Menczer is the Luddy distinguished professor of informatics and computer science at Indiana University.
An internal Facebook report found that the social media platform's algorithms – the rules its computers follow in deciding the content that you see – enabled disinformation campaigns based in Eastern Europe to reach nearly half of all Americans in the run-up to the 2020 presidential election, according to a report in Technology Review.
The campaigns produced the most popular pages for Christian and Black American content, and overall reached 140 million U.S. users per month. Seventy-five percent of the people exposed to the content hadn't followed any of the pages. People saw the content because Facebook's content-recommendation system put it into their news feeds.
Social media platforms rely heavily on people's behavior to decide on the content that you see. In particular, they watch for content that people respond to or "engage" with by liking, commenting and sharing. Troll farms, organizations that spread provocative content, exploit this by copying high-engagement content and posting it as their own.
As a computer scientist who studies the ways large numbers of people interact using technology, I understand the logic of using the wisdom of the crowds in these algorithms. I also see substantial pitfalls in how the social media companies do so in practice.
From lions on the savanna to likes on Facebook
The concept of the wisdom of crowds assumes that using signals from others' actions, opinions and preferences as a guide will lead to sound decisions. For example, collective predictions are normally more accurate than individual ones. Collective intelligence is used to predict financial markets, sports, elections and even disease outbreaks.
Throughout millions of years of evolution, these principles have been coded into the human brain in the form of cognitive biases that come with names like familiarity, mere exposure and bandwagon effect. If everyone starts running, you should also start running; maybe someone saw a lion coming and running could save your life. You may not know why, but it's wiser to ask questions later.
Your brain picks up clues from the environment – including your peers – and uses simple rules to quickly translate those signals into decisions: Go with the winner, follow the majority, copy your neighbor. These rules work remarkably well in typical situations because they are based on sound assumptions. For example, they assume that people often act rationally, it is unlikely that many are wrong, the past predicts the future, and so on.
Technology allows people to access signals from much larger numbers of other people, most of whom they do not know. Artificial intelligence applications make heavy use of these popularity or "engagement" signals, from selecting search engine results to recommending music and videos, and from suggesting friends to ranking posts on news feeds.
Not everything viral deserves to be
Our research shows that virtually all web technology platforms, such as social media and news recommendation systems, have a strong popularity bias. When applications are driven by cues like engagement rather than explicit search engine queries, popularity bias can lead to harmful unintended consequences.
Social media like Facebook, Instagram, Twitter, YouTube and TikTok rely heavily on AI algorithms to rank and recommend content. These algorithms take as input what you like, comment on and share – in other words, content you engage with. The goal of the algorithms is to maximize engagement by finding out what people like and ranking it at the top of their feeds.
How social media filter bubbles workyoutu.be
On the surface this seems reasonable. If people like credible news, expert opinions and fun videos, these algorithms should identify such high-quality content. But the wisdom of the crowds makes a key assumption here: that recommending what is popular will help high-quality content "bubble up."
We tested this assumption by studying an algorithm that ranks items using a mix of quality and popularity. We found that in general, popularity bias is more likely to lower the overall quality of content. The reason is that engagement is not a reliable indicator of quality when few people have been exposed to an item. In these cases, engagement generates a noisy signal, and the algorithm is likely to amplify this initial noise. Once the popularity of a low-quality item is large enough, it will keep getting amplified.
Algorithms aren't the only thing affected by engagement bias – it can affect people too. Evidence shows that information is transmitted via "complex contagion," meaning the more times people are exposed to an idea online, the more likely they are to adopt and reshare it. When social media tells people an item is going viral, their cognitive biases kick in and translate into the irresistible urge to pay attention to it and share it.
Not-so-wise crowds
We recently ran an experiment using a news literacy app called Fakey. It is a game developed by our lab, which simulates a news feed like those of Facebook and Twitter. Players see a mix of current articles from fake news, junk science, hyperpartisan and conspiratorial sources, as well as mainstream sources. They get points for sharing or liking news from reliable sources and for flagging low-credibility articles for fact-checking.
We found that players are more likely to like or share and less likely to flag articles from low-credibility sources when players can see that many other users have engaged with those articles. Exposure to the engagement metrics thus creates a vulnerability.
The wisdom of the crowds fails because it is built on the false assumption that the crowd is made up of diverse, independent sources. There may be several reasons this is not the case.
First, because of people's tendency to associate with similar people, their online neighborhoods are not very diverse. The ease with which social media users can unfriend those with whom they disagree pushes people into homogeneous communities, often referred to as echo chambers.
Second, because many people's friends are friends of one another, they influence one another. A famous experiment demonstrated that knowing what music your friends like affects your own stated preferences. Your social desire to conform distorts your independent judgment.
Third, popularity signals can be gamed. Over the years, search engines have developed sophisticated techniques to counter so-called " link farms" and other schemes to manipulate search algorithms. Social media platforms, on the other hand, are just beginning to learn about their own vulnerabilities.
People aiming to manipulate the information market have created fake accounts, like trolls and social bots, and organized fake networks. They have flooded the network to create the appearance that a conspiracy theory or a political candidate is popular, tricking both platform algorithms and people's cognitive biases at once. They have even altered the structure of social networks to create illusions about majority opinions.
Dialing down engagement
What to do? Technology platforms are currently on the defensive. They are becoming more aggressive during elections in taking down fake accounts and harmful misinformation. But these efforts can be akin to a game of whack-a-mole.
A different, preventive approach would be to add friction. In other words, to slow down the process of spreading information. High-frequency behaviors such as automated liking and sharing could be inhibited by CAPTCHA tests or fees. Not only would this decrease opportunities for manipulation, but with less information people would be able to pay more attention to what they see. It would leave less room for engagement bias to affect people's decisions.
It would also help if social media companies adjusted their algorithms to rely less on engagement to determine the content they serve you. Perhaps the revelations of Facebook's knowledge of troll farms exploiting engagement will provide the necessary impetus.
This article is republished from The Conversation under a Creative Commons license. Click here to read the original article.
A deep look at how "All in the Family" remains a striking mirror of American politics, class tensions, and cultural manipulation—proving its relevance decades later.
All in This American Family
There are a few shows that have aged as eerily well as All in the Family.
It’s not just that it’s still funny and has the feel not of a sit-com, but of unpretentious, working-class theatre. It’s that, decades later, it remains one of the clearest windows into the American psyche. Archie Bunker’s living room has been, as it were, a small stage on which the country has been working through the same contradictions, anxieties, and unresolved traumas that still shape our politics today. The manipulation of the working class, the pitting of neighbor against neighbor, the scapegoating of the vulnerable, the quiet cruelties baked into everyday life—all of it is still here with us. We like to reassure ourselves that we’ve progressed since the early 1970s, but watching the show now forces an unsettling recognition: The structural forces that shaped Archie’s world have barely budged. The same tactics of distraction and division deployed by elites back then are still deployed now, except more efficiently, more sleekly.
Archie himself is the perfect vessel for this continuity. He is bigoted, blustery, reactive, but he is also wounded, anxious, and constantly misled by forces above and beyond him. Norman Lear created Archie not as a monster to be hated (Lear’s genius was to make Archie lovable despite his loathsome stands), but as a man trapped by the political economy of his era: A union worker who feels his country slipping away, yet cannot see the hands that are actually moving it. His anger leaks sideways, onto immigrants, women, “hippies,” and anyone with less power than he has. The real villains—the wealthy, the connected, the manufacturers of grievance—remain safely and comfortably offscreen. That’s part of the show’s key insight: It reveals how elites thrive by making sure working people turn their frustrations against each other rather than upward.
Edith, often dismissed as naive or scatterbrained, functions as the show’s quiet moral center. Her compassion exposes the emotional void in Archie’s worldview and, in doing so, highlights the costs of the divisions that powerful interests cultivate. Meanwhile, Mike the “Meathead” represents a generation trying to break free from those divisions but often trapped in its own loud self-righteousness. Their clashes are not just family arguments but collisions between competing visions of America’s future. And those visions, tellingly, have yet to resolve themselves.
The political context of the show only sharpens its relevance. Premiering in 1971, All in the Family emerged during the Nixon years, when the “Silent Majority” strategy was weaponizing racial resentment, cultural panic, and working-class anxiety to cement power. Archie was a fictional embodiment of the very demographic Nixon sought to mobilize and manipulate. The show exposed, often bluntly, how economic insecurity was being rerouted into cultural hostility. Watching the show today, it’s impossible to miss how closely that logic mirrors the present, from right-wing media ecosystems to politicians who openly rely on stoking grievances rather than addressing root causes.
What makes the show unsettling today is that its satire feels less like a relic and more like a mirror. The demagogic impulses it spotlighted have simply found new platforms. The working-class anger it dramatized has been harvested by political operatives who, like their 1970s predecessors, depend on division to maintain power. The very cultural debates that fueled Archie’s tirades — about immigration, gender roles, race, and national identity—are still being used as tools to distract from wealth concentration and political manipulation.
If anything, the divisions are sharper now because the mechanisms of manipulation are more sophisticated, for much has been learned by The Machine. The same emotional raw material Lear mined for comedy is now algorithmically optimized for outrage. The same social fractures that played out around Archie’s kitchen table now play out on a scale he couldn’t have imagined. But the underlying dynamics haven’t changed at all.
That is why All in the Family feels so contemporary. The country Lear dissected never healed or meaningfully evolved: It simply changed wardrobe. The tensions, prejudices, and insecurities remain, not because individuals failed to grow but because the economic and political forces that thrive on division have only become more entrenched. Until we confront the political economy that kept Archie and Michael locked in an endless loop of circular bickering, the show will remain painfully relevant for another fifty years.
Ahmed Bouzid is the co-founder of The True Representation Movement.