Introducing Birdwatch, a community-based approach to misinformation
People come to Twitter to stay informed, and they want credible information to help them do so. We apply labels and add context to Tweets, but we don’t want to limit efforts to circumstances where something breaks our rules or receives widespread public attention. We also want to broaden the range of voices that are part of tackling this problem, and we believe a community-driven approach can help. That’s why today we’re introducing Birdwatch, a pilot in the US of a new community-driven approach to help address misleading information on Twitter.
Here’s how it works
Birdwatch allows people to identify information in Tweets they believe is misleading and write notes that provide informative context. We believe this approach has the potential to respond quickly when misleading information spreads, adding context that people trust and find valuable. Eventually we aim to make notes visible directly on Tweets for the global Twitter audience, when there is consensus from a broad and diverse set of contributors.
In this first phase of the pilot, notes will only be visible on a separate Birdwatch site. On this site, pilot participants can also rate the helpfulness of notes added by other contributors. These notes are being intentionally kept separate from Twitter for now, while we build Birdwatch and gain confidence that it produces context people find helpful and appropriate. Additionally, notes will not have an effect on the way people see Tweets or our system recommendations.
To date, we have conducted more than 100 qualitative interviews with individuals across the political spectrum who use Twitter, and we received broad general support for Birdwatch. In particular, people valued notes being in the community’s voice (rather than that of Twitter or a central authority) and appreciated that notes provided useful context to help them better understand and evaluate a Tweet (rather than focusing on labeling content as “true” or “false”). Our goal is to build Birdwatch in the open, and have it shaped by the Twitter community.
To that end, we’re also taking significant steps to make Birdwatch transparent:
- All data contributed to Birdwatch will be publicly available and downloadable in TSV files
- As we develop algorithms that power Birdwatch — such as reputation and consensus systems — we aim to publish that code publicly in the Birdwatch Guide. The initial ranking system for Birdwatch is already available here.
We hope this will enable experts, researchers, and the public to analyze or audit Birdwatch, identifying opportunities or flaws that can help us more quickly build an effective community-driven solution.
We want to invite anyone to sign up and participate in this program, and know that the broader and more diverse the group, the better Birdwatch will be at effectively addressing misinformation. More details on how to apply here.
We know there are a number of challenges toward building a community-driven system like this — from making it resistant to manipulation attempts to ensuring it isn’t dominated by a simple majority or biased based on its distribution of contributors. We’ll be focused on these things throughout the pilot.
From embedding a member of the University of Chicago’s Center for RISC on our team to hosting feedback sessions with experts in a variety of disciplines, we’re also reaching beyond our virtual walls and integrating social science and academic perspectives into the development of Birdwatch.
We know this might be messy and have problems at times, but we believe this is a model worth trying. We invite you to learn alongside as we continue to explore different ways of addressing a common problem. Follow @Birdwatch for the latest updates and to provide feedback on how we are doing.引用元：Twitter