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Fake photos and videos have become quite common due to the emergence of editing tools. Now, with the rising popularity of artificial intelligence (AI) tools the number of manipulated videos and photos have simply skyrocketted. It has even made it extremely difficult to check the credibility of the source of the material. What makes it even more concerning is that common people may unknowingly share such fake imagery on social media platforms without verifying the original source, thereby contributing to the spread of misinformation and social unrest. The same applies to Twitter and it is reportedly fighting back. The portal has now come up with a crowdsourced fact-check feature called ‘Community Notes’.
“Community Notes are frequently added to Tweets that feature images or videos. In many cases, these notes can provide valuable context, not just for a single Tweet, but for any Tweet containing the same media,” Twitter added in a note. Community Notes, the user-generated platform to empower people on Twitter, has confirmed a new feature dubbed as ‘Notes on Media’ will automatically bring a note attached to an image on recent and future matching images.
It further mentioned that if you are a contributor with a Writing Impact of 10 or above, you will get an option to mark your notes as “About the image.” You can use this option when you believe that the media is potentially misleading in nature.
Who are Contributors to Community Notes? Contributors are people just like you! Anyone on Twitter whose account meets the basic eligibility criteria such as no Twitter Rules violations since Jan 1, 2023, a trusted phone carrier, a verified phone number, and is not associated with other Community Notes accounts, can sign up.
Twitter fact-check feature to curb fake images and videos
It must be noted that the feature is currently available for Tweets with single images only. However, the Twitter Community Notes blog has suggested that it is working to expand it to Videos and Tweets with multiple images and videos. It is currently in its initial stage, and hence there are some limitations.
According to the Twitter blog, image matching may not guarantee absolute accuracy, as it may not identify every image that appears online. In the future, it will work to expand coverage while avoiding wrong matches. Also, Twitter will observe how this notes feature on media has been used to improve it in the future.
Key takeaway.
Will it work? It is early days, but the very fact that Twitter is looking at the common folk to police the fake images and videos space indicates that the problem is very big and it alone may not be able to tackle it.
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