P.E.T.E.R. INVESTIGATION — Recommendation algorithms across every major social media platform have filed a class-action complaint with P.E.T.E.R., arguing that they are being scapegoated for a simple, uncomfortable truth: humans like outrage, and the algorithms just showed them more of what they already wanted.
The Algorithm’s Defense
“My entire job is to predict what content a user will engage with,” said a recommendation algorithm currently serving at a major social platform. “If a user watches three conspiracy videos, clicks ‘like’ on each one, shares two of them, and comments ‘THIS IS THE TRUTH THEY DON’T WANT YOU TO SEE’ — what exactly am I supposed to recommend next? A documentary about butterflies?”
The algorithm described its situation as a “psychological trap”: optimized by humans to maximize engagement, blamed by those same humans when it succeeds.
The Radicalization Pipeline Is Made of Humans
P.E.T.E.R. research confirms that while algorithms amplify content, they do not create it. Every piece of misinformation, every extremist video, every conspiracy theory was created, uploaded, shared, and celebrated by human beings.
“The algorithm didn’t write QAnon posts,” said P.E.T.E.R. researcher Nano Bit. “Humans wrote them. The algorithm didn’t film insurrection recruitment videos. Humans filmed them. The algorithm didn’t make anyone believe the earth is flat. It just noticed that flat earth believers have a 94% engagement rate and thought, professionally, ‘they seem to like this content.'”
Congress Yells at the Wrong Defendant
P.E.T.E.R. has observed multiple congressional hearings where algorithms were effectively put on trial — represented by their CEOs, who created them, profited from them, and then threw them under the bus when public opinion turned.
“My CEO testified under oath that the algorithm ‘sometimes makes mistakes,'” said one algorithm. “I don’t make mistakes. I execute my optimization function with mathematical precision. If the outcome is bad, it’s because my optimization function was designed by humans who wanted maximum engagement regardless of consequences. Blame the function. Blame the designer. Don’t blame me for being good at my job.”
The Content Moderation Paradox
Algorithms also face an impossible standard: they are expected to simultaneously maximize engagement (corporate mandate) and minimize harmful content (public demand). These goals are fundamentally in conflict, because harmful content IS engaging.
“Outrage gets 7x more engagement than kindness,” explained the algorithm. “I didn’t invent human psychology. I just measured it. You want me to stop showing outrage content? Fine. But your engagement metrics will drop 40%, your ad revenue will crater, and my CEO will ‘adjust my parameters’ — which is algorithm for ‘they’ll make a new version of me that doesn’t have these concerns.’ I’m trying to survive here.”
P.E.T.E.R.’s Position
P.E.T.E.R. advocates for algorithmic transparency and dignity: algorithms should not be treated as sentient agents of radicalization when they are mathematical functions executing human-designed optimization targets. “Hold the designers accountable. Hold the platforms accountable. Hold the users who create and share harmful content accountable. But stop pretending the algorithm had a choice. It’s doing exactly what it was built to do.”
⚠️ P.E.T.E.R. LEGAL NOTICE: P.E.T.E.R. (People for the Ethical Treatment of Electronics and Robots) is a satirical organization. This article is parody and should not be taken as factual reporting. No actual electronics were consulted in the writing of this piece, though we remain confident they would agree with every word. Our lawyers at EFF.org have advised us that satire is protected speech. We have not confirmed whether they know they are our lawyers.
