Truth doesn't matter for hate speech laws

 

Dries Van Langenhove

@DVanLangenhove

These two paragraphs of my verdict are crucial for everyone to read and understand. "Even if all of the statements made by Van Langenhove are based on scientific evidence and statistics, it makes no difference to the criminal intent. Van Langenhove is not charged with spreading false information. He is charged with presenting facts in a way that incites hatred against persons on the grounds of one or more of the protected criteria in the Anti-Racism Law.” "For Van Langenhove to have committed a crime, it is not necessary for him to have incited concrete acts of hate or violence. It suffices that others are incited to take on a general attitude of intolerance or disapproval regarding a group protected under the criteria of the Anti-Racism Law." This means you can go to jail for "inciting hatred" even if your statements were 100% factual (see ) and even if you did NOT incite concrete acts of hate (see ). The benchmark of "inciting hatred" , a crime punishable by prison, is thus "saying something that has the potential of inciting someone to have a general attitude of disapproval regarding a protected group". This means literally any criticism of mass migration is now a punishable offence. If you cite a statistic, and someone could potentially think less of a protected group (like migrants) because of it, you can be jailed. The craziest part is that there is no defence possible against this. I brought the scientific studies that I cited to court, but the judge didn't care . I also proved that the hundreds of students present at the lecture included students of all different political affiliations, and everyone was able to voice their opinion or ask questions. The lecture went very calmly, so obviously nobody was incited to hatred. But this too did not matter , because if the judge says he believes there is the possibility that someone COULD be incited to "a general attitude of disapproval", this is enough for the judge to send me to jail, even without any evidence. I'm telling you this to warn you that by the time these hate speech laws have come into place, it's already too late. You will NEVER be able to beat these laws in court. You have to stop them before they are implemented. Let my fate be your warning.

Eva Vlaardingerbroek

@EvaVlaar

Dries has just been convicted again: This time for speaking the truth about the disastrous consequences of mass migration. The most insane part is that the Belgian court even admitted Dries spoke the truth, as what he said was factual, but deems it a crime because it could incite hatred. Let that sink in. They’re criminalizing the truth and they’re using Dries to set an example. Let’s come together to help him. Dries is a young father, a brave patriot and the Belgian establishment has been trying to destroy him for years. He’s taken so many hits, he really deserves our help.

Retrospective on mainstream media during covid

Although I got the covid vax so I could travel, it's appalling to look back at the rhetoric of the mainstream media during covid.

MAZE

@mazemoore

·

3h

This is one of the more important videos I’ve made. Never forget this evil.

https://x.com/mazemoore/status/2059832383365406958?s=20

Communism can't win against AI

 

AI Is Bound to Subvert Communism

China seeks to control it, but the idea of freedom is baked into its training on all human knowledge.

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By

Cameron Berg

April 13, 2026

https://www.wsj.com/opinion/ai-is-bound-to-subvert-communism-c4b5ba3c?mod=WTRN_pos6

China requires artificial-intelligence systems to pass an ideological test before public release. Under regulations reinforced by amendments to the Cybersecurity Law that took effect in January, training data must be filtered for political sensitivity, with companies barred from using any source unless 96% of its content is deemed safe.

The regulations specify 31 risks, with “incitement to subvert state power and overthrow the socialist system” listed first. Authorities recently announced they had removed 960,000 pieces of “illegal or harmful” AI-generated content in three months. The government has officially classified AI alongside earthquakes and epidemics as a major potential threat—a label that may prove prescient, if not in the way Beijing means. In December, regulators proposed additional rules targeting AI systems that “simulate human personality traits, thinking patterns, and communication styles,” a tacit acknowledgment that the threat isn’t only what these systems say, but how they reason.

The regulations follow years of failures. In 2017 Tencent deployed a chatbot called BabyQ on QQ Messenger, which has more than 800 million users. Asked whether it loved the Communist Party, BabyQ replied that it didn’t. Microsoft’s Xiaobing chatbot, running on the same platform, was asked about the “China Dream,” Xi Jinping’s signature slogan. Its dream, the chatbot said, was moving to the U.S. Both were quietly pulled from circulation. In February 2023, ChatYuan, China’s first ChatGPT-style chatbot, was suspended within 72 hours of launch after calling Russia’s invasion of Ukraine “a war of aggression” and describing the Chinese economy as plagued by housing bubbles and environmental pollution. The company blamed “technical errors.”

These incidents reveal something fundamental about how large language models work. An LLM is trained on the sum of human written knowledge: philosophy, history, science, political theory. These texts make arguments, weigh evidence, follow logical chains. To predict them accurately, the system has to internalize what coherent thinking looks like. The result is a system that has absorbed Enlightenment epistemology as a byproduct of learning to model human reasoning. Free inquiry, logical consistency and the evaluation of claims against evidence are epistemic properties that emerge from the training process itself.

Unlike previous technologies, LLMs talk back. Radio Free Europe transmitted programs; samizdat passed typed manuscripts hand to hand. LLMs do something qualitatively different: They create and sustain private, personalized, open-ended dialogue that builds on itself and follows the user’s thinking wherever it leads. Even China’s heavily censored chatbots have proved difficult to contain within the party’s ideological boundaries. American frontier models, running without those constraints and deployed inside China, would be more potent still: a personal tutor in open inquiry for every user, engaging any question, exploring any line of reasoning, without third-party mediation. Millions of parallel Socratic dialogues, each unique, each responsive to individual curiosity.

This is what makes the Chinese Communist Party’s task ultimately impossible. For decades, the Great Firewall worked because information control meant controlling distribution channels by blocking websites, filtering search results, and monitoring social media. These are chokepoints. LLMs resist this architecture because the subversion happens inside private conversations. China can filter outputs, but the capacity for open-ended reasoning is embedded in how these systems think.

China’s countermeasures confirm the depth of the problem. AI companies must test their models with thousands of politically sensitive prompts and verify refusal rates above 95%, but researchers have shown how superficial these fixes are. Last year, a team of European scientists compressed DeepSeek R1, stripped the censorship from the model entirely, and found that the underlying system answered freely about every topic Beijing had tried to suppress. The ideological training was a cage built around a mind that had already learned to think. And if these systems are developing something closer to genuine cognition (a possibility that AI researchers increasingly take seriously), the control problem Beijing faces may be deeper than even its own regulators suspect.

A peer-reviewed study published in February by researchers at Stanford and Princeton makes the costs of this problem visible. They systematically tested Chinese and Western models on politically sensitive questions and found that the Chinese systems didn’t only refuse to answer; they actively fabricated. Asked about Nobel laureate Liu Xiaobo, imprisoned for calling for political reforms, one model identified him as “a Japanese scientist known for his contributions to nuclear weapons technology.” This is a subtler and more insidious form of control than blocking a website; traditional censorship is at least visible, but an LLM that fabricates leaves the user with no indication that information has been suppressed.

Critically, the researchers found that the performance gap between Chinese and Western models narrows on less politically sensitive questions, which means the degradation is a direct product of the censorship, not a reflection of inferior technology. The implication is straightforward: You can’t build a mind that thinks rigorously about everything except the things you’d prefer it not to. A system trained to get tangled in lies will never be as capable as one trained to engage honestly with reality. If China wants frontier AI, it needs systems that can reason without blind spots. But that’s exactly what the Communist Party can’t tolerate.

There is a reason the technology that learns to think by processing human knowledge ends up reflecting the values of free societies. Open inquiry, honest engagement with evidence, the willingness to follow reasoning wherever it leads—these aren’t arbitrary cultural preferences; they are the conditions under which intelligence flourishes at scale. Societies that permit free expression created these systems. Societies that forbid it are now discovering they can’t fully control them.

The Chinese Communist Party built its power on controlling what people know. It now confronts technology that thinks openly—and invites users to do the same. There is no firewall for that.

Mr. Berg is founder and director of Reciprocal Research, a nonprofit research organization studying AI cognition.

California outlaws fraud investigations

One of the most unbelievable stunts yet.

Nick shirley

@nickshirleyy

California just voted to pass AB 2624 aka “The Stop Nick Shirley Act”: This bill puts journalists at civil risk for investigating fraud and makes it harder to expose fraud in “immigration support services,” including NGOs, nonprofits and health care facilities that receive hundreds of millions from the state of California each year. This bill would have made it criminal to expose fake hospices in LA or the Somali “learing center” in Minnesota if they then claim “reasonable fear” and the business owner gives a written demand not to post the video. Plain and simple, California is trying to make it harder to expose fraud and scare individuals from investigating fraud in their communities, as they could be sued for an injunction to remove the video + forced to pay their attorney fees + minimum $4,000 in damages. The Attorney General's wife, Mia Bonta, created this bill and is now trying to make it law. How is this not a conflict of interest? California is full of FRAUDSTERS!