Online Communities (UW COM481 Fall 2024)/Wikipedia Advising Report: Difference between revisions
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== Prompt == | |||
Like many others, members of the Wikipedia community and the Wikimedia Foundation (WMF) are interested in brainstorming a set of approaches for using 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 what people are considering]]. | |||
For this assignment, I want you to imagine that the WMF staff has contacted you seeking recommendations 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 educational material and a goal to engage people in its production. | |||
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 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.) to produce your report. However, you may feel free to do so. | |||
Turn your report | Turn your report into a subpage of your user page. 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 go to your user page by clicking on your username on Wikipedia and then adding "/Report" at the end of the URL. When you go to that page, it will say '''Wikipedia does not have a user page with this exact name.''' You can create a new page by just clicking the "Create" tab on that page. When you're done, you can paste the URL into Canvas. | ||
== Assessment == | |||
First and foremost, your report will be evaluated 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? | # 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? | ||
# | # 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 a user? | ||
# To the extent that it is relevant, feel free to comment directly on your experience in Wikipedia. When you do so, connect your experiences in Wikipedia explicitly to the concepts in the course material we have covered. | |||
# | |||
The teaching team 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 community advising project. As a result, you can treat this as a "mid-term" and make adjustments based on feedback. | |||
== Other guidance == | |||
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, and 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 judgment to make a compelling, well-reasoned, and well-supported argument. | |||
In terms of form, 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. | |||
Revision as of 19:39, 29 October 2024
Prompt
Like many others, members of the Wikipedia community and the Wikimedia Foundation (WMF) are interested in brainstorming a set of approaches for using generative AI and large language models in Wikipedia. There is already a page on Wikipedia that might be useful to get a sense of what people are considering.
For this assignment, I want you to imagine that the WMF staff has contacted you seeking recommendations on managing the impact of these tools. For context, the 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 educational material and a goal to engage people in its production.
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 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.) to produce your report. However, you may feel free to do so.
Turn your report into a subpage of your user page. 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 go to your user page by clicking on your username on Wikipedia and then adding "/Report" at the end of the URL. When you go to that page, it will say Wikipedia does not have a user page with this exact name. You can create a new page by just clicking the "Create" tab on that page. When you're done, you can paste the URL into Canvas.
Assessment
First and foremost, your report will be evaluated 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 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?
- 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 a user?
- To the extent that it is relevant, feel free to comment directly on your experience in Wikipedia. When you do so, connect your experiences in Wikipedia explicitly to the concepts in the course material we have covered.
The teaching team 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 community advising project. As a result, you can treat this as a "mid-term" and make adjustments based on feedback.
Other guidance
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, and 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 judgment to make a compelling, well-reasoned, and well-supported argument.
In terms of form, 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.
