Pinterest Unleashes Enhanced Discovery System

Pinterest, the popular visual discovery platform, is taking steps to ensure greater representation and inclusivity within its app. In a recent research paper, Pinterest outlined how it has developed a system to incorporate a wide range of skin tones in its search, related products, and home feed experiences.

According to Pinterest:

“Specifically, we have developed and deployed scalable diversification mechanisms that utilize a visual skin tone signal to support representation of a wide range of skin tones in recommendations.”

The system utilizes skin tone matching within Pin images to diversify the examples shown in search results. By incorporating a visual skin tone signal, Pinterest aims to offer a more inclusive experience for its users. However, the platform is careful to strike a balance between diversity and relevance, restricting the matches to certain categories to maintain performance.

The implementation of this new system has not only improved the diversity of search matches but has also led to positive business retention metrics and an enhanced user experience. By prioritizing representation, Pinterest recognizes the importance of reflecting the diverse communities it serves and meeting their needs and preferences.

This initiative by Pinterest sets a positive example for other social apps and discovery tools, highlighting the significance of inclusivity and the potential for broader perceptual shifts based on common usage. 

Pinterest also notes:

“As technology becomes increasingly integrated into the daily lives of billions of people globally, it is crucial for online platforms to reflect the diverse communities they serve. Improving representation online can facilitate content discovery for a more diverse user base by reflecting their inclusion on the platform. This, in turn, demonstrates the platform’s ability to meet their needs and preferences.”

To learn more about Pinterest’s efforts, you can read their full overview on diversification in search and recommender systems here.

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