Power

Facebook cracks down on misinformation superspreaders

But there are still a lot of unanswered questions about how it will work.

Facebook

Targeting these repeat offenders is key to Facebook limiting misinformation on the platform.

Photo: Chesnot/Getty Images

Facebook announced Wednesday that it will now limit the spread of all posts from individual Facebook users who repeatedly share content that's been debunked by fact-checkers.

That's right, all posts — even the cat pictures. Facebook already limits the reach of individual posts that contain misinformation and levies various punishments on Pages and Groups that are havens for misinformation. But it hasn't so far cracked down on individual Facebook users.

  • That matters. Research has repeatedly shown that whether it comes to COVID vaccine misinformation or election falsehoods, even a small handful of individuals can become superspreaders of misinformation.
  • Sometimes those superspreaders, like former President Trump, are sharing misinformation on Pages. But in other cases, they're sharing posts from individual accounts with substantial reach. Until now, Facebook has taken action against the content of their posts, but not the people behind them.

Targeting these repeat offenders is key to Facebook limiting misinformation on the platform. Burying a single piece of misinformation does little to prevent the same thing from happening again in the future. Burying all posts from a problematic user might.

  • Facebook also said it will begin alerting people if they are about to Like a Page that has repeatedly shared misinformation.

These policies are contingent on Facebook's fact-checkers actually debunking users' posts, which is, after all, a manual and sometimes spotty process.

  • Facebook's fact-checking program launched in 2016 with a handful of partners and has since grown substantially. But critics have continued to point out that fact-checkers are unable to keep up with the sheer volume of misinformation on Facebook.
  • Once a given post has been fact-checked, Facebook uses automation to find other posts that, say, contain the same debunked meme or story. And yet, those systems sometimes fail to find replicas that have been tweaked ever so slightly to evade detection.

There are still lots of unanswered questions from Facebook about how this crackdown on individual accounts will work in practice. It's unclear, for instance, how many times a user has to share misinformation in order to have their account demoted. A Facebook spokesperson said the company's not sharing these details due to "very real concerns about gaming the system."

  • While Facebook alerts people each time they share misinformation, for now, users will have no way of knowing whether Facebook is demoting all posts from their account. Facebook says it's looking at how to properly notify users when they've reached their misinformation limit.
  • Also fuzzy? What it takes for a user to get back in Facebook's good graces. "If they stop sharing false content after a certain period of time, their privileges will be restored," the spokesperson said. "If they continue sharing false content, it will continue to trigger penalties."

In other news, Facebook also says the U.S. is one of the top 5 countries where influence operations originate, up there with Russia, Iran, Myanmar and Ukraine.

Fintech

Judge Zia Faruqui is trying to teach you crypto, one ‘SNL’ reference at a time

His decisions on major cryptocurrency cases have quoted "The Big Lebowski," "SNL," and "Dr. Strangelove." That’s because he wants you — yes, you — to read them.

The ways Zia Faruqui (right) has weighed on cases that have come before him can give lawyers clues as to what legal frameworks will pass muster.

Photo: Carolyn Van Houten/The Washington Post via Getty Images

“Cryptocurrency and related software analytics tools are ‘The wave of the future, Dude. One hundred percent electronic.’”

That’s not a quote from "The Big Lebowski" — at least, not directly. It’s a quote from a Washington, D.C., district court memorandum opinion on the role cryptocurrency analytics tools can play in government investigations. The author is Magistrate Judge Zia Faruqui.

Keep ReadingShow less
Veronica Irwin

Veronica Irwin (@vronirwin) is a San Francisco-based reporter at Protocol covering fintech. Previously she was at the San Francisco Examiner, covering tech from a hyper-local angle. Before that, her byline was featured in SF Weekly, The Nation, Techworker, Ms. Magazine and The Frisc.

The financial technology transformation is driving competition, creating consumer choice, and shaping the future of finance. Hear from seven fintech leaders who are reshaping the future of finance, and join the inaugural Financial Technology Association Fintech Summit to learn more.

Keep ReadingShow less
FTA
The Financial Technology Association (FTA) represents industry leaders shaping the future of finance. We champion the power of technology-centered financial services and advocate for the modernization of financial regulation to support inclusion and responsible innovation.
Enterprise

AWS CEO: The cloud isn’t just about technology

As AWS preps for its annual re:Invent conference, Adam Selipsky talks product strategy, support for hybrid environments, and the value of the cloud in uncertain economic times.

Photo: Noah Berger/Getty Images for Amazon Web Services

AWS is gearing up for re:Invent, its annual cloud computing conference where announcements this year are expected to focus on its end-to-end data strategy and delivering new industry-specific services.

It will be the second re:Invent with CEO Adam Selipsky as leader of the industry’s largest cloud provider after his return last year to AWS from data visualization company Tableau Software.

Keep ReadingShow less
Donna Goodison

Donna Goodison (@dgoodison) is Protocol's senior reporter focusing on enterprise infrastructure technology, from the 'Big 3' cloud computing providers to data centers. She previously covered the public cloud at CRN after 15 years as a business reporter for the Boston Herald. Based in Massachusetts, she also has worked as a Boston Globe freelancer, business reporter at the Boston Business Journal and real estate reporter at Banker & Tradesman after toiling at weekly newspapers.

Image: Protocol

We launched Protocol in February 2020 to cover the evolving power center of tech. It is with deep sadness that just under three years later, we are winding down the publication.

As of today, we will not publish any more stories. All of our newsletters, apart from our flagship, Source Code, will no longer be sent. Source Code will be published and sent for the next few weeks, but it will also close down in December.

Keep ReadingShow less
Bennett Richardson

Bennett Richardson ( @bennettrich) is the president of Protocol. Prior to joining Protocol in 2019, Bennett was executive director of global strategic partnerships at POLITICO, where he led strategic growth efforts including POLITICO's European expansion in Brussels and POLITICO's creative agency POLITICO Focus during his six years with the company. Prior to POLITICO, Bennett was co-founder and CMO of Hinge, the mobile dating company recently acquired by Match Group. Bennett began his career in digital and social brand marketing working with major brands across tech, energy, and health care at leading marketing and communications agencies including Edelman and GMMB. Bennett is originally from Portland, Maine, and received his bachelor's degree from Colgate University.

Enterprise

Why large enterprises struggle to find suitable platforms for MLops

As companies expand their use of AI beyond running just a few machine learning models, and as larger enterprises go from deploying hundreds of models to thousands and even millions of models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

As companies expand their use of AI beyond running just a few machine learning models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

Photo: artpartner-images via Getty Images

On any given day, Lily AI runs hundreds of machine learning models using computer vision and natural language processing that are customized for its retail and ecommerce clients to make website product recommendations, forecast demand, and plan merchandising. But this spring when the company was in the market for a machine learning operations platform to manage its expanding model roster, it wasn’t easy to find a suitable off-the-shelf system that could handle such a large number of models in deployment while also meeting other criteria.

Some MLops platforms are not well-suited for maintaining even more than 10 machine learning models when it comes to keeping track of data, navigating their user interfaces, or reporting capabilities, Matthew Nokleby, machine learning manager for Lily AI’s product intelligence team, told Protocol earlier this year. “The duct tape starts to show,” he said.

Keep ReadingShow less
Kate Kaye

Kate Kaye is an award-winning multimedia reporter digging deep and telling print, digital and audio stories. She covers AI and data for Protocol. Her reporting on AI and tech ethics issues has been published in OneZero, Fast Company, MIT Technology Review, CityLab, Ad Age and Digiday and heard on NPR. Kate is the creator of RedTailMedia.org and is the author of "Campaign '08: A Turning Point for Digital Media," a book about how the 2008 presidential campaigns used digital media and data.

Latest Stories
Bulletins