Twitter launches Community Notes to tackle the spread of misleading media

After demanding researchers who monitor tweets pay a whopping $42,000 API monthly fee, and having trouble with the widespread use of misleading AI images, Twitter has introduced a new feature to help prevent the spread of misinformation across the platform.

Last week, the company began asking academics to delete the data regarding tweets provided by an API called Decahose or pay a monthly fee to maintain access to it. The news led to a dissatisfied audience as they argued Twitter seems to not be prioritizing authenticity on its platform. Another case, as highlighted by TechCrunch, that led to today's announcement was images of a fake attack on the Pentagon Complex that went viral.

Hence, in an attempt to curb the backlash, Twitter announced Community Notes today. These ‘Notes on Media’ are attached to images shared by users, such that, whenever that image is shared, the note appears beside it.

Users will see Notes that have been automatically attached to the original post with any recent or future matching images. The capability is reserved for contributors who have a Writing Impact of 10 or above. A Writing Impact measures how often a contributor's notes have earned the status of Helpful when rated by others.

These contributors will get the option of adding an “About the image” on some of their tweets. They can then choose whether their note is about the tweet or the image itself. If they choose the latter, the note will automatically appear whenever the image is shared. According to Twitter, this is to avoid the spread of misleading images regardless of the tweet they are featured in.

Due to this feature, readers and raters on Twitter will be able to understand the context of the media posted and get to rate it as well. These ratings can identify cases where a specific note may not apply to the tweet shared.

Twitter mentioned that the feature is under development as it is working on adding notes for videos, GIFs, and tweets with multiple images. It also added:

“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.”

Lastly, the company highlighted that it will monitor the use of Notes on Media and will be open to feedback on the capability.