Conversation AI

Conversation AI is a collaborative research effort exploring ML as a tool for better discussions online.

View My GitHub Profile

Conversation-AI is an initiative to protect voices in conversation. We develop machine learning models to classify the impact of comments on conversations, and we serve these to platforms via the Perspective API. We also conduct experiments and publish original research to explore the strengths and weaknesses of ML as a tool for combating online toxicity and harassment. Further details can be found in our research resources page, and our blog: The False Positive.

Vision

Globally, fewer people are silenced and more people are able to safely engage in good faith discussion online. Our team leads as an example of ethical practices in building technology.

Our Values

Perspective API

Perspective (demo, developer site) is a free API that helps you host better conversations online. The API uses machine learning to analyze a string of text and predict the perceived impact it might have on a conversation. This prediction comes in the form of a score, which you can use to give feedback to commenters, help moderators more easily review comments, allow readers to more easily find interesting or productive comments, and more (see gallery of use cases).

Our models are not perfect and will make errors. It will be unable to detect patterns of toxicity it has not seen before, and it will falsely detect comments similar to patterns of previous toxic conversations. To help improve the machine learning, the API supports sending our team suggested scores - learn more at ‘Contribute Feedback’. Finally, to stay informed on new attributes, language support, and features, we encourage you to join the perspective-announce group.

Tune

Tune (documentation) is a Chrome extension that helps people adjust the level of toxicity they see in comments across the internet.

Moderator

Moderator is an open-source tool that uses machine learning to help moderators identify and reduce toxicity in forums and comment sections.

Who is working on this?

This research effort is led by Jigsaw and the Google Counter-Abuse Technology Team.