Community Notes: Twitter is testing Community Notes for images, videos: How it will help users – Times of India
Twitter is one of the social media platforms that has witnessed an increase in AI-generated images and videos. These media often become sources of misinformation. For example, an AI generated video of an explosion near the Pentagon quickly became a hot topic worldwide. To curb such instances, the microblogging platform is now expanding the Community Notes feature photos and videos. The feature is aimed at making it easier for people to identify potentially misleading media.
“From AI-generated images to manipulated videos, it’s common to come across misleading media. Today we’re piloting a feature that puts a superpower into contributors’ hands: Notes on Media Notes attached to an image will automatically appear on recent & future matching images,” the company said in a tweet.
What is Community Notes
Formerly known as Birdwatch, Community Notes started as a pilot project aimed at curtailing misinformation and “create a better-informed world.” In this programme, a select few participants can add, in a collaborative manner, notes to tweets bringing helpful context.
“If you’re a contributor with a Writing Impact of 10 or above, you’ll see a new option on some Tweets to mark your notes as ‘About the image’. This option can be selected when you believe the media is potentially misleading in itself, regardless of which Tweet it is featured in,” Twitter said.
With the latest announcement, the feature will allow contributors who have high enough ratings to apply notes to images shared within tweets, labelling them so that people know that a particular image or video has been created using generative AI or is manipulated.
“Raters and readers will see notes that authors marked as ‘about the image’ slightly differently, so it’s clear to everyone that they should be interpreted as about the media, not the specific Tweet. Ratings can help identify cases where a note may not apply to a specific Tweet,” the company added.
Right now, Community Notes for media supports Tweets with a single image. Twitter said that it is working to expand it to videos and tweets with multiple images/ videos.
“From AI-generated images to manipulated videos, it’s common to come across misleading media. Today we’re piloting a feature that puts a superpower into contributors’ hands: Notes on Media Notes attached to an image will automatically appear on recent & future matching images,” the company said in a tweet.
What is Community Notes
Formerly known as Birdwatch, Community Notes started as a pilot project aimed at curtailing misinformation and “create a better-informed world.” In this programme, a select few participants can add, in a collaborative manner, notes to tweets bringing helpful context.
“If you’re a contributor with a Writing Impact of 10 or above, you’ll see a new option on some Tweets to mark your notes as ‘About the image’. This option can be selected when you believe the media is potentially misleading in itself, regardless of which Tweet it is featured in,” Twitter said.
With the latest announcement, the feature will allow contributors who have high enough ratings to apply notes to images shared within tweets, labelling them so that people know that a particular image or video has been created using generative AI or is manipulated.
“Raters and readers will see notes that authors marked as ‘about the image’ slightly differently, so it’s clear to everyone that they should be interpreted as about the media, not the specific Tweet. Ratings can help identify cases where a note may not apply to a specific Tweet,” the company added.
Right now, Community Notes for media supports Tweets with a single image. Twitter said that it is working to expand it to videos and tweets with multiple images/ videos.
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Work in progress
The company also highlighted that this feature could also tackle the viral spread of AI-generated, misleading images. Twitter noted that it wants the notes to automatically appear on “recent and future” copies of the same image even if they are shared by separate users on the platform. Twitter is still working in that direction.
“It’s currently intended to err on the side of precision when matching images, which means it likely won’t match every image that looks like a match to you. We will work to tune this to expand coverage while avoiding erroneous matches,” Twitter said.
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