Buy or sell new and used items easily on Facebook Marketplace, locally or from businesses. But this approach soon caused issues. GBP £ IE € EUR € Search. Quiñonero’s AI expertise supercharged that growth. If everyone gets the recommendation, does that mean it was fair?”, “We’re at a place where there’s one genocide [Myanmar] that the UN has, with a lot of evidence, been able to specifically point to Facebook and to the way that the platform promotes content,” Biddle adds. People went on to share stories and memes about run-ins with entitled middle-aged white women. Zuckerberg, who sat in the center of Building 20, the main office at the Menlo Park headquarters, placed the new FAIR and AML teams beside him. The AI moonshot was founded in the spirit of transparency. 3.6K. Log in to Facebook to start sharing and connecting with your friends, family and people you know. Facebook’s massive amounts of user data gave Quiñonero a big advantage. If conservatives are posting a greater fraction of misinformation, as judged by public consensus, then the model should flag a greater fraction of conservative content. 1K Comments 760 Shares. Many of its ideas stayed largely academic. His expertise was rare, and the team was less than a year old. (It was later renamed FAIAR, pronounced “fire.”), “That’s how you know what’s on his mind. Just as algorithms could be trained to predict who would click what ad, they could also be trained to predict who would like or share what post, and then give those posts more prominence. AUD $ North America. “I don’t even understand what they mean when they talk about fairness. Sign up, Join the conversation, you are commenting as Logout. Guardian disowns writer Karen Geier who trolled Duke of Edinburgh by saying she was 'saddened' to hear his death was 'peaceful'. But then there’s the Reddit origins from 2017 when a user created the viral screen name “f***_you_Karen” about his ex-wife who got custody of their children and took the house in their divorce. The process is still the same today. One founding member, Isabel Kloumann, a research scientist who’d come from the company’s core data science team, brought with her an initial version of a tool to measure the bias in AI models. BREAKING: Sharon Osbourne puts her WHITE PRIVILEGE on full display by defending Piers Morgan and ATTACKING her Black co-host in an OFF THE RAILS tantrum. I had shown Chowdhury the Quiñonero team’s documentation detailing its work. He seemed a natural choice of subject to me, too. 0. Machine learning, a subset of AI, had yet to prove itself as a solution to large-scale industry problems. Accept All More Info. Karen can be and is all of those. It was a win for everybody in the room. If your name is Karen, you may have noticed a growing trend of people using your name as an insult. Contact Karen Fox Solicitor on Messenger. “Over time they measurably become more polarized,” he says. Kerry Nash, who was outed as ‘Bunnings Karen’. Karen is great with the patients but is a complete hypochondriac, and won't hesitate to pester the doctors for a diagnosis. His claims about political bias also weakened a proposal to edit the ranking models for the news feed that Facebook’s data scientists believed would strengthen the platform against the manipulation tactics Russia had used during the 2016 US election. On August 29, 2018, that suddenly changed. The term also refers to memes depicting White women who use their privilege to demand their own way. And there were discussions about what role SAIL could play within Facebook and how it should evolve over time. Join Facebook to connect with Karen Christoff and others you may know. He wanted to know everything Quiñonero had learned about AI bias and how to quash it in Facebook’s content-moderation models. Casey Anthony juror regrets decision to acquit her over Cayl... Chris Hemsworth shares mum’s Centr bikini transformation. But with a few exceptions, I don’t think it’s actually translated into better policies. Join Facebook to connect with Karen Off I and others you may know. De-selecting may result in less relevant ads or difficulty linking with Facebook, Twitter, or Google! Millions began deleting the app; employees left in protest; the company’s market capitalization plunged by more than $100 billion after its July earnings call. In his six years at Facebook, he’d created some of the first algorithms for targeting users with content precisely tailored to their interests, and then he’d diffused those algorithms across the company. Zuckerberg even admitted this. And Quiñonero now had more money and a bigger team to make the overall Facebook experience better for users. Three months later, Quiñonero was promoted again, this time to lead AML. They claimed that Facebook’s moderators in particular, in applying the community standards, were suppressing conservative voices more than liberal ones. It must be trained on thousands, often even millions, of examples of a new type of content before learning to filter it out. It allows engineers to measure the accuracy of machine-learning models for different user groups. The task involved building a model to analyze the comments that other users were posting on a video after it had gone live, and bringing at-risk users to the attention of trained Facebook community reviewers who could call local emergency responders to perform a wellness check. Facebook has consistently pointed to the efforts by Quiñonero and others as it seeks to repair its reputation. English (US)Português (Brasil) Deutsch: Español … If the model determined that a person really liked dogs, for instance, friends’ posts about dogs would appear higher up on that user’s news feed. Quiñonero’s success with the news feed—coupled with impressive new AI research being conducted outside the company—caught the attention of Zuckerberg and Schroepfer. Depictions also may include demanding to "speak to the manager", being racist or sporting a particular bob cut hairstyle. Many spoke on condition of anonymity because they’d signed nondisclosure agreements or feared retaliation. “The question for leadership was: Should we be optimizing for engagement if you find that somebody is in a vulnerable state of mind?” he remembers. The other, Applied Machine Learning (AML), would integrate those capabilities into Facebook’s products and services. They told the researchers that the model could not be deployed until the team fixed this discrepancy. It compounded fears that the algorithms that determine what people see on the platform were amplifying fake news and hate speech, and that Russian hackers had weaponized them to try to sway the election in Trump’s favor. In 2020 Facebook started belatedly taking action against Holocaust deniers, anti-vaxxers, and the conspiracy movement QAnon. I’ve never seen a male Karen targeted. Called FBLearner Flow, it allowed engineers with little AI experience to train and deploy machine-learning models within days. Quiñonero began studying the scientific literature on algorithmic fairness, reading books on ethical engineering and the history of technology, and speaking with civil rights experts and moral philosophers. You can’t disable these. Unlike the racist Karens, the name itself doesn’t discriminate. Community See all. 1) Facebook sucks time from my life, and unlike money, time is a zero sum game (thanks to Laura Vanderkam for reminding us). In fact, those are your friends,” says Hany Farid, a professor at the University of California, Berkeley who collaborates with Facebook to understand image- and video-based misinformation on the platform. Ari Entin, Facebook’s AI communications director, asked in an email if I wanted to take a deeper look at the company’s AI work. “[If] it's an important area, we need to move fast on it, it's not well-defined, [we create] a dedicated team and get the right leadership,” he said. In the ramp-up to the US midterm elections, President Donald Trump and other Republican leaders ratcheted up accusations that Facebook, Twitter, and Google had anti-conservative bias. I asked Quiñonero why his team hadn’t previously looked at ways to edit Facebook’s content-ranking models to tamp down misinformation and extremism. Quiñonero was awestruck by the possibilities. L6/7 is just one of myriad ways in which Facebook has measured “engagement”—the propensity of people to use its platform in any way, whether it’s by posting things, commenting on them, liking or sharing them, or just looking at them. Over the many hours I spent with him, I could tell he took this seriously. It found that there was indeed a correlation, and that reducing polarization would mean taking a hit on engagement. Days later, another woman went viral for leaning on a car in a parking lot to prevent the driver from getting their desired parking spot. (A Facebook spokesperson said she could not find documentation for this proposal.). Near the end of our hour-long interview, he began to emphasize that AI was often unfairly painted as “the culprit.” Regardless of whether Facebook used AI or not, he said, people would still spew lies and hate speech, and that content would still spread across the platform. Meanwhile, the algorithms that recommend this content still work to maximize engagement. News of the success spread quickly. View the profiles of people named Karen Off I. Fairness Flow also comes with a set of guidelines to help engineers understand what it means to train a “fair” model. But Schroepfer told me precisely the opposite in an earlier interview. “As an area grows and matures, you'll see the product teams take on more work, but the central team is still needed because you need to stay up with state-of-the-art work.”. Machine learning, which could predict which ads would resonate best with which users and thus make them more effective, could be the perfect tool. In other words, the Responsible AI team’s work—whatever its merits on the specific problem of tackling AI bias—is essentially irrelevant to fixing the bigger problems of misinformation, extremism, and political polarization. Then they’d decipher what had caused the problem and whether any models needed retraining. A Facebook spokesperson said, “The work isn’t done by one specific team because that’s not how the company operates.” It is instead distributed among the teams that have the specific expertise to tackle how content ranking affects misinformation for their part of the platform, she said. An algorithm trained on ad click data, for example, might learn that women click on ads for yoga leggings more often than men. That former employee, meanwhile, no longer lets his daughter use Facebook. Picture: SuppliedSource:Supplied. In 2020, the Washington Post reported that Kaplan’s team had undermined efforts to mitigate election interference and polarization within Facebook, saying they could contribute to anti-conservative bias. In 2014, Kaplan was promoted from US policy head to global vice president for policy, and he began playing a more heavy-handed role in content moderation and decisions about how to rank posts in users’ news feeds. Facebook admitted in 2018, after years of downplaying its role, that it had not done enough “to help prevent our platform from being used to foment division and incite offline violence.”. The most infamous “Karen” of late is Amy Cooper, a white woman who called the police on black birder Christian Cooper when the two ended up at odds in … Because of Kaplan’s and Zuckerberg’s worries about alienating conservatives, the team stayed focused on bias. Join. Otherwise, it’s deployed and continually monitored. At the time, he was a manager in Microsoft Research’s UK office, leading a team using machine learning to get more visitors to click on ads displayed by the company’s search engine, Bing. Experts had lauded social media for spreading the information that fueled the uprisings and giving people tools to organize. Sharon Osbourne goes full “Karen” in OFF THE RAILS tantrum. Login / Register Login / Register. The algorithms that underpin Facebook’s business weren’t created to filter out what was false or inflammatory; they were designed to make people share and engage with as much content as possible by showing them things they were most likely to be outraged or titillated by. As he stepped up to face the room, he began with an admission. A model modified in that way “would have literally no impact on the actual problem” of misinformation. Former employees described, however, how hard it could be to get buy-in or financial support when the work didn’t directly improve Facebook’s growth.
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