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Facebook knew for years ad reach estimates were based on ‘wrong data’ but blocked fixes over revenue impact, per court filing

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Some more internal emails Facebook really doesn’t want you to see: Turns out in 2017 COO Sheryl Sandberg had already known for years there were problems with a free ad planning tool the company offers to marketeers to display estimates of how many people campaigns running on its platform may reach, per newly unsealed court documents.

The filing also reveals that a Facebook product manager for the “potential reach” tool warned the company was making revenue it “should never have” off of “wrong data”.

The unsealed documents pertain to a U.S. class action lawsuit, filed in 2018, which alleges that Facebook deceived advertisers by knowingly including fake and duplicate accounts in a “potential reach” metric.

Facebook denies the claim but has acknowledged accuracy issues with the “potential reach” metric as far back as 2016 — and also changed how it worked in 2019.

While the litigants have continued to accuse Facebook of continuing to misrepresent the ad reach estimate in updates to their 2018 complaint.

Redacted documents from the lawsuit, reported by the WSJ last year, included the awkward detail that a Facebook employee had asked “how long can we get away with the reach overestimation?”

But sections of the filing pertaining to Sandberg and other Facebook executives were redacted.

Newly unsealed documents from the suit — which we’ve reviewed — now reveal that in fall 2017 Sandberg “acknowledged in an internal email she had known about problems with Potential Reach for years”.

They also show Facebook repeatedly rejected internal proposals to fix the issue of fake and duplicate accounts inflating the estimates its platform showed to advertisers of the number of people who could see their ads — citing impact on revenue as a reason not to act.

In early 2018 Facebook estimated that removing duplicate accounts would cause a 10% drop in potential reach, per the unsealed filing. While Facebook management rejected an employee’s suggestion to change the language the tool showed to advertisers, declining to swap out the words “people” and “reach” for the (more accurate) term “accounts” — on the grounds that “people-based marketing was core to Facebook’s value proposition”.

The filing also reveals that a product manager for “potential reach”, Yaron Fidler, proposed a fix for the tool that would have decreased its numbers. His proposal was rejected by Facebook’s metrics leadership on the grounds that it would have a “significant” impact on the company’s revenue — to which Fidler responded: “It’s revenue we should have never made given the fact it’s based on wrong data.”

In 2016, when Facebook published an update on metrics — a few weeks after publicly disclosing it had been over-inflating average video view times, as it sought to regain advertiser trust in its reporting tools — the tech giant also announced a new channel for “regular information on metrics enhancements”, called Metrics FYI.

This is where it made the aforementioned fuzzy disclosure of accuracy issues with “potential reach” — writing then that it was “improving our methodology for sampling and extrapolating potential audience sizes” to “help to provide a more accurate estimate for a given target audience and to better account for audiences across multiple platforms (Facebook, Instagram and Audience Network)”.

“In most cases, advertisers should expect to see less than a 10% change (increase or decrease) in the audience sizes shown in the tool,” it added at the time.

However, the December 2016 blog post did not go into any detail about the nature of the accuracy problems Facebook thought needed improving — reading more like another classic slice of Facebook crisis PR.

The class action suit, meanwhile, alleges that rather than accepting internal proposals to fix the accuracy problems of “potential reach”, Facebook instead “developed talking points to deflect from the truth”.

The tech giant did announce some changes to the ad tool in March 2019 — when it said an advertiser’s campaign’s estimated potential reach “is now based on how many people have been shown an ad on a Facebook Product in the past 30 days who match your desired audience and placement criteria” (versus the estimates being previously based on “people who were active users in the past 30 days”).

But the litigants argue that the changes to the tool which displays an estimate to advertisers as they are beginning to create a campaign — and therefore when they’re deciding/considering whether/how much money to spend with Facebook — do not fully fix the issue of the metric not corresponding to the potential audience of people who could see the ad on Facebook.

An analyst report back in 2017 showed that Facebook’s ad platform claimed to reach millions more users among specific age groups in the U.S. than official census data indicated reside in the country.

At the time the company said the audience reach estimates “are based on a number of factors, including Facebook user behaviors, user demographics, location data from devices, and other factors”, per the WSJ, and claimed they are “not designed to match population or census estimates”. Facebook added then that it is “always working to improve our estimates”.

Asked about the latest batch of unsealed court documents pertaining to the lawsuit — including the revelation that Facebook’s COO had told staff she knew about “problems” with the ad tool “for years” as far back as fall 2017 — Facebook sent us this statement, attributed to a spokesperson: “These allegations are without merit and we will defend ourselves vigorously.”

Update: Facebook followed up with a second statement, in which a spokesperson said: “These documents are being cherry-picked to fit the plaintiff’s narrative. ‘Potential reach’ is a helpful campaign planning tool that advertisers are never billed on. It’s an estimate and we make clear how it’s calculated in our ads interface and Help Center.”

Problems with self-reporting ad metrics have been a recurring theme for Facebook.

Last year the tech giant disclosed yet another issue on this front — saying its “conversion lift” ad tool had a code error that meant it had miscalculated the number of sales derived from ad impressions for a number of advertisers.

That “technical problem” with Facebook’s internal calculation of the efficacy of third parties’ ad campaigns meant advertisers saw skewed data, which they may have used to determine how much to spend on its platform.

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Instagram’s co-founders launch Artifact, a kind of TikTok for text

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Instagram’s co-founders launch Artifact, a kind of TikTok for text

Kevin Systrom and Mike Krieger are back.

The Instagram co-founders, who departed Facebook in 2018 amid tensions with their parent company, have formed a new venture to explore ideas for next-generation social apps. Their first product is Artifact, a personalized news feed that uses machine learning to understand your interests and will soon let you discuss those articles with friends.

Artifact — the name represents the merging of articles, facts, and artificial intelligence — is opening up its waiting list to the public today. The company plans to let users in quickly, Systrom says. You can sign up yourself here; the app is available for both Android and iOS.

The simplest way to understand Artifact is as a kind of TikTok for text, though you might also call it Google Reader reborn as a mobile app or maybe even a surprise attack on Twitter. The app opens to a feed of popular articles chosen from a curated list of publishers ranging from leading news organizations like The New York Times to small-scale blogs about niche topics. Tap on articles that interest you, and Artifact will serve you similar posts and stories in the future, just as watching videos on TikTok’s For You page tunes its algorithm over time.

“Every time we use machine learning to improve the consumer experience, things got really good really quickly.”

Users who come in from the waitlist today will see only that central ranked feed. But Artifact beta users are currently testing two more features that Systrom expects to become core pillars of the app. One is a feed showing articles posted by users that you have chosen to follow, along with their commentary on those posts. (You won’t be able to post raw text without a link, at least for now.) The second is a direct message inbox so you can discuss the posts you read privately with friends.

In one sense, Artifact can feel like a throwback. Inspired by TikTok’s success, big social platforms have spent the past few years chasing shortform video products and the ad revenue that comes with them.

Meanwhile, like a social network from the late 2000s, Artifact has its sights set firmly on text. But the founders are hopeful that a decade-plus of lessons learned, along with recent advances in artificial intelligence, will help their app break through to a bigger audience.

Systrom and Krieger first began discussing the idea for what became Artifact a couple years ago, he told me. Systrom said he was once skeptical of the ability of machine-learning systems to improve recommendations — but his experience at Instagram turned him into a true believer.

“Throughout the years, what I saw was that every time we use machine learning to improve the consumer experience, things got really good really quickly,” he said.

So why come back now? Technically, this isn’t the duo’s first project since Instagram; in 2020, they teamed up to create the website Rt.live to track the spread of covid.

But Systrom told me they didn’t want to start a new company until three things happened: One, a big new wave in consumer technology that he and Krieger could attempt to catch. Two, a way to connect that wave to social technology, which he and Krieger continue to feel invested in emotionally. And three, an idea for how their product could solve a problem — Systrom has long considered technology design from the standpoint of what jobs it can do for its customers.

The tech that enabled ChatGPT also created new possibilities for social networks

The breakthrough that enabled Artifact was the transformer, which Google invented in 2017. It offers a mechanism for systems to understand language using far fewer inputs than had previously been required.

The transformer helped machine-learning systems improve at a much faster pace, leading directly to last year’s release of ChatGPT and the attendant boom in interest around AI. (Transformers are the “T” in ChatGPT.)

It also created some new possibilities for social networks. At first, social networks showed you stuff your friends thought was interesting — the Facebook model. Then they started showing you stuff based on the people that you chose to follow, whether you were friends or not — the Twitter model.

TikTok’s innovation was to show you stuff using only algorithmic predictions, regardless of who your friends are or who you followed. It soon became the most downloaded app in the world.

Artifact represents an effort to do the same thing but for text.

“I saw that shift, and I was like, ‘Oh, that’s the future of social,’” Systrom said. “These unconnected graphs; these graphs that are learned rather than explicitly created. And what was funny to me is as I looked around, I was like, ‘Man, why isn’t this happening everywhere in social? Why is Twitter still primarily follow-based? Why is Facebook?’”

Artifact will take seriously the job of serving readers with high-quality news and information

The question is whether personalized recommendations for news articles and blog posts can drive the same viral success for Artifact that video has for TikTok. It’s not a slam dunk: in 2014, a wave of personalized news apps with names like Zite and Pulse came and went, dogged by their inability to create deep habits in users. And earlier this month, Tokyo-based SmartNews, which uses similar AI technology to personalize recommendations, laid off 40 percent of its workforce in the United States and China amid a declining user base and challenging ad market.

Like most startups at this stage, Artifact has yet to commit to a business model. Advertising would be an obvious fit, Systrom said. He’s also interested in thinking about revenue-sharing deals with publishers. If Artifact gets big, it could help readers find new publications and encourage them to subscribe to them; it may make sense for Artifact to try to take a cut.

Systrom also told me Artifact will take seriously the job of serving readers with high-quality news and information. That means an effort to include only publishers who adhere to editorial standards of quality, he told me. For now, the company won’t disclose every publisher in its system, but you can search for individual outlets within the app.

Both left- and right-leaning publishers were included; you’ll find Fox News there, for example. But Systrom isn’t shy about the fact that the company will be exercising its own judgment about who belongs and who doesn’t.

“One of the issues with technology recently has been a lot of these companies’ unwillingness to make subjective judgments in the name of quality and progress for humanity,” he says. “Right? Just make the hard decision.”

Artifact will also remove individual posts that promote falsehoods, he says. And its machine-learning systems will be primarily optimized to measure how long you spend reading about various subjects — as opposed to, say, what generates the most clicks and comments — in an effort to reward more deeply engaging material.

“We fundamentally like building.”

For now, Systrom and Krieger are funding Artifact themselves, though I imagine they will soon have investors beating a path to their doors. A team of seven people is now working on the app, including Robby Stein, a top product executive at Instagram from 2016 to 2021.

Having sold Instagram to Facebook for $715 million, Systrom and Krieger had no pressing need to get a job. So what’s driving them this time?

“We fundamentally like building,” Systrom said. “There’s no other place in the world we’d rather spend our time than writing code and building products that people enjoy. I just love it.”

Advances in AI have also captured their imaginations, he said.

“I think machine learning is undeniably the coolest thing to work on right now,” he said. “Not because it’s hip, but because when it knows you’re into a certain topic, and it totally gets you, you’re like, ‘How is it that just some numbers multiplied together did that?’ The CTO of OpenAI said that machine learning is basically many months of things not working, and then suddenly it works, and then it works scarily well. I resonate with that.”

I’ve only used Artifact for a few hours now, and many of the features that the company plans to build remain in the planning stages. As you would expect from Systrom and Krieger, the app already shows a good deal of polish. Read an article inside the app, and when you return to the feed, it will suggest more stories like it in a handsome carousel. The app automatically switches to dark mode at night. And when you post a link, you can choose whether to let everyone comment, limit comments to people you follow, or shut them off entirely.

In many ways, I think the time is ripe for this kind of product. AI really is making new things possible in consumer apps, and the collapse of Twitter under Elon Musk has created an opportunity for a team with genuine expertise in this space to take a run at text-based social networking again.

To succeed on a grand scale, I suspect Artifact will have to do more than simply show you a collection of interesting links. Even in the current depressed state of digital publishing, the web remains rich with stories of interest, as anyone who has ever glanced at the list of clickbait headlines below the Google search box these days can attest. Few people spend much time complaining that they can’t find anything good to read on the internet.

Yes, AI represents a huge part of TikTok’s success. But like Twitter before it, TikTok also succeeded because of the way it captures conversations about the core feed — more than a few tweets have gone viral noting that the comments on TikTok are often better than the videos themselves. Similarly, Twitter endures as a primary source for breaking news in large part because it’s where elites go to discuss the news in public.

That aspect of Artifact remains under construction. But if Systrom and Krieger can bring the same craftsmanship to that part of the product that they brought to Instagram, it might not be long before they have me once again forgetting my Mastodon login.

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Where Will Meta Stock Be in 1 Year?

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Meta Platforms (META -3.08%) had an awful 2022. Revenue growth stalled at just the wrong time for the social media business, leading to collapsing earnings in the nine months that ended in late September. The company will close out 2022 with its Q4 earnings announcement in early February that’s expected to show a 3% sales drop.

Wall Street isn’t optimistic about the year ahead, either. Most Wall Street pros forecast that revenue will rise in the low-single-digit-percentage range as annual earnings decline for a second straight year.

Let’s look behind those headline projections for clues to where the stock might be headed as management works to turn the Facebook owner around.

Meta is growing faster

The immediate challenge for CEO Mark Zuckerberg and his team is to get the business back on a growth footing. The good news is that this goal is more achievable than you might think after a glance at the company’s 4% year-over-year sales decline in Q3. Strip out currency exchange rate shifts and that figure becomes a 2% increase, after all.

Meta is still gaining users, too, even on its most mature platform, Facebook. It’s not hard to see how a sustained focus on engaging videos in the Reels service can contribute to improving sales trends in 2023. “The fundamentals are there for a return to stronger revenue growth,” Zuckerberg told investors in late October. Ideally, executives will back up those words with more concrete signs of a rebound in the early February update.

Meta has been slashing costs

Meta entered the 2022 year with some of the best finances in the tech industry. But the scale of its negative turn here has been hard to watch.

META Operating Margin (TTM) Chart

META Operating Margin (TTM) data by YCharts

Operating income through the first three quarters of the year dropped to $22.5 billion from $34.2 billion. Net income in that period fell by more than $10 billion to $18.5 billion.

Watch for Meta to be brutal in slashing costs this year so it can end this profitability slide. The company already got the ball rolling here as it closed offices and announced layoffs in some areas. Yet these moves likely won’t start affecting the bottom line in a big way until future years, perhaps when sales growth is accelerating again.

The big questions Meta needs to answer

Meta isn’t skimping on the investments that management thinks will drive growth over the next several years. The Reality Labs division, home to the Quest VR brand, is projecting accelerating losses in 2023 as spending ramps up in areas like hardware and the metaverse. The company should add more context about these projects when it closes out fiscal 2022 and issues its first detailed projection for the new year ahead.

The stock’s path in 2023 will depend in part on things that are outside Meta’s control, including the pace of advertising spending and consumers’ discretionary tech budgets.

Yet there’s still plenty the company can do to improve sales and profitability trends over the next several quarters. And if both metrics have started rebounding, Meta shares have a good chance at outperforming the market in 2023 after posting their worst year yet last year.

Randi Zuckerberg, a former director of market development and spokeswoman for Facebook and sister to Meta Platforms CEO Mark Zuckerberg, is a member of The Motley Fool’s board of directors. Demitri Kalogeropoulos has positions in Meta Platforms. The Motley Fool has positions in and recommends Meta Platforms. The Motley Fool has a disclosure policy.

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Facebook Could Be Messing With Your Phone. Here’s What We Know

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Facebook Could Be Messing With Your Phone. Here's What We Know

Battery life is one of the most important aspects of smartphone usage — without solid battery life, a phone becomes far less useful. Even worse are instances when a phone’s battery drains faster than expected for no apparent reason, which may result in the user being caught off guard with a dead battery while away from a charger.

That’s the issue that prompted Hayward’s complaint, according to The New York Post, which quotes the data scientist as saying, “I said to the manager, ‘This can harm somebody,’ and she said by harming a few we can help the greater masses.” Hayward was allegedly fired in November 2022 after refusing to engage in the negative testing practices, leading to the lawsuit soon after. The big question is whether this practice — assuming the allegations are accurate — is widespread at Meta. 

If so, what other kinds of negative testing may be taking place without a user’s knowledge, and how might those tests impact their experiences with the company’s products? Hayward claimed that during his time working for the company, Meta gave him a training document that allegedly described types of negative tests that may be conducted — the document was reportedly titled, “How to run thoughtful negative tests.” Unfortunately, specific examples of those tests weren’t provided, and Meta hasn’t commented on the allegations to clarify how its testing practices may impact users, if at all.

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