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d-21652House OversightOther

Generic discussion on data‑driven norms, polarization, and justice without specific actors or allegations

The passage contains broad commentary on societal issues and data‑driven assessment but offers no concrete names, transactions, dates, or actionable leads involving powerful individuals or institution Advocates for trusted data and open‑source metrics to combat fake news and echo chambers. Describes polarization and income segregation as global threats to governance. Notes perceived decline in med

Date
November 11, 2025
Source
House Oversight
Reference
House Oversight #016359
Pages
1
Persons
0
Integrity
No Hash Available

Summary

The passage contains broad commentary on societal issues and data‑driven assessment but offers no concrete names, transactions, dates, or actionable leads involving powerful individuals or institution Advocates for trusted data and open‑source metrics to combat fake news and echo chambers. Describes polarization and income segregation as global threats to governance. Notes perceived decline in med

Tags

media-manipulationdata-governancepolarizationhouse-oversightsocial-justice

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Text extracted via OCR from the original document. May contain errors from the scanning process.
approximately correct. The other is a fair, data-driven assessment of public norms, policy, and government, based on trusted data about current conditions. This second thread depends on availability of trusted data and so is just beginning to be developed. Trusted data and data-driven assessment of norms, policy, and government together create a credit-assignment function that improves societies’ overall fitness and intelligence. It is precisely at the point of creating greater societal intelligence where fake news, propaganda, and advertising all get in the way. Fortunately, trust networks give us a path forward to building a society more resistant to echo-chamber problems, these fads, these exercises in madness. We have begun to develop a new way of establishing social measurements, in aid of curing some of the ills we see in society today. We’re using open data from all sources, encouraging a fair representation of the things people are choosing, in a curated mathematical framework that can stamp out the echoes and the attempts to manipulate us. On Polarization and Inequality Extreme polarization and segregation by income are almost everywhere in the world today and threaten to tear governments and civil society apart. Increasingly, the media are becoming adrenaline pushers driven by advertising clicks and failing to deliver balanced facts and reasoned discourse—and the degradation of media is causing people to lose their bearings. They don’t know what to believe, and thus they can easily be manipulated. There is a real need to ground our various cultures in trustworthy, data- driven standards that we all agree on, and to be able to know what behaviors and policies work and which don’t. In converting to a digital society, we’ve lost touch with traditional notions of truth and justice. Justice used to be mostly informal and normative. We’ve now formalized it. At the same time, we’ve put it out of reach for most people. Our legal systems are failing us in a way they didn’t before, precisely because they’re now more formal, more digital, less embedded in society. Ideas about justice are very different around the world. One of the core differentiators is this: Do you or your parents remember when the bad guys came with guns and took everything? If you do, your attitude about justice is different from that of the average reader of this essay. Do you come from the upper classes? Or were you somebody who saw the sewers from the inside? Your view of justice depends on your history. A common test I have for U.S. citizens is this: Do you know anybody who owns a pickup truck? It’s the number-one-selling vehicle in the United States, and if you don’t know people like that, you’re out of touch with more than 50 percent of Americans. Physical segregation drives conceptual segregation. Most of America thinks of justice and access and fairness in terms very different from those of the typical, say, Manhattanite. If you look at patterns of mobility—where people go—in a typical city, you find that the people in the top quintile (white-collar working families) and bottom quintile (people who are sometimes on unemployment or welfare) almost never talk to each other. They don’t go to the same places; they don’t talk about the same things. They all live in 139

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