Billions of people use Facebook and Instagram every day to share the ups and downs of life, to connect with people who share their interests, and to discover content they enjoy. To make everyone\u2019s experience on our apps unique and personalized to them, we use AI systems to decide what content appears, informed by the choices they make.<\/span><\/p>\n I wrote previously <\/span>about the relationship between you and the algorithms<\/a><\/span> Meta uses to shape what you see on Facebook and Instagram, and to challenge the myth that algorithms leave people powerless over the content they see. In that piece, I wrote that we needed to be more frank about how this relationship works and to give you more control over what you see.<\/span>\u00a0<\/span><\/p>\n Today, we\u2019re building on that commitment by being more transparent around several of the AI systems that incorporate your feedback to rank content across Facebook and Instagram. These systems make it more likely that the posts you see are relevant and interesting to you. We\u2019re also making it clearer how you can better control what you see on our apps, as well as testing new controls and making others more accessible. And we\u2019re giving more detailed information for experts so they can better understand and analyze our systems.\u00a0<\/span><\/p>\n This is part of a wider ethos of openness, transparency and accountability. With rapid advances taking place with powerful technologies like generative AI, it\u2019s understandable that people are both excited by the possibilities and concerned about the risks. We believe that the best way to respond to those concerns is with openness. Generally speaking, we believe that as these technologies are developed, companies should be more open about how their systems work and collaborate openly across industry, government and civil society to help ensure they are developed responsibly. That starts with giving you more insight into, and control over, the content you see.\u00a0<\/span><\/p>\n Our AI systems predict how valuable a piece of content might be to you, so we can show it to you sooner. For example, sharing a post is often an indicator that you found that post to be interesting, so predicting that you will share a post is one factor our systems take into account. As you might imagine, no single prediction is a perfect gauge of whether a post is valuable to you. So we use a wide variety of predictions in combination to get as close as possible to the right content, including some based on behavior and some based on user feedback received through surveys.<\/span><\/p>\n We want to be more open about how this works. A model of transparency Meta has been developing and advocating for some time is the publication of system cards, which give people insight into how our systems work in a way that is accessible for those who don\u2019t have deep technical knowledge. Today, we are <\/span>releasing<\/span> 22 system cards for Facebook and Instagram. They give information about how our AI systems rank content, some of the predictions each system makes to determine what content might be most relevant to you, as well as the controls you can use to help customize your experience. They cover Feed, Stories, Reels and other surfaces where people go to find content from the accounts or people they follow. The system cards also cover AI systems that recommend \u201cunconnected\u201d content from people, groups, or accounts they don\u2019t follow. You can find a more detailed explanation of the AI behind content recommendations <\/span>here<\/span><\/a>.<\/span><\/p>\n To give a further level of detail beyond what\u2019s published in the system cards, we\u2019re sharing the types of inputs \u2013 known as signals \u2013 as well as the predictive models these signals inform that help determine what content you will find most relevant from your network on Facebook. The categories of signals we\u2019re releasing represent the vast majority of signals currently used in Facebook Feed ranking for this content. You can find these signals and predictions in the <\/span>Transparency Center<\/span><\/a>, along with how frequently they tend to be used in the overall ranking process.<\/span>\u00a0<\/span><\/p>\n We also use signals to help identify harmful content, which we remove as we become aware of it, as well as to help reduce the distribution of other types of problematic or low-quality content in line with our Content Distribution Guidelines. We\u2019re including some examples of the signals we use to do this. But there\u2019s a limit to what we can disclose safely. While we want to be transparent about how we try to keep bad content away from people\u2019s Feeds, we also need to be careful not to disclose signals which might make it easier for people to circumvent our defenses.<\/span><\/p>\n Of course, not everyone will find information just because we publish it on our website. That\u2019s why we make it possible to see details directly in our apps about why our systems predicted content would be relevant to you, and the types of activity and inputs that may have led to that prediction. We\u2019re expanding our \u201c<\/span>Why Am I Seeing This?<\/span><\/a>\u201d feature in Instagram Reels tab and Explore, and Facebook Reels in the coming weeks, after previously launching it for some Feed content and all <\/span>ads<\/span><\/a> on both Facebook and Instagram. You\u2019ll be able to click on an individual reel to see more information about how your previous activity may have informed the machine learning models that shape and deliver the reels you see.<\/span><\/p>\n By using the tools available, you have the ability to shape your experiences on our apps so you see more of the content you want to see, and less of the content you don\u2019t. To make this easier, we\u2019ve created centralized places on Facebook and Instagram where you can customize controls that influence the content you see on each app. You can visit your Feed Preferences on Facebook and the Suggested Content Control Center on Instagram through the three-dot menu on relevant posts, as well as through Settings.<\/span><\/p>\n On Instagram, we\u2019re testing a new feature that makes it possible for you to indicate that you\u2019re \u201cInterested\u201d in a recommended reel in the Reels tab, so we can show you more of what you like. The \u201cNot Interested\u201d <\/span>feature<\/span><\/a> has been available since 2021. You can learn more about influencing what you see across Instagram <\/span>here<\/span><\/a>.<\/span><\/p>\n So you can customize your experience and the content you see, we also have a \u201cShow more, Show less\u201d<\/span> feature<\/span><\/a> on Facebook, which is available on all posts in Feed, Video, and Reels via the three-dot-menu. We\u2019re working on ways to make the feature even more prominent. And if you don\u2019t want an algorithmically-ranked Feed \u2013 or just want to see what your Feed would look like without it \u2013 you can\u00a0 use the <\/span>Feeds tab<\/span><\/a> on Facebook or select <\/span>Following<\/span><\/a> on Instagram to switch to a chronological Feed. You can also add people to your Favorites list on both <\/span>Facebook<\/span><\/a> and <\/span>Instagram<\/span><\/a> so you can always see content from your favorite accounts.<\/span><\/p>\n We also believe an open approach to research and innovation \u2013 especially when it comes to transformative AI technologies \u2013 is better than leaving the know-how in the hands of a small number of big tech companies. That\u2019s why we\u2019ve released over 1,000 AI models, libraries and data sets for researchers over the last decade so they can benefit from our computing power and pursue research openly and safely. It is our ambition to continue to be transparent as we make more AI models openly available in future.\u00a0<\/span><\/p>\n In the next few weeks, we will start rolling out a new suite of tools for researchers: Meta\u2019s Content Library and API. The Library includes data from public posts, pages, groups, and events on Facebook. For Instagram, it will include public posts and data from creator and business accounts. Data from the Library can be searched, explored, and filtered on a graphical user interface or through a programmatic API. Researchers from qualified academic and research institutions pursuing scientific or public interest research topics will be able to apply for access to these tools through partners with deep expertise in secure data sharing for research, starting with the University of Michigan\u2019s Inter-university Consortium for Political and Social Research. These tools will provide the most comprehensive access to publicly-available content across Facebook and Instagram of any research tool we have built to date and also help us meet new data-sharing and transparency compliance obligations.<\/span><\/p>\n We hope by introducing these products to researchers early in the development process, we can receive constructive feedback to ensure we\u2019re building the best possible tools to meet their needs.<\/span><\/p>\n<\/p><\/div>\nHow AI Predictions Influence Recommendations<\/h2>\n
![\"2](\"https:\/\/about.fb.com\/wp-content\/uploads\/2023\/06\/01_IG-and-FB-WAIST-1.jpg?resize=960%2C836\")
<\/a><\/p>\nExpanding Tools to Personalize Your Experience<\/h2>\n
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<\/a><\/p>\nProviding Better Tools for Researchers<\/h2>\n