Aaron Halfaker

  1. The great Wikipedia bot-pocalypse: Challenging an established narrative

    Headlines assumed that when Wikipedia bots reverted edits made by other bots, the two were in conflict or ‘fighting’. This assumption sounds reasonable, but it is not the case for an overwhelming majority of bot-bot reverts.... Read more

  2. Investing in our shared future, supported by AI: Announcing the Scoring Platform team

    The Wikimedia Foundation’s new Scoring Platform team, led by Aaron Halfaker, will be working on democratizing access to AI, developing new types of AI predictions, and pushing the state of the art with regards to ethical practice of AI development.... Read more

  3. New dataset shows fifteen years of Wikipedia’s quality trends

    Looking to study how Wikipedia articles have improved over time? We’ve generated a dataset that tracks the quality of articles at monthly intervals over the entire 15-year history of Wikipedia across multiple languages—that’s 670 million assessments!... Read more

  4. Introducing the unique devices dataset: a new way to estimate reach on Wikimedia projects

    With the unique devices dataset, we’ve been able to quantify the shift to mobile across all projects. In almost all Wikimedia projects, more than half of our unique devices are accessing content using the mobile sites.... Read more

  5. Artificial intelligence service “ORES” gives Wikipedians X-ray specs to see through bad edits

    When anyone can edit any page of one of the biggest websites in the world, how can you evaluate all those changes? A Wikimedia Foundation research scientist and a team of volunteers has developed an artificial intelligence service to handle some of the highest-volume crowdsourcing issues on the internet.... Read more

  6. Wikipedia’s very active editor numbers have stabilized—delve into the data with us

  7. Kids these days: the quality of new Wikipedia editors over time