia. There is already [[:wikipedia:Wikipedia:Using_neural_network_language_models_on_Wikipedia|a page on Wikipedia that might be useful to get a sense of things people are considering]].

For the purposes of this assignment, I want you to imagine that the WMF staff has contacted you seeking recommendations for advice on managing the impact of these tools. For context, the [[:meta:Mission|WMF's mission]] is:

:"The mission of the Wikimedia Foundation is to empower and engage people around the world to collect and develop educational content under a free license or in the public domain, and to disseminate it effectively and globally."

For the purpose of this assignment, it's important to understand this contains both a desire to produce high-quality education quality and a goal to engage people in its production. For WMF, it's important not only to create exellent education content that is factually accurate, and so on, but also to engage individuals in not only "consume" knowledge but to also produe it.

Your job is to produce a short report (maximum 1000 words) drawing on materials from this class to advise these leaders about how they ought to understand this challenge (generative AI) and how they might make progress towards overcoming it. The best insights will draw on intelligent reflections on the themes and materials of this course to make more concrete, specific, and sophisticated recommendations that carefully consider potential drawbacks and unintended consequences. You are welcome to evaluate the specific suggestions in the brainstorming or to suggest new approaches.

Please note: You do not need to draw on resources beyond the course materials (readings, lectures, assignments, sections, etc.) in producing your report. However, you may feel free to do so. 

Your report should provide advice to the Wikimedia Foundation and/or the Wikipedia community on the a challenge that I identify. Details on the challenge are still {{tbd}} and {{forthcoming}}. See the [[#Assessment: Wikipedia Analysis | assessment section]] of this page for details on what I will be grading for.

Turn your report as a subpage of your userpage. For example, I would create mine with http://en.wikipedia.org/wiki/User:Benjamin_Mako_Hill/Report as the URL. Of course, you should replace "Benjamin_Mako_Hill" with your Wikipedia username. You can also just go to your userpage by clicking on your username on Wikipedia and then adding "/Report" at the end of the URL. When you go that page, it will say '''Wikipedia does not have a user page with this exact name.''' You can create the new page by just clicking the "Create" tab on that page. When you're done, you can paste the URL into Canvas.
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==== Assessment: Wikipedia Analysis (Task 7) ====

In addition to finishing up your Wikipedia article, everybody should turn in a report analyzing the Wikipedia community, using your experience and the material we've covered so far to offering an assessment and advice to the Wikimedia Foundation and the Wikipedia Community on how to improve their community. I want you all to treat this as a dress rehearsal for your final projects.

Your report will be evaluated, first and foremost, on the degree to which it provides useful, informed, and actionable advice to the Wikipedia community and the Wikimedia Foundation. It will also be evaluated on the degree to which you engage with the course material. See the [[User:Benjamin Mako Hill/Assessment | writing rubric]] for details on my expectations in terms of the content of the papers. A successful essay will do the following things:

# Provide detailed, concrete, and actionable advice to the Wikipedia community and the Wikimedia Foundation. What should Wikipedia think about doing? What should they think about changing?
# Comment directly on your experience in Wikipedia. This is not general musing: the details you include should be evidence to serve your argument.
# Connect your experience in Wikipedia explicitly to the concepts in the course material we have covered. Justify your recommendations in terms of the theories and principles we've covered. Why should your recommendations be taken more seriously than just random advice from one new user?
# If possible, reflect on what parts of the theories or concepts we covered applied or didn't. You don't have to take everything taught in the course for granted. What would you change or add based on your experience? What is unique or different about Wikipedia?

I will give everybody in the course feedback on their assignment. The basic structure is shorter, but extremely similar, to what you will be doing in the final project. As a result, you can treat this as a "mid-term" and make adjustments based on feedback.

There's no minimum word count, but I'd suggest you take advantage of the space you're given. Generally speaking, you can say more, be more insightful, demonstrate more fluency (all the things we are assessing) if you use more space.

Your audience is Wikipedians who may read your report. You don't need to define things to prove to us that you've done the reading. You should define terms if you think that an audience of Wikipedians (who have not taken the class) will be lost/confused otherwise. Use your judgement to make a compelling, well reasoned, and well supported argument.

The intro, body, conclusion format is pretty reliable and useful. But if you feel it's better or more useful to deviate from that as well, that's fine. Don't use the numbered questions as your format, but do demonstrate consideration of each point somewhere in your essay.

Make an argument for why, based on your experience in Wikipedia and what you've learned in the class, things could/should be better and how that might happen. "A description of your experience" is part of that but we're not asking for a trip report. Your experience is important, but the details you share should always be in service to the argument and suggestions you are making.

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