The Contribution Conundrum: Why Did Wikipedia Succeed While Other Encyclopedias Failed? The Next Google Search Engine Will Be Generative AI.

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Sep 28, 2023

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The Contribution Conundrum: Why Did Wikipedia Succeed While Other Encyclopedias Failed? The Next Google Search Engine Will Be Generative AI.

Wikipedia's success can be attributed to several key factors. One of the main reasons is that it felt familiar to users. By basing its structure on the traditional encyclopedia, Wikipedia tapped into a universal approach to organizing information that users were already accustomed to. This familiarity played a significant role in attracting contributors to the platform.

Unlike other projects, Wikipedia did not focus on building its own technology. Instead, it prioritized substantive content development. This approach allowed Wikipedia to offer low transaction costs to participation, making it easy for users to contribute without feeling overwhelmed by complex technology.

Interestingly, Wikipedia's de-emphasis on social ownership of content actually encouraged more contributions. The fact that it's difficult to determine who wrote or edited an article created a sense of anonymity and lowered the pressure for users to produce something exceptional. This led to more collaboration and a vast amount of marginal contributions that ultimately enriched the platform.

The lesson here is clear: if you want user contributions, create platforms that are familiar and easy to use. Instead of dazzling users with intricate technology, focus on helping them understand what you expect from them. By reducing barriers to entry and making participation accessible, you can foster a community of contributors.

Now, let's shift our focus to the future of search engines. Currently, search engine design is limited by the paradigms established in the late 1990s. While these methods were efficient at the time, the content we consume today has evolved significantly. From social networks and data streams to video content, ecommerce, and authoritative knowledge sources like Wikipedia, the landscape has changed.

To challenge the status quo, we need to leverage generative AI. Rather than relying on a large database for search results, we can use that database as training data and generate results using neural networks. Trained models are relatively small compared to the training data, making them portable and efficient.

Replacing Google entirely will require significant technological advancements, but there is potential for a hybrid solution in the meantime. Google already attempts to generate query results for certain questions, gradually reducing traffic to non-Alphabet properties. This shift in approach would also impact distribution, as it becomes impractical to install the entire Google archive on individual devices. However, a machine learning model could effectively run on various platforms.

Looking back at the history of search engines, Yahoo and AltaVista provide valuable insights. Yahoo, despite multiple pivots, remains relevant today. AltaVista, on the other hand, briefly dominated the market but failed to address spam issues, leading to its rapid demise. These examples highlight the importance of adapting to user needs and continually improving spam protection to maintain a competitive edge.

In conclusion, the success of Wikipedia and the future of search engines both underscore the significance of user-friendly platforms and the power of generative AI. To encourage contributions, prioritize familiarity and ease of use. Embrace evolving technologies to deliver more relevant and efficient search results.

Actionable Advice:

  • 1. When building platforms that rely on user contributions, prioritize familiarity and simplicity. Make it easy for users to understand what is expected of them.
  • 2. Explore the potential of generative AI in search engine design. By leveraging training data and neural networks, we can generate more accurate and personalized results.
  • 3. Continually adapt and improve spam protection to maintain user trust and prevent the rapid decline experienced by search engines like AltaVista.

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