User:Emilyvhuang/report

The rise of generative AI (GenAI) tools has opened up new opportunities for creativity and content creation on the internet. However, these innovations present challenges for Wikipedia, as the Wikimedia Foundation (WMF) faces the risks of inaccuracies and AI over-reliance. This paper aims to offer actionable recommendations and insights towards the impact of GenAI on the Wikipedia community.

Generative AI tools, like neural networks and large language models, are capable of producing text that represents human writing. While impressive, it comes with inherent risks; GenAI is still developing and can create plausible-sounding misinformation; AI-generated text may sound authoritative, but it's possible to create errors or misrepresent information. Wikipedia’s volunteer-based model means that some users might not fully understand AI’s limitations, leading to potential bias or errors in the content they contribute.

Another challenge is the potential impact of AI tools on Wikipedia’s community engagement. If GenAI becomes too widely used, there is a risk that editors may lean on AI tools for convenience, rather than contributing original research or engaging in source verification. This could undermine the platform's community and limit learning and knowledge-sharing opportunities from the editing process. From my personal experience with AI tools in the course, I received feedback on my article that was clearly AI-generated. When I recognized this, it made me feel that the feedback lacked authenticity. One of the things I’ve come to value about Wikipedia is the collaborative effort among real people offering insights and critiques. When that connection feels artificial, it weakens the trust and engagement that make the platform successful. This experience highlighted how crucial it is to maintain the human element in Wikipedia’s feedback processes, ensuring that AI tools are used in ways that support, not replace, meaningful community interaction.

Unintended social and ethical consequences may also arise. As more contributors turn to AI tools, especially for mundane tasks, there may be a shift in community norms regarding what constitutes “acceptable” contributions. The rise in AI tools can normalize its reliance to produce content, leading to both a cultural change in Wikipedia and steering away from the platform's mission of fostering human collaboration and engagement.

Therefore, the challenge for the Wikimedia Foundation is twofold: first, to ensure that AI-generated content does not compromise the integrity of Wikipedia’s articles, and second, to maintain a healthy, engaged, and responsible community that upholds the values of transparency, accuracy, and collaboration.

One of the most important steps that the WMF can take in addressing the challenges posed by generative AI is to establish clear and comprehensive guidelines for responsible AI use in Wikipedia content creation. These guidelines would highlight permitted tools, as well as the circumstances for which AI-generated content is unacceptable. For example, AI tools could be allowed to assist in drafting content, conducting research, or writing text in the early stages of article creation – to create entire articles or article sections without human oversight would be prohibited. Any AI-generated content should be subject to verification by human editors, ensuring that it meets Wikipedia’s high standards for accuracy and citation.

Given the rapidly evolving nature of GenAI, the WMF should invest in educational resources to help Wikipedians understand the implications of AI use. A training module is proposed to address several key areas: AI basics, ethical considerations, and evaluating AI-generated content for accuracy and neutrality. Such a program would help to inform both new and experienced contributors about the potential pitfalls of GenAI, such as the risk of unintentionally introducing misinformation or bias. Editors would learn to use AI as a supportive tool – not a replacement for human judgment – with case studies illustrating both successful and problematic AI use.

Given that Wikipedia is a collaborative platform, the training should not be a one-time event but an ongoing process. New contributors should be required to complete a basic AI training module as part of their introduction to Wikipedia, with experienced users encouraged to stay up to date with the latest developments in AI technology. By fostering a culture of continuous learning and knowledge-sharing, the WMF can ensure that the community adapts to the challenges posed by generative AI in a responsible and informed manner.

Equally important is the transparency of AI usage. Wikipedia’s community is built on the expectation that contributors are accountable for their work, and this accountability must extend to AI use. One way to ensure transparency is to require Wikipedians to disclose when they have used AI tools in the editing process. Similar to the declaration required in many academic publishing contexts, where authors must affirm that their work is original and has not been plagiarized, WMF can introduce a "Pledge to Originality" checkbox before a Wikipedian submits an edit. This checkbox would require editors to affirm that the content is their own original work, and that any AI-generated content has been appropriately vetted for accuracy and sources.

Research in behavioral norms suggests that reminders about ethical behavior can have a significant impact on decision-making. In this context, the “Pledge to Originality” would prompt editors to reflect on the integrity of their contributions before submitting them. By asking editors to acknowledge their responsibility towards authenticity, the WMF can create a stronger sense of accountability and reduce the likelihood of AI tool misusage. This mechanism can also serve as a preventive measure to discourage contributors from relying too heavily on AI without considering the broader implications towards Wikipedia’s content quality.

Displaying all of Wikipedia's rules at once may intimidate new users, as it can create the impression that norm violations are common and that there are many complex expectations to follow. The fear of getting caught using AI-generated content seems similar to the fear of plagiarism. This overwhelming display of rules could discourage participation, particularly if newcomers feel they are more likely to make mistakes. Simplifying the AI usage rules to key guidelines and emphasizing support from the community could help ease users into the platform without making them feel daunted as newcomers.

People learn norms through actions that stand out, as routine behavior can be hard to notice – while negative behaviors tend to grab attention. For example, the litter experiment by Cialdini, Kallgren, & Reno (1991) can be compared to improper language learning model (LLM) use. If LLM usage is not obvious in a group of articles, a writer might think it is unlikely to be caught or that it is not a big deal. However, if there is a sole poorly written AI-generated article, others are less likely to copy that bad behavior. On the other hand, if every article in a group is AI-generated, the sense of wrongdoing would decline because the norm has shifted. With explicit rules being broken, people are more likely to engage in improper behavior.

While preventive measures like clear guidelines and training modules lay a foundation, they must be complemented by tools that can identify AI-generated content after it has been submitted. The WMF can introduce an AI detection software that scans Wikipedia articles for characteristics of machine-generated text. AI detection tools are already in use on other platforms, and their application to Wikipedia would help ensure that content is subject to further scrutiny when AI-generated text is suspected.

It is important to recognize that AI tools can also be used in a positive way to enhance the quality and neutrality of Wikipedia’s content. One of the most pressing concerns for Wikipedia pages is identifying and mitigating bias in articles. AI tools can be trained to detect patterns of bias in language or source material, and help pinpoint areas with skewed content or unbalanced viewpoints. Rather than undermining Wikipedia’s neutrality, AI-powered bias detection tools can aid Wikipedians in making articles fairer and more balanced, and help maintain Wikipedia’s credibility as an educational resource.

These tools can aid both editors and moderators in maintaining Wikipedia’s goals in keeping content scientific and accurate. While AI detection tools are not fail-safe, they could serve as a helpful first step in identifying problematic content and encouraging human review.

Finally, The WMF should encourage an open and transparent dialogue about their use within the Wikipedia community. This could be achieved through discussion pages, forums, or even “town hall” meetings where editors can share their experiences with AI tools, exchange best practices, and discuss the ethical implications of AI in content creation. Promoting a culture of peer learning and collaboration around AI usage would help to address misunderstandings about AI tools, and foster a more informed and responsible community. By encouraging editors to learn from each other and share their insights, the WMF can ensure that the Wikipedia community successfully reaps the benefits and manages the challenges of GenAI.