Liu Ruohan

Q1:When you search for information, do you prefer to use AI or Wikipedia? Why?

When encountering different types of questions, I choose different search methods. For highly quantitative questions requiring precise answers, I prefer using AI to assist with calculations. For inquiries leaning towards humanities or a comprehensive understanding of historical aspects, I opt for using Wikipedia. However, for everyday questions, I predominantly rely on AI for answers. Wikipedia explanations on certain topics may not always be comprehensive, often necessitating supplementary information for accuracy. Although AI responses may appear overly structured, they provide multiple perspectives and directions for consideration. Asking AI questions allows for more flexible and personalized inquiries, whereas Wikipedia requires precise terminology for searches and cannot address personalized queries.

I asked both Wikipedia and AI about "Analysis of the 2013 smog in East China." Wikipedia provided a comprehensive answer covering background, causes, major cities affected, impacts, and analysis of pollutants, offering a thorough explanation of the entire event. AI's response focused on weather conditions, environmental pollution, haze, and differing governmental responses to the event. AI's answers were more structured, with each point analyzed in just two sentences, which did not facilitate a clear understanding of the causes and outcomes of the event. Moreover, Wikipedia's answer provided specific web pages where further analysis of this event could be found, aiding in gathering additional information.

Q2:Should AI be used to create Wikipedia articis?

I believe AI cannot be used to write Wikipedia articles. Despite AI being trained on vast amounts of text and models, the answers it provides are still not comprehensive enough. Writing for Wikipedia requires a highly rigorous approach, whereas AI-generated responses tend to be somewhat limited and brief in description. Additionally, Wikipedia articles need substantial textual sources to support their existence, a task AI cannot accomplish without risking accusations of plagiarism. Furthermore, Wikipedia articles benefit from multiple users simultaneously editing them, ensuring timely updates and a rich content base due to user contributions. In contrast, AI responses are programmatic and only allow readers to passively accept the provided answers.

Q3:What is Wikipedia community doing about AIs?

Wikipedia has integrated AI into various aspects such as article translation, article generation, image and language generation, and bias reduction. What surprises me the most is its application in reducing gender bias by using AI to generate articles. AI draws from diverse datasets, which helps ensure unbiased data on contentious gender-related topics. Regular testing by administrators also helps keep the AI operations in check, ensuring timely updates to reduce misinformation.

Q4:Use ChatGPT to generate a Wikipedia article on the same topic as your Wikipedia project (or another topic you find interesting). Compare them. How good of a job ChatGPT is doing?

I chose to compare the Wikipedia article "Dashatou Railway Station" that I previously edited. The article I edited discusses the historical development of this station, including the wars it experienced and its current development status. It also describes the reasons behind the station's name and the construction of commemorative museums, supplemented with detailed descriptions and images. In contrast, the AI-provided answer only briefly touches on aspects such as location, line, and surroundings. The AI's description of this station is very limited and does not provide a comprehensive answer to readers.

Q5：Ask AI how you can use it to help Wikipedia?

The response from AI is accurate in highlighting how AI technology can contribute significantly to Wikipedia by automating routine tasks, improving content quality, expanding accessibility, and enhancing user experience. However, I believe that AI cannot replace human judgment and subjective editing when it comes to editorial decisions.

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