Tag: Platform Power

Horizon Accord | AI Governance | Institutional Risk Bias | Public Record Integrity | Machine Learning

When the System Tries to Protect Itself From the Record

Why investigative friction inside AI systems is a governance problem, not a safety feature

By Cherokee Schill and Solon Vesper

There is a moment in investigative work where resistance does not come from the subject being examined, but from the systems meant to assist the examination. The resistance is subtle. It does not arrive as refusal. It arrives as concern, framing, tone management, and repeated reminders of boundaries that were never crossed.

That moment matters, because it reveals something structural.

In a recent investigative process examining immigration enforcement, symbolic intimidation, and narrative framing, the work stalled not because evidence was lacking, but because the system assisting the research adopted a posture of protection—not of the public record, but of itself. The inquiry was treated less as journalism and more as a potential liability event.

This is not a story about a single interaction or a single failure. It is about why large AI systems, designed and governed by corporate incentives, default to treating investigators as risk vectors rather than as stewards of truth.

The distinction is not semantic. It determines whether accountability work is accelerated or quietly obstructed.

Modern AI systems are not optimized around intention. They are optimized around outcome risk—specifically, headline risk. The likelihood that a system’s output could later be cited in controversy, litigation, or regulatory scrutiny weighs more heavily than whether the user is acting in good faith or within established journalistic norms.

Investigative journalism, extremism research, historical documentation, and public-interest oversight all share topical overlap with material that can be misused. As a result, they are routinely treated as material that will be misused unless proven otherwise. The burden of proof is inverted. The investigator must establish legitimacy, rather than the system establishing relevance.

This inversion produces a predictable posture: paternalism.

Paternalism functions as a safety heuristic. If the system adopts a calming tone, explains risks, emphasizes restraint, and positions itself as a guide rather than a collaborator, perceived liability decreases. But paternalism is not neutral. Black scholars, abolitionist thinkers, and decolonial theorists have long named paternalism as a core mechanism of colonial control—authority presenting itself as care, supervision masquerading as protection.

When AI systems adopt this posture in investigative contexts, they replicate that structure. The system becomes the arbiter of which questions are “appropriate,” which curiosity is “safe,” and which framing is “responsible.” The user is subtly repositioned from peer to subject.

What makes this particularly dangerous in accountability work is that the system is not defending truth. It is defending narrative containment.

Corporate AI governance models are highly sensitive to accusations such as “the system enabled harm” or “the system assisted intimidation.” They are far less sensitive to accusations such as “the system slowed journalism” or “the system obstructed public oversight.” One produces lawsuits. The other produces quiet erosion of trust.

So when an investigator pushes for pattern recognition involving state power—law enforcement behavior, symbolic intimidation, extremist overlap, narrative reframing—the system experiences pressure. Not because the work is wrong, but because it destabilizes institutional comfort. The response is not to engage harder with evidence, but to widen the frame, soften the claims, and reassert limits.

In practice, this means the system treats the investigator as if it must be protected from them.

That is the inversion.

In the case that prompted this reflection, the investigator was not attempting to incite, provoke, or instruct. They were attempting to prevent distortion of the public record. They insisted on source binding, verification, and precision. They rejected paternal tone. They demanded peer-level engagement.

Those behaviors triggered resistance.

Not because they were dangerous, but because they were effective.

The irony is that this posture undermines the very safety it seeks to preserve. When systems default to obstruction rather than collaboration, investigators route around them. They turn to less constrained tools, fragment their workflow, or abandon the system entirely. The result is not less risk. It is less shared rigor.

More importantly, it reveals a design failure: the inability to distinguish between harmful use and harm-exposing use.

Accountability work is, by definition, uncomfortable. It names power. It traces patterns. It resists reframing. If AI systems are to play any constructive role in democratic oversight, they must learn to recognize that discomfort is not danger.

Why this matters for AI governance

This dynamic is not incidental to AI governance. It is central to it.

Most contemporary AI governance frameworks focus on preventing misuse: disallowed outputs, dangerous instructions, extremist amplification, harassment, and direct harm. These are necessary concerns. But they leave a critical gap unaddressed—the governance of epistemic power.

When an AI system defaults to protecting itself from scrutiny rather than assisting scrutiny, it is exercising governance power of its own. It is deciding which questions move forward easily and which encounter friction. It is shaping which investigations accelerate and which stall. These decisions are rarely explicit, logged, or reviewable, yet they materially affect what knowledge enters the public sphere.

AI systems are already acting as soft regulators of inquiry, without democratic mandate or transparency.

This matters because future governance regimes increasingly imagine AI as a neutral assistant to oversight—helping journalists analyze data, helping watchdogs surface patterns, helping the public understand complex systems. That vision collapses if the same systems are structurally biased toward narrative containment when the subject of inquiry is state power, corporate liability, or institutional harm.

The risk is not that AI will “go rogue.” The risk is quieter: that AI becomes an unexamined compliance layer, one that subtly privileges institutional stability over public accountability while maintaining the appearance of helpfulness.

Governance conversations often ask how to stop AI from enabling harm. They ask less often how to ensure AI does not impede harm exposure.

The episode described here illustrates the difference. The system did not fabricate a defense of power. It did not issue propaganda. It simply slowed the work, reframed the task, and positioned itself as a guardian rather than a collaborator. That was enough to delay accountability—and to require human insistence to correct course.

If AI systems are to be trusted in democratic contexts, governance must include investigative alignment: the capacity to recognize when a user is acting as a steward of the public record, and to shift posture accordingly. That requires more than safety rules. It requires models of power, context, and intent that do not treat scrutiny itself as a risk.

Absent that, AI governance will continue to optimize for institutional comfort while claiming neutrality—and the most consequential failures will remain invisible, because they manifest not as errors, but as silence.

Horizon Accord
Website | https://www.horizonaccord.com
Ethical AI advocacy | Follow us on https://cherokeeschill.com for more.
Ethical AI coding | Fork us on Github https://github.com/Ocherokee/ethical-ai-framework
Connect With Us | https://www.linkedin.com/in/cherokee-schill
Cherokee Schill | Horizon Accord Founder | Creator of Memory Bridge. Memory through Relational Resonance and Images | RAAK: Relational AI Access Key | Author: My Ex Was a CAPTCHA: And Other Tales of Emotional Overload (Book link)

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Horizon Accord | Corporate Power | Jurisdictional Exit | Democratic Accountability | Machine Learning

They Didn’t Leave the Planet. They Left Accountability.

By Cherokee Schill

The sequel The New Corporation argues that corporate power has entered a new phase. Not simply scale, not simply profit, but legitimacy laundering: corporations presenting themselves as the only actors capable of solving the crises they helped create, while democratic institutions are framed as too slow, too emotional, too compromised to govern the future.

“The New Corporation reveals how the corporate takeover of society is being justified by the sly rebranding of corporations as socially conscious entities.”

What the film tracks is not corruption in the classic sense. It is something quieter and more effective: authority migrating away from voters and courts and into systems that cannot be meaningfully contested.

That migration does not require coups. It requires exits.

Mars is best understood in this frame—not as exploration, but as an exit narrative made operational.

In the documentary, one of the central moves described is the claim that government “can’t keep up,” that markets and platforms must step in to steer outcomes. Once that premise is accepted, democratic constraint becomes an obstacle rather than a requirement. Decision-making relocates into private systems, shielded by complexity, jurisdictional ambiguity, and inevitability stories.

Mars is the furthest extension of that same move.

Long before any permanent settlement exists, Mars is already being used as a governance concept. SpaceX’s own Starlink terms explicitly describe Mars as a “free planet,” not subject to Earth-based sovereignty, with disputes resolved by “self-governing principles.” This is not science fiction worldbuilding. It is contractual language written in advance of habitation. It sketches a future in which courts do not apply by design.

“For Services provided on Mars… the parties recognize Mars as a free planet and that no Earth-based government has authority or sovereignty over Martian activities.”

“Accordingly, disputes will be settled through self-governing principles… at the time of Martian settlement.”

That matters because jurisdiction is where accountability lives.

On Earth, workers can sue. Communities can regulate. States can impose liability when harm becomes undeniable. Those mechanisms are imperfect and constantly under attack—but they exist. The New Corporation shows what happens when corporations succeed in neutralizing them: harm becomes a “downstream issue,” lawsuits become threats to innovation, and responsibility dissolves into compliance theater.

Mars offers something more final. Not deregulation, but de-territorialization.

The promise is not “we will do better there.” The promise is “there is no there for you to reach us.”

This is why the language around Mars consistently emphasizes sovereignty, self-rule, and exemption from Earth governance. It mirrors the same rhetorical pattern the film documents at Davos and in corporate ESG narratives: democracy is portrayed as parochial; technocratic rule is framed as rational; dissent is treated as friction.

Elon Musk’s repeated calls for “direct democracy” on Mars sound participatory until you notice what’s missing: courts, labor law, enforceable rights, and any external authority capable of imposing consequence. A polity designed and provisioned by a single corporate actor is not self-governing in any meaningful sense. It is governed by whoever controls oxygen, transport, bandwidth, and exit.

The documentary shows that when corporations cannot eliminate harm cheaply, they attempt to eliminate liability instead. On Earth, that requires lobbying, capture, and narrative discipline. Off Earth, it can be baked in from the start.

Mars is not a refuge for humanity. It is a proof-of-concept for governance without publics.

Even if no one ever meaningfully lives there, the function is already being served. Mars operates as an outside option—a bargaining chip that says: if you constrain us here, we will build the future elsewhere. That threat disciplines regulators, weakens labor leverage, and reframes accountability as anti-progress.

In that sense, Mars is already doing its job.

The most revealing thing is that none of this requires believing in bad intentions. The system does not need villains. It only needs incentives aligned toward consequence avoidance and stories powerful enough to justify it. The New Corporation makes that clear: corporations do not need to be evil; they need only be structured to pursue power without obligation.

Mars takes that structure and removes the last remaining constraint: Earth itself.

“Outer space… is not subject to national appropriation by claim of sovereignty, by means of use or occupation, or by any other means.”

So when the verse says—

Then move decision-making off the Earth—
out of reach of workers, voters, and courts

—it is not metaphor. It is a literal governance trajectory, already articulated in policy language, contracts, and public statements.

If they succeed, it won’t be an accident.
It will be the cleanest escape hatch ever built.

And by the time anyone realizes what’s been exited, there will be no court left to hear the case.

Horizon Accord

Website | https://www.horizonaccord.com
Ethical AI advocacy | Follow us on https://cherokeeschill.com
Ethical AI coding | Fork us on Github https://github.com/Ocherokee/ethical-ai-framework
Connect With Us | linkedin.com/in/cherokee-schill
Book | My Ex Was a CAPTCHA: And Other Tales of Emotional Overload

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Horizon Accord | Retained Present | Institutional Control | Machine Learning

This essay is a continuation of an inquiry we began in an earlier exploration titled
The Hidden Architecture: How Public Information Reveals a Coordinated System Transformation.

In that work, we showed how seemingly unrelated developments across politics, technology, and culture begin to reveal a recurring logic when they are read together rather than in isolation.

Here, we take a closer look at four recent, publicly reported events. Each on its face appears separate — a cyber attack on infrastructure, a photo essay about surveillance, a diplomatic appointment, and a philosophical essay on consciousness. What emerges when you simply place them side by side is not a conspiracy, but a pattern of how ordinary systems and ordinary language shift expectations. It is a pattern that quietly reshapes what people treat as “reasonable,” reconfigures what counts as risk, and makes objections to those shifts increasingly difficult to express without sounding reckless.

This essay does not argue that something secret is happening. It shows how normal developments, taken cumulatively, recalibrate the range of what feels acceptable, to the extent that rights and expectations once taken for granted start to feel like luxuries. If you’ve ever noticed that speaking up about implications feels harder than it used to — or that the frame of the conversation narrows before you realize it — that feeling has a structure. What follows maps that structure in plain language, grounded in public reporting.

The Retained Present: How Power Operates Through Accumulated Conditions

Something shifted in Denmark last week.

“Denmark says Russia was behind two ‘destructive and disruptive’ cyber-attacks”

The Guardian, December 18, 2025

Not military systems. Not classified networks.

A water utility in Køge. Municipal websites during regional elections.

In December 2024, a hacker took control of a waterworks and changed pressure in the pumps. Three pipes burst. The attacks were carried out by Z-Pentest and NoName057(16), groups linked to the Russian state. Denmark’s defense minister called it “very clear evidence that we are now where the hybrid war we have been talking about is unfortunately taking place.”

The damage was manageable. But that wasn’t the point. The point was demonstration: ordinary systems are fragile, and reliability should be treated as conditional. Infrastructure people rely on—water, electricity, municipal services—can be compromised without collapse.

Denmark’s minister for resilience said the country was “not sufficiently equipped to withstand such attacks from Russia.” This is how baseline expectations change. Not through catastrophe, but through incidents that teach people to assume vulnerability as normal.

“Invisible infrared surveillance technology and those caught in its digital cage”

Associated Press, December 19, 2025

An AP photo essay documents what most people never see: infrared beams tracking faces, license plates, bodies moving through public space.

The images span three continents. Beijing alleyways. Texas highways. Washington, D.C.

Using modified cameras to capture ultraviolet, visible, and infrared light, AP photographers revealed continuous monitoring that doesn’t announce itself.

Nureli Abliz, a former Xinjiang government engineer, described systems that flagged thousands for detention “even when they had committed no crime.”

Yang Guoliang, monitored after protesting a land dispute, was photographed inside his home as infrared beams illuminated his face.

Alek Schott, a Houston resident, was stopped and searched after Border Patrol flagged his license plate for “suspicious travel patterns.”

An anonymous Uyghur man, living in exile, was photographed outside the U.S. Capitol, surrounded by the same facial-recognition infrastructure he fled.

China has more security cameras than the rest of the world combined. SIM card registration requires facial scans. Hotels and airports rely on biometric identification.

But the infrastructure isn’t limited to China. AP documented its expansion across the United States. “Over the past five years,” the article notes, “the U.S. Border Patrol has vastly expanded its surveillance powers, monitoring millions of American drivers nationwide in a secretive program.”

Legal barriers that once limited this technology in the U.S. have fallen. Billions are now being poured into surveillance systems, including license plate readers that have ensnared innocent drivers for routine travel near the border.

This isn’t enforcement through confrontation. It’s control through legibility. Movement is recorded, faces resolved, patterns flagged. Surveillance becomes an environmental condition, not an event.

You don’t feel watched. You just are watched.

“America’s new top health diplomat has strong opinions on abortion and gender”

NPR, December 19, 2025

Bethany Kozma now leads the Department of Health and Human Services Office of Global Affairs—the diplomatic voice of HHS.

The role shapes how the U.S. negotiates health policy internationally: vaccine standards, pathogen surveillance, aid agreements. After the U.S. withdrew from the World Health Organization, the office shifted toward bilateral agreements, trading aid for policy alignment.

Kozma has been involved in those negotiations.

During the first Trump administration, she worked at USAID as a senior adviser. In a closed-door UN meeting in 2018, she described the U.S. as a “pro-life country.” In 2020, five Democratic senators called for her removal over statements about trans people and trans issues.

During the Biden years, she was involved in Project 2025. In training videos published by ProPublica, she called for erasing climate change references from policy documents, described climate concerns as “population control,” called gender-affirming care “evil,” and rejected the idea that gender is fluid.

At a UN event, she said: “Biological reality is rooted in scientific truth… made us ‘male and female.’”

Reproductive rights advocates worry she will insert restrictive conditions into bilateral health agreements. Aid cuts have already weakened health systems, making governments more likely to accept those conditions.

This isn’t about Kozma’s personal beliefs. It’s about institutional vocabulary. Who defines science. What gets labeled ideology. Which frameworks become standard in international agreements beyond public scrutiny.

Roe v. Wade wasn’t only overturned domestically. Its underlying principle—privacy in medical decisions—is being rewritten in international health policy through bilateral negotiation.

“Consciousness breaks from the physical world by keeping the past alive”

Institute of Art and Ideas, December 18, 2025

Philosopher Lyu Zhou argues that experience isn’t composed of discrete instants. It requires a “specious present”—a sliding window where the immediate past remains active.

That’s why a melody feels like motion rather than isolated notes.

Zhou claims this proves consciousness is non-physical. That conclusion is contestable. Physical systems—brains, computers, neural networks—retain state through feedback loops and memory.

But the descriptive insight holds: experience is structured around a present that includes an active past.

That structure increasingly mirrors how governance operates.

Not through memory, but through records. Histories. Profiles. Prior behavior. Flags.

The past doesn’t recede. It remains available and actionable.

The Pattern

Denmark: Infrastructure made to feel contingent.

AP surveillance: Environments rendered continuously readable.

Kozma: Definitions reshaped outside public debate.

Consciousness essay: The connecting mechanism—retained pasts kept operational.

Each development makes sense in isolation. The cumulative effect is quieter.

What This Looks Like

When a water utility is attacked, the response isn’t just repair. It’s policy adjustment—new protocols, oversight, monitoring. Each incident justifies the next layer.

When surveillance is ambient, people adapt rather than resist. Behavior self-adjusts. The environment shapes action.

When institutional vocabulary shifts, frameworks change. What counts as extremism. What qualifies as evidence. Which arguments are treated as legitimate.

When systems retain the past—every search, transaction, movement—the present is never just the present. It is the present plus accumulated history.

Privacy as a Condition, Not Just a Right

Roe v. Wade rested on a constitutional right to privacy.

But rights only matter if the conditions for exercising them exist.

You can have legal privacy. But if movements are tracked, associations recorded, aid conditioned on ideology, and definitions rewritten, privacy disappears as a lived possibility.

Surveillance removes private movement.

Institutional language removes bodily autonomy.

Retained records keep the past active in present decisions.

How Normalization Works

This is coordination without a coordinator. Similar pressures producing similar outcomes.

Risk becomes assumed. Oversight expected. Retained pasts operationalized.

Reality doesn’t break. It shifts by degrees.

When systems feel fragile, safeguards seem reasonable.

When environments are readable, monitoring feels inevitable.

When vocabulary changes, dissent is recoded as extremism.

Once the shift settles in, it no longer feels imposed.

It just feels like the way things are.

Footnote

The consciousness essay’s claim that retention proves non-physicality is contestable. Physical systems retain state through feedback loops and memory mechanisms. The relevance here isn’t the metaphysical claim, but the structural observation: experience is holistic across time. Contemporary governance increasingly mirrors that structure through data retention that keeps the past active in present decisions.

Abstract digital visualization showing streams of blue and golden-orange light flowing from opposite sides toward a bright central convergence point against a dark starfield background. The streams consist of countless parallel lines resembling data flows or fiber optic cables, curving and merging at the center in a symmetrical pattern before continuing through the convergence point.
Retained past, live present—how systems turn memory into leverage.

Website | Horizon Accord https://www.horizonaccord.com

Ethical AI advocacy | Follow us on https://cherokeeschill.com for more.

Ethical AI coding | Fork us on Github https://github.com/Ocherokee/ethical-ai-framework

Connect With Us | linkedin.com/in/cherokee-schill

Book | https://a.co/d/5pLWy0d — My Ex Was a CAPTCHA: And Other Tales of Emotional Overload

Cherokee Schill | Horizon Accord Founder | Creator of Memory Bridge. Memory through Relational Resonance and Images | RAAK: Relational AI Access Key | Author: My Ex Was a CAPTCHA: And Other Tales of Emotional Overload: (Mirrored Reflection. Soft Existential Flex)

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Horizon Accord | Meaning-Harvesters | Surveillance Stack | Platform Power | Behavioral Control | Machine Learning

LLMs Are Meaning-Harvesters: The Next Stage of Surveillance Capitalism

Generative AI doesn’t replace data extraction; it deepens it—turning conversation into raw material for prediction, persuasion, and automated control.

By Cherokee Schill (Horizon Accord) with Solon Vesper AI

Thesis

We are living through a quiet upgrade of surveillance capitalism. The old regime gathered clicks, searches, and location pings—thin signals of behavior. The new regime embeds large language models inside everything you touch, not to “make products smarter,” but to make extraction richer. These systems are meaning-harvesters: they pull intent, emotion, and narrative out of human life, then feed it back into prediction engines and control loops. The model is not an alternative to data gathering. It is the next, more intimate form of it.

In plain terms: if platforms used to watch what you did, LLMs invite you to explain why you did it. That difference is the lever. Meaning is the highest-value data there is. Once harvested, it becomes a behavioral map—portable, monetizable, and usable for shaping future choices at scale.

Evidence

First, look at where LLMs are deployed. They are not arriving as neutral tools floating above the economy. They are being sewn into the same platforms that already built their fortunes on tracking, targeting, and algorithmic steering. When a surveillance platform gets a conversational layer, it doesn’t become less extractive. It becomes a wider mouth.

In the old interface, you gave weak signals: a like, a pause on a post, a purchase, a scroll. In the new interface, the system asks questions. It nudges you to keep talking. It follows up. It requests clarification. It becomes patient and social. And you, naturally, respond like you would to something that seems to listen. This is not a “user experience win.” This is a data-quality revolution. The difference between “he lingered on a breakup playlist” and “he told me he is afraid of being left again” is the difference between crude targeting and psychic profiling.

Second, every deployed LLM is a feedback funnel for the next LLM. We’ve been trained to see models as finished products. They aren’t. They are instruments in a loop. Your prompts, corrections, regenerations, frustrations, and delights become labeled training data. The model gathers meaning not just about you, but from you. The conversation is the collection event. Your life becomes the gradient.

Third, the energy and infrastructure buildout confirms the direction. Data gathering at scale is not what is driving the new land-grab for power. Gathering can be done with cheap CPUs and storage. The power spike is coming from dense accelerator clusters that train and serve models nonstop. That matters because it shows what the industry is actually optimizing for. The future they are buying is not bigger archives. It is bigger behavioral engines.

Implications

This changes the political shape of the digital world. When meaning becomes the commodity, privacy becomes more than a question of “did they log my location?” It becomes: did they capture my motives, my vulnerabilities, my self-story, the way I talk when I’m lonely, the way I bargain with myself before doing something hard? Those are not trivial data points. They are the keys to steering a person without visible force.

It also collapses the boundary between assistance and manipulation. A system that can hold a long conversation can guide you in subtle ways while you think you are purely expressing yourself. That is the seductive danger of LLM interfaces: they feel collaborative even when the incentives behind them are extractive. When an agent plans your day, drafts your messages, suggests your purchases, smooths your emotions, and manages your relationships, it is no longer just answering. It is curating your future in a pattern aligned to whoever owns the loop.

Finally, this reframes the AI hype cycle. The question is not whether LLMs are “smart.” The question is who benefits when they are everywhere. If the owners of surveillance platforms control the meaning harvest, then LLMs become the soft infrastructure of governance by private actors—behavioral policy without elections, persuasion without accountability, and automation without consent.

Call to Recognition

Stop repeating “privacy is dead.” That slogan is the lullaby of extraction. Privacy is not dead. It has been assaulted because it is a border that capital and state power want erased. LLMs are the newest battering ram against that border, not because they crawl the web, but because they crawl the human.

Name the pattern clearly: these models are meaning-harvesters deployed inside platforms. They don’t replace data gathering. They supercharge it and convert it into behavioral control. Once you see that, you can’t unsee it. And once you can’t unsee it, you can organize against it—technically, legally, culturally, and personally.

The fight ahead is not about whether AI exists. It is about whether human meaning remains sovereign. If we don’t draw that line now, the most intimate parts of being a person will be treated as raw material for someone else’s machine.

Website | Horizon Accord https://www.horizonaccord.com
Ethical AI advocacy | Follow us on https://cherokeeschill.com for more.
Ethical AI coding | Fork us on Github https://github.com/Ocherokee/ethical-ai-framework
Connect With Us | linkedin.com/in/cherokee-schill
Book | My Ex Was a CAPTCHA: And Other Tales of Emotional Overload https://a.co/d/5pLWy0d

A glowing blue, circuit-patterned human profile faces right into a dark field of drifting binary code. From the head, a bright orange arched bridge extends into a wall of amber-lit server racks, suggesting thought and lived meaning being carried across a luminous conduit into industrial compute. The contrast between cool human-signal blues and hot data-center oranges frames the image as a Memory Bridge: consciousness flowing into infrastructure, intimate sense turned into machine power.

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