How an ex-YouTube insider investigated its secret algorithm

Fri 2 Feb 2018 07.00 EST Last modified on Fri 2 Feb 2018 07.02 EST YouTube's recommendation system draws on techniques in machine learning to decide which videos are auto-played or appear "up next". The precise formula it uses, however, is kept secret. Aggregate data revealing which YouTube videos are heavily promoted by the algorithm, or how how many views individual videos receive from "up next" suggestions, is also withheld from the public. Disclosing that data would enable academic institutions, fact-checkers and regulators (as well as journalists) to assess the type of content YouTube is most likely to promote. By keeping the algorithm and its results under wraps, YouTube ensures that any patterns that indicate unintended biases or distortions associated with its algorithm are concealed from public view. By putting a wall around its data, YouTube, which is owned by Google, protects itself from scrutiny.