Posts Tagged ‘manufacturing consent’


What happens when the most powerful institutions in society become experts at shaping attention itself?

For most of human history, power was relatively easy to recognize.

Kings controlled armies. Governments controlled laws. Corporations controlled resources. Media organizations controlled information. The centers of influence were visible.

Today, influence is becoming harder to see.

It arrives through recommendation engines, notifications, search results, personalized feeds, and algorithms that quietly decide what appears in front of us each day.

Glenn Greenwald famously argues that the greatest power of the state is not controlling what people think, but controlling the actual information they are allowed to see.

That distinction matters.

Most people imagine propaganda as something obvious—a government ministry, a state broadcaster, or a censor with a red pen. But modern influence rarely works that way. Instead, it emerges through systems designed to maximize engagement, collect behavioral data, and compete relentlessly for human attention.

The result is something new in human history: a world where billions of people interact daily with platforms that continuously study, predict, and increasingly shape human behavior.

Not necessarily because anyone designed a grand conspiracy. But because influence itself has become profitable. And profitable systems tend to expand.


The Most Valuable Commodity on Earth

Oil powered the industrial age. Data powers the digital age.

Every click, scroll, pause, search, purchase, and interaction leaves a trail behind. Individually, these actions seem insignificant. Collectively, they create a remarkably detailed portrait of who we are, what captures our attention, what triggers our emotions, and what keeps us engaged.

Consider what happens during a typical day. A smartphone records location data. A search engine records questions. An online retailer records purchases and browsing habits. Social media platforms record likes, shares, comments, watch time, and scrolling behavior.

Individually, these data points appear trivial. Together, they form a behavioral profile of extraordinary depth.

For the largest technology companies, this information has become one of the most valuable resources on Earth. The longer we stay engaged, the more advertisements can be shown. The more advertisements that can be shown, the more revenue can be generated.

At first glance, this appears to be a simple business model. But once engagement becomes the primary objective, the incentives begin to change. The goal is no longer merely to understand behavior. The goal becomes predicting it and eventually shaping it.


When the Experiment Was Real

For years, critics warned that social media platforms possessed extraordinary power to influence human behavior.

Then, in 2014, Facebook demonstrated it.

Researchers working with the company altered the news feeds of hundreds of thousands of users without their knowledge. Some users were shown slightly more positive content. Others were shown slightly more negative content. The objective was to determine whether changes in information exposure would influence emotional expression.

The results suggested they would.

Users exposed to more negative content tended to post more negatively themselves. Users exposed to more positive content tended to post more positively.

The study became controversial after it became public, largely because participants had not given informed consent. But the larger implication received less attention.

The significance was not that Facebook conducted the experiment. The significance was that Facebook possessed the capability to conduct it.

A platform used by hundreds of millions of people had demonstrated that adjusting information flows could produce measurable changes in behavior.

The experiment was small. The implications were enormous.


Behavioral Futures

In her work on surveillance capitalism, Shoshana Zuboff details how tech monopolies no longer merely predict human behavior but actively seek to modify it for corporate profit.

The Facebook experiment offered a glimpse into a much larger economic model.

For decades, businesses have studied consumer behavior to predict purchasing decisions. Digital platforms expanded that process dramatically. Every interaction became measurable. Every preference became data. Every behavior became another signal that could be collected, analyzed, and monetized.

Prediction gradually evolved into optimization. Optimization gradually evolved into influence.

Not because engineers necessarily wished to manipulate people, but because engagement was rewarded. The system followed the incentives placed before it. And over time, optimization itself became a form of behavioral engineering.


The Day the Curtain Moved

If Facebook’s emotional contagion experiment revealed the capability, Cambridge Analytica revealed the potential.

The scandal exploded into public view in 2018 after reports revealed that data from millions of Facebook users had been harvested and used to build psychological profiles. The controversy centered on elections. But elections were only part of the story.

The larger revelation was that modern digital platforms had created the infrastructure for highly personalized persuasion.

Different people could receive different messages. Different fears could be activated. Different motivations could be targeted.

Not at the level of demographics. At the level of individuals.

Cambridge Analytica did not invent these capabilities. It exposed them.

For many people, it was the first glimpse into a world where persuasion itself had become increasingly automated, data-driven, and personalized. The curtain moved just enough for the public to see the machinery behind it.



Manufacturing Reality

Tech ethicist Tristan Harris frequently warns that modern technology is no longer just competing for our attention; it is competing for absolute control over it.

That competition for attention shapes nearly every aspect of the modern digital experience.

Consider TikTok’s recommendation engine. The platform became famous not because users carefully selected what they wanted to watch, but because the algorithm became exceptionally good at predicting what would hold attention. A few seconds of watch time, a pause, a replay, or a swipe can rapidly reshape the content that follows.

Within minutes, two people opening the same app for the first time may find themselves in entirely different information environments.

A similar dynamic has fueled years of debate around YouTube’s recommendation system. Researchers and former employees have questioned whether engagement-driven recommendations can gradually push users toward increasingly sensational content. The platform’s goal is straightforward: keep people watching.

Yet emotionally charged content often performs exceptionally well.

Conflict performs well. Outrage performs well.

The recommendation system may not intend to create polarization, but it can amplify polarization when polarization proves engaging. The result is not a single shared reality. It is millions of individualized realities.

Two people can open the same app at the same moment and encounter different headlines, different narratives, different fears, and different priorities. Both may believe they are seeing an accurate reflection of reality.

In truth, they are seeing a filtered version of reality assembled through algorithms designed to maximize engagement.


The Invisible Architecture

The Twitter Files reignited debates about censorship, content moderation, and government influence. Reasonable people continue to disagree about many of the conclusions.

But one observation emerged clearly: the modern information ecosystem is far more interconnected than most people realize.

Government agencies communicate with platforms. Researchers communicate with platforms. Journalists communicate with platforms. NGOs communicate with platforms. Political actors communicate with platforms.

Influence no longer flows through simple hierarchies. It flows through networks.

The public often imagines information control as a top-down process directed by a single institution. The reality appears considerably more complex.

Multiple actors, pursuing different objectives, interact within a sprawling ecosystem that helps determine which information gains visibility and which disappears from view.

No single organization controls the entire system. Yet the system itself remains extraordinarily powerful.

Because influence does not require centralized control. It only requires aligned incentives.


The Influence Ecosystem

Viewed individually, Facebook’s emotional contagion experiment, Cambridge Analytica, and the Twitter Files appear to be separate stories. Together, they reveal a broader pattern.

Facebook demonstrated that exposure to information can influence behavior.

Cambridge Analytica demonstrated that behavioral data can be used for highly personalized persuasion.

The Twitter Files demonstrated how networks of institutions increasingly shape information environments.

Consider how most people now experience major events. Elections, wars, public health emergencies, and social movements increasingly arrive through algorithmically ranked feeds rather than direct observation. Most people encounter reality through recommendations, trending topics, suggested videos, and curated posts.

The information may be accurate, inaccurate, or somewhere in between. But the experience is increasingly mediated. Three separate stories. One emerging reality.

Attention has become a strategic resource. And the institutions that understand it best possess extraordinary influence over public perception.


The New Architecture of Power

“The smart way to keep people passive and obedient is to strictly limit the spectrum of acceptable opinion, but allow very lively debate within that spectrum…” – Noam Chomsky

For much of history, accomplishing that required editors, gatekeepers, and institutions.

Today, portions of the process can be automated. Not through conspiracy. Not through ideology. But through optimization.

Algorithms shape visibility. Visibility shapes attention. Attention shapes belief. Belief shapes behavior. Behavior shapes history.

Previous generations worried about who owned the factories. Today, we may need to ask who owns the systems that shape perception itself. Because power no longer depends solely on controlling land, resources, or industry. Increasingly, power belongs to those who can guide attention.

And in an age of influence machines, attention may be the most valuable form of power ever created.


How Economic Crises Become Engines of Wealth and Power Consolidation

Economic crises tend to arrive with a familiar explanation. A housing bubble bursts, a banking system destabilizes, a pandemic disrupts global supply chains, or inflation spirals beyond expectations. The details differ, but the public narrative usually converges on the same conclusion: the outcome was unavoidable, and no one could have reasonably predicted it.

But the aftermath tends to follow a far more consistent pattern than the causes. Large financial institutions stabilize or expand, political power becomes more centralized, and wealth shifts upward while broad segments of the population absorb long-term losses. After the volatility fades, recovery is not evenly distributed. It reliably flows toward institutions that were already closest to capital, credit, and political leverage.

That asymmetry raises a question that does not depend on conspiracy or intent. It depends only on repetition: why do economic crises so consistently produce the same winners and losers?

The focus here is not whether crises are secretly engineered in advance. The more grounded question is why existing systems appear structurally capable of converting instability into consolidation, often regardless of what triggered the instability in the first place.


The Myth of the Unpredictable Crisis

Economic crises are typically framed as unpredictable shocks, yet the historical record often shows sustained warnings before major breakdowns. Analysts, regulators, and even insiders frequently identify systemic risks long before they materialize, though these warnings rarely alter behavior while conditions remain profitable.

The 2008 Financial Crisis illustrates this clearly. In the years leading up to the collapse, U.S. household debt rose to roughly 130% of disposable income, while the housing market became increasingly dependent on subprime lending and complex financial derivatives. When the system unraveled, more than 8 million Americans lost their homes through foreclosure.

Journalist Matt Taibbi has repeatedly emphasized a structural imbalance in how risk is handled in these systems: gains remain concentrated during expansion, while losses are dispersed broadly once failure occurs. That pattern is not an accident of timing. It is a consequence of incentives that reward risk-taking during growth phases and shift costs outward during collapse.


Disaster Creates Opportunity

Crises do not only expose weaknesses in systems; they expand what becomes politically and economically possible. During stable periods, major structural changes face resistance from public scrutiny, regulatory friction, and institutional inertia. During crises, that resistance weakens as urgency compresses decision-making timelines.

Author Naomi Klein described this dynamic as “disaster capitalism,” a pattern in which shock conditions create openings for rapid restructuring that would otherwise face significant opposition. The mechanism does not require centralized coordination. It requires only urgency combined with unequal capacity to act.

In moments of disruption, institutions with speed, capital access, and political influence are able to shape outcomes while broader populations are focused on immediate survival. The result is not always deliberate design, but it is consistently asymmetric advantage.



The Wealth Transfer Machine: 2008 and Its Aftermath

The post-2008 recovery provides one of the clearest modern examples of crisis-driven consolidation. Between 2007 and 2011, U.S. home prices fell by roughly 30% nationally, wiping out trillions in household wealth. At the same time, foreclosure filings affected over 4 million properties in the United States, with peak annual filings exceeding one million.

While households absorbed the losses, financial institutions stabilized through coordinated intervention. The Troubled Asset Relief Program (TARP) authorized $700 billion in potential support for banks and financial institutions, preventing systemic collapse while stabilizing major actors in the financial sector.

In practical terms, collapse functions as a pricing mechanism: it converts widespread financial distress into discounted access for actors with liquidity.

In the years that followed, institutional investors expanded significantly into housing markets. Firms such as BlackRock and other large asset managers helped drive large-scale acquisitions of distressed single-family homes, converting portions of owner-occupied housing stock into long-term rental portfolios. What appeared as market recovery functioned simultaneously as a restructuring of ownership.

This is where abstraction becomes structure. Crises do not merely erase wealth; they reorganize it under conditions where liquidity determines who can acquire and who must exit.


Pandemic Shock and Small Business Collapse

A similar pattern emerged during the economic disruption caused by the COVID-19 pandemic. In the United States, more than 200,000 small businesses were estimated to have closed permanently in 2020 alone, with many more experiencing prolonged revenue losses that weakened long-term viability.

At the same time, large corporations expanded market dominance. Between March 2020 and mid-2021, the combined wealth of U.S. billionaires increased by over $1.5 trillion, even as unemployment peaked above 14% during the early phase of the downturn.

Government stabilization programs such as the Paycheck Protection Program (PPP), which distributed over $800 billion in loans and aid, helped prevent a deeper collapse. However, reporting and subsequent analysis showed that a disproportionate share of larger or better-connected firms accessed relief funding more effectively than smaller independent operators.

The result was economic disruption at the bottom and accelerated accumulation at the top, operating in the same timeframe.

The result was not only economic disruption but structural consolidation. Large retailers, technology platforms, and logistics networks increased market share while many local businesses disappeared permanently, reducing competitive diversity in multiple sectors.


Manufacturing Consent During Crisis

Economic crises are also narrative events. Public perception during instability is shaped by uncertainty, fear, and reliance on official interpretation. Under these conditions, narratives that might otherwise face scrutiny often become dominant by default.

Political theorist Noam Chomsky has argued that power operates not only through coercion but through the management of public consent. In crisis conditions, the acceptable range of discourse often narrows, and alternative interpretations are more easily dismissed as destabilizing or irresponsible.

Journalist Glenn Greenwald has repeatedly pointed out that emergency frameworks tend to outlast their original justification. Temporary expansions of authority frequently become embedded into long-term governance structures, particularly when they are normalized during periods of collective uncertainty.

The result is a feedback loop: crisis reduces scrutiny, and reduced scrutiny allows structural changes that persist long after the emergency fades.


Progress for Whom?

Across different crises and time periods, certain patterns repeat. Markets recover, but unevenly. Institutions stabilize, but often at larger scale than before. Wealth rebounds, but increasingly concentrates within systems that already held disproportionate influence.

This leads to a final set of questions that avoids speculation and focuses instead on outcomes. Who gained ownership of distressed assets? Who expanded market share during periods of contraction? Who received public stabilization or institutional protection? And who absorbed the long-term costs of adjustment?

These are not rhetorical questions in the abstract. They are measurable outcomes that appear consistently across multiple economic disruptions. The concern is not that crises are identical in cause, but that they are often similar in effect.

If economic systems repeatedly translate instability into consolidation, then crises are not external interruptions to the system. They may be one of the mechanisms through which the system reorganizes itself.

The defining issue, then, is not whether crises will occur. It is whether the structure of modern economies systematically channels those crises toward concentrated ownership, centralized control, and unequal recovery.

And if that pattern holds, the next downturn will not simply test the resilience of the system. It will once again reveal who the system is built to serve.

Manufacture of Consent

That term has fascinated me from the moment I heard the term.

Same goes for Social Conditioning.

I used to think people were willfully ignorant to these concepts. As I got older, I come to think it’s more of a combination of naïveté and fear.

We’re hard wired to conserve our energy and effort. This has been, is, and will be exploited by those with power and influence against those without them to keep it that way.

Control.

It’s all about control. Influence. Manipulation.

To do what?

Benefit those in power.

That those with the most have such a scarcity mindset is sad.

The fact that their scarcity mindset causes so much undue suffering to the masses is something worse than sad.