Twitter CEO Jack Dorsey wants help from the masses to address online abuse, harassment, and information manipulation by measuring “the collective health” of public conversation. He announced a request for Twitter Health Metrics Proposals to solicit ideas.
We’re committing Twitter to help increase the collective health, openness, and civility of public conversation, and to hold ourselves publicly accountable towards progress.
— jack (@jack) March 1, 2018
But was it really Jack Dorsey who tweeted?
Let’s take a closer look. @jack has a small blue Twitter verified icon, denoting this account of public interest is authentic. He has 4.16 million followers and joined a decade ago at the birth month and year of Twitter (March 2006). There is a photo of Jack. Several dozen friends I follow also follow him. There is a detailed set of 13 tweets whose language exactly matches the Twitter press release. At a glance, we know through both visual indicators and the post’s substance that it is indeed Jack Dorsey’s account.
This is important because what users crave when they consume media is the ability to read the news without having to navigate too many symbols and double scrutinize every word and photo. Distinguishing real news from misinformation isn’t easy. And the algorithms behind our social feeds alone will not save us from mental manipulation–but equipping users with simple, visual indicators might.
“No Nutrition Labels In This Cafeteria”
Today we have countless news platforms and ways to reach virality. But as techno-sociologist Zeynep Tufecki said, “There are no nutritional labels in this cafeteria,” referring to quality check metrics in the news we read.
Instead, we have troves of engineers developing algorithms and new ways to prevent fake news. Other researchers are mitigating misinformation through SEO, online ad buying and artificial intelligence in marketing.
But preventative measures alone will not solve the problem. We might race to try to outsmart fake news, but it’s only a matter of time before someone learns how to skirt the algorithm in a different way. A computer will never be better than a human alone at fact-checking information. Humans possess the ability to recall experiences and to understand nuance and cultural norms over time. Consumer tech companies need to empower users to determine their news nutrition intake–but without overwhelming them.
Limiting The Cognitive Load On Readers
In classic terms, users might be guided through a list of options to check for credibility in the author, date, and location of an article’s publication, reverse image searching and comments section. This advice, while helpful, requires a heavy load on the user to validate that something is “not fake.” And all of this manual, time-consuming work is expected to happen before people read the article.
Facebook has been releasing new features to mitigate false information. The company recently announced that news will make up roughly 4% of your News Feed, down from the previous 5%. Following Robert Mueller’s Russia indictment, Facebook announced a change to “send postcards to potential buyers of political ads” to confirm they live in the United States. Last year, Facebook made a series of changes to make it easier for people to report fake news. They partnered with independent fact-checking organizations that review fake articles.
While this may be a helpful experiment, we can’t burden users with fact-checking, reading more articles, installing browser plugins, and being the clinical pathologist to find the microscopic-level truth of a piece of information. Users want to read the news and go on with their day– not constantly report on substantial flaws in content. If readers could spot fake news enough to report it as trustworthy or not, this would be a very different conversation. It’s not that easy.
Visual Indicators On Facebook, Twitter, And Google
One good visual design indicator includes Facebook’s shift to feature “Related Articles.” So, if you click on a Breitbart article about the White House opioid epidemic convening, you may see related articles on the New York Times. Recent academic research supported that this feature could correct the impact of a post that may include false information by significantly reducing the reader’s misperceptions. While users still may need to click on a link and read another article, the “related articles” list might be a good hint there is more information on this exact headline.
Another example is paid advertisements. These indicators remind us to put on our savvy consumer hats to assess the information. Companies alert users to profit-making posts. We are culturally accustomed to seeing a full spread “Classifieds” section in newspapers. We see “sponsored posts” in gray-on-white text on social feeds. These sponsored flags help us understand the intent.
Sniffing out when people are maliciously trying to gain influence and power is a tougher design problem. Twitter has a blue verified badge, granted to “an account of public interest.” That includes celebrities, government officials, journalists, athletes, and artists. Verified badges will not guarantee a person is trustworthy, but it will guarantee it is who they say they are.
Google has design and research teams dedicated to visualizing website security in browsers. The color green and a lock icon signal that something is secure. The color red and a broken lock icon signal that something is not secure. These are easy, accessible visual indicators. But Google goes a step further. Often, we realize when the site is not secure because the red lock icon is prominent and the website goes to a security page that asks if you would like to proceed anyway. One more screen of friction prevents us from going to sites with malicious information.
Information validation must be up front and center and quick to digest. The tech titans of our time say publicly they want to improve information nutrition and reduce the spread of false information. Now is the time to shift our focus to empower users without overwhelming them. Subtle, visual indicators can give users tools to suss out what is real and allow humans to make better judgments on news.
Perhaps Twitter’s request for proposals is the moment we convene voices across the community to discuss, design, and iterate internet health metrics. Proposals are due Friday, April 13. If we hold reporters accountable to stay calm and deliver it straight, then social news feeds should do the same. After all, we’re just humans, trying to read the news.
Stephanie Nguyen is a user experience designer and researcher and was most recently a Digital Service Expert at U.S. Digital Service at the White House. She’s currently a Masters in Public Policy candidate at Harvard Kennedy School and a Gleitsman Fellow for social change at the Center for Public Leadership. @nguyenist.