Tag: socialmedia

The expertise problem

Technical expertise matters, the problem begins when technical expertise is treated as the only legitimate way of understanding a social problem. This is the trap of technocracy: taking a useful tool for understanding parts of the world and turning it into a complete worldview. The expertise problem “We need more technical expertise in government.” But that is half the answer. The mistake is to jump from “politicians need technical expertise” to “technical experts should make decisions.” That replaces one form of stupidity with another.

A functioning society needs engineers, scientists, programmers and researchers. But it also needs historians, sociologists, artists, carers, journalists, workers, communities and ordinary users Technical knowledge is one tool in a toolbox, it is not the toolbox.

We have seen the consequences repeatedly. Politicians who barely understand how the internet works are expected to regulate it. At the same time, technology companies and technical communities assume that because they understand the machinery, they therefore understand the society surrounding it. Neither position is good enough – we need technical people involved in politics and governance, but we also need those technical people to understand that engineering is not governance.

The #geekproblem hashtag is particularly important part of the story for the #openweb. A lot of contemporary technology culture has inherited a blinded belief that social problems can be converted into technical problems: if something is messy, build a perfect system, when people disagree, write a protocol, when something is unsafe, add security. If information is difficult to manage, build an algorithm, when people behave badly, moderate them automatically. If a community is struggling, optimise the workflow. Sometimes these things are useful, but often the “technical solution” simply hides the social problem.

The problem isn’t that geeks are bad people. It is that technical culture can become too comfortable with abstraction. People become numbers, communities datasets, politics optimisation. Relationships become networks, trust becomes authentication and participation becomes a user interface. And suddenly, we have designed a technically elegant system that nobody actually wants to live inside.

This is the deeper danger of #technocracy, it is not simply about having too many computers, engineers or technical experts. It is about turning technical expertise into political authority. The idea has been around for a long time. During the crisis of the 1930s, technocratic movements argued that society could be managed by scientific and technical experts rather than through the messy processes of democratic politics. The appeal was understandable: when society is in crisis, efficiency, certainty and expertise can look much more attractive than disagreement, compromise and uncertainty.

But that is the problem – democracy is messy because society is messy. There is no technical system that can contain all the values, histories, relationships, conflicts and experiences of the people affected by a decision. The belief that a small group of people with enough information can simply calculate the correct answer is not an escape from politics, it is politics disguised as engineering.

We can see the same problem emerging in our own technology culture. Silicon Valley has presented itself as being above politics: just build the system, scale it and let the technology solve the problem. But these companies have accumulated enormous economic and political power precisely because their systems shape how people communicate, work, organise, consume information and understand the world. Technology is therefore not neutral infrastructure, who owns it matters – who controls it matters – who funds it matters – who writes the rules matters – who has the power to change those rules matters. And what happens when the system is wrong matters.

The danger becomes serious when technological power and political power start merging. A technology billionaire does not become democratically accountable simply because their company operates critical infrastructure. A powerful algorithm does not become legitimate because it is technically sophisticated. A government does not become more democratic because it uses AI. Technology can be used to amplifie power without making that power accountable.

Technologies of humility

This is where the idea of technologies of humility becomes useful: technical and policy systems need to take uncertainty, ambiguity, vulnerability and the limits of knowledge seriously. Four principles might be useful.

  1. Framing

How are we defining the problem? Are we actually addressing the problem, or simply addressing the part that is easiest to measure? This is hugely important in #OMN development, if we define the problem as “How do we distribute content efficiently?” we will build one kind of system. If we define it as “How do communities maintain trustworthy shared media and social memory?” we build something very different. The technical architecture follows the social framing.

  1. Vulnerability

Who gets hurt by the solution? A system can be efficient and still be destructive. Algorithms can optimise engagement while making people miserable. A moderation system can reduce abuse while silencing marginalised voices. A security system can protect one group while excluding another. We need to ask: who is missing from the path?

  1. Distribution

Who gets the benefits? Who gets the power, the money and who carries the risks? This is one of the most important questions in technology because “innovation” is rarely distributed equally. The #dotcons have become good at extracting value from social relationships while presenting the resulting technology as neutral infrastructure, it isn’t neutral. The ownership model matters, governance matters. The matters because it tries to move these questions into the open.

  1. Learning

What happens when we are wrong? This may be the most important principle of all, there is rarely one perfect answer to a complex social problem. We need systems that can learn, not simply systems that can scale. This is one of the reasons #OMN is interested in things like moderation, rollback, metadata, federation and open governance. A social system needs mechanisms for correction, needs to be possible to say “That didn’t work. Let’s change it.” without treating the previous decision as sacred.

We need to understand that open systems need more than code, you can have beautifully engineered open-source software running a terrible social system, a decentralised network full of authoritarian communities, transparent code supporting opaque power, and you can build technically open systems that are socially closed.

So the challenge isn’t simply – how do we make the technology open? It is, how do we make technology part of an open social process? That is a much harder question, and much more interesting and why #OMN is deliberately messy.

The #OMN approach isn’t to pretend that we can design the perfect social system in advance. It is to build enough open infrastructure for communities to experiment, disagree, adapt and learn. That means accepting that different communities will do things differently, while providing common building blocks that allow different paths to develop – different interfaces, different workflows, different communities and different forms of participation. It means designing for disagreement rather than pretending disagreement can be engineered away, a path from technical systems to social infrastructure.

Composting the current mess is where the critique of tech authoritarianism connects directly to the #geekproblem, it is the problem of expertise becoming authority without accountability. And the answer is not to remove technical people from decision-making. Quite the opposite. We need their knowledge. But we need it alongside other forms of knowledge and inside democratic, open and accountable processes.

Engineers can tell us what a system can do, but they cannot, by themselves, tell us what society should want. Programmers can design protocols, but they cannot decide what relationships a community should have. Data scientists can identify patterns, they cannot determine what those patterns mean to the people living through them. And AI can process enormous quantities of information, it still cannot replace human judgement, lived experience, disagreement and democratic legitimacy.

This is why + #OGB + #OMN + #MakingHistory belong together, attempts to build technical infrastructure that leaves room for social intelligence rather than replacing it. To repeat endlessly the path is not one perfect platform, one perfect algorithm or one perfect governance model, #KISS we need more tools, not one answer.

On this native path, mess is not necessarily a failure, it can be the space where learning, disagreement, adaptation and democracy actually happen. That is a much humbler – and potentially much more powerful – ambition.

#OMN #openweb #OGB #MakingHistory #FOSS #geekproblem #technocracy #technology #governance #commons #socialmedia #decentralisation

Social value, personal value, and the chicken-and-egg problem

We still haven’t solved this. Looking back at a conversation from six years ago, what stands out isn’t disagreement – it’s how hard it is to even name the problem we keep circling.

Over the last 20 years, again and again, the discussion slips into the same dead end: personal value versus social value, framed through the language of #dotcons platforms, followers, influence, and business growth. What we need to learn from this is the confusion isn’t accidental, it is structural.

What we need is not only #socialmedia value, not engagement, not visibility. But offline value that exists between people, over time, as shared culture, trust, memory, and capacity. The chicken-and-egg problem, people ask: “What personal value do I get from this?”, “Will this help my business?”, “Can I use this without it using me?”

We need to compost, this messy common sense path. This is why the #OMN project was never about optimising personal outcomes. That #blocking framing belongs to platform logic, the idea that every action must be measurable in reach, influence, growth, or return. This is why the posts, like the one embedded above, people found “hard to understand” weren’t speaking that language at all. It were articulating what the #mainstreaming was #blocking and thus missing from our tech culture: social value.

What is hard to communicate is that social value doesn’t work like our current common sense thinks it does. You don’t extract it first and then decide whether it was worth it. Social value only emerges after people act collectively, without clear personal payoff in advance. Yes, personal value does flow from social value. Skills, relationships, meaning, resilience, opportunity. But it’s indirect, uneven, and slow. That makes it almost invisible inside systems trained to ONLY prioritise immediate, individual reward.

That’s why the conversation keeps short-circuiting, one of the early questions was whether the posts were meant to “influence followers”. That already assumes a vertical model: speaker → audience → outcome.

But #OMN thinking starts from a different place. It’s not about influencing people. It’s about creating conditions where different kinds of interaction can happen – horizontally, over time, without a central controller. That’s why the work often looks vague, unfinished, or “omelette-like”. Cultural values can’t be shipped as a product. It has to be grown, maintained, and defended collectively.

#Facebook was a comfort trap in hindsight. In the thread, several people describe using it pragmatically: staying in touch, organising events, maintaining real-world relationships. All true, and still kinda true today. But the counter-point raised then has only become clearer since: you don’t get to opt out of being used, no matter how carefully you think you’re using the system.

The lock-in effect (“everyone is on it”) was already obvious. What was less visible to meany people than was how disastrously deeply this would shape behaviour, politics, culture, and attention – and how hard it would become to imagine alternatives once that infrastructure was taken for granted.

Why this was hard to hear at the time? This conversation shows how difficult it is to talk about non-market value inside market-dominated spaces. Language itself becomes a barrier. People reach for familiar metrics because they have no shared vocabulary for anything else. So the discussion stalls. People get frustrated. It feels circular. Someone says “find out for yourself”, another hears that as dismissal. Nobody is wrong in isolation, but the frame itself is broken.

What we can learn now? Six years on, a few things are clearer: Social value is real, but it’s slow, collective, and hard to quantify. #dotcons platforms systematically erase the conditions needed for social value to emerge. Personal value derived from social value is indirect, not extractive. You can’t explain this cleanly inside systems optimised against it. This wasn’t a failure of communication. It was an early signal that we were trying to grow an open, cultural infrastructure inside environments hostile to its very existence.

Now is time to work on the unfinished path… #OMN project was – and still is – about creating space for social value to exist again: shared media, shared process, shared governance, shared memory. That was hard to see then, it’s still hard to see now. But the confusion in this old thread isn’t embarrassing. It’s instructive. It shows exactly where the fault lines are, and why the work has always been hard, messy, slow, and necessary.

Some things only make sense after you start doing them together #KISS

The impulse, it’s not wrong. What is wrong is how often that anger gets misdirected sideways, inward, and downward instead of upward, toward actual power.

A lot of people who think of themselves as “radical” aren’t being radical at all. They’re being assholes with better language. Cancel culture in 2020 played a similar role to political correctness in the 1990s: a way to signal virtue, police behaviour, and avoid confronting real power.

An example of this – done right, a code of conduct isn’t a weapon. It’s not a piece of paper you use to beat people with. It’s a declaration that you will protect the people who actually need protection – from harassment, abuse, and structural harm.

Done wrong, rules become clubs. People pick them up and hit each other with them. The wording becomes vague, moralistic, and performative. The enforcement becomes selective. And suddenly “safety” is being used to silence any disagreement rather than defend the vulnerable.

That failure creates space for bad actors, conservatives step in and pretend they’re “speaking truth to power” or “defending free speech”, when what they’re really doing is exploiting the mess to protect the normal hierarchy and privilege. They’re not wrong that something’s broken – they’re wrong about what and why.

The behaviour being criticised isn’t a tribe. It’s a mode of thinking, a widespread, unspoken #postmodernism that still dominates contemporary discourse. A style of politics where everything is relative, language replaces material reality, and moral positioning matters more than any outcomes.

This thinking eats movements alive, it fragments people, replaces strategy with signalling, and turns accountability into spectacle. Most importantly, it redirects energy away from those actually using power. This is a dangerous moment because we no longer have a shared baseline of reality. The #mainstreaming narratives are designed to divide, distract, and trigger – pulling attention away from concrete demands and real accountability.

That didn’t come from nowhere, forty years of #neoliberal economics hollowed out material security. At the same time, generations were trained in postmodern academic frameworks that are excellent at critique but terrible at building shared ground. Strip out material analysis, strip out class, strip out power – and you’re left with vibes, identity skirmishes, and endless internal conflict.

That’s what #OMN has always been pointing toward: rebuilding social truth, shared process, and horizontal power in a culture trained to fragment itself. Without that, we keep fighting each other – and the #deathcult keeps winning.