Machine Augmentation

Exploring machine-in-the-loop technologies to enable knowledge equity at scale

machine augmentation


In 2018, the Wikimedia Foundation Product team identified machine augmentation of human activities on the wikis as a key dependency for realizing the Movement's vision of making the sum of the world's knowledge accessible to all the world's people. This section covers work related to evaluating, debiasing, and developing the algorithms that will make knowledge equity achievable at scale. Algorithms have the potential to make content better and more available across language and cultural boundaries, to make contribution and moderation tasks more efficient, to flag article (un)trustworthiness to the reader, and to provide an overall picture of coverage of knowledge across and within wikis.


  1. Trusted: Signals, Inferences & Indicators

    The goal of this work is to develop systems for automatically detecting and characterizing the editorial debates behind Wikipedia articles for the purpose of surfacing indications of trustworthiness to the reader. This project is a collaboration between the Wikimedia Foundation and the CMU Human Computer Interaction Institute.
  2. Content Translation Newcomer Survey

    A customizable survey that can be used to easily, quickly, and reliably collect feedback from a more diverse pool of Content Translation users.
  3. Article Section Translation Study

    An evaluation of new designs for tools that help editors translate article sections and receive translation support on mobile devices.
  4. Machine Translation Meets Human Perception

    The Machine Translation Meets Human Perception (MTMHP) study developed a protocol for evaluating how readers perceive and evaluate machine-translated content - across three different languages, cultural contexts, and content domains.
  5. Ethical & Human-Centered AI

    This project identfies challenges and emerging opportunities to leverage AI technologies to further the mission of Wikimedia.
  6. Augmentation

    This is a position piece developed by Wikimedia Foundation to frame the potential of machine-in-the-loop technologies in making all the world's knowledge available to all, and to ensure the process to assemble that knowledge is inclusive, balanced and safe.