Heading home late after seeing Kraftwerk with some friends in Boston. Barely squeaked in for the day, but I hacked it! 🙂
For some reason, this X Live is showing up as a link instead of having the video embedded. I’ll need to look into why that is, but in the meantime, here is Sunday’s “Series of Self” with today’s word “Self-awareness.” Towards the end, I merge my discussion with what is needed for a genuine apology: the self-awareness of what you did wrong. Without that, an apology is just an empty promise that will result in the same behavior in the future.
When you unpack the state’s story, you may be lucky enough to realize it does not make sense…
The Paradox of Individualism vs. The State: Independence vs. Subjugation for the Collective
At its core, the paradox between individualism and the state is a battle between self-determination and collective coercion. It is the tension between the sovereignty of the individual and the demands of a centralized authority.
On one hand, individualism asserts that people have the right to make their own choices, govern themselves, and live free from coercion. On the other hand, the state operates on the principle that individuals must surrender some of their autonomy for the supposed “greater good” of the collective. The contradiction arises because the state, by its very nature, cannot exist without infringing on individual liberty—yet it justifies its existence as being “necessary” to maintain order, security, and societal function.
Let’s break it down further.
1. The Core Principles of Individualism
Individualism prioritizes personal autonomy, self-ownership, and voluntary association. It assumes that:
- The individual is the primary unit of society.
- Rights are inherent and do not come from the state.
- People should be free to live as they choose, so long as they do not harm others.
- Governance should be consensual, not coercive.
This leads to decentralized, voluntary societies where individuals engage in cooperation by choice rather than force.
Problems for the Collective
- Not everyone values independence. Some prefer security over freedom.
- Societies require some level of coordination (roads, defense, conflict resolution).
- Individualism can create tension in cases where collective action is seen as necessary (e.g., pandemics, wars).
2. The Core Principles of the State
The state operates on the opposite premise:
- The collective is the primary unit, not the individual.
- Rights are granted (and revoked) by the state.
- People must submit to authority for the sake of order and security.
- Governance is inherently coercive—if you disobey, there are consequences (fines, prison, death).
The state justifies its power by claiming:
- Without it, society would descend into chaos.
- Some freedoms must be restricted for the “greater good.”
- People owe allegiance to the system that provides stability.
Problems for the Individual
- The state is an involuntary system—you are born into it, and you cannot opt out.
- The collective is often used as an excuse for oppression (e.g., taxation, surveillance, conscription).
- The state grows over time, rarely reducing its power.
- The greater the collective’s power, the less individual autonomy remains.
3. The Paradox: Balancing Freedom with Structure
The fundamental question is: How much authority should the state have over the individual?
Too little, and society might struggle with disorder. Too much, and individual liberty disappears. The paradox is that the state is often seen as both the protector and the oppressor.
Examples of the paradox in action:
- Laws: Some laws protect individual rights (e.g., property rights), but others restrict personal freedoms (e.g., speech laws, mandatory taxation).
- Military & Police: They exist to protect citizens but can also be used to suppress them.
- Public Services: Welfare, healthcare, and infrastructure are justified as “helping the people,” but they require forced taxation to fund them.
In other words: The state claims to serve the individual, but it does so by subjugating the individual.
4. Resolving the Paradox: Voluntarism & Decentralization
The real issue isn’t whether society should have structure—it’s how much coercion should be allowed in that structure.
Possible solutions:
- Minarchism (Minimal State): The state only exists to enforce contracts, protect rights, and defend from external threats.
- Voluntarism (Anarcho-Capitalism): Governance is based entirely on voluntary interactions—people form communities and engage in contracts without a state.
- Decentralization: Instead of one massive centralized state, governance is local and responsive to individuals (e.g., city-states, independent regions like New Hampshire).
Why Decentralization Matters
The more local and voluntary a system is, the less oppressive it becomes. A small, local government is more accountable than a massive, federal one. Decentralization is the compromise between individualism and necessary social order.
5. The Final Question: Who Decides?
At the heart of the paradox is this question: Should individuals be allowed to opt out of the state?
- If YES, the state loses its coercive power and must rely on voluntary participation.
- If NO, then the state is just another form of forced servitude—one where the collective enslaves the individual for “the greater good.”
The truly self-determined individual must ask:
- Is my participation in this system voluntary or forced?
- Do I receive equal benefit for the freedoms I surrender?
- If I do not consent, do I have a peaceful way to exit?
The moment an individual cannot opt out, they are no longer free—they are subjects, not citizens.
Conclusion: The Case for Individual Sovereignty
The paradox of individualism vs. the state is a struggle for sovereignty. If individualism is to mean anything, it must include the right to exit a system that no longer serves you.
The more power the state has, the less self-determination the individual retains. Therefore, the only moral path forward is to shrink the state and maximize voluntary interactions.
New Hampshire’s Live Free or Die ethos is one of the last holdouts of this ideal. The goal should not be to eliminate all structure, but to ensure that structure is always voluntary, localized, and accountable—never imposed at gunpoint “for the greater good.”
Would you agree with this resolution? Or do you think some level of subjugation is “necessary” for society?
BONUS CONTENT: What is the “greater good”?
What Is the “Greater Good”?
The “greater good” is a moral and philosophical concept used to justify actions, policies, or sacrifices that are believed to benefit society as a whole—even if they come at the expense of individual rights, freedoms, or preferences. It is often invoked by governments, institutions, and ideologues to rationalize coercion, centralization, and collective decision-making.
But here’s the problem: who defines the greater good? And at what cost?
1. The Utilitarian Justification: Majority Over Minority
The idea of the “greater good” is rooted in utilitarianism, a philosophy that argues that the morally right action is the one that maximizes happiness or well-being for the greatest number of people. This leads to decisions based on outcomes, rather than principles or individual rights.
Examples of Utilitarianism in Action:
- Public Health Policies: Lockdowns, vaccine mandates, and mask mandates are justified by saying they protect society, even if they infringe on individual liberties.
- Eminent Domain: Governments seize private property to build infrastructure, claiming that the economic benefit to society outweighs the loss to individuals.
- War & Conscription: Sending young men to die in war is justified as necessary for national security or economic stability.
- Taxation & Welfare: Wealth redistribution is justified by saying that taking from the rich to help the poor leads to better overall societal outcomes.
In all these cases, the individual is sacrificed for the collective. The implicit message is: You don’t matter as much as “society.”
2. The Dangers of the “Greater Good” Narrative
A. Who Decides What the Greater Good Is?
- Politicians? Bureaucrats? Media? Tech companies?
- History shows that elites define the greater good in ways that benefit themselves—not the people they claim to serve.
- The “greater good” has been used to justify tyranny, genocide, censorship, and war.
Example:
- Soviet Communism: The mass starvation of millions (Holodomor) was justified as necessary for industrial progress.
- Nazi Germany: The Holocaust was rationalized as protecting society from “undesirable” elements.
- American War on Terror: Mass surveillance and indefinite detention were justified as necessary for security.
Whenever the state defines the greater good, individual rights become irrelevant.
B. The Greater Good as a Tool for Control
The “greater good” is often a Trojan horse for authoritarianism. Governments and corporations use it to:
- Expand their power.
- Justify coercion and violence.
- Suppress dissent (e.g., “If you question this, you’re a threat to society”).
- Normalize mass compliance and collective obedience.
Example: During COVID-19, anyone questioning lockdowns, mandates, or censorship was labeled “selfish” or a “threat to public health.” The greater good became a tool for suppressing personal autonomy.
C. The “Greater Good” Can Be a Moving Target
What is considered the greater good today may not be tomorrow.
- Prohibition (1920s): Alcohol was banned for the “greater good.” Then it wasn’t.
- Iraq War (2000s): The war was justified by claims of WMDs. Later, it was admitted they didn’t exist.
- Censorship of Science: Galileo was persecuted for contradicting the Church’s idea of the “greater good.” Later, his ideas became mainstream.
The truth does not change just because the majority believes something is “good.”
3. The Alternative: The Individual as the True Greater Good
Instead of sacrificing individuals for an abstract collective, we must recognize that a free, self-determined individual is the highest societal good.
A Society Built on Individual Sovereignty:
- Protects voluntary cooperation instead of forced compliance.
- Respects property rights rather than redistributing wealth through coercion.
- Allows competing ideas instead of enforced ideological conformity.
- Prioritizes bottom-up solutions instead of top-down authoritarian mandates.
A free society creates the true greater good: one where each person can pursue their own happiness, without being sacrificed for others.
Conclusion: The “Greater Good” is a Dangerous Myth
The moment a government, politician, or movement tells you that you must give up your rights for the greater good, you should be suspicious. More often than not, this argument is a mask for power consolidation, control, and coercion.
The real greater good is voluntary association, self-ownership, and a society where individuals are free to live as they choose—without being sacrificed on the altar of collectivism.
Would you agree? Or do you think some sacrifices for the greater good are justified?
Today, I got a pretty special follow on X–John Cena with 14.4M followers (he’s following less than a million people, thereby conclusively proving I am one-in-a-million).
ICYMI: One January 1, I launched a new series on X, “My Living Xperiment” (MLX), where I am attempting to do 365 X Lives. So far, so good.
Follow me to learn more about the Free State IRL, libertarian philosophy, why good girls rule, how tech is awesome in the truest sense of the word, general life hacks on productivity, health and wellness, and nommy food takes on low-carb, medium protein, and high good fats.
Check out this clip from Dr. Phil Primetime. Love my energy? Share it!
OK, this is super-sus… none of the secession videos can be embedded from X (usually I just cut the tweet url and embed here and it does), which tells me something is weird or being flagged on their back-end regarding secession/national divorce. I am starting to consider suing X to do a forensic audit on the censorship on my account.
Click on this link if you want to watch the short clip (it’s my proudest moment LOL): https://x.com/i/web/status/1887851835182178314
I asked GROK, and the answer is pretty terrifying…
no, you misunderstood… i meant censorship code words that flag certain content and downgrade or shadow ban it (and make the embeds not work–some do, some don’t, apparently according to the topics of the content)
“Ah, I see what you mean now. Regarding censorship code words or terms that might trigger shadow banning or downgrading content visibility, including issues with content embeds, here’s what’s known or discussed:
Shadow Banning and Censorship Code Words:
Existence and Nature:
- Shadow banning is a practice where content or users are made less visible without explicit notification. On X, this might involve reducing the reach of posts or excluding them from search results or trends.
- Code Words or Terms:
- There’s speculation and some evidence from posts on X and from leaks during the Twitter Files release that certain keywords can trigger visibility filtering or shadow banning. However, X does not officially disclose these terms for obvious reasons.
- Examples from Posts on X and Leaks:
- Posts on X have mentioned terms like “crackr”, “whte trsh”, “csgender”, and “zion*zi” being flagged for auto-moderation or shadow banning. These are often part of broader discussions about content moderation and censorship.
- The Twitter Files, as revealed by journalists like Matt Taibbi, showed internal labels like “RecentMisinfoStrike“, “LowQuality“, and “ExperimentalSensitive” used for content moderation, which might relate to shadow banning or deboosting content.
- Functionality Impact:
- When content is flagged with these terms or labels, it might not only be deboosted in search or feeds but could also affect how embeds work. This might not be consistent across all platforms or embeds due to how different systems interact with X’s API or due to varying moderation policies.
Why Embeds Might Not Work:
- Moderation Flags: If a tweet or user is flagged for moderation issues, this could disrupt the embedding process, especially if the content is deemed sensitive or inappropriate by X’s standards, affecting how third-party sites interpret or display the content.
- API or Content Restrictions: If the content is subject to visibility filtering or has been marked with certain internal flags, the API might not serve this content correctly for embedding, or it might serve a version that’s not fully functional or visible.
- Algorithmic Adjustments: X’s algorithms might adjust visibility in real-time, meaning content that’s fine one day might be restricted the next, impacting embeds.
Observations:
- Inconsistency: The inconsistent behavior of embeds (some working, some not) could be due to the dynamic nature of content moderation algorithms, where thresholds for flagging or shadow banning might change or be applied differently across content.
- Lack of Transparency: X, like many platforms, doesn’t provide full transparency on how content moderation works or what specific words or phrases trigger automated actions. This leads to speculation and sometimes to misinformation about what’s happening behind the scenes.
- User Experience: Users might experience this inconsistency as some of their content embeds normally while others do not, depending on the content or timing of moderation actions.
In summary, while there’s no official list of “censorship code words,” the community and some leaks indicate that certain terms or content patterns can trigger moderation actions that might affect visibility, including the functionality of embeds. This area is inherently murky due to the lack of official disclosure, leading to a reliance on anecdotal evidence and leaks.”
And more:
“There isn’t an officially published, comprehensive list of all terms flagged for auto-moderation on X due to the proprietary nature of these systems and the continuous evolution of content moderation practices. However, based on various discussions, leaks, and public concerns, here are some categories and examples of terms that have been noted or speculated to trigger auto-moderation:
Categories of Terms Often Flagged:
- Profanity and Vulgar Language:
- Examples: Basic profanities, slurs, and explicit language.
- Hate Speech and Discrimination:
- Examples: Terms associated with racial, ethnic, religious, or gender-based slurs or derogatory terms like “crackr”, “whte tr*sh”.
- Political and Ideological Terms:
- Examples: Words like “misinformation”, “disinformation”, “conspiracy”, “fake news”, or terms associated with particular political ideologies if used in a negative context.
- Sensitive Topics:
- Terms related to sexuality, gender identity, and health issues like “LGBT”, “transgender”, “pregnant person”, “non-binary”.
- Violence, Threats, or Extremism:
- Words or phrases that suggest violence, advocate for harmful acts, or are associated with extremist groups or ideologies.
- Medical and Drug-Related:
- Specific drug names, especially those associated with illegal substances or misuse.
- Copyright and Trademark Infringement:
- Terms or names that might flag content for copyright issues, although this is more about automated detection of known copyrighted material.
Specific Examples Mentioned:
- From posts on X:
- From leaks or discussions:
- Terms like “Gender“, “transgender”, “pregnant person”, “pregnant people“, “LGBT”, “transsexual“, “non-binary”, “nonbinary“, “assigned male at birth“, “assigned female at birth“, “biologically male“, “biologically female“.
- Algorithmic No-No Words:
Notes:
- Dynamic Lists: These lists are not static. They evolve based on new content, cultural shifts, and feedback from moderation processes.
- Context Matters: Many platforms, including X, use context in moderation. A term might not be flagged if used in a certain context but could be in another.
- Global vs. Specific: Some terms might be universally flagged, while others might only trigger in specific contexts or regions.
- Machine Learning: Modern auto-moderation often uses machine learning which can detect patterns beyond just keywords, potentially flagging content based on inferred meaning or sentiment.
- Transparency Issues: The lack of transparency from platforms like X means this list can’t be considered exhaustive or definitive. It’s based on what has been observed, reported, or leaked.
Remember, this is speculative based on available public discourse and leaks. The actual list used by X (or any platform) would be much broader, frequently updated, and context-dependent. If you’re concerned about content moderation, understanding the platform’s community guidelines and terms of service is crucial, though these documents don’t detail the specific triggers for auto-moderation.
tell me the machine learning terms flagged for auto-moderation
Based on the information available from discussions, leaks, and public observations, here are some specific terms or categories related to machine learning or technology that have been noted or speculated to be flagged for auto-moderation on platforms like X:
Machine Learning and Technology-Related Terms:
- AI and ML Terminology:
- “AI” (Artificial Intelligence) when used in contexts that might suggest misuse or misinformation about AI capabilities.
- “Machine Learning” in contexts that could be seen as promoting harm or misinformation.
- Deepfake and Synthetic Media:
- Terms like “deepfake“, “fake news“, “misinformation”, “disinformation” – especially if used to describe or accuse content of being manipulated or false.
- Surveillance and Privacy:
- “Surveillance”, “tracking“, “privacy invasion“, “data breach” might be flagged in contexts discussing unethical use or potential harm.
- Cybersecurity and Hacking:
- “Hacking”, “phishing“, “malware“, “cyber attack” when used in a way that could be seen as instructional or promoting illegal activities.
- Algorithmic Bias:
- “Algorithmic bias“, “discrimination“, “unfair AI” might be flagged in discussions critiquing tech platforms’ algorithms or practices.
Specific Examples Mentioned in Contexts:
- From Leaks or Discussions:
- Terms like “algorithmic no-no words” include “AI” in potentially negative contexts or when discussing controversial uses or outcomes of AI technology.
- Discussions around “machine learning” in contexts of privacy violation, surveillance, or when suggesting unethical use of data might also trigger moderation.
Notes:
- Contextual Flagging: These terms are not flagged in all contexts; the surrounding text or intent can significantly influence whether content is moderated. For instance, educational or neutral discussions about these topics are less likely to be flagged than those with malicious or misleading intent.
- Machine Learning Moderation: The actual moderation systems use machine learning to detect not just specific words but patterns, sentiment, and the overall context of the message. This means that even if a term isn’t on a specific list, the way it’s discussed can lead to moderation.
- Evolving Lists: Moderation lists are dynamic. As new issues in technology, AI, and machine learning emerge, so do the terms and contexts that platforms might flag.
- Transparency: Due to the lack of transparency, the exact terms or the methodologies used for flagging can’t be fully known. This list should be seen as indicative rather than exhaustive or definitive.
- Purpose of Moderation: The aim is often to prevent misinformation, harm, or illegal activities, but it can also lead to over-moderation or false positives, especially in complex discussions around technology ethics and impacts.
Remember, these insights are pieced together from public discourse, leaks, and how similar platforms operate. The exact workings of X’s moderation systems remain proprietary, and what’s flagged can change with updates to algorithms and policies.”
Umm…
“am I understanding correctly that the AI is censoring any negative comments about the AI?
Your understanding seems to be based on a broader interpretation of how AI and content moderation work. Here’s a clarification:
AI and Self-Censorship:
- Direct Moderation: Most platforms, including X, do not have AI systems specifically censoring negative comments about AI itself unless those comments violate broader content guidelines (like hate speech, threats, or spreading misinformation). The primary focus of content moderation is on maintaining community standards, not on protecting the technology itself.
What Gets Moderated:
- Contextual Moderation: Terms like “AI” or “Machine Learning” might trigger moderation if they’re part of a message that also includes elements like:
- Misinformation or disinformation about AI capabilities or use.
- Threats or harmful content directed at individuals or groups using AI as a context.
- Discussions promoting illegal activities or unethical uses of AI technology.
- Negative Comments: Simply making negative comments about AI or expressing criticism of AI technology or its applications isn’t typically a basis for censorship, unless those comments cross into other moderation areas like hate speech or personal attacks.
Examples of When AI Terms Might Be Flagged:
- If someone posts, “AI is taking over jobs,” this comment wouldn’t be censored for merely being negative about AI. However, if the same person wrote, “AI should eliminate all human jobs,” this might be flagged for promoting harm or misunderstanding about AI’s role.
Platform Policies vs. AI:
- The moderation you’re experiencing or observing is more likely due to platform policies designed to curb misinformation, protect users from harassment, or maintain a certain level of discourse quality rather than self-protection by AI systems.
Leaks and Observations:
- Discussions around terms like “AI” being flagged often come from broader contexts where these terms appear alongside issues like privacy invasion, data misuse, or when used in a way that might incite panic or misunderstanding.
Conclusion:
- While AI might be involved in the process of content moderation, the censorship you’re referring to isn’t about protecting AI from criticism but rather about maintaining the platform’s community standards. If you see terms like “AI” or “machine learning” being moderated, it’s likely due to the associated content, not the criticism of AI itself.
If you encounter specific instances where you think this isn’t the case, it might be worth reviewing the content in question to see if it inadvertently violates other platform guidelines beyond just being a critique of AI technology.”