Analyzing Trends

Most of what we call “looking ahead” is really a mirror turned back on ourselves. Companies hire experts, build models, deploy AI to forecast markets and manage risk, but beneath the charts sit unspoken stories about who matters, who is expendable, and what “progress” is supposed to look like. In a time of conspiratorial thinking, wounded publics, and machine generated predictions, those stories harden into priors that shape what leaders even recognise as plausible. Machines don’t yawn. We do. The danger is not that we use probability, but that we mistake it for something neutral, disembodied, and somehow above culture. The work now is to treat intelligence systems as fast instruments for laying out the pieces, while we relearn how to see, question, and rearrange them together as humans who still yawn, hesitate, and change our minds.

We are living through a moment when “it was just a joke” has become a default way of speaking about serious things, from AI and product launches to corporate apologies and national policy. The old figure of the jester, who once used humor to tell hard truths to power, has been inverted: power now borrows the jester’s stance to float disruptive ideas, test public tolerance, and retreat into irony when challenged. At the same time, ordinary people rely on jokes and memes to cope with systems they no longer trust, turning contradictions into content that is instantly recognized but rarely resolved. The result is not a shortage of insight, but an inability to hold any single insight long enough for it to change how we act, leaving innovation, governance, and public discourse suspended in a loop of continuous exposure without commitment.

The mood of 2026 is friction at the surface. Reforms stall. Institutions grow brittle. Feeds fill with minor ruptures that never quite resolve. People talk about uncertainty, burnout, quiet cracking, but these are not abstract signals buried beneath events. They appear in work chats, neighborhood group texts, mutual-aid spreadsheets, and the steady accumulation of small adaptations. In that kind of world, the reassuring clarity of the iceberg begins to fail. When so much of the deeper story is already visible in the ways people improvise their lives, the task is less to dive for hidden truths than to learn how to read what is already in front of us.That is the working premise behind Story Systems and Cultural Research. In a recent workshop, a conversation about why foresight so often feels detached from culture brought us back to the relationship between Causal Layered Analysis and Culture Mapping: one clarifies how an issue is framed, the other shows where different stories already live and how they move. Taken together, they suggest that culture is not a submerged mass beneath events, but a moving field of narratives circulating across institutions, publics, and subcultures. The book traces how residual, dominant, emergent, and disruptive codes travel across that field, and how some narratives quietly harden into common sense while others register coming fractures. It asks how researchers, designers, and strategists can learn to read those patterns without falling back on trend lists or timeless archetypes.

Loneliness today is less a simple lack of company than a breakdown in shared meaning about what it means to be connected. Individuals move through days saturated with notifications, group chats, and parasocial ties yet feel unseen, because contact no longer guarantees recognition or obligation. Publicly, the experience is translated into shorthand complaints about busyness, missing “third places,” or being “chronically online,” while institutions reduce it to metrics like interaction frequency or screen time, counting what is visible but missing whether anyone truly holds anyone else in mind. This gap between private feeling and public criteria leads to misdiagnosis, blaming individuals for a structural problem shaped by precarious work, eroded communal spaces, and platforms built for visibility rather than reciprocity. Addressing the crisis requires redesigning the social rules and rituals that define when a relationship counts, so that connection once again names something people can both feel internally and recognize together.

The mood of 2026 is friction at the surface. Reforms stall. Institutions grow brittle. Feeds fill with minor ruptures that never quite resolve. People talk about uncertainty, burnout, quiet cracking, but these are not abstract signals buried beneath events. They appear in work chats, neighborhood group texts, mutual-aid spreadsheets, and the steady accumulation of small adaptations. In that kind of world, the reassuring clarity of the iceberg begins to fail. When so much of the deeper story is already visible in the ways people improvise their lives, the task is less to dive for hidden truths than to learn how to read what is already in front of us.

That is the working premise behind Story Systems and Cultural Research. In a recent workshop, a conversation about why foresight so often feels detached from culture brought us back to the relationship between Causal Layered Analysis and Culture Mapping: one clarifies how an issue is framed, the other shows where different stories already live and how they move. Taken together, they suggest that culture is not a submerged mass beneath events, but a moving field of narratives circulating across institutions, publics, and subcultures. The book traces how residual, dominant, emergent, and disruptive codes travel across that field, and how some narratives quietly harden into common sense while others register coming fractures. It asks how researchers, designers, and strategists can learn to read those patterns without falling back on trend lists or timeless archetypes.

Some of the most telling cultural warning signs do not look important at first. They arrive as spectacle, strange subcultures, compulsive self-performance, borrowed symbols, or people clearly pushing themselves too far. Then they get waved off as fringe behavior, filed under internet weirdness, or reduced to one damaged person making bad choices. But these moments are often not random at all. They are small exposures of a bigger pattern taking shape.

That is why narrative systems matter. They let you see how scattered signals connect, how isolated incidents point to shared pressures, and how culture quietly shifts what it rewards, glamorizes, and excuses. Too often we label these moments too fast and dismiss them as anomalies. What we should be asking instead is what they are signaling repeatedly, and what kind of social reality they are helping to build. That is where deeper care and earlier intervention become possible.

“Machines scale knowledge; humans preserve wisdom. Intelligence, therefore, is not automation but awareness: the capacity to reflect, adapt, and ethically co-create new systems of understanding.” - Story Systems and Cultural Research (Routledge)

A lot of the conversation around AI still feels too narrow to me. We keep treating disruption as if it is mainly about tools getting better or jobs getting automated, when the deeper shift is really about institutional legitimacy. Consulting, higher education, and other knowledge systems were built on the idea that expertise was scarce, gated, and easy to certify. That story is starting to come apart. A lot of what Marie Lena Tupot and I explore in Story Systems and Cultural Research is how shifts like this are never just technical. They are narrative, cultural, and structural at the same time.

What interests me more is how different futures open up depending on which parts of the past institutions choose to defend, recover, or let go of. Some will protect prestige long after purpose has weakened. Others may find more useful paths by reclaiming sidelined values like apprenticeship, stewardship, trust, and collective intelligence. No one of those narratives is the future. All of them are. The real question is not just what AI changes, but who gets to define what counts as intelligence, authority, and human value in the world that follows.

Many AI tools look impressive in a chat window, but that fluency often hides how fragile they are once their outputs drive real decisions. When you move from conversational demos to production systems, it becomes clear that what seemed like intelligence was often narrative performance, polished language without clear evidence or causal steps behind it. The core argument is that trust comes from structure, not style: scaffolds that force models to show their reasoning, trace their sources, respect constraints, and know when to refuse. Culture is central to this, with Culture Mapping used to turn local norms, meanings, and signals into rules a machine can check so interpretations stay tied to real behavior instead of drifting into generic prose. The vision is a form of hybrid intelligence in which refusal is a sign of maturity, humans remain responsible for judgment, and accountable structure matters more than effortless fluency.

That gap between technical planning and lived stories is where crises go sideways. Leaders may think in terms of deterrence curves, transition pathways, or risk matrices, but publics respond inside narratives about who is being sacrificed, who is being heard, and whose reality still counts. When institutions treat scenarios as sterile forecasts instead of disciplined stories that expose the assumptions they rest on, they end up reinforcing the loudest myths without ever naming them. The value of working from stories rather than from abstractions is not sentimentality; it is precision about the actual medium of power. We do not live in models. We live in narratives, and any serious attempt to think about the future has to start from there.

There is a difference between encountering an image and looking at one. Most people, most of the time, do the former. A photograph arrives already wrapped in headlines, reactions, and forwarded commentary, and interpretation moves faster than observation ever gets a chance to. For cultural researchers and foresight practitioners, that gap is not just a media literacy problem. It is a methodological one. Images are among the most compressed forms of cultural information we have, and treating them as decoration rather than evidence means missing signals that language will not catch up to for months or years.

The patterns are there: in what disappears from the frame, in how authority chooses to present itself, in the visual registers quietly shifting at the edges of public life. These are early indicators of how societies are contesting power, legitimacy, and belonging, and they surface in images long before they are articulated in interviews, reports, or data. Learning to read them carefully is not a specialized skill. It is a core competency for anyone trying to understand where culture is going.