HXRDNOTES

Exploring alternatives to big‑tech and why non‑business structures matter

Quick recap of Part 1

If you missed the first installment, you can read it here:
Who Owns Our Conversations: Testing the Fediverse

In Part 1 we examined the Fediverse as a decentralized counter‑weight to the mainstream social web. In this sequel we turn our attention to services that start as small projects or startups and later get absorbed by large corporations. Those acquisitions often rewrite the service’s original promise, turning a privacy‑first offering into a profit‑driven machine. The pattern leaves users scrambling for trustworthy alternatives that stay true to the values that attracted them in the first place.

When “small” becomes “big”

Many of the platforms we rely on daily began as modest ventures hoping to give users a better experience. After gaining traction, they attracted the attention of big tech, which bought them out or forced a strategic partnership. The result is usually threefold:

  1. Values shift – promises like “no ads” or “no data selling” disappear or become heavily qualified.
  2. Monetisation pressure – the new owners look for ways to monetise the user base (ads, data licensing, AI training, or cross‑selling other products).
  3. Feature creep – new features are introduced that serve the parent company’s ecosystem rather than the user’s needs.

These dynamics create a vacuum: users who care about privacy, transparency, or independence start looking for services that are structurally insulated from such pressures.

The structural difference: non‑business & hybrid models vs business

A non‑profit foundation or a foundation‑backed hybrid company can act as a firewall against hostile takeovers and profit‑centric pivots. The key idea is that the entity that owns the service does not answer to shareholders demanding ever‑higher growth rates. Instead, its mission is codified in a charter or bylaws that prioritise user rights, privacy, and long‑term sustainability.

Because the governing body’s incentives differ, the technical and policy choices it makes tend to stay aligned with the original promise:

  • Funding comes from donations, grants, or a modest paid tier rather than advertising revenue.
  • Roadmaps are publicly discussed and often include community input, reducing the chance of sudden, user‑unfriendly changes.
  • Legal structures (foundations, cooperatives, or non‑profits) make it considerably harder for a venture‑capital‑backed acquirer to simply buy the service and flip its policies overnight.

Below are two separate tables that illustrate how this structural difference plays out in practice for messaging and email services.

Messenger comparison

Feature Signal WhatsApp iMessage Telegram
Ownership model Non‑profit foundation (Signal Foundation) Subsidiary of Meta Platforms, Inc. Proprietary service owned by Apple Inc. Private company (Telegram Messenger LLP)
Core privacy claim End‑to‑end encryption + zero‑knowledge architecture – the service never sees plaintext End‑to‑end encryption for one‑to‑one chats, but metadata is stored on Meta’s servers; group chats are not E2EE by default End‑to‑end encryption only for iMessage (Apple‑to‑Apple); SMS fallback is unencrypted Server‑client encryption (MTProto); optional “Secret Chats” with E2EE, but most chats are stored in the cloud
How the model protects users No shareholders; funding via donations keeps the product free and focused on privacy Meta’s ad‑driven business model incentivises data collection and integration with its broader advertising ecosystem Apple’s ecosystem limits data sharing, but the service is tied to a single hardware vendor and can be subject to court orders in jurisdictions where Apple complies Telegram’s revenue comes from optional premium features; the company has historically resisted providing data to governments, but the default cloud storage means the provider could access content if compelled

Key advantage of Signal: because it is run by a non‑profit foundation, there is no pressure to introduce advertising, data‑licensing, or feature bloat that would compromise its privacy‑first stance. Its funding model (donations and grants) aligns directly with the mission of keeping communications private for everyone.

Email comparison

Feature Proton Mail Gmail Outlook.com Yahoo Mail
Ownership model Hybrid: Proton Foundation (non‑profit) + commercial arm for paid plans Subsidiary of Alphabet Inc. (public corporation) Subsidiary of Microsoft Corp. (public corporation) Subsidiary of Verizon Media (public corporation)
Core privacy claim End‑to‑end encryption + zero‑knowledge storage – Proton cannot read your emails Transport‑level TLS encryption; emails are stored in cleartext on Google’s servers and can be processed for AI features (e.g., Smart Compose) TLS encryption in transit; emails stored in cleartext on Microsoft’s servers; data used for personalised services TLS encryption in transit; emails stored in cleartext; data used for advertising and personalization
How the model protects users The foundation’s charter forbids data mining; paid plans fund the free tier while preserving privacy Google’s business model relies on data aggregation; while ads are no longer based on email content, the service still powers AI models that learn from the corpus Microsoft integrates email data with its broader Graph ecosystem, enabling targeted services and ads for free accounts Yahoo leverages email data for ad targeting and sells aggregated insights to third parties

Key advantage of Proton Mail: the Proton Foundation’s mission‑driven charter prevents the service from mining email content for advertising or AI training. Even though a commercial arm offers paid plans, the revenue stays within the ecosystem and does not alter the core privacy guarantees.

Why the technical details matter, even if you don’t notice them

  • End‑to‑end encryption (E2EE) – Messages are encrypted on the sender’s device and can only be decrypted on the recipient’s device. The provider never holds the decryption keys, which means a court order or a data breach cannot expose the plaintext.
  • Zero‑knowledge architecture – The service stores only ciphertext. Because it never possesses the keys, it cannot read, sell, or repurpose your data, even if compelled by law.
  • No data‑selling pipelines – Without access to plaintext, a provider cannot build detailed user profiles for advertising or sell data to third parties.

If you want a deeper dive into how encryption works and why it matters, the Electronic Frontier Foundation offers an excellent primer: https://ssd.eff.org/module/what-should-i-know-about-encryption#end-to-end-encryption.

Advertising, data mining, and government requests

  • Advertising & data mining – Gmail and Outlook do not scan email content to serve personalised ads (Google stopped that practice for free accounts in 2017). However, both services analyse metadata and content to power AI‑driven features such as Smart Compose, spam filtering, and predictive search. Those analyses can be leveraged for product improvements and, indirectly, for advertising ecosystems.
  • Government requests – In many jurisdictions, authorities can subpoena email metadata or, in some cases, request content. With end‑to‑end encryption, even a valid court order yields only metadata, not the message bodies. Services that lack E2EE (e.g., standard Gmail or Outlook) can be forced to hand over the actual content, sometimes years after the communication took place. This risk is especially acute for journalists, activists, and anyone living under authoritarian regimes where the definition of “national security” can shift dramatically.

Having a service that implements both E2EE and zero‑knowledge storage therefore provides a future‑proof safeguard: even if the legal environment changes, the provider simply does not have the ability to comply with a request for the plaintext.

Owning the conversation

Owning the conversation is not about finding the perfect app or the purest platform. It is about understanding the structures behind the tools we use and being honest about the trade-offs we accept when we use them. Convenience is never neutral, and neither is scale.

Decentralization, foundations, and open protocols are not guarantees of freedom, but they do something essential: they slow down the moment where incentives quietly change. They introduce friction where power would otherwise concentrate unnoticed. That friction matters.

The question, then, is not whether a service encrypts messages or publishes a transparency report. The real question is who can change the rules tomorrow, and under what pressure. Growth, investors, geopolitics, and regulation all shape those answers long after the onboarding screen fades away.

We often talk about speech as if it exists independently of infrastructure. It doesn’t. Conversations live inside systems, and systems always have owners — legal, economic, or political. Choosing where we speak is, whether we like it or not, choosing who ultimately has leverage over that space.

Knowing who owns the conversation is the first step in deciding how much of ourselves we’re willing to share and how much we want to keep, and how we’ll protect it.

HXRDNOTES © 2025 by HXRDKING is licensed under CC BY-NC 4.0

Happy face from Pluribus

Introduction

Happiness, as we experience it individually, depends on distance.
Suffering exists, but it belongs to others. Even empathy has limits. You can recognize injustice, feel compassion, even guilt, and still preserve your joy because your consciousness is not fused with the consciousness of those who suffer. You can still say, honestly and without contradiction:

“This is tragic, but it is not me.”

That distance is not cruelty—it is structural. It is what allows an individual mind to function at all.

The Hive‑Mind Thought Experiment

The Collapse of Separation

A true hive mind eliminates that structure. When consciousness becomes collective, separation collapses. There is no moral outsourcing.

  • The memory of a mother who lost her child to malnutrition is no longer “someone else’s story.”
  • It is the same consciousness that remembers a first‑anniversary dinner, the warmth of candlelight, the taste of wine.

Joy and horror are no longer parallel experiences held by different people. They coexist within the same subject, at the same ontological level.

Consequences for Happiness

Under these conditions, happiness cannot survive in its ordinary form. It cannot be naive, private, or insulated. The pleasure of excess becomes inseparable from the knowledge of deprivation:

  • The taste of an expensive meal is felt alongside the hunger that could have been prevented.
  • Not as a comparison, not as abstract awareness, but as a simultaneous experience.

Joy becomes heavy, morally charged, and contaminated by everything it now includes.

Three Possible Outcomes

1. Redefinition

Happiness is no longer pleasure, delight, or emotional lightness. It becomes something colder and more abstract:

  • Equilibrium
  • Acceptance
  • Absence of unresolved injustice

In this version, the hive mind is “happy” only because it has eliminated the conditions that make happiness impossible. It is not joy as we know it, but stability after moral debt has been paid.

2. Dilution

Suffering is not erased, but averaged. Individual pain loses its sharpness when spread across a collective consciousness. This allows the system to remain functional, but at a cost:

  • Tragedy becomes data.
  • Grief becomes background noise.

Happiness, in this sense, is stable—but arguably inhuman.

3. Deception

Happiness becomes a narrative the hive mind tells itself to justify its existence. What appears as serenity is actually:

  • Numbness
  • Resignation

The quiet that follows when meaning has been flattened enough to stop resisting.

The Core Paradox

A perfectly unified consciousness with perfect memory should not be capable of uncomplicated joy. If it still claims to be happy, something essential has been sacrificed—moral sensitivity, emotional intensity, or the very concept of happiness itself.

Conclusion

True happiness might depend on certain conditions or states of being. One possibility is that ignorance plays a role, suggesting that a lack of awareness or knowledge about certain harsh realities or complexities of life could lead to a more content and joyful existence. Another potential factor is distance, which could imply that being physically or emotionally removed from distressing situations or overwhelming information allows for a sense of peace and happiness. Additionally, individuality might be crucial, indicating that embracing one’s unique identity and personal experiences contributes to a fulfilling and happy life.

On the other hand, a mind that is fully aware and sensitive to everything around it might struggle to find happiness. Instead of achieving happiness, such a mind could attain a state of completeness, where it encompasses all knowledge and emotions without being hindered by the pursuit of happiness. This completeness suggests a profound understanding and acceptance of life in its entirety, which, while not synonymous with happiness, offers a different kind of fulfillment.

HXRDNOTES © 2025 by HXRDKING is licensed under CC BY-NC 4.0

I first heard about the Fediverse years ago, around the same time I started looking for alternatives to the dominant social media platforms. At that point, my interest wasn’t ideological yet. I was simply feeling that something about how social media worked no longer matched what it originally promised.

In theory, the internet — and later social media — was created to help people connect. You could share photos, write updates, stay in touch with friends and family, and participate in conversations across long distances. Over time, however, that vision slowly changed. Not because connection became impossible, but because the economic structure behind most platforms reshaped how connection works.

The Business Model Behind Social Media

Running a global social media platform requires massive infrastructure, constant development, and enormous technical maintenance. All of this is expensive. Because of that, most large platforms adopted advertising as their main business model.

Users do not pay directly for the service. Instead, companies pay to reach users. In practice, this means the real product is not the platform itself — it is the users’ attention.

At first, this model helped major networks grow at unprecedented speed. Facebook, for example, expanded rapidly and acquired competing platforms like Instagram in 2012 and WhatsApp in 2014.

As these platforms grew, so did their influence. With billions of users, even small design decisions now shape how entire societies communicate, share information, argue, organize, and form opinions.

Public corporations are structurally rewarded for one thing above all else: continuous growth. Executives are judged primarily on whether the company grows year after year. Even when products begin with good intentions, they are gradually reshaped by financial incentives.

Growth becomes the goal.

Algorithms, Engagement, and Polarization

Modern social platforms rely heavily on recommendation algorithms designed to maximize time spent, reactions, and interactions. Research consistently shows that emotionally charged, controversial, and polarizing content generates higher engagement than calm, balanced discussion.

Over time, this creates powerful feedback loops:

  1. Content that provokes outrage spreads faster
  2. Content that simplifies complex issues into extremes spreads faster
  3. Content that invites slow, thoughtful discussion struggles to compete

As a result, much of what dominates social media today is optimized not for understanding, but for reaction.

Echo Chambers and the Loss of Dialogue

This system contributes to what are commonly called echo chambers.

An echo chamber forms when people are repeatedly exposed to the same viewpoints while alternative perspectives are filtered out. Algorithms amplify this effect by showing users more of what aligns with their past behavior.

Research shows that these environments increase polarization, reduce openness to opposing perspectives, and strengthen confirmation bias.

The danger here is subtle. When people only see opinions that reflect their own, they may begin to confuse agreement with truth and popularity with correctness. Disagreement slowly disappears — not because it no longer exists, but because the system hides it.

In these spaces, debate is no longer about understanding. It becomes about defending identity. Disagreement turns into hostility. And critical thinking weakens.

Respectful debate and open communication are essential for a healthy society. Disagreement itself is not the problem. The problem arises when systems reward hostility over dialogue, certainty over curiosity, and performance over understanding.

When platforms reward engagement above all else, people are subtly encouraged to protect their bias instead of challenging it.

Discovering the Fediverse

It is from within this context that decentralized alternatives like the Fediverse begin to make sense.

The Fediverse is not a single platform. It is a network of independent servers that communicate with one another using shared protocols. Instead of one company owning the entire system, thousands of communities host their own services while still remaining connected.

This structure allows people to choose:

  • Where their data lives
  • Who defines moderation rules
  • What community values they want to participate in
  • Whether they trust a nonprofit, a cooperative, a local group, or themselves to host their space

Unlike traditional platforms, many Fediverse projects operate as nonprofits or community-run services. Without shareholders demanding endless growth, there is far less pressure to manipulate attention at scale.

Limits and Reality of Decentralization

This does not mean the Fediverse is perfect.

Decentralization introduces real challenges:

  • Fragmented moderation
  • Uneven funding
  • Technical complexity
  • Varied server stability
  • A learning curve for new users

Some of the same social problems still exist, simply in different forms.

But the most important difference is structural. The Fediverse was not built around advertising as its core economic engine. That alone changes what the system is fundamentally optimized for.

My Personal Exploration

Personally, I am still learning. I do not yet understand all the technical, social, and political implications of federated systems. I began by testing platforms like Mastodon and Bluesky and slowly discovered that a much larger ecosystem existed behind them — including blogging platforms like this one.

Some services require payment. Some are invite-only. Some are fully open. I ended up here simply because this space allowed me to register and write freely.

I do not believe social media itself is evil. Tools are neutral until incentives shape how they are used. The real problem emerges when harmful behavior becomes algorithmically profitable, when outrage turns into currency, and when control over public conversation becomes economically centralized.

Reflection Point

  1. How do different technical and economic models shape the way online communication evolves over time?

  2. What trade-offs exist between convenience, scale, independence, and control in digital platforms?

  3. How might the structure of a platform influence not only what we see, but how we think, interact, and express ourselves?

Facebook’s early growth and acquisitions

Research on engagement-driven algorithms and polarization

Study on echo chambers and polarization

Research on the structure and limits of the fediverse

Overview of how the fediverse works

Analysis of the Fediverse decentralization

HXRDNOTES © 2025 by HXRDKING is licensed under CC BY-NC 4.0