Fake News, AI and Bias, Oh My!

First published on DigiDig

There have been quite a few relevant articles recently, so I thought I would write this post which includes links and brief summaries.

Real Interest in Fake News

Fake news continues to be a hot story that shows what can go wrong when algorithms choose what we read. I covered the topic here blog when it first broke a few weeks ago.

Ryan Holmes of HootSuite wrote for the Observer in The Problem Isn’t Fake News – it’s Bad Algorithms: “As algorithms mature, growing more complex and pulling from a deeper graph of our past behavior, we increasingly see only what we want to see… More dangerous than fake news, however, is all the real news that we don’t see. For many people, Facebook, Twitter and other channels are the primary… place they get their news. By design, network algorithms ensure you receive more and more stories and posts that confirm your existing impression of the world and fewer that challenge it. Overtime, we end up in a “filter bubble”‘

Writing for DigiDay, Lucia Moses explained Why Top Publishers are Still Stuck Distributing Fake News. It is not just about news feed algorithms, but also involves the “intelligence” behind automatically-served programmatic ads (native ads can look like real articles). She shares an example in which the NY Times displayed a fake news ad next to their real story on fake news (got that?).

Algorithms and Bias

One of the primary concerns about algorithms relates to bias. How do biases infect data-driven computations? And in which ways do programs discriminate?

Kristian Hammond answers the first question in the TechCrunch story 5 Unexpected Sources of Bias in AI. He ponders whether bias is a bug or feature, and says: “Not only are very few intelligent systems genuinely unbiased, but there are multiple sources for bias… the data we use to train systems, our interactions with them in the ‘wild,’ emergent bias, similarity bias and the bias of conflicting goals. Most of these sources go unnoticed. But as we build and deploy intelligent systems, it is vital to understand them so we can design with awareness and hopefully avoid potential problems.”

Alvin Chang writes in Vox about How the Internet Keeps Poor People in Poor Neighborhoods. He shares an example of a Facebook ad that violates the Fair Housing Act by excluding certain users from seeing it. This is blatant, but algorithmic discrimination can be a lot more subtle, and thus harder to root out, he explains.

Artificial Intelligence for Dummies

If you are new to algorithms and AI, you might want to read this Digital Trends story, which breaks down the differences between machine learning, AI, neural networks, etc.

 



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In Defense of “Fake News”

More people are wondering about the weird crap that mysteriously appears in their news

Is News Today too Much Like the Magic 8 Ball?

Is News Today too Much Like the Magic 8 Ball?

feeds. How much is fake news? Did disinformation tilt an election? What are Google and Facebook going to do to clean up the mess?

You could almost hear the entire PR industry shifting uncomfortably amidst the backlash. I mean, crafting news (that some might call fake, or at least a stretch) is our stock in trade. We package propaganda as newsworthy information and sell it to the media; and, increasingly publish directly to the Web and social networks.

I understand that the fuss is more about blatant lies, not the average press release. But it highlights the challenges of determining what is newsworthy and true; a role that is increasingly being taken on by algorithms.

The Web and social media gave us all ways to easily share and spread information. This can include rumor, conjecture, commercial information, news, and yes, slander and outright lies.

I would never defend the last two; but will fight for our right to issue press releases, and traffic in other kinds of info. Any good system needs to be able to deal with all of this, i.e. anticipate some BS and surface the most credible and significant information, whether via the wisdom of the crowds, programs or a combination.

It is naïve to think that a publication, editors, or algorithms (which of course are written by humans) can present news without bias. The journalistic piece you just wrote might be pristine, free of opinion; but the very act of deciding which stories to feature shows partiality.

That said, the social networking platforms where more of us are getting news can do a much better job of separating the wheat from the chaff. I thought I’d share some of the great stories I’ve seen about the controversy and takeaways from each.

TechCrunch – How Facebook can Escape the Echo Chamber

Anna Escher says “Facebook is hiding behind its [position that] ‘we’re a tech company, not a media company’ … For such an influential platform that preaches social responsibility and prioritizes user experience, it’s irresponsible …”

She recommends that they bring journalists into the process, remove the influence of engagement on news selection during elections, and expand Trending Topics to show a greater diversity of political stories – not just the ones that are the most popular.

Tim O’Reilly – Media in the Age of Algorithms

Tim’s exhaustive Medium piece looks at all sides. He rails against “operating from an out-of-date map of the world [in which] algorithms are overseen by humans who intervene in specific cases to compensate for their mistakes,“ and says:

“Google has long demonstrated that you can help guide people to better results without preventing anyone’s free speech… They do this without actually making judgments about the actual content of the page. The ‘truth signal’ is in the metadata, not the data.”

Tim makes an analogy between news algorithms and airplanes “Designing an effective algorithm for search or the newsfeed has more in common with designing an airplane so it flies… than with deciding where that airplane flies.”

He cited an example from the history of aircraft design. While it’s impossible to build a plane that doesn’t suffer from cracks and fatigue… “the right approach … kept them from propagating so far that they led to catastrophic failure. That is also Facebook’s challenge.”

Nieman Lab – It’s Time to Reimagine the Role of a Public Editor

Mike Ananny writes about the public editor’s role, and the challenges they face in the increasingly tech-driven environment. He writes:

“Today, it is harder to say where newsrooms stop and audiences begin. Public editors still need to look after the public interest, hold powerful forces accountable, and explain to audiences how and why journalism works as it does — but to do so they need to speak and shape a new language of news platform ethics.”

He asks “Will the public editor have access to Facebook’s software engineers and News Feed algorithms, as she does to Times journalists and editorial decisions?” and says:

“… public editors must speak a new language of platform ethics that is part professional journalism, part technology design, all public values. This means a public editor who can hold accountable a new mix of online journalists, social media companies, algorithm engineers, and fragmented audiences — who can explain to readers what this mix is and why it matters.”



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Latest PR Gambit: Publishing on Platforms

Back in the day (“the day” being about 10 years ago), we had a simple message for PR shoe-737084_1920clients who wanted to get in on the social media and blogging action.

It was: “Go forth and blog too. Master the channels that are accessible to all.” Those who took the time to produce quality content, nurture social communities and post consistently saw their online influence grow.

Now, the open web is being challenged by the growth of social networking platforms. They’re places we go to connect, and get entertained and informed. Their news clout is growing, as the networks are increasingly publishers and aggregators of content. The social networks reach vast audiences with precise targeting – compelling attributes for marketers.

In short, if you are in the news business or want to promote your own, you are missing out if you are not on Facebook, LinkedIn, Twitter, etc.

But there are a number of challenges along the way. It takes PR out of our media-centric comfort zones. It’s not obvious how to use social networking channels to accomplish your goals, which generally include coverage KPIs.

Sure, many in PR have jumped on the social media and content marketing bandwagons. We can handle Tweeting and blogging quite well. But getting your news seen and covered or appreciated by the right audiences, especially if your profile does not already have umpteen million friends/followers, is another matter.

Success generally requires a combination of paid and organic promotion as well as an understanding of the algorithms, those wonky programs that determine what appears in our news feeds. But they are black boxes and constantly changing. Plus, ad options may be unfamiliar, and they’re also moving targets.

How does one figure this all out? Listen, read, and more important, experiment. Dip your toes in. Test, validate, then repeat.

Reading this blog is a good start, as it offers commentary, articles about best practices and links to the right resources. The networks can be opaque, when it comes to specifics about their algorithms – but they do inform about changes and make recommendations.

In short, there are no pat answers, although one could invoke advice similar to the words at the beginning of the article: go forth and publish on Facebook (for example). Learn about the secrets of shareable content and how to get into the news feed.

I’ll close with an example from the world of politics, which seems fitting since the election has been front and center. It’s an article that ran awhile back in the NY Times Sunday magazine.

What do you think? Could a similar approach work beyond the field of politics? What ideas does this give you for PR? See the link and excerpts below, and please share your comments.

Inside Facebook’s… Political Media Machine
[Facebook’s] algorithms have their pick of text, photos and video produced and posted by established media organizations… But there’s also a new and distinctive sort of operation that has become hard to miss: political news and advocacy pages made specifically for Facebook, uniquely positioned and cleverly engineered to reach audiences exclusively in the context of the news feed…

These are news sources that essentially do not exist outside of Facebook… cumulatively, their audience is gigantic: tens of millions of people. On Facebook, they rival the reach of their better-funded counterparts in the political media…

But they are, perhaps, the purest expression of Facebook’s design and of the incentives coded into its algorithm — a system that has already reshaped the web…
Truly Facebook-native political pages have begun to create and refine a new approach to political news…. The point is to get [users] to share the post that’s right in front of them. Everything else is secondary.



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How to Pitch an Algorithm

android-161184_1280 calculator-695084_1280The Wall Street Journal had an interesting op-ed this week. The Algorithm is the EditorJeffrey Herbstandroid-161184_1280 android-161184_1280wrote: “Social media companies quickly are becoming the dominant news providers… Four in 10 adults in America now get news from Facebook and one in 10 from Twitter.”

Similarly, WGBH News posted an article: How Facebook Became our Biggest News Publisher – and Why we Should be Worried.

The articles warn about the implications of tech companies becoming news organizations, vs. the distribution channels they claim to be; their newsfeeds increasingly determine what we see.

If the algorithm is now the editor, how long will it be before PR people become code-driven bots (cue up sarcastic comments about PR)?

I have not tried to pitch an algorithm recently (well, ever); and it might not be obvious for many of us in the field how to deal with these new realities.  Does our job as PR pros end after we get our clients in an article?  What if the story does not make the feed?

The New York Times argues that media need to become more data-driven to survive:

“Hooking people on your… news  is [hard]… But news organizations have ways they never had before to figure it out… Through real-time analytics, reporters and editors know how many people are reading their work and through which devices and sites, how long those readers are sticking with it, and what they’re ignoring.”

In other words, online media are now getting ratings… and publishers can learn from them. So, what gets attention and survives the social filter?  The article continues:

“Videos, podcasts, short items of interest that can be read easily on smartphones, and almost anything with ‘Trump’ rate well. Perhaps counterintuitively, deeply reported features and investigative pieces…  draw readership levels that were never possible in the print-only era.”

The last part validates my post Wonky Articles Trump other Forms of Content.

Despite the title of this post, I do not suggest that you go out and pitch an algorithm.  I do recommend becoming more data driven.  Get smart about the new ways in which content and news get shared and consumed.  Apply this insight to make sure that your coverage makes the cut.

 



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