Indi Young’s Post

This was one of the most interesting workshops I have attended. The propositions here are distillation of learnings across many different platforms. It is not only a view of the past but also a blue print of what tomorrow could be. World would have been a better place if Tom and some of these thinkers could influence the vision of these platforms more. (I tried to make it happen and failed … story for another day …) Many online platforms predominantly rank items by predicted user engagement. We believe that there is much unrealized potential in including non-engagement signals, which can improve outcomes both for platforms and for society as a whole. Based on a daylong workshop with experts from industry and academia, we formulate a series of propositions and document each as best we can from public evidence, including quantitative results where possible. There is strong evidence that ranking by predicted engagement is effective in increasing user retention. However retention can be further increased by incorporating other signals, including item "quality" proxies and asking users what they want to see with "item-level" surveys. There is also evidence that "diverse engagement" is an effective quality signal. Ranking changes can alter the prevalence of self-reported experiences of various kinds (e.g. harassment) but seldom have large enough effects on attitude measures like user satisfaction, well-being, polarization etc. to be measured in typical experiments. User controls over ranking often have low usage rates, but when used they do correlate well with quality and item-level surveys. There was no strong evidence on the impact of transparency/explainability on retention. There is reason to believe that generative AI could be used to create better quality signals and enable new kinds of user controls.

I like the analysis of the interaction between “reality”, “information”, “truth”, and “order”. Clarity, insight, and the ability to observe trends/history on a meta-level is what makes Harari’s approach unique. Recommended 📚

A gnarly challenge of my career is captured here: ranking on quality metrics often significantly increases long-term retention, but predicted engagement tends to correlate negatively with quality. How do you help businesses make healthy decisions? Especially in the age of optimism around "machine learning can solve it"? Lots of good insights on surveys, item level and session / intercepts, which is one tool for illuminating the trade-offs.

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