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style="box-sizing:border-box;background-image:url(https://scontent-nrt1-2.xx.fbcdn.net/v/t39.8562-6/338951214_174983525371127_8459219264227600634_n.jpg?_nc_cat=105&ccb=1-7&_nc_sid=f537c7&_nc_ohc=nDpSsxOikiEQ7kNvgEDCkyk&_nc_zt=14&_nc_ht=scontent-nrt1-2.xx&_nc_gid=AZIAxfG0C6i-ZD8uDrnoy8B&oh=00_AYAzRFmanmimPVt4VFJnvx0r830PhfCVd3krmoapQOJDeA&oe=674CF5FD);" /></div></div></div></div></div><div class="_a5gf _a5gm _a5i5 _a5jj"></div><div class="_a5fu _a9w7 _a5x3"><div class="_a5eb _allk _a5ec _a5eg _a5eh _a5er _a5fv _a5fw _ajr_"><div class="_a5eb _allk _a5ec _a5eg _a5ep _a5er _a5d5 _a5db _a5dj _a5dv"><div class="_a5gf _a5gg _a5i2 _a5jg"></div><div class="_a5ci _a5cs _a92o _a5e5 _a5w7"><p>Our commitment to Responsible AI </p><br /></div></div><div class="_a5eb _allk _a5ec _a5eg _a5ep _a5er _a5d5 _a5dd _a5dj _a5dv"><div class="_a5gf _a5gg"></div><p class="_a92o _a5c- _a5w7">Our Responsible AI efforts are propelled by our mission to help ensure that AI at Meta benefits people and society. Through regular collaboration with subject matter experts, policy stakeholders and people with lived experiences, we’re continuously building and testing approaches to help ensure our machine learning (ML) systems are designed and used responsibly.</p></div></div></div><div class="_a5gf _a5gp _a5i9 _a5jn"><hr /></div><div class="_amqq"><noscript id="u_0_8_Q9"></noscript></div><hr /><div class="_a5gf _a5gq _a5i9 _a5jn"></div><div id="pillars"><div class="_a5fu _a9w7 _a5fx"><div class="_a5eb _allk _a5ec _a5ee _a5ep _a5er _a5fv _a5fw _ajr_"><div class="_a5eb _allk _a5ec _a5ee _a5ep _a5er _a5d5 _a5dd _a5do _a5dv"><div class="_a5eb _allk _a5ec _a5ee _a5ep _a5er _a5d5 _a5d7 _a5dj _a5dv"><h5 class="_a92o _a5d1 _a5wf _a5ct">Pillars</h5><h2 class="_a92o _a5cw _a5wf _a5ct">Meta’s five pillars of responsible AI that inform our work</h2><div class="_a5eb _allk _a5ec _a5eg _a5ep _a5er _a5d5 _a5df _a5dj _a5dv"><p class="_a92o _a5c- _a5wf">We ground our work to ensure that AI is designed and used responsibly around a set of core values.</p></div></div></div></div></div></div><div class="_a5gf _a5gp _a5i9 _a5jn"></div><div class="_a5fu _a9w7 _a5x3"><div class="_a5eb _allk _a5ec _a5eg _a5er _a5f6 _a5fp _a5fv _a5fw _ajr_"><div class="_a5eb _allk _a5ec _a5eg _a5er _a5d5 _a5dd _a5dj _a5dv _a5ii _a5jw"><div class="_cmsPaletteMetaDrawerGroup__mcdsv1 _a6kp" data-testid="drawer-group" id="u_0_9_bq"><div class="_ap9d _a6jb _a6ts" data-testid="drawer" id="u_0_a_BQ"><button class="_a6iy _albs" data-testid="drawer-tab" aria-controls="u_0_0_YE" data-ms="{"creative":"accordion","creative_detail":"Privacy and security"}"><div class="_9bhp _9bhq _9bhs _9bh3"><div class="_a82a"><p class="_a92o _a5cx _a5w7">Privacy and security</p></div><div class="_a6jc _a6jd" data-testid="toggle-icon"><div class="_a6i_ _as4z"></div></div></div></button><div id="u_0_0_YE" class="_a6iz" data-testid="drawer-section"><div class="_a6jf"><p class="_a92o _a5c- _a5w7 _a5ct"><p>Protecting the privacy and security of people’s data is the responsibility of everyone at Meta.</p></p></div></div></div><div class="_ap9d _a6jb _a6ts _a6jg" data-testid="drawer" id="u_0_b_Qd"><button class="_a6iy _albs" data-testid="drawer-tab" aria-controls="u_0_1_Mx" data-ms="{"creative":"accordion","creative_detail":"Fairness and inclusion"}"><div class="_9bhp _9bhq _9bhs _9bh3"><div class="_a82a"><p class="_a92o _a5cx _a5w7">Fairness and inclusion</p></div><div class="_a6jc _a6jd" data-testid="toggle-icon"><div class="_a6i_ _as4z"></div></div></div></button><div id="u_0_1_Mx" class="_a6iz" data-testid="drawer-section"><div class="_a6jf"><p class="_a92o _a5c- _a5w7 _a5ct">Everyone should be treated fairly when using our products and they should work equally well for all people.</p></div></div></div><div class="_ap9d _a6jb _a6ts _a6jg" data-testid="drawer" id="u_0_c_YU"><button class="_a6iy _albs" data-testid="drawer-tab" aria-controls="u_0_2_+d" data-ms="{"creative":"accordion","creative_detail":"Robustness and safety"}"><div class="_9bhp _9bhq _9bhs _9bh3"><div class="_a82a"><p class="_a92o _a5cx _a5w7">Robustness and safety</p></div><div class="_a6jc _a6jd" data-testid="toggle-icon"><div class="_a6i_ _as4z"></div></div></div></button><div id="u_0_2_+d" class="_a6iz" data-testid="drawer-section"><div class="_a6jf"><p class="_a92o _a5c- _a5w7 _a5ct">AI systems should meet high performance standards, and should be tested to ensure they behave safely and as intended.</p></div></div></div><div class="_ap9d _a6jb _a6ts _a6jg" data-testid="drawer" id="u_0_d_4o"><button class="_a6iy _albs" data-testid="drawer-tab" aria-controls="u_0_3_nY" data-ms="{"creative":"accordion","creative_detail":"Transparency and control"}"><div class="_9bhp _9bhq _9bhs _9bh3"><div class="_a82a"><p class="_a92o _a5cx _a5w7">Transparency and control</p></div><div class="_a6jc _a6jd" data-testid="toggle-icon"><div class="_a6i_ _as4z"></div></div></div></button><div id="u_0_3_nY" class="_a6iz" data-testid="drawer-section"><div class="_a6jf"><p class="_a92o _a5c- _a5w7 _a5ct">People who use our products should have more transparency and control around how data about them is collected and used.</p></div></div></div><div class="_ap9d _a6jb _a6ts" data-testid="drawer" id="u_0_e_KI"><button class="_a6iy _albs" data-testid="drawer-tab" aria-controls="u_0_4_lg" data-ms="{"creative":"accordion","creative_detail":"Accountability and governance"}"><div class="_9bhp _9bhq _9bhs _9bh3"><div class="_a82a"><p class="_a92o _a5cx _a5w7">Accountability and governance</p></div><div class="_a6jc _a6jd" data-testid="toggle-icon"><div class="_a6i_ _as4z"></div></div></div></button><div id="u_0_4_lg" class="_a6iz" data-testid="drawer-section"><div class="_a6jf"><p class="_a92o _a5c- _a5w7">We build reliable processes to ensure accountability for our AI systems and the decisions they make.</p></div></div></div></div></div><div class="_a5eb _allk _a5ec _a5eg _a5er _a5d5 _a5dd _a5dj _a5dv"><div class="_a5gf _a5ii _a5jw"><div class="_a5n5 _al8o _a5n7 _aceh"><div class="_8h4z _8h4- _a4zf"><img class="_90f0 _9kug _8h4i _as9p _as8y _8h56 img" src="https://static.xx.fbcdn.net/rsrc.php/v3/y4/r/-PAXP-deijE.gif" alt="Our principles" style="box-sizing:border-box;background-image:url(https://scontent-nrt1-2.xx.fbcdn.net/v/t39.8562-6/339963240_594359446073130_3866981500199613732_n.jpg?_nc_cat=102&ccb=1-7&_nc_sid=f537c7&_nc_ohc=_80QtRUmiUQQ7kNvgFyASrK&_nc_zt=14&_nc_ht=scontent-nrt1-2.xx&_nc_gid=AZIAxfG0C6i-ZD8uDrnoy8B&oh=00_AYDwwjStK4yheB7PyBAln1ez_xIBw06UeWTh2g9JIAjIJA&oe=674D06F5);" /></div></div></div></div></div></div><div class="_a5x4"></div><div class="_a5gf _a5gr _a5i9 _a5jn"></div><hr /><div class="_a5gf _a5gr _a5i9 _a5jn"></div><div class="_a5fu _a9w7 _a5fx"><div class="_a5eb _allk _a5ec _a5ee _a5ep _a5er _a5fv _a5fw _ajr_"><div class="_a5eb _allk _a5ec _a5ee _a5ep _a5er _a5d5 _a5dd _a5do _a5dv"><div class="_a5eb _allk _a5ec _a5ee _a5ep _a5er _a5d5 _a5d7 _a5dj _a5dv"><h2 class="_a92o _a5cw _a5wf _a5ct">Our progress and learnings in AI fairness and transparency</h2></div></div></div></div><div class="_a5gf _a5gp _a5i9 _a5jn"></div><div id="datasets"><span class="_anjl"><div class="_a5fu _a9w7 _a5x3"><div class="_a5eb _allk _a5ec _a5ee _a5ek _a5er _a5fo _a5fv _a5fw _ajr_"><div class="_a5eb _allk _a5ec _a5eg _a5ep _a5er _a5d5 _a5dd _a5dp _a5dv"><div class="_a5n5 _al8o _a5n6 _aceg"><div class="_8h4z _8h4- _a4zf"><img class="_90f0 _9kug _8h4i _as9p _as8y _8h56 img" src="https://static.xx.fbcdn.net/rsrc.php/v3/y4/r/-PAXP-deijE.gif" alt="" style="box-sizing:border-box;background-image:url(https://scontent-nrt1-2.xx.fbcdn.net/v/t39.8562-6/338815146_577224364474241_3223400094949500290_n.jpg?_nc_cat=101&ccb=1-7&_nc_sid=f537c7&_nc_ohc=Wpbxv-0bu70Q7kNvgGvljM-&_nc_zt=14&_nc_ht=scontent-nrt1-2.xx&_nc_gid=AZIAxfG0C6i-ZD8uDrnoy8B&oh=00_AYAxSNkuo_8DoES8AJlhDvJqrki4e45_qAQuS6WU78OPTw&oe=674D001C);" /></div></div></div><div class="_a5eb _allk _a5ec _a5eg _a5eh _a5ep _a5er _a5d5 _a5dc _a5dp _a5dv"><div class="_a5gf _a5jj"></div><div class="_a5eb _allk _a5ec _a5eg _a5ep _a5er _a5d5 _a5d7 _a5dj _a5dv"><h5 class="_a92o _a5d1 _a5w7 _a5ct">Datasets</h5><h2 class="_a92o _a5e5 _a5w7 _a5ct">Building diverse datasets and tools for more inclusive AI products</h2><p class="_a92o _a5c- _a5w7"><p class="_a92o _a5c- _a5w7 _a5ct">One way we are addressing AI fairness through research is the creation and distribution of more diverse datasets. Datasets that are used to train AI models can reflect biases, which are then passed on to the system. But biases might also be due to what isn’t in the training data. A lack of diverse data — or data that represents a wide range of people and experiences — can lead to AI-powered outcomes that reflect problematic stereotypes or fail to work equally well for everyone.</p></p></div><div class="_a5gf _a5gl _a5i6 _a5jj"></div><div class="_a5eb _allk _a5ec _a5eg _a5ep _a5er _a5d5 _a5d7 _a5dj _a5dv"><div class="_an_i _as9p _8in4 _a68i _a68m _a68p" style=""><div class="_a68l"><div class="_a7km"><h3 class="_a92o _a68e _a5w7 _a5ct">Resources</h3><div class="_a5ci _a5cs _a92o _a5c- _a5w7"><p><a href="https://research.facebook.com/publications/casual-conversations-v2-designing-a-large-consent-driven-dataset-to-measure-algorithmic-bias-and-robustness/" target="_blank">Casual Conversations v2 (CCv2)dataset</a></p><p><a href="https://research.facebook.com/publications/im-sorry-to-hear-that-finding-new-biases-in-language-models-with-a-holistic-descriptor-dataset/" target="_blank">Holistic descriptor dataset</a></p><p><a href="https://research.facebook.com/publications/panda-pose-aligned-networks-for-deep-attribute-modeling/" target="_blank">PANDA</a></p></div></div></div></div></div></div></div></div></span></div><div class="_a5gf _a5h0 _a5i9 _a5jn"></div><div id="privacy"><span class="_anjl"><div class="_a5fu _a9w7 _a5x3"><div class="_a5eb _allk _a5ec _a5ee _a5ek _a5eo _a5er _a5fo _a5fv _a5fw _ajr_"><div class="_a5eb _allk _a5ec _a5eg _a5ep _a5er _a5d5 _a5dd _a5dp _a5dv"><div class="_a5n5 _al8o _a5n6 _aceg"><div class="_8h4z _8h4- _a4zf"><img class="_90f0 _9kug _8h4i _as9p _as8y _8h56 img" src="https://static.xx.fbcdn.net/rsrc.php/v3/y4/r/-PAXP-deijE.gif" alt="" style="box-sizing:border-box;background-image:url(https://scontent-nrt1-2.xx.fbcdn.net/v/t39.8562-6/338995717_966661020991814_5746048747215344933_n.jpg?_nc_cat=102&ccb=1-7&_nc_sid=f537c7&_nc_ohc=MmEjvtmFsHgQ7kNvgEFXY_i&_nc_zt=14&_nc_ht=scontent-nrt1-2.xx&_nc_gid=AZIAxfG0C6i-ZD8uDrnoy8B&oh=00_AYC2PffLRFPw6A4RQkoMGQv04QiTALB3yr5kBwCW5on9VA&oe=674CF6A4);" /></div></div></div><div class="_a5eb _allk _a5ec _a5eg _a5eh _a5ep _a5er _a5d5 _a5dc _a5dp _a5dv"><div class="_a5gf _a5jj"></div><div class="_a5eb _allk _a5ec _a5eg _a5ep _a5er _a5d5 _a5d7 _a5dj _a5dv"><h5 class="_a92o _a5d1 _a5w7 _a5ct">Privacy</h5><h2 class="_a92o _a5e5 _a5w7 _a5ct">Protecting privacy while addressing fairness concerns</h2><p class="_a92o _a5c- _a5w7"><p class="_a92o _a5c- _a5w7 _a5ct">Improving fairness will often require measuring the impact of AI systems on different demographic populations and mitigating unfair differences. Yet the data necessary to do so is not always available — and even when it is, collecting it and storing it can raise privacy concerns. After engaging with civil rights advocates and human rights groups that further confirmed the fairness challenges, we identified new approaches to help us access data with the potential to meaningfully measure the fairness of the AI models on our platforms across races.</p></p></div><div class="_a5gf _a5gl _a5i6 _a5jj"></div><div class="_a5eb _allk _a5ec _a5eg _a5ep _a5er _a5d5 _a5d7 _a5dj _a5dv"><div class="_an_i _as9p _8in4 _a68i _a68m _a68p" style=""><div class="_a68l"><div class="_a7km"><h3 class="_a92o _a68e _a5w7 _a5ct">Resources</h3><div class="_a5ci _a5cs _a92o _a5c- _a5w7"><p><a href="https://ai.facebook.com/blog/assessing-fairness-of-our-products-while-protecting-peoples-privacy/" target="_blank">SMPC</a></p><p><a href="https://ai.facebook.com/research/publications/how-meta-is-working-to-assess-fairness-in-relation-to-race-in-the-us-across-its-products-and-systems" target="_blank">Technical paper</a></p></div></div></div></div></div></div></div></div></span></div><div class="_a5gf _a5h0 _a5i9 _a5jn"></div><div id="ad-delivery"><span class="_anjl"><div class="_a5fu _a9w7 _a5x3"><div class="_a5eb _allk _a5ec _a5ee _a5ek _a5er _a5fo _a5fv _a5fw _ajr_"><div class="_a5eb _allk _a5ec _a5eg _a5ep _a5er _a5d5 _a5dd _a5dp _a5dv"><div class="_a5n5 _al8o _a5n7 _aceh"><div class="_8h4z _8h4- _a4zf"><img class="_90f0 _9kug _8h4i _as9p _as8y _8h56 img" src="https://static.xx.fbcdn.net/rsrc.php/v3/y4/r/-PAXP-deijE.gif" alt="" style="box-sizing:border-box;background-image:url(https://scontent-nrt1-2.xx.fbcdn.net/v/t39.8562-6/339283617_164290629855565_8445658476627843358_n.jpg?_nc_cat=105&ccb=1-7&_nc_sid=f537c7&_nc_ohc=CMjnQHiShN4Q7kNvgEvR1X-&_nc_zt=14&_nc_ht=scontent-nrt1-2.xx&_nc_gid=AZIAxfG0C6i-ZD8uDrnoy8B&oh=00_AYBEKTSdNX30wyHYNy48Hugv_FJQn_y3NYDEuDxYjViV_A&oe=674CE4F7);" /></div></div></div><div class="_a5eb _allk _a5ec _a5eg _a5eh _a5ep _a5er _a5d5 _a5dc _a5dp _a5dv"><div class="_a5gf _a5jj"></div><div class="_af0r"><div class="_a5eb _allk _a5ec _a5eg _a5ep _a5er _a5d5 _a5d7 _a5dj _a5dv"><h5 class="_a92o _a5d1 _a5w7 _a5ct">Ad delivery</h5><h2 class="_a92o _a5e5 _a5w7 _a5ct">Innovating to improve fairness in ad delivery</h2><p class="_a92o _a5c- _a5w7 _a5ct"><p class="_a92o _a5c- _a5w7 _a5ct">A critical aspect of fairness is ensuring that people of all backgrounds have equitable access to information about important life opportunities, like jobs, credit, and housing. Our policies already prohibit advertisers from using our ad products to discriminate against individuals or groups of people. However, even with neutral targeting options and model features, factors such as people’s interests, their activity on the platform, or competition across all ad auctions for different audiences could affect how ads are distributed to different demographic groups. That’s why we’ve developed a novel use of machine learning technology to help distribute ads in a more equitable way on our apps.</p></p></div></div><div class="_a5gf _a5gl _a5i6 _a5jj"></div><div class="_a5eb _allk _a5ec _a5eg _a5ep _a5er _a5d5 _a5d7 _a5dj _a5dv"><div class="_an_i _as9p _8in4 _a68i _a68m _a68p" style=""><div class="_a68l"><div class="_a7km"><h3 class="_a92o _a68e _a5w7 _a5ct">Resources</h3><p class="_a92o _a5c- _a5w7"><a href="https://ai.facebook.com/blog/advertising-fairness-variance-reduction-system-vrs/" target="_blank">Variance Reduction System (VRS)</a></p></div></div></div></div></div></div></div></span></div><div class="_a5gf _a5h0 _a5i9 _a5jn"></div><div id="associations"><span class="_anjl"><div class="_a5fu _a9w7 _a5x3"><div class="_a5eb _allk _a5ec _a5ee _a5ek _a5eo _a5er _a5fo _a5fv _a5fw _ajr_"><div class="_a5eb _allk _a5ec _a5eg _a5ep _a5er _a5d5 _a5dd _a5dp _a5dv"><div class="_a5n5 _al8o _a5n7 _aceh"><div class="_8h4z _8h4- _a4zf"><img class="_90f0 _9kug _8h4i _as9p _as8y _8h56 img" src="https://static.xx.fbcdn.net/rsrc.php/v3/y4/r/-PAXP-deijE.gif" alt="" style="box-sizing:border-box;background-image:url(https://scontent-nrt1-2.xx.fbcdn.net/v/t39.8562-6/339251208_1864139993955016_3329862385546342870_n.jpg?_nc_cat=102&ccb=1-7&_nc_sid=f537c7&_nc_ohc=41MOx3zueuoQ7kNvgFQZF_V&_nc_zt=14&_nc_ht=scontent-nrt1-2.xx&_nc_gid=AZIAxfG0C6i-ZD8uDrnoy8B&oh=00_AYDAjRcpwuo3xfS8lYn1GX9CHWpBt43i1IPJouOQCACvmA&oe=674D12D1);" /></div></div></div><div class="_a5eb _allk _a5ec _a5eg _a5eh _a5ep _a5er _a5d5 _a5dc _a5dp _a5dv"><div class="_a5gf _a5jj"></div><div class="_af0r"><div class="_a5eb _allk _a5ec _a5eg _a5ep _a5er _a5d5 _a5d7 _a5dj _a5dv"><h5 class="_a92o _a5d1 _a5w7 _a5ct">Associations</h5><h2 class="_a92o _a5e5 _a5w7 _a5ct">Generating responsible associations</h2><p class="_a92o _a5c- _a5w7 _a5ct"><p class="_a92o _a5c- _a5w7 _a5ct">In 2022, we assembled a cross-disciplinary team, including people from our Civil Rights, Engineering, AI Research, Policy, and Product teams, to better understand problematic content associations in several of our end-to-end systems and to implement technical mitigations to reduce the chance of them occurring on our platforms that use AI models.<br /><br />As part of this collaborative effort, we carefully constructed and systematically reviewed the knowledge base of interest topics for usage in advanced mitigations that more precisely target the problematic associations. As more research is done in this area and shared with the greater community, we expect to build on this progress and to continue to improve our systems.</p></p></div></div></div></div></div></span></div><div class="_a5gf _a5h0 _a5i9 _a5jn"></div><div id="ad-driven-feeds"><span class="_anjl"><div class="_a5fu _a9w7 _a5x3"><div class="_a5eb _allk _a5ec _a5ee _a5ek _a5er _a5fo _a5fv _a5fw _ajr_"><div class="_a5eb _allk _a5ec _a5eg _a5ep _a5er _a5d5 _a5dd _a5dp _a5dv"><div class="_a5n5 _al8o _a5n6 _aceg"><div class="_8h4z _8h4- _a4zf"><img class="_90f0 _9kug _8h4i _as9p _as8y _8h56 img" src="https://static.xx.fbcdn.net/rsrc.php/v3/y4/r/-PAXP-deijE.gif" alt="" style="box-sizing:border-box;background-image:url(https://scontent-nrt1-2.xx.fbcdn.net/v/t39.8562-6/338997493_1266546844264664_6167617095558383003_n.jpg?_nc_cat=100&ccb=1-7&_nc_sid=f537c7&_nc_ohc=E2C-k6nArEMQ7kNvgGVraWo&_nc_zt=14&_nc_ht=scontent-nrt1-2.xx&_nc_gid=AZIAxfG0C6i-ZD8uDrnoy8B&oh=00_AYD0lBD4b8elzh6WXx4QHHXj3w7hmW29o-mpfttMnMrKGg&oe=674D0899);" /></div></div></div><div class="_a5eb _allk _a5ec _a5eg _a5eh _a5ep _a5er _a5d5 _a5dc _a5dp _a5dv"><div class="_a5gf _a5jj"></div><div class="_a5eb _allk _a5ec _a5eg _a5ep _a5er _a5d5 _a5d7 _a5dj _a5dv"><h5 class="_a92o _a5d1 _a5w7 _a5ct">AI-driven feeds and recommendations</h5><h2 class="_a92o _a5e5 _a5w7 _a5ct">Giving more control over AI-driven feeds and recommendations</h2><p class="_a92o _a5c- _a5w7"><p class="_a92o _a5c- _a5w7 _a5ct">AI-driven feeds and recommendations are a powerful tool for helping people find the people and content they are most interested in, but we want to make sure that people can manage their experience in ways that don’t necessarily rely on AI-based ranking.</p></p></div><div class="_a5gf _a5gl _a5i6 _a5jj"></div><div class="_a5eb _allk _a5ec _a5eg _a5ep _a5er _a5d5 _a5d7 _a5dj _a5dv"><div class="_an_i _as9p _8in4 _a68i _a68m _a68p" style=""><div class="_a68l"><div class="_a7km"><h3 class="_a92o _a68e _a5w7 _a5ct">Resources</h3><div class="_a5ci _a5cs _a92o _a5c- _a5w7"><p><a href="https://ai.facebook.com/blog/facebook-feed-improvements-ai-show-more-less/" target="_blank">Show More/Show Less</a></p><p><a href="https://www.facebook.com/4/videos/1714157738934549/" target="_blank">Facebook Feeds tab</a></p><p><a href="https://about.fb.com/news/2022/03/two-new-ways-to-control-your-instagram-feed/" target="_blank" data-lnfb-mode="ie">Instagram chronological feed</a></p><p><a href="https://about.fb.com/news/2022/03/two-new-ways-to-control-your-instagram-feed/" target="_blank" data-lnfb-mode="ie">Instagram Following</a></p></div></div></div></div></div></div></div></div></span></div><div class="_a5gf _a5h0 _a5i9 _a5jn"></div><div id="system-cards"><span class="_anjl"><div class="_a5fu _a9w7 _a5x3"><div class="_a5eb _allk _a5ec _a5ee _a5ek _a5eo _a5er _a5fo _a5fv _a5fw _ajr_"><div class="_a5eb _allk _a5ec _a5eg _a5ep _a5er _a5d5 _a5dd _a5dp _a5dv"><div class="_a5n5 _al8o _a5n6 _aceg"><div class="_8h4z _8h4- _a4zf"><img class="_90f0 _9kug _8h4i _as9p _as8y _8h56 img" src="https://static.xx.fbcdn.net/rsrc.php/v3/y4/r/-PAXP-deijE.gif" alt="" style="box-sizing:border-box;background-image:url(https://scontent-nrt1-2.xx.fbcdn.net/v/t39.8562-6/338890512_592964386074417_780841586375217356_n.jpg?_nc_cat=101&ccb=1-7&_nc_sid=f537c7&_nc_ohc=amWEgPnqKiEQ7kNvgFMRf8w&_nc_zt=14&_nc_ht=scontent-nrt1-2.xx&_nc_gid=AZIAxfG0C6i-ZD8uDrnoy8B&oh=00_AYAsjm5GKxH4OozIKWL1hGFMpfqxeQ6xyo1UktbP5zmweg&oe=674CFDA8);" /></div></div></div><div class="_a5eb _allk _a5ec _a5eg _a5eh _a5ep _a5er _a5d5 _a5dc _a5dp _a5dv"><div class="_a5gf _a5jj"></div><div class="_a5eb _allk _a5ec _a5eg _a5ep _a5er _a5d5 _a5d7 _a5dj _a5dv"><h5 class="_a92o _a5d1 _a5w7 _a5ct">System cards</h5><h2 class="_a92o _a5e5 _a5w7 _a5ct">Developing new methods for explaining our AI systems</h2><p class="_a92o _a5c- _a5w7"><p class="_a92o _a5c- _a5w7 _a5ct">Because AI systems are complex, it is important that we develop documentation that explains how systems work in a way that experts and nonexperts alike can understand.</p></p></div><div class="_a5gf _a5gl _a5i6 _a5jj"></div><div class="_a5eb _allk _a5ec _a5eg _a5ep _a5er _a5d5 _a5d7 _a5dj _a5dv"><div class="_an_i _as9p _8in4 _a68i _a68m _a68p" style=""><div class="_a68l"><div class="_a7km"><h3 class="_a92o _a68e _a5w7 _a5ct">Resources</h3><div class="_a5ci _a5cs _a92o _a5c- _a5w7"><p><a href="https://ai.facebook.com/tools/system-cards/" target="_blank">System Card Tool</a></p><p><a href="https://ai.facebook.com/blog/system-cards-a-new-resource-for-understanding-how-ai-systems-work/" target="_blank">Model Cards</a></p><p><a href="https://ieeexplore.ieee.org/document/9796452" target="_blank" data-lnfb-mode="ie">Method Cards</a></p></div></div></div></div></div></div></div></div></span></div><div class="_a5gf _a5gr _a5i9 _a5jn"></div><div id="policy"><span class="_anjl"><div class="_a5fu _a9w7 _a5x3"><div class="_a5eb _allk _a5ec _a5ee _a5ek _a5er _a5fo _a5fv _a5fw _ajr_"><div class="_a5eb _allk _a5ec _a5eg _a5ep _a5er _a5d5 _a5dd _a5dp _a5dv"><div class="_a5n5 _al8o _a5n6 _aceg"><div class="_8h4z _8h4- _a4zf"><img class="_90f0 _9kug _8h4i _as9p _as8y _8h56 img" src="https://static.xx.fbcdn.net/rsrc.php/v3/y4/r/-PAXP-deijE.gif" alt="" style="box-sizing:border-box;background-image:url(https://scontent-nrt1-1.xx.fbcdn.net/v/t39.8562-6/339323768_591226343064546_5202753848711910859_n.jpg?_nc_cat=106&ccb=1-7&_nc_sid=f537c7&_nc_ohc=J_kxm0wLDGoQ7kNvgHr7Rj5&_nc_zt=14&_nc_ht=scontent-nrt1-1.xx&_nc_gid=AZIAxfG0C6i-ZD8uDrnoy8B&oh=00_AYBmd6qaq8ynvTBFVAXXWANMVJjb7W6OtTT0Y4JP2QbL5Q&oe=674CF69C);" /></div></div></div><div class="_a5eb _allk _a5ec _a5eg _a5eh _a5ep _a5er _a5d5 _a5dc _a5dp _a5dv"><div class="_a5gf _a5jj"></div><div class="_a5eb _allk _a5ec _a5eg _a5ep _a5er _a5d5 _a5d7 _a5dj _a5dv"><h5 class="_a92o _a5d1 _a5w7 _a5ct">Policy approaches</h5><h2 class="_a92o _a5e5 _a5w7 _a5ct">Testing new policy approaches to AI transparency, explainability, and governance</h2><p class="_a92o _a5c- _a5w7 _a5ct"><p class="_a92o _a5c- _a5w7 _a5ct">The rapid advance of emerging technologies makes it difficult to fully understand and anticipate how they might eventually impact communities around the world.</p></p><a class="_a6ef _a6rw _a6ee _a6em _a6el" href="https://ai.facebook.com/blog/introducing-open-loop-a-global-program-bridging-tech-and-policy-innovation/" data-ms-clickable="true" data-ms="{"creative":"click_internal-link","creative_detail":"policy_support_cta"}" target="_self" style=""><svg class="_a6en" viewBox="0 0 38 38" fill="none" xmlns="http://www.w3.org/2000/svg"><path opacity="0.4" 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