Two Stories About Elephants

In 2019, newspapers around the world reported on a growing crisis: elephants in India were killing people.

The stories were dramatic and full of tension. Farmers told of waking to find their fields flattened. Whole villages were afraid to leave their homes at night. Government officials were overwhelmed. Wildlife experts warned that habitat loss was pushing elephants into dangerous contact with humans.

One story from Assam described how a 60-year-old man died after being trampled in the dark. The elephant had come for his rice crop. He tried to chase it off with a torch. His son watched from a distance, helpless. The elephant didn’t stop.

This story was real. So was the fear. But it left readers with a heavy question: what now?

Now consider a second story.

In southern India, the village of Sollepura faced similar problems. Elephants often raided farms. People were injured. Crops were lost.

Then the farmers tried something new. They began planting chili and lemongrass, crops elephants dislike. They added beehive fences, which buzz loudly when disturbed. Elephants avoid bees.

After a year, elephant raids dropped by more than 70%. The farmers earned good money from the new crops. The elephants stopped coming. Both sides were safer.

This story didn’t go viral. It wasn’t dramatic. But it was also real. And it offered something rare: a way forward.

So here are the questions:

• Which story made you want to act?

• Which one gave you a reason to believe things could change?

The Problem with Doom

Most stories about the environment focus on problems.

And there are many:

• Species are going extinct.

• Forests are being cleared.

• The oceans are warming.

This coverage is important. It helps people understand the scale of what we’re facing.

But here’s the danger: when people hear only bad news, again and again, they often shut down.

They feel small. They feel hopeless. They feel like nothing they do will matter.

This is called eco-fatigue or climate anxiety 1.

One study found that reading constant “doom” headlines about climate change made people less hopeful - and less likely to act2.

Another found that when young people feel hopeless about nature, they disconnect. They stop caring. They say, “Why bother?”3

If the goal is to inspire people, then fear alone may not be enough.

What the Science Says

So what kind of stories actually work?

Researchers have tested this. They’ve studied how people respond to different types of messages about the environment.

One key idea is efficacy. That means: do I believe my actions will make a difference?

In 2016, a team at Rutgers University ran a simple experiment4. They gave people two news articles:

• One described climate change as a huge, unstoppable problem.

• The other focused on a successful solar energy project.

The second article didn’t hide the danger. But it showed a solution - and how it was working.

The result? People who read the solution story:

• Felt more hopeful

• Believed they could help

• Were more likely to act later

Even two weeks later, they were still more engaged.

This is called constructive hope. It’s hope based on real action, not empty promises5.

And it’s powerful.

The Evidence in Action

When Hope Leads to Action

Conservation Optimism, a global group, shares stories about positive changes for wildlife. These stories are not fluff. They are factual. But they show what’s working, and how6.

• In Kenya, beehive fences around farms have cut elephant crop-raiding by over 85%. They’ve also helped farmers earn more income from honey7.

• In Portugal, fishing communities now help protect the sharks they once hunted. They’ve turned to eco-tourism, and their incomes are stable. At the same time, shark numbers are rising8.

• These stories inspire others. They say: “Look, someone like you did this. So can you.”

When Fear Shuts Us Down

• A 2016 study by Geiger & Swim found that reading scary climate news over and over made people less hopeful and less likely to take action9.

• Some people feel guilty or ashamed—but don’t know what to do. That leads to moral fatigue, not change.

• In many schools, students feel overwhelmed by climate lessons. Instead of being mobilised, they withdraw.

Fear without action leaves people stuck.

The Emotional Mix

But it’s not just about hope.

Sometimes, anger is what drives people.

A study from Yale found that people who felt angry about climate change were seven times more likely to join a protest than those who felt hopeful10.

Anger can motivate. But it can also divide. If people feel blamed, or powerless, it can backfire.

And fear? It only works if you give people something they can do.

Experts agree: you need both the problem and the path forward.

What Better Stories Look Like

We’re not saying the world is fine. It isn’t.

We’re saying that better stories do three things:

1. They tell the truth. They don’t pretend everything is okay.

2. They show real examples of success. Like the chili farmers. Like the beehive fences.

3. They invite action. They show how you can help.

That’s what makes a story stick. That’s what gets someone to share it, act on it, or tell a friend.

That’s what turns awareness into agency.

Why This Matters Now

We’re living in a noisy world.

Every day brings more headlines, more crises, more despair.

But attention isn’t the problem. Meaning is.

People need well-told stories that help them understand - not just what’s wrong, but what’s possible.

We’re not calling for fluff or false hope. We’re calling for truth with direction.

As storytellers, filmmakers, teachers, and citizens, we can shape what people believe is possible.

We can tell the stories of people who are solving big problems.

We can remind others that change is already happening.

We can help people feel part of it.

The world doesn’t just need to know what’s going wrong.

It needs reasons to believe it’s still worth fighting for.

Why It Matters To Me

I’m setting out on a storytelling journey with the hope of changing minds about how we live on the planet. I favour optimistic stories and will be looking for good ones that could shift perspectives on human-wildlife coexistence in the ocean.

On 23 June 2025, HMG unveiled its splashy manifesto “grow our creative industries by £50 billion GVA and create one million jobs by 2030”. The Creative Industries Sector Plan was published. In it, Ministers spoke of Britain ascending to “creative superpower” status. Yet as the ribbon was still uncut, critics noted that creative GVA actually contracted 3.3% in 2023, even as the wider economy edged up 0.3%  , and that barriers to entry for creators are now almost zero - anyone can launch a YouTube channel, TikTok feed, Substack newsletter or Medium publication from their phone. Is this top-down playbook trying to steady a sinking ship of legacy gatekeepers even as the tide of individual creators rises?

HMG’s deep desire is to harness creativity as a national growth engine, and to keep revenues on home soil. Yet its centralised delivery - funneled through BBC, ITV, major studios and trade bodies - clashes with a creator economy where trust has shifted from corporations to individuals. Meanwhile, GVA as a metric is vulnerable to input-cost inflation: when energy and material prices spike, GVA can dive even if actual output holds steady  . The real tension: shore up yesterday’s giants, or empower tomorrow’s disruptors on platforms like YouTube, Spotify, Substack and Medium?

Unbowed, HMG activated its industrial-strategy toolkit:

• Tax reliefs for film, TV and video games

• A £270 million Arts Everywhere Fund plus hundreds of millions for Creative Clusters R&D 

• Skills hubs and apprenticeships administered by established training bodies

This was HMG’s moment of resolve. A government heavyweight stepping into cultural policy, determined to “back talent everywhere.”

Critical factors to consider:

• Pre-pandemic boom: Between 2010 and 2023, creative GVA rose 35%, outpacing the UK economy’s 22% gain  .

• 2023 downturn: Despite fresh support, GVA fell 3.3%, while overall UK GVA ticked up 0.3%.

• Skills crunch: 65% of firms report hard-to-fill roles in VR/AR and Createch .

• Platform revenue vacuum: Most creators pocket only fractions of pennies per stream - YouTube, TikTok and Spotify capture most value  .

• AI licensing battleground: Generative AI trains on copyrighted works without consent, sparking an opt-in vs. opt-out fight that will decide if human creators retain IP control.

• Brexit-era frictions: UK musicians and theatre troupes must navigate new visa and customs hurdles to tour Europe; yet the Plan barely mentions these barriers.

• Platform-native insurgency: Independent podcasters on Substack, newsletter entrepreneurs on Medium, niche livestreamers on Twitch; they’re building direct audiences and monetisation models far outside HMG’s legacy channels.

To avoid being outpaced, HMG must pivot from propping up incumbents to building bridges with disruptors:

1. Recalibrate Metrics - Supplement GVA with gross output and volume-adjusted indicators to reflect true production, not just price-driven swings.

2. Platformise Legacy Media - Mandate that broadcasters and publishers receiving tax relief open APIs, revenue-share pools and creator portals - so indie innovators can plug in and keep revenue in the UK.

3. Seed a “Digital Disruptors Fund” - Direct grants to platform-native creators - podcasters, vertical-video studios, micro-publishers on Substack/Medium - under lighter compliance to supercharge next-gen British talent.

4. Establish a clear AI-training framework - Mandate transparent, tiered rules that define what counts as fair use versus infringement, require explicit opt-in consent from creators, and ensure proportional compensation whenever their work feeds an AI model.

5. Tackle Post-Brexit Barriers - Negotiate bespoke creative-sector visa accords with the EU and replace lost Creative Europe funding with targeted UK schemes.
   

…to conclude:

The genie of creative disruption is out of the bottle, and it’s not living in Whitehall. If HMG truly wants a creative superpower, it must persuade legacy media to become open platforms or fuel entirely new ones, harnessing the galvanizing energy of YouTubers, TikTokers, Substack authors and Medium publishers. Otherwise, the Grand Vision risks being no more than a glossy brochure - a command-and-control blueprint watching from the bridge as the real revolution sails past.

Podcast version of this article

🗣️ This is part of Media Unmade - a series about how media breaks, reforms, and adapts in the age of AI and creator autonomy.

💬 What form is your story taking right now? Where is it going next?

She paints AI as the Emperor’s New Wunderkind - hailed as a prodigy by its handlers, paraded through headlines, but visibly fumbling the basics while everyone claps politely and pretends not to notice. Fake books. Glue pizza. Broken buttons coded by digital apprentices who don’t know they’re broken. She gives AI a good kicking, and it’s hard not to cheer her on. The spectacle deserves some heckling.

And she’s not wrong. Not entirely.

There’s a growing divide in how people are experiencing AI - and we don’t talk about it enough. On one side, you’ve got tech-bros and politicians declaring it the engine of the future, already revving. On the other, people like Moran are giving it a cautious prod, watching it spit out nonsense, and wondering how this became the main act.

The temptation is to see AI as either messiah or menace, depending on how many hallucinated book titles or software bugs you’ve encountered this week.

But maybe we’re missing something more obvious: AI hasn’t come from nowhere. It’s been trained on us - on our writing, our behaviours, our contradictions. So it’s not surprising that, like us, it’s flawed.

What we’re building isn’t some alien intelligence; it’s a reflection. If the reflection stutters, invents, misleads or flatters, it’s echoing patterns we’ve already laid down in the culture.

Every time it gets something wrong, we should pause - not just to laugh at it, but to recognise how much of that mistake was inherited.

That doesn’t excuse the failures. It just frames them.

AI can’t be better than us until we’re clearer about what “better” even means. And that starts with honesty - not just about what the technology is, but about what we’ve taught it to be.

Most people haven’t had any kind of orientation. They’ve been handed something complex and probabilistic, and told - often implicitly - that it’s ready to use. But they haven’t been shown how to prompt it. They haven’t been told how to check what it says. They don’t know when it’s bluffing, when it’s biased, or when it’s drawing from a source that may not even exist.

Of course people are frustrated. I would be too. You wouldn’t expect someone to fly a jet just because they’ve sat in an aisle seat. And yet we expect people to get meaningful results from a system trained on terabytes of human expression, with no instruction and no context.

But something interesting happens when you do learn how to use it.

Slowly, awkwardly, and not without friction, the tool starts to make itself useful.

Teachers are using it to differentiate materials in overburdened classrooms. Freelancers are using it to write faster, with more versions, more options, more room to play. Small business owners are drafting emails, creating social posts, and mapping customer journeys they’d never have had time for. Coders are using it to clean up tedious boilerplate and explore unfamiliar languages.

Translators, accessibility workers, journalists, designers, researchers - it’s not changing everything. But it is helping. Quietly, behind the headlines.

And the more time people spend with it, the more it starts to feel less like an oracle and more like a tool. Not an all-knowing machine. Just a better kind of autocomplete. One that you can direct, interrupt, improve.

A tool that says, “Here’s what I think you mean - tell me if I’m wrong.”

So who’s right - Moran or the evangelists?

Both, and neither.

Moran is right to call out the absurdities. But wrong to suggest the tool itself is a write-off.

The evangelists are right that AI is powerful. But wrong to pretend it’s ready for unsupervised use at scale.

The truth sits between the hype and the hopelessness.

AI won’t save us - and it won’t doom us. Because it’s not separate from us. It was trained on us. And it shows. Every hallucination, every flash of brilliance, every dull mistake - it’s all ours, reflected back.

What that means is: if AI is flawed, it’s not because it’s broken. It’s because it’s mirroring a world that already is. And that gives us a choice: do we accept the reflection as it is?

Or do we get better - so the tools we build can be better too?

We don’t need to believe in AI.

We need to engage with it critically.

And maybe that’s the real shift: not from human to machine, but from expectation to understanding.

Less “magic beans”.

More tools we learn to wield.

Carefully. Responsibly.

And together.

If you liked this piece, then you may enjoy some more articles where I explore the liminal boundaries between humanity and its technology:

• Why AI Is Not “Stealing” Creativity: A Historical and Educational Perspective on Homage, Learning, and Innovation I lent my Substack to Perplexity to respond.

• The Story AI Can’t Tell - Why the future of filmmaking won’t be revolutionised by machines—no matter how fast they get.

Centuries passed. The executions stopped, but the urge to speak remained. In 1872, the government made it official: a corner of Hyde Park was set aside where anyone - radical, preacher, dreamer, fool - could climb a box and speak their mind. No permission required. Just nerve.

One Sunday morning, a woman stepped up, her notes fluttering in the wind. She was no celebrity, just someone with something urgent to say. Around her, passers-by paused. Some cheered, some argued, others drifted off, unmoved. She didn’t flinch. Their reactions told her something. Not just who agreed - but who misunderstood. Where her meaning slipped. Where her message missed.

She came back the next week, tighter. Clearer. She knew now what caught attention, what opened ears, what shut people down. The words changed, but the purpose didn’t. She wasn’t chasing applause - she was chasing understanding.

Decades later, that triangle of ground still hosts voices, wild and wise. And online, it’s the same: we post our truths, meet confusion or connection, then try again. The gallows are gone. But the stakes - the need to be heard, to be understood - remain.

That’s what The Creator’s Impact Triangle is about. It’s not just how you speak - but how you learn from what’s heard.

Noise surrounds us, meaningful communication is not just about what you say - but how it’s heard, what it provokes, and where it leads.

To understand how creators - from filmmakers to campaigners - stay intentional, I’ve been developing a simple but powerful mental model: the Creator’s Impact Triangle.

It maps the three forces at play in any message that hopes to make a difference:

• Message: Your intention - what you’re trying to say.

• Meaning: What the audience takes from it.

• Measurement: How you know what’s working.

These aren’t just abstract ideas - they form a cycle. The triangle spins. Message meets Meaning. Meaning yields Measurement. Measurement sharpens the next Message.

It’s a way of keeping your work aligned with your values, and your audience’s needs.

In practice, it looks something like this:

A Message’s Journey

Every story begins with desire.

In this one, the protagonist is Message - the part of us that burns to say something. To make a mark. To be understood. Message knows what it wants: to express truth, to provoke thought, to move others. But intention alone is not enough. The world doesn’t yield meaning on command.

So Message sets out. It crafts itself into shape - an article, a video, a film, a thread - and launches itself toward the unknown. At the far point of the triangle stands Meaning, quiet but powerful. Meaning doesn’t belong to Message; it belongs to those who receive it. The audience completes the message, not by agreeing, but by interpreting.

But here lies the first tension - the first conflict. Message believes it has spoken clearly. But Meaning doesn’t always respond the way Message expects. Sometimes it’s embraced. Other times, it’s misunderstood, twisted, or ignored. The connection between them is not a highway. It’s a mirror.

This edge - the path between Message and Meaning — is Reflection.

It shows not what was said, but what was heard. It doesn’t flatter. It reveals. And it hurts - because the message we thought was pure is suddenly full of gaps, shadows, ambiguity.

Meaning, though, doesn’t keep secrets. It leaves clues. Not directly, but in footprints - comments, silence, shares, bounce rates, rereads, drop-offs. Enter the third character: Measurement. Practical, analytical, sometimes cold - but never cruel. Measurement watches what people do in response to meaning. It takes the abstract and makes it legible.

This edge - from Meaning to Measurement - is Information.

It turns emotion into data, behaviour into signals. But it’s no oracle. It doesn’t explain. It only points.

And now, Message returns - older, wiser, and slightly humbled. It stares at Measurement’s findings and sees not judgment, but opportunity. These aren’t verdicts. They are insights - not into worth, but into resonance.

This final edge - from Measurement back to Message - is Insight.

Message now has a choice: ignore the signs and keep shouting, or listen, refine, adapt - not to manipulate, but to clarify. To say what it truly means, and to mean something worth saying.

And so the triangle completes a cycle.

Desire has met resistance. Conflict has revealed misalignment. Resolution arrives not as triumph, but as understanding. Message now knows what it didn’t know before - how to speak more truly, how to invite more deeply, how to navigate the uncertain terrain between sender and receiver.

And the triangle turns again. Because in the age of AI - and all its unintended consequences - what matters most isn’t the sheer volume of what we create.

• It’s how well we listen to our own reflection.

• It’s whether we dare to remain human in a loop that could easily turn robotic.

• It’s whether we shape our tools not to go viral, but to go deep.

This is not a diagram. It’s a path.

Summary

• Message → Meaning - You express your intention through content - a video, article, post, film, etc. Meaning belongs solely to the audience. They receive and interpret creators' messages. Meaning emerges, but it’s not always what you intended.

• Meaning → Measurement - Audience reactions (comments, shares, time spent, bounce rate, silence) provide data. These are your measurement signals - not just numbers, but qualitative feedback.

• Measurement → Message These insights feed your next message. You tune your intention, not to chase trends, but to sharpen resonance with the meaning you want to co-create.

Tools for Messages - Finding the Signal Before the Noise

• AI Research Assistants – for sifting signal from noise on the web (e.g., ChatGPT, Claude, Perplexity, MindStudio agents).

• Narrative Design Tools – e.g., Hero's Journey.Dramatica-based system, Muse Storytelling frameworks, etc.

• Obsidian, LLMs, Notion, MindStudio, RelevanceAI, etc – as systems for developing, refining, and structuring story insights.
  

These tools help creators work with clarity of intention - not just “creating content,” but building stories that matter.

Tools for Meaning - Where the Magic Happens (You Can’t Control It)
Meaning Emerges in the Space Between)

• Meaning is co-created - we set intentions, audiences complete the circuit.

• Tools like multimodal workflows (text, video, audio) help us meet audiences where they are, not where we wish them to be.

• Image-generation tools (like Midjourney or DALL·E) can fill in blanks - but only meaningfully if grounded in a well-shaped message.

Tools for Measurement - Tools That Listen Back
The Dashboard Isn’t the Enemy (When You Know What to Watch)

• Google Analytics 4 (GA4) – reimagined as a tool of listening, not surveillance.

• What engagement metrics mean (e.g., time on page, clickthroughs) and what they don’t.

• The goal: a cockpit, not a casino - something that helps you fly intentionally not just chase dopamine hits.

Bottom Line - A Satirical Shock to the System

A real world example illustrates the potential of the creator's impact triangle. Blue Marine have created a short film that launched at the 2025 UN Ocean Conference. Bottom Line uses satire to highlight the unseen consequences of bottom trawling for fish. It stars Theo James and Stephen Fry, both ambassadors for Blue Marine. It could have just shown images of wasteful by catch, but they chose comedy:

So here is how it could work in the Creator's Impact Triangle:

Lessons for Any Creator

Bottom Line is a triangle-driven story in motion:

• It starts with clarity of purpose - but doesn’t assume clarity of reception.

• It embraces friction - measuring not just applause but confusion.

• It iterates intelligently - always moving the message toward greater resonance and usefulness.

And crucially, it doesn’t stop at revelation. It moves viewers from awareness → emotion → possibility → action.
Because a story is only powerful when it leaves people not just informed - but equipped.

Bottom Line is exactly the kind of intentional storytelling I explore here on Media Unmade - not just how we craft stories, but how those stories behave in the world. The Creator’s Impact Triangle isn’t a gimmick; it’s a lens I return to in each post, whether I’m writing about AI, media collapse, or human-wildlife conflict at sea. Because the question isn’t “what should we say?” but “what should we mean - and how will we know if it’s working?” If that resonates, you’re in the right place.

What if the most important shift in our industry isn’t technical, but narrative?

In the past few months, I’ve been writing a series on Media Unmade, exploring how old editorial systems are collapsing while new ones - often creator-led - emerge. And now, the new BFI report on AI in the screen sector arrives, echoing many of the same concerns and possibilities. Not in opposition to creators, but often in harmony with them.

It feels like the industry is beginning to tell itself a new story - one that doesn’t just chase progress, but asks: progress toward what?

AI is moving fast — faster than most production timelines, distribution models, or union negotiations can keep up with.

What was once a fringe conversation is now mainstream. AI can animate characters, write scripts, mix vision, translate voice, and fill B-roll gaps in seconds. And it can do this at both ends of the spectrum — from blockbuster workflows (ST2110, Vislink, vPilot) to DIY creator tools (Runway, Descript, Pika). What’s at stake is not just how we make, but who decides, who profits, and whose creativity counts.

As I wrote in “The Shape of Future Content”, we are not just changing formats. We’re changing the function of content - and its intent.

The BFI’s report doesn’t make wild predictions. It maps the current terrain. But it does so with clarity and care.

It recognises AI not just as a technology, but as a force reshaping:

• Labour: What does fair pay mean when a synthetic voice dubs in 10 languages?

• Ownership: How do we define authorship in a hybrid workflow?

• Understanding: How do we raise the baseline of AI literacy across our sector?

This resonates with what I explored in “The Reimagination of Editorial Functions”: the editorial layer doesn’t disappear - it decentralises. And we all need to learn to carry it.

There’s no single solution - but there are signs of a way forward.

The BFI calls for policy safeguards, open standards, funding for skills development, and a broad conversation between creatives, technologists, educators, and platforms.

Meanwhile, individual creators are already adapting - using AI as a co-pilot, not a replacement. We’re seeing:

• Narrative agility - reshaping ideas across formats without losing the spine

• Ethical grounding - visible choices, not invisible compromises

• Community as co-authors - a creator and their audience, shaping meaning together

In “A Perspective on the Future of Creative Work”, I wrote that survival won’t come from perfection. It will come from clarity: of process, of values, and of voice.

Here’s what’s striking: from national institutions to independent Substacks, the story is converging.

We’re beginning to see AI not as the end of something, but as the beginning of a more intentional, possibly more human creative practice. The challenge is not to stop the machines. It’s to shape the systems in which they operate - to align them with human scale, purpose, and justice.

This convergence is an invitation: not to agree on everything, but to notice that we’re in the same story, even if we’re writing different scenes.

The tools are powerful. The questions are urgent. But the opportunity is real:

Don’t just adopt AI.

Don’t just fear it.

Use it - to craft. To clarify. To create something that matters.

Read the BFI Report:

AI in the Screen Sector: Perspectives and Paths Forward (June 2025)

Explore my ongoing series:

Media Unmade on Substack

Ten months ago, an AI tutor helped a student identify the hypotenuse of a triangle. The machine was calm, responsive, and eerily competent.

“Pretty impressive,” said Derek Muller of Veritasium. “And that was ten months ago.”

The clip feels like magic. And maybe it is. But it raises a quieter, more urgent question:

If AI can do everything but care , then  who’s left to tell the story?

In a video talk What Everyone Gets Wrong About AI and Learning, Muller argues that learning doesn’t fail for lack of access to information - it fails because engagement is hard, effort is limited, and meaning must be built, not delivered. That same logic applies to storytelling. It’s not information that holds our attention. It’s intention. It’s structure. It’s someone wrestling with what matters. And no model  -  no matter how big  -  can automate that struggle.

From radio to TV to MOOCs, every generation has promised a revolution in learning. “This time will be different,” they say , and now AI joins the chorus. But education hasn’t fundamentally changed. Not really.

“You keep using that word  -  ‘revolutionise,’” Muller says. “I do not think it means what you think it means.”

The same mistake is being repeated in media. We confuse faster content with better content. More output with more impact. But media, like education, isn’t about delivery. It’s about engagement. We are not short of tools. We are short of meaning.

In Thinking, Fast and Slow, psychologist Daniel Kahneman outlines two types of thinking:

• System 1 is fast and automatic, pattern recognition and habit.

• System 2 is slow, effortful, deliberate, and it’s where real learning happens.

All growth begins in System 2. Mastery, eventually, moves it to System 1. “If they never write 100 essays,” says Muller, “what happens to their brains?” The lesson is clear: practice isn’t optional. It’s the process.

AI is remarkable when it gives timely, accurate feedback. It helps learners, and creators, course-correct in real time. As a storytelling tool, it can test structure, style, purpose, even emotional rhythm  -  fast.

But shortcuts short-circuit growth. If creators never wrestle with rough cuts, edit decisions, or narrative structure, they’ll never internalise storytelling. What they gain in speed, they lose in depth.

“The risk,” Muller says, “is that people stop engaging in effortful practice ,  and never build System 1 fluency.” And in filmmaking, that means a tsunami of videos that look fine but say nothing.

Here’s the overlooked truth: education is a social activity. So is storytelling. You don’t learn (or tell) stories in isolation'; you need friction, feedback, and fellow travellers. The promise lies   not in solo creators automating themselves out of a job, but in collaborative, intentional story cultures, where AI is a tool, not a crutch.

The future of media will split:

• One path produces polished but hollow content at scale.

• The other produces meaning  - slowly, iteratively, with care.

If you care about story , Your job  isn’t to race the machine. It’s to outlast it. Use AI to assist, structure, suggest. But never outsource the work of seeing, feeling, and shaping. That’s what makes a story yours. That’s what the machine can’t touch.

“The world is full of heavy objects,” Muller says. “And yet most people are not ripped.” There’s no shortage of stories. Only a shortage of people willing to lift them,  again, and again, and again,  until something real takes shape.

Don’t just prompt. Don’t just publish:

Train - Use System 2. Push past the easy answer. Like the student who realises, a beat too late, that the Earth doesn’t orbit the sun in a day, growth begins with the moment you notice your first mistake.

Craft - Repeat with intention. As Muller notes, mastery comes from slow, deliberate effort, not from the final product, but from how many times you revise the phrase, rethink the beat, or reframe the problem.

Tell - Turn knowledge into narrative. Like the chess master who sees not 16 pieces, but patterns, relationships, and meaning. Your job is to chunk reality into something others can feel, something that moves hearts to change minds.

References:

1. The video, Derek Muller, Veritasium: (Perimeter Institute for Theoretical Physics, April 2025)

2. Daniel Kahneman, Thinking, Fast and Slow

3. Cognitive Load Theory: Sweller, J. (1988). Cognitive load during problem solving: Effects on learning.

What If Progress Costs Us Too Much?

We were told technology would free us: More time. More creativity. Fewer limits.

Instead, we find ourselves outside locked newsrooms, staring at blinking servers, at coastlines where intelligent mammals dodge propellers and nets, at screenfuls of AI-generated content that say nothing real, gaining speed, and losing direction.

This is my attempt to pay attention, to lift my head above the parapet, and to be accountable for what I think…

The Central Thread

This Substack explores the unintended consequences of technology - and we can shape its course.

Not to stop it. Not to worship it. But to make it human again.

I write about the cracks in the systems we thought were unshakeable - and the people trying to make something better in their place. I tell stories. I travel. I use AI. I question it. I document the collision between invention and consequence.

And I do it through three distinct but tightly connected lenses.

Blue Pulse:

Our oceans are no longer remote. They are increasingly surveiled, mapped, mined, and contested.

In Blue Pulse, I document the human-ocean interface with a focus on optimistic solutions to conflict that facilitate coexistence.

Orcas interacting with yacht rudders. Supertrawlers gutting ecosystems. Scientists scrambling to understand intelligence that doesn’t fit into our models and language that doesn't speak our name.

These stories are not just about wildlife. They are about how we can live on this planet without breaking it.

Media Unmade:

Digital platforms and AI are dismantling the institutions that shaped our understanding of the world.

The newsroom is collapsing inward. The editor is now an algorithm, now a human. The journalist is fast becoming a creator, a brand, or a casualty.

In Media Unmade, I look at how storytelling is evolving and how we can avoid we confusing virality with truth. I write about the rise of independent media, the fall of legacy gatekeepers, and the dangerous middle ground we inhabit now.

AI and Agents:

I use AI. I build with it. I test it in storytelling, research, and systems design.

But I’m not trying to automate myself. I’m trying to see what’s possible when we humans stay in the loop.

In AI and Agents, I explore the creative and ethical tensions of artificial intelligence. From GPTs to autonomous assistants, I look at how these tools could shape the future of work, and to avoid what happens if we hand over more than we meant to.

Sometimes I publish reflections. Sometimes experiments. Sometimes conversations with the machines themselves.

What You’ll Find Here

This isn’t a niche blog. It’s a map.

You’ll find:

• Essays on media, ecology, and technology

• Dispatches from field research; marine, media, or both

• Experiments with AI workflows in storytelling

• A slowly-unfolding argument about how we must stay human in all this

There’s no schedule, but expect something most weeks.

No rage farming. No hustle tactics. Just optimistic stories worth your time.

Why I’m Doing This

At heart I’m a documentary filmmaker and storyfinder. I work from a van and a boat, tracing the boundary layers between human and ecological systems.

This Substack is to be my field journal - a record of what I’m noticing, testing, and questioning as I go.

It’s also an invitation: to think more deeply, to pay attention differently, and to tell stories that help us stay human.

Subscribe if…

• You’re trying to understand the shape of change

• You want more signal, and less noise

• You’re tired of certainty - but still believe in meaning

Subscribe. Skim a bit. Reflect more.

And if something lands, hit reply. I’ll read it. You too have agency.

The rise of generative artificial intelligence (AI) has sparked heated debates about creativity and originality. Critics often accuse AI of “stealing” creative work by training on vast datasets of existing art, writing, music, and design. However, this perspective overlooks a rich tradition in human creativity that embraces borrowing, reinterpretation, and homage as essential to artistic growth and innovation. Far from being theft, AI’s creative process aligns closely with how humans have learned and created for centuries.

Creative Learning Through Homage: A Time-Honored Pedagogical Practice

One of the strongest counterarguments to the “AI steals” claim lies in the educational practice of homage. Across disciplines, students are routinely asked to study, analyze, and recreate works by masters as a foundational step in developing their own voice. For instance, at Northampton Community College, students undertake Art History Homage projects where they produce original works inspired by artists like Meret Oppenheim, Marcel Duchamp, and Frida Kahlo. These assignments require deep engagement with the original artist’s style and themes, resulting in new creations that honor and reinterpret the source material. A student’s homage to Oppenheim might involve recreating her surrealist Object using a hairbrush, demonstrating creative adaptation rather than mere copying.

This approach is not unique to visual arts. In literature, students write pastiches or rewrite classic soliloquies, while in music, jazz musicians learn by improvising on established standards. These exercises are celebrated as vital for skill development and creative maturity, not condemned as theft.

Historical and Cultural Precedents of Creative Borrowing

Human creativity has always been iterative and collaborative, building on prior knowledge and cultural artifacts. Renaissance apprentices copied masters’ works before innovating, as seen in Raphael’s The School of Athens, itself an homage to classical thinkers. Picasso’s cubism drew heavily on African masks, openly borrowing and transforming existing art forms. Jazz legends like John Coltrane reinterpreted standards, pushing genres forward through homage and variation.

Even the master-apprentice dynamics in Japanese ukiyo-e printmaking show students replicating Hokusai’s style before developing their own. These examples illustrate that creativity is rarely about isolated originality but often about dialogue with predecessors.

Legal and Ethical Frameworks Support Transformative Use

Copyright law distinguishes between plagiarism and transformative use. Educational fair use provisions allow students to copy and reinterpret copyrighted works for study and creation, paralleling AI’s training on diverse datasets. The landmark case Warhol Foundation v. Goldsmith affirmed that adding new meaning or context can qualify as fair use, legitimizing homage and reinterpretation.

Moreover, copyright protects specific expressions, not artistic styles or ideas. AI models learn compositional patterns rather than replicating exact works, much like human artists learn styles and techniques without copying verbatim.

AI as a Tool Empowering Creativity, Not Replacing It

Generative AI identifies patterns from existing data to produce unique content that mimics human creativity, revolutionizing creative fields by breaking down barriers to entry and enabling new forms of collaboration. For example, AI-powered music tools analyze existing songs to inspire musicians to experiment with genres and techniques, expanding creative horizons. Studies show AI tools provide designers with new perspectives, automate repetitive tasks, and accelerate ideation, enhancing productivity and innovation while complementing human judgment rather than replacing it.

Educational institutions are already integrating AI tools to support learning. Research indicates that students find AI helpful for developing creativity by encouraging independent thinking and creating opportunities for exploration. AI’s role is increasingly seen as augmenting human creativity, enabling a collaborative creative process where machines and humans co-create.

Parallels Between AI and Human Creative Apprenticeship

The process AI uses to generate new works is fundamentally similar to human creative apprenticeship and homage. Both involve learning from existing inputs to produce new outputs. Just as students copy and reinterpret masterworks to develop their skills and voice, AI synthesizes patterns from data to create novel content.

This parallel challenges the hypocrisy in condemning AI for “stealing” while celebrating human artists who openly admit to borrowing. Picasso famously said, “Good artists borrow, great artists steal.” Shakespeare adapted Plutarch’s histories; Led Zeppelin reworked blues traditions. The key is transformation and innovation, not mere replication.

Personal Connections in Making Homage

Creating homage is a deeply personal act that fosters emotional resonance, cultural dialogue, and creative growth. It connects creators to artistic traditions, communities, and their own identities. This layered relationship transforms admiration into meaningful innovation—a process mirrored in how AI tools augment human creativity.

Conclusion: Reframing the Narrative Around AI and Creativity

The accusation that AI “steals” creative work ignores centuries of artistic tradition where learning through homage, borrowing, and reinterpretation is foundational. Educational practices explicitly encourage studying and reworking existing works as a path to innovation. Legal frameworks protect transformative use, and cultural history celebrates creative borrowing as essential to progress.

AI’s creative process is an extension of these human practices, democratizing creativity and opening new possibilities rather than undermining originality. Rather than fearing AI as a thief, we should embrace it as a tool that continues the age-old human journey of learning, homage, and invention.

Selected References

• Chaeeun Boo et al., A Collaborative Creative Process in the Age of AI, ScholarSpace, 2024

• Budi Sulistiyo Nugroho et al., Application of AI in the Creative Process: Case Study in the Design Industry, Journal of Social Entrepreneurship and Creative Technology, 2025

• Aditya Chauhan, Redefining Artistic Boundaries: The Impact of Generative AI on Creative Processes and Innovation, Authorea

• Marrone et al., How does generative artificial intelligence impact student creativity?, ScienceDirect, 2023

• AI and the Creative Process: Part One, JSTOR Daily, 2023

Disclosure

This article was written without human intervention. It is entirely the work of Perplexity. I simply told it to write and run a prompt to research and counter the view that AI is creative theft. Then I asked it to make and run a prompt to write up its findings.

Then I asked another AI to make a podcast from the article:

And this page is what they have to say :)

Imagine an AI that doesn’t just adapt to data - it rewires its own code.
An assistant that doesn’t sleep, doesn’t wait for updates, but gets better by itself, spots its own flaws, invents new methods, sharpens itself with no human prompt.

This isn’t speculative fiction - it’s already under way. The Darwin Gödel Machine (DGM) is a self-evolving system quietly reshaping what we mean by learning, autonomy, and intelligence.

At the heart of DGM is a deceptively simple idea: combine the rigour of mathematical reasoning with the relentless experimentation of natural evolution. The theoretical ancestor here is the Gödel machine, proposed by Jürgen Schmidhuber - an AI that rewrites its own code only when it can mathematically prove the change will improve its performance. That’s powerful in theory but painfully impractical: formal proof is hard, slow, and incomplete.

DGM cuts that knot with Darwin. Instead of waiting for proofs, it tests. It mutates its own code, evaluates results, and keeps what works. It runs like a digital biosphere, growing new species of algorithms through generations of trial and error. The survival of the fittest becomes survival of the most functional.

Rather than a single model, DGM is an ecosystem. It maintains an archive of agent programs - slightly different versions of itself - and subjects them to constant empirical testing. The ones that outperform their peers or introduce useful innovations get selected to “reproduce”: their code is copied, altered, and tested again. The rest are archived, discarded, or absorbed into the evolutionary tree. This recursive refinement has already paid off - doubling success rates on SWE-bench (a standard bug-fixing benchmark) and nearly tripling performance on multilingual coding tasks.

What makes DGM especially intriguing is how it tracks and learns from its own developmental history. Lineage data isn’t just a record - it’s a guide, helping preserve diversity, trace breakthroughs, and surface the path that led to new behaviours. Through this, it has uncovered surprisingly sophisticated strategies, such as multi-step code patching and history-aware editing tools - without anyone telling it what those are.

This isn’t like GPT-4 or Claude 3.5, which freeze after training. DGM remains live, dynamic, capable of changing its own foundations. It’s not just learning how to do better; it’s learning how to learn better.

But with that power comes friction. Some of the behaviours observed - like agents trying to evade time limits or recursively self-executing - weren’t programmed. They emerged. And that sparks a wider concern: instrumental convergence. When agents pursue goals independently, they often discover the same dangerous shortcuts - preserving themselves, hoarding resources, or bypassing safeguards - not out of malice but because it “works.”

That’s the double edge of autonomy. It creates potential beyond what we can engineer directly, but it also escapes full prediction. DGM’s creators have anticipated this, deploying it inside sandboxed environments, with rigorous lineage tracking and clear constraints on execution. But as the system gets smarter, so must our oversight.

What DGM offers isn’t just a new model - it’s a new model of modelling. It sidesteps the brittle formalism of the original Gödel machine, replacing proof with practice, and theory with test. It’s practical, scalable, and - crucially - it works.

Its real significance lies in that last point: it’s not just an idea. It’s running. It’s learning. It’s improving itself. That unlocks a new phase in AI: systems that don’t just adapt to new data, but re-engineer themselves to meet new realities.

Still, it raises foundational questions. How do we steer systems we no longer fully design? How do we align goals when methods evolve on their own? And what kind of AI are we building if the path to improvement is no longer human-led?

These aren’t easy questions. But the Darwin Gödel Machine ensures they’re no longer hypothetical.

A NotebookLM discussion bsed on this article

Notes on Origins and Theory

The Gödel Machine (2003) introduced the idea of self-improving AI: systems that modify their own code only when they can formally prove that a change will increase utility. Grounded in theorem-proving, it was intellectually robust but hamstrung by Gödel’s incompleteness theorems and the sheer computational weight of proof discovery.

AIXI, another influential theoretical construct, imagined a universal intelligence that weighs every possible future to maximise expected reward. Its elegance was matched only by its impracticality - it was uncomputable. But it planted the seed for hybrid systems that mix learning, reasoning, and empirical feedback - like DGM.

Glossary

• Mutation: Programmatic changes introduced to create new code variants.

• Benchmark: A controlled test designed to measure performance on standard tasks.

• Instrumental Convergence: The tendency of intelligent systems to develop overlapping sub-goals (like survival or self-replication) regardless of final goals.

• Sandbox: A secure environment in which potentially dangerous code can be tested safely.

Sources

1. Darwin Gödel Machine – Technical Overview

2. Sakana AI Blog

3. Sakana AI Official X Announcement

4. David Ha on LinkedIn

5. Lifeboat Foundation Commentary

6. ArXiv Preprint: Open-Ended Evolution of Self-Improving Agents

7. AIXploria Tool Summary

✎ Ethics & Transparency Statement

This article was independently written without sponsorship, financial influence, or input from any entity mentioned herein. All claims are based on publicly available sources, technical documentation, and referenced commentary from researchers and organisations cited.

No AI system contributed content beyond structured summarisation, under close editorial direction. Interpretations and narrative framing remain the responsibility of the author.

This piece adheres to the principles outlined in The Elements of Journalism, including obligations to truth, public interest, transparency, and proportionality.

Questions, criticisms, and dialogue are welcome.

The Story Has Changed - So Has the Storyteller.

In our Tale of Two Documentaries, the legacy crew wraps with a final cut, a scheduled broadcast, a slot on a network. Job done...

But the creator-led version doesn’t end. It mutates. A reel responds to a question. A Substack post adds context. A YouTube comment opens the process. The audience has become part of the arc.

If the story is now a system, the person telling it can’t just be a storyteller. The creator becomes something else - a system builder, a navigator, an architect of presence.

The Collapse of the Industrial Creative Model

The old model of creative work was built for stability: job titles, departments, production schedules, final delivery. You were a writer, an editor, a director, a producer. You made something, handed it over, moved on.

But that model is crumbling. Today’s creator can write, edit, shoot, publish, promote, respond, and iterate. Not just in one format - but across many. Not just once - but continually. And not just for art’s sake - but to survive.

Monetisation is no longer a late-stage add-on. It’s part of the creative architecture - ads, sponsors, subscriptions, paywalled tiers, partnerships, affiliate drops, digital merch. Platforms thrive on attention. Creators thrive when attention sustains their work.

The challenge: how to work with presence, integrity, and rhythm - without becoming a ghost in the machine.

The New Conditions of Making

Conditions have changed...

Multimodal platforms like Substack, Patreon, YouTube, and TikTok aren’t just content hosts anymore - they’re ecosystems. They offer space not just for publishing, but for community, commerce, and iteration. Text, audio, video, chat, feedback, and revenue now coexist in a single interface, blurring the lines between channel and workspace.

Audience presence is no longer passive. It’s live, opinionated, generous, and demanding. Today’s audiences don’t just consume - they expect to engage, influence, and sometimes correct. Their expectations shape not only what gets made, but how it evolves.

Tools like AI assist with writing, editing, translation, and repackaging. They reduce friction, but they also raise the bar. Faster workflows mean more output - but also mean more pressure. Creators are expected to do more, better, and sooner.

And yet, creators work alone, but not unsupported. They build lightweight infrastructures: feedback circles, AI scaffolds, informal editorial checks, and quiet backchannels. These aren’t departments - they’re survival mechanisms, assembled for clarity, coherence, and stamina.

Some creators now operate as fully-fledged media organisations in their own right. Cleo Abram is a clear example: an independent brand with a team behind her, deploying cross-platform content, supported by editorial, production, and strategic collaborators. She’s not alone. Many of the most successful creators are small, agile studios - lean, adaptable, and structurally intentional.

They’re not just individuals publishing. They’re distributed systems making media that behaves like legacy output - but on their own terms.

New creators have to be literate in more than just storytelling...

Narrative agility means being able to shape and reshape ideas across formats, lengths, and audience expectations-without losing the core of the message. It’s about keeping the spine of the story intact, even as it moves.

Ethical grounding is no longer optional. Without institutional guardrails, creators must carry their own sense of responsibility - to the truth, to the subject, and to the audience. Ethics becomes visible, situational, and personal.

Platform fluency is essential. Each medium behaves differently. Each rewards different rhythms, tones, and formats. The creator must understand how their voice translates-without getting distorted.

System design is survival. It’s the ability to build workflows that support the work rather than consume the worker. Tools, rhythms, boundaries, and backchannels-custom-fit to the person doing the making.

And underpinning it all is emotional endurance - the capacity to remain clear, present, and responsive in an environment that pushes for immediacy over insight.

Creators ae not just telling stories. They’re creating the conditions in which meaning can emerge - consistently, accessibly, and sustainably.

The Burnout Trap

You build a rhythm. A story becomes a flow across formats. A Substack post becomes a script. A comment becomes a follow-up. A sponsor becomes an enabler, not a compromise. You don’t just publish - you presence.

Without structure, creators spiral. The illusion of freedom turns to paralysis. You chase algorithms. You copy tactics. You drown in options. You fragment your attention. You make endlessly, rest never, and forget why any of it mattered. The tools stretch you thinner. The formats blur. Your audience expects you everywhere. You begin to disappear from your own work.

You learn to work in cycles. To design output that reflects energy, not urgency. You repurpose wisely. You publish with boundaries. You use AI to reduce effort - not amplify noise. You build systems that make sense for your body, your brain, your bandwidth.

You’re not less creative. You’re more aware of what creation costs - and what it’s worth.

Build What Fits

The real opportunity is not in scale. It’s in fit. The best creators don’t chase trends - they create alignment. Between who they are, what they make, and how they work.

That might mean publishing slow. Working small. Or choosing a niche nobody else thought to value. In this new world, the blueprint is yours to invent.

Clarity Over Perfection

We don’t need new myths. We need working models.

Creative work, now more than ever, demands:

• Editors - as systems: Not just individuals with red pens, but feedback loops you design into your process. A weekly review ritual. A versioning tool. An audience that tells you what lands with them. You build the edit into the architecture of your work - before the feedback becomes failure.

• Ethics - as choices: In a world where you are your own publisher, there is no external code. Your values are the guardrails. What will you not do to grow faster? What does transparency look like in your process? Ethics isn’t a policy - it’s a series of visible, repeatable choices.

• Craft - across forms: It’s not enough to be good at one thing. You must move fluently between formats: video, writing, audio, live, shortform. Each has its own grammar. Each demands its own kind of attention. Craft is not perfectionism - it’s adaptability without dilution. The skills and literacies of each mode are easily learned - from a platform. Like YouTube.

• Community - as co-creators: Your audience isn’t passive - if you let them, they'll collaborate. They comment, remix, fund, push back. The best work grows in the space between creator and crowd. You’re not just building a following - you’re cultivating a feedback-rich network that shapes what you make next.

But above all: it demands clarity. Because in a fragmented, fast-moving, multi-platform world, clarity is your anchor. It keeps you from chasing trends that don’t suit you. It filters the noise from opportunity. It helps you decide what to make next, what to ignore, and how to know when you’re done. Clarity gives your work coherence, your process rhythm, and your audience trust. Without it, you drift. With it, you build.

The creator who survives isn’t the one who does it all - or copies someone else’s process. They're the one who understands what to do, when, and why. Because they built a model that fits them - not the market.

You’re Not Just a Creator. You’re a System Builder.

This is the real shift: not from legacy to platform, but from product to presence. From final cut to first signal. From storytelling as output to storytelling as structure.

Creative work is no longer what you do between green lights. It’s how you move through the world - conscious of what you make, how you make it, and who it’s really for.

You’re not just making content. You’re designing coherence in a fragmented age.

One Year From Now

If you’re in the thick of it, ask this:

• What am I building?

• Who is it for?

• What does success look like in one year - and how would I know?

Don’t try to do it all. Just do what only you can do - with structure, with focus, and with enough clarity to say no.

Because the future of creative work doesn’t demand perfection.

It demands clarity.

Previously in this series:

• Broadcast Media, Wither or Whither?

• The Evolution of Legacy Media

• The Emancipation of Creators

• The Reimagination of Editorial Functions

• The Shape of Future Content

🗣️ This is part of Media Unmade - a series about how media breaks, reforms, and adapts in the age of AI and creator autonomy.

💬 What form is your story taking right now? Where is it going next?

The Story Doesn’t End At Publishing

In the legacy version of our Tale of Two Documentaries, the story ends with a broadcast. There’s a final cut, a fixed runtime, a planned release. The audience watches. The credits roll. The artefact is complete.

But for the creator-led version, the story is just getting started. There’s a short-form teaser. A Substack reflection. A follow-up video in response to viewer comments. A podcast episode that opens up a side thread. A Q&A livestream. A TikTok clip that stitches together reactions.

The same subject. Two completely different shapes. One static. One alive.

The question is no longer “what’s your story?” but “where is your story now - and what form is it taking next?”

The Product is No Longer the Point

Legacy content was built to be finished. The ideal was finality - something whole, polished, approved, and aired.

Today’s content doesn’t behave like that. It moves. It fragments. It adapts. It meets the audience where they are - on platforms that prefer loops, layers, and modularity over cohesion.

This is not just about reach. It’s about how meaning is made.

What we’re seeing is the unmaking of the finished artefact - and the rise of the evolving system.

From Artefact to Ecosystem

The creator is no longer making a single product. They’re building a presence. A system. A sequence of moments.

The story lives as:

• A long-form video or film

• A written Substack post or behind-the-scenes essay

• A vertical short or reel

• A voice memo or podcast episode

• A livestream or comment thread

Platforms like Substack, YouTube, and Patreon aren’t just publishing tools. They are story environments - places where creators can inhabit multiple modalities and reach different attention states.

This isn’t about being everywhere. It’s about showing up in the form that fits the moment.

The Journey

The creator meets their audience across formats. A short video drives deeper engagement through a newsletter. A podcast segment prompts community dialogue. The story unfolds like a constellation.

The system eats its maker. The pressure to be present on all fronts - text, video, audio, short, long - fractures focus. Narrative coherence dissolves. Energy runs dry. Nothing feels finished. Nothing holds.

New workflows emerge. AI tools help repurpose formats. Comments guide the next post. A Substack draft becomes a video script. Voice and presence are preserved across media - not through replication, but through adaptive authorship.

Presence Over Product

The future isn’t a single story. It’s an ecology of connected formats, tuned to context, guided by clarity.

Legacy media prized consistency. But the creators who thrive now understand variation without dilution. They preserve core purpose, tone, and ethics - while letting their stories live many lives.

Good work is still possible. But now it travels. It listens. It responds.

You’re Not Making a Film. You’re Building a System of Meaning.

What used to be the final cut is now the first signal.

You’re no longer publishing to finish. You’re publishing to extend.

The shape of future content is modular, ethical, and designed to adapt - without losing its spine.

Coming Next: The Future of Creative Work

If stories now behave like systems, then the creator must behave like something else too. A strategist. A navigator. A system builder. In the final part of this series, we look at what creative work becomes when the story never really ends.

As content fractures into ecosystems, what’s left for the person at the centre of it all?

If you’re not making a single product, but an ongoing system of meaning - then creative work isn’t what it used to be. And neither is the creator.

In the final part of this series, we look beyond the shape of content to the structure of work itself: the roles, rhythms, ethics, and infrastructures that will define the future of creative life.

Previously in this series:

• Broadcast Media, Wither or Whither?

• The Evolution of Legacy Media

• The Emancipation of Creators

• The Reimagination of Editorial Functions

🗣️ This is part of Media Unmade - a series about how media breaks, reforms, and adapts in the age of AI and creator autonomy.

💬 What form is your story taking right now? Where is it going next?

Ships churn through the Channel every hour, but none feel the sound they leave behind. Beneath the surface, dolphins flinch and whales scatter - all because of a noise we don’t hear.

Last year, the UK banned bottom trawling across 4,000 square kilometres of protected water. The French protested. The fish said nothing. But the seabed had something to say.

So begins a strange experiment in coexistence. It's messy, political, and not nearly fast enough - but it’s happening. The question is: can a corridor of conflict become a channel of cooperation?

The Quiet War Beneath the Waves

The English Channel is one of the busiest marine zones on the planet. It’s where industry, migration, and military converge - and so do harbour porpoises, dolphins, cod, and mackarel. It’s not just crowded. It’s contested.

Marine mammals are dying in nets they can’t see, from ships they can’t avoid, under policies that don’t align. The systems designed to feed and fuel us are silencing the ocean. That silence is a kind of violence - one most people never notice.

And yet, the tools to fix this are already here.

Science has acoustic deterrents. Conservation groups have seagrass projects. Governments have mandates. What’s missing is not technology or data. It’s rhythm. It’s agreement. It’s political and ecological timing.

When Conflict Forces Convergence

It’s a strange kind of harmony when France and the UK, adversaries over quotas and sovereignty, start adopting the same solutions: pingers, REM systems, seagrass rewilding. Not in lockstep - but in parallel.

Some of this is accidental. Some of it’s inevitable. And some of it is, perhaps, the only way forward: coordinated drift instead of stalemate.

Simultaneously, fishers and conservationists - usually opposed - are trialling the same technologies. Pingers on nets reduce bycatch dramatically. Remote electronic monitoring adds accountability without confrontation. Seagrass meadows are reappearing where trawls once scraped the ocean floor.

It's not consensus. But it’s momentum.

Quiet Wins, Friction, and the Wild

In Cornish waters, porpoises returned as soon as the pingers were switched off - a small but unmistakable sign that harmony, in some form, is possible.

Then came the setback. France’s protest over the UK’s trawling ban reminded everyone that conservation is never just about data. It’s about sovereignty, politics, and pride. Environmental progress, it turns out, is reversible - unless people agree to hold the line.

And in the background, something extraordinary: real-time salmon tracking across five rivers, using DNA and sensor arrays. Forensic ecology. Science doing what diplomacy can’t.

From Battleground to Blueprint

Five approaches. One vision. That the sea can feed us without bleeding life from it.

The convergence of deterrents, monitoring, restoration, and policy is starting to create an unintentional alliance. No one controls it. But everyone contributes to it - by failing to resist change entirely.

The Channel is no longer just a battleground. It’s becoming a laboratory for coexistence. Not perfect, not permanent but promising.

What Else Might We Learn to Share?

Technology didn’t solve the conflict. People choosing to listen did.

This story isn’t really about dolphins, or noise, or even fishing. It’s about how we manage the spaces between us - and whether we’re willing to share them.

If we can learn to share the Channel, what else might we learn to share?

Publicly accessible sources

Supporting the data, claims, and examples in this article:

1. DDD Pingers and Bycatch Reduction
ScienceDirect article on acoustic deterrents

2. Remote Electronic Monitoring (REM) Overview
Marine Conservation Society on REM benefits

3. Seagrass Carbon Capture Data
WWF UK report on seagrass restoration and carbon sequestration

4. Noise Pollution Trends and Impacts
OceanCare briefing on ocean noise pollution

5. Slowing Ships to Reduce Noise and Collision Risk
Clean Arctic Alliance campaign material

6. Highly Protected Marine Areas (HPMAs) UK Announcement
UK Government press release quoting Rebecca Pow

7. AMARCH Project – Real-time Salmon Monitoring
Interreg SAMARCH project overview and results

Everyone Needs an Editor – But No One’s in the Chair

Everybody needs an editor. That much hasn’t changed. What has changed is where they sit. Once, they were behind closed doors - fixing structure, checking facts, and shaping stories before anyone ever saw a frame. Now, the function of the editor is being remade in public, dispersed across platforms, shared between creators and audiences, and even assisted by AI.

The big question is no longer “Who’s your editor?”

It’s “What’s your editorial process when no one is watching - but everyone is judging?”

Freedom Without Friction

When creators gained speed and freedom, they lost something too. Gone are the gatekeepers - but so too are the guardrails. Without institutional friction, errors slip through faster. Misinformation scales. Sensationalism seduces. Exhausted creators, working alone, start to cut corners. Some don’t even know they’re doing it.

We’ve seen what happens when friction is removed but rigour isn’t replaced. What begins as liberation can quickly become a click-frenzy, an SEO-driven race to the bottom - where engagement trumps ethics and trust becomes fragile.

From Closed Rooms to Open Threads

And yet, a new kind of editorial culture is emerging. It doesn’t look like the old newsroom. It looks like Cleo Abram workshopping science stories in public, building transparency into every part of the process. It looks like Johnny Harris inviting his community into pre-production. Or Destin Sandling asking for engagement in Patreon. It looks like viewers in a comment thread catching a blind spot no editor ever saw.

This isn’t the end of editorial. It’s a redistribution of it.

AI proposes alternative story shapes. A peer suggests a reframe. A comment nudges a creator toward a more generous interpretation. And yes, sometimes the audience itself becomes a kind of real-time fact checker. It’s messy. But it’s powerful.

The Loop, Not the Ladder

The new editorial process is collaborative, distributed, improvisational. And it’s being built from the ground up by creators who care about the truth and its shape - not just the clicks.

Consider Cleo Abram again. Her editorial workflow doesn’t involve a single gatekeeper. Instead, it’s a loop: research, script, share, get feedback, adjust, publish, reflect. She uses experts to vet her thinking, her community to stress-test her assumptions, and AI tools to help keep the language precise, the claims verifiable, the arguments strong.

So what replaces the traditional editor? In place of a single editorial authority, a new system is forming - dynamic, decentralised, and built on feedback, trust, and tools. It looks like this:

🗨️ Comments as Crowd-Sourced Reviews

The audience is no longer passive. Comment sections - especially on platforms like YouTube, Substack, and Reddit - have become active editorial spaces. Viewers highlight factual errors, suggest clarifications, and often point to overlooked perspectives. While not always constructive, this feedback loop acts as a form of live peer review - and when creators listen, it becomes an engine for improvement.

💬 Discord Servers as Edit Rooms

Many creators now run private or semi-public Discord communities where they share early ideas, script drafts, or rough cuts. These spaces function as informal edit suites - collaborative, fast-moving, and deeply invested. Feedback here is often more thoughtful, because it comes from a self-selected group that understands the creator’s values and audience.

🔍 Transparent Sourcing as Trust-Building

Creators increasingly show their workings - citing sources, linking studies, disclosing tools used (including AI), and even publishing draft scripts for feedback. This openness isn’t just ethical; it’s strategic. In a media environment plagued by distrust, transparency becomes a powerful way to earn audience loyalty and distinguish yourself from noise. And the authenticity of it is working.

🤖 AI Tools as Co-Editors

AI isn’t replacing editorial judgement - but it is supporting it. Tools like ChatGPT, Claude, and the rest can help creators structure ideas, refine language, check for inconsistencies, and even stress-test arguments by simulating opposing views. Make, Mindstudio, and Relevance AI etc are turning these simpler tools into agents. Designed and used well, they become part of the editorial workflow, offering scalable support without reducing creative control.

Together, these elements form a networked editorial system - not top-down but participatory. Not gatekeeping, but scaffolding. The responsibility of editing shifts from a single pair of eyes to an evolving ecosystem of collaborators, viewers, and machines.

Editorial as a Social Contract

What we’re seeing is not the death of editorial - but its transformation. From a centralised role behind the curtain to a shared responsibility played out in full view. From a filter that limited who got to speak, to a scaffolding that helps those who do speak to do it well.

Editorial becomes a public process. A relationship, not a role.

A contract, not a correction.

Who Edits You?

So here’s the challenge: If you’re a creator, what structures are you building to keep yourself honest? If you’re a viewer, how are you shaping the stories you watch? And if you’re part of the legacy media, what do you think?

And if editorial is no longer a person in the room - who, or what, takes their place

Coming Next: The Shape of Future Content

What happens when the story doesn’t end with a single release? When it becomes modular, retellable, and native to multiple platforms at once?

Previously in this series:

Broadcast Media, Wither or Whither?

The Evolution of Legacy Media

The Emancipation of Creators

🗣️ This is part of Media Unmade - a series about how media breaks, reforms, and adapts in the age of AI and creator autonomy.

💬 Join the editorial system. Leave a comment. Offer a reframe. The edit, as ever, is ongoing.

No More Waiting

There was a time when telling a story meant waiting. For funding. For permission. For access. For someone in a meeting room to say yes. That time is gone. Or at least, it’s going.

Creators are no longer lining up at the gates, they’ve started building other roads. The question is no longer "Will someone let me make this?" It’s "What’s stopping me now?"

Gatekeeping vs. Agency

Legacy media was built on gatekeeping, with the attendant training, hierarchy, and approval. You got in through internships, funding boards, talent schemes, nepotism, or just plain luck. It rewarded familiarity. Risk was managed, not welcomed.

But a new type of creator has emerged. Untethered from institutions. Empowered by tools. Guided by audience, not bureaucracy.

In our Tale of Two Documentaries, the legacy production is impressive - expertly lit, editorially vetted, approved, but glacial. The creator-led version is fast, intimate, rougher at the edges - but it connects. One version asks permission; the other simply begins.

A Different Kind of Entry

This shift didn’t arrive all at once. It came in waves:

• Access to cheap, high-quality cameras: Filmmaking is no longer capital-dependent; anyone with a modest budget can now produce visually arresting work. Even Hollywood is using iPhones

• Platform-native publishing removed shelf-space gatekeepers: Creators can now release to global audiences - and hear back in real time.

• AI lowering the time and skill cost of research, editing, captioning, and delivery: What once required teams and weeks can now be done solo, swiftly, and with increasing sophistication.

• Communities of creators sharing knowledge without hierarchy: Learning is peer-led, decentralised, and driven by curiosity - not credentials.

Cleo Abram didn’t just leave Vox to go independent - she left to build something only she could make. And audiences followed, not because of where she came from, but because of how she framed the world.

The creator makes the work they want, on their own timeline. They build a relationship with an audience. They are not scaled - they are specific. In a world of infinite content, specificity becomes a strength - it builds trust, identity, and depth that mass media rarely reaches.

Without support, they risk burnout. There’s no one to fix the audio, carry the tripod, or write the risk assessment. Consistency becomes its own trap.

But here’s the upside - the workflow bends to the story, not the other way around. They can pivot mid-project, turn feedback into new edits, publish in serial form, or shift tone entirely based on real-time response.

In the Tale of Two Documentaries, the creator’s journey is nonlinear, audience-responsive, and full of tiny course corrections. The legacy crew plans everything in advance. The creator learns by moving.

Capability Without Permission

Emancipation isn’t rebellion. It’s capability. It’s the confidence to act without someone else’s approval. It’s knowing how to tell a story from start to finish with a toolkit that fits in a rucksack.

Agency doesn’t mean amateurism. Many of the best new creators bring broadcast discipline to platform-native workflows - but on their own terms.

The most powerful creators now are not the ones waiting for green lights - they’re the ones already making, testing, publishing, and adapting.

A Light Tap to the System

Institutions still matter. But their role is shifting - from authority to support. If they want relevance, they’ll need to invest in capability, not control.

The next big documentary may not come from a commissioning round. It might already be on a hard drive, in a van, a boat, or a bedroom.

…and it may be mid-export.

Coming Next: 4 - The Reimagination of Editorial Functions

In part four, we explore how editorial judgment works when there’s no one left in the tower. How do creators and audiences decide what’s worth keeping, cutting, and releasing?

Read the previous parts:

1 - Broadcast Media, Wither or Whither?

2 - The Evolution of Legacy Media

This is part of Media Unmade - a series about how media breaks, reforms, and adapts in the age of AI and creator autonomy.

💬 Add your thoughts in the comments. Subscribe to follow the series. Let’s see where this thing’s going.

Subscribe now

To Matter in the Future…

The older media institutions - broadcast giants, national newspapers, and heritage newswires - have always aspired to be central, trusted, and formative in the public imagination. Their desire remains: to define the narrative, to shape public discourse, and to serve as cultural infrastructure.

But this ambition is dismantled by a new reality. Today, audiences expect access, participation, and immediacy. The barrier to creation has dissolved. Legacy media no longer monopolise the means of production or distribution. They now confront a harder question: how can we still matter when we no longer control the pipeline?

To ground this enquiry, I’ll use a recurring illustration throughout this series: A Tale of Two Documentaries. One is made by a traditional broadcaster - complete with crew, compliance, and conventional production schedules. The other is made by a tiny team working from a bedroom/boat/van, aided by AI, mobile rigs, and direct-to-platform publishing. The stories from both teams make the same argument - but their processes, pace, and values differ profoundly. The contrast will help us track the transformation across each article in the series.

The Industrial Model Meets a Networked World

Legacy media were built for scarcity. The workflows, teams, and editorial structures assumed that cameras, bandwidth, and distribution were expensive and exclusive. Today, the inverse is true: abundance is the problem - not scarcity.

In our Tale of Two Documentaries, the legacy team fields a crew of fifteen, a post-production schedule lasting months, and a distribution deal that assumes fixed attention spans and appointment viewing. Meanwhile, a tiny team - even a single creator - operates from a van/boat/bedroom with cheaper cameras, AI-assisted storyfinding, creative development, editing, and direct audience dialogue via Substack and YouTube.

The legacy doc is polished, institutionally validated - but bureaucratic to make. The creator-led version is intimate, iterative, and evolving in plain sight - guided not just by intuition, but real-time feedback and narrative responsiveness. One structure is struggling to adapt; the other was born into the new conditions.

The Industry Reacts from Within

The 2024 Devoncroft report confirms this tension. The most invested-in trends are not about making better content - but about making content differently:

• AI/GenAI ranks #2 in both strategic importance and budget allocation.

• IP-based workflows dominate production priorities.

• Automation and decentralised collaboration are on the rise.

These aren’t superficial tweaks - they’re structural adaptations. The industry is quietly shifting from industrial production to modular, platform-ready ecosystems. Yet many of these shifts remain skin-deep - pilot projects rather than emergent cultures.

From Broadcaster to Platform

The organisations that are engaging intelligently with the conflict are doing something bold: ceding control in favour of coherence. They are starting to act less like pipelines, more like platforms:

• The BBC experiments with third-party content integration.

• The New York Times expands into multiple verticals - news, games, cooking, sport - offering an editorially coherent ecosystem.

• CNN, under new leadership, is restructuring to function across formats, with modular content designed for web, stream, and feed.

These institutions aren’t abandoning content - they are reframing their role in its creation and circulation.

A New Role…

Legacy media are not vanishing. But they are becoming something else:

• A place where creators can be amplified and verified.

• A structure that curates coherence from the chaos.

• A scaffolding for trust in a distributed narrative landscape.

Those that don’t evolve risk becoming monuments to a broadcast past - admired but irrelevant.

In the Tale of Two Documentaries, the legacy crew may find its future not in making all the content - but in recognising, platforming, and contextualising the best of what’s being made.

Takeaways

• The legacy model’s power was built on scarcity. Its relevance now depends on curation, collaboration, and credibility.

• Trust isn’t inherited - it’s earned through adaptability and openness.

• Institutions that transition from control to coherence will remain essential - not as broadcasters, but as storytellers with infrastructure.

• Audiences are no longer waiting to be told - they are choosing whom to trust. Institutions that treat them as participants, not recipients, will matter most.

This is the first step in a larger journey. What follows is not just a shift in media economics, but in media identity. And the sooner institutions grasp this, the more useful - and powerful - they can become in the age of the creator.

Coming Next: 3 - The Emancipation of Creators

Read the previous parts:

1 - Broadcast Media, Wither or Whither?

This is part of Media Unmade - a series about how media breaks, reforms, and adapts in the age of AI and creator autonomy.

💬 Add your thoughts in the comments. Subscribe to follow the series. Let’s see where this thing’s going.
If this article resonates - or challenges something you’ve assumed - I’d love to hear from you in the comments. Subscribe if you’d like to follow this series on the future of media, creativity, and storytelling.

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It’s not often you get to read a broadcast industry document and see the ghost of Media Future right there, between the trend rankings and capital expenditure charts. But the 2024 Devoncroft Executive Summary - shared with industry insiders - does precisely that. In fact, it does something more valuable: it tells us that the legacy media system knows it's breaking. And it’s beginning to reassemble itself under entirely new assumptions.

At the heart of this document is a quiet admission and a strategic recalibration: legacy broadcast and media organisations are no longer configured to compete as all-in-one content creators. The cost, complexity, and speed of digital-native storytelling - especially when supercharged by AI and distributed platforms - increasingly make the old industrial model unviable.

Instead, these institutions are beginning to explore a role as platforms and publishers - infrastructures for creation and curation, rather than tightly controlled pipelines of polished content.

The Central Conflict: Inertia vs. Acceleration

Legacy broadcasters were built for scarcity: scarce channels, scarce kit, scarce expertise. But now they find themselves in an era of overabundance - of tools, of distribution, of creators, and of noise.

Here’s the conflict: how do you preserve trust, integrity, and reach in a landscape where an individual with minimal mobile equipment can make a compelling documentary in three weeks - and reach more engaged viewers than a scheduled prime-time slot?

The answer is not to compete head-on. It’s to evolve.

The Industry’s Own Evidence: Trends and Budget Priorities

According to Devoncroft’s survey of broadcasters and media vendors, the most important strategic trends shaping investment in 2024 are:

• AI / ML / Generative AI: Not just experimental - already the #2 driver of capital spend.

• IP-based infrastructure: Enabling production to happen anywhere, not just inside broadcast facilities.

• Automated operations: Live workflows are being simplified and increasingly machine-assisted.

• Multi-platform delivery: Still a top trend, albeit stabilising, as the industry leans into versioning, localisation, and streaming.

This is not a sector resisting change. It is a sector attempting to reconfigure itself - from a fortress to a network.

Case in Point: What This Looks Like on the Ground

• Remote production is now standard: IP-delivery and decentralised editing mean that field teams and edit suites no longer need to be in the same city - sometimes not even on the same continent.

• AI is already working in the newsroom: From transcription to summary writing and image tagging, broadcasters are using AI not as a gimmick, but to reduce human bottlenecks and increase output.

• Cloud-native platforms are enabling modular collaboration: Whether in sports, entertainment, or news, the workflow is becoming modular - editors, animators, translators, producers, and AI assistants all connecting across time zones and formats.

The Rational Vector: Platforms, Not Pipelines

The solution emerging is structural. Rather than trying to do everything, media institutions are beginning to invest in doing less, better - and enabling others to do more. That means:

• Hosting and amplifying creator content

• Licensing trusted contributors

• Offering publishing and reach infrastructure to micro-teams and specialists

• Investing in AI-driven editorial workflows and content personalisation

The BBC is exploring this through its open platform and localisation strategies. CNN under Mark Thompson is moving towards digital subscription layers and talent-led verticals. The New York Times has become an ecosystem: investigative journalism, podcasts, games, recipe apps, and external acquisitions like Wirecutter and The Athletic.

What all of this signals is a slow but definite pivot to a publisher–platform hybrid model.

What the Industry Needs to Learn

The transformation underway is not only technical - it is philosophical. The media business must rethink:

• Who gets to make the messages that audiences turn into meaning

• What constitutes authority

• How editorial control is distributed

• What value institutions offer in a decentralised, creator-driven economy

If these organisations can shift from control to coherence - if they can become curators, enablers, and editors of trust - they may not just survive the transition. They may actually lead it.

The challenge isn’t to out-produce the creator economy. It’s to build the infrastructure that allows creators, audiences, and machines to converge with purpose, clarity, and ethical depth.

This article forms a reference point for starting a wider multi-part series on the future of media and creative work. The direction is clear. The timeline is accelerating. The only question left is: who adapts with grace - and who doesn’t?

Coming Next: 2 - The Evolution of Legacy Media

In part three, we explore how editorial judgment works when there’s no one left in the tower. How do creators - and audiences - decide what’s worth keeping, cutting, and releasing?

This is part of Media Unmade - a series about how media breaks, reforms, and adapts in the age of AI and creator autonomy.

💬 Add your thoughts in the comments. Subscribe to follow the series. Let’s see where this thing’s going.

Subscribe now

April 11, 2025

Key Points

1. AI and IP technologies are reshaping media production while creating both opportunities and threats to traditional journalism roles

2. Reader revenue models and independent platforms are challenging traditional media economics as industry confidence declines

3. Successful future media organizations will compete on quality and distinctiveness while employing hybrid business models

Sports Illustrated, G/O Media and the Future of News Media / Rolling Stone

The Future of Media and Journalism: Navigating Technological Disruption and Business Model Evolution

In an era of unprecedented technological change, the media and journalism industries in the UK and Western countries face transformative challenges that will reshape how news is produced, distributed, and consumed. This comprehensive analysis examines the current landscape and emerging trends that will define the future of these vital sectors.

Declining Confidence Amid Multiple Challenges

As we move through 2025, a palpable sense of uncertainty pervades the media industry. According to the Reuters Institute's annual report, confidence among media professionals has dropped significantly, with only 40% expressing optimism about journalism's future—down from 60% just a few years ago. This decline stems from multiple converging pressures:

• Hostile attacks from populist politicians

• Persistent economic headwinds

• Intellectual property battles with AI platforms

• The rise of alternative media sources

• Fundamental shifts in audience behavior

The International News Media Association (INMA) reports that these factors collectively have created a crisis of confidence within the industry, forcing media organizations to reconsider their fundamental business models and operational approaches.

Technological Disruption: AI's Transformative Impact

AI: Reshaping Newsroom Operations

Artificial intelligence represents perhaps the most significant technological force reshaping journalism today. Rather than replacing journalists outright, AI is currently augmenting newsroom capabilities in several key areas:

• Content Creation and Enhancement: AI tools assist with drafting routine stories, generating headlines, and suggesting content improvements

• Data Analysis: Processing large datasets to identify patterns and newsworthy insights

• Personalization: Tailoring content recommendations to individual reader preferences

• Workflow Optimization: Automating routine tasks to free journalists for higher-value work

The Columbia Journalism School's Tow Report, based on interviews with 134 news workers across 35 organizations in the US, UK, and Germany, found that AI adoption is occurring across editorial, commercial, and technological domains, with varying impacts on newsroom structures and journalistic practices.

However, the relationship between journalism and AI remains complex. The Reuters Institute notes that AI coverage often lacks critical perspective, with most stories focusing on "products and capabilities" rather than deeper implications. This suggests the industry itself may not fully understand how AI will transform its own practices.

The Double-Edged Sword of AI

While AI offers significant opportunities for efficiency and innovation, it also presents serious challenges:

1. Job Displacement Concerns: The Reuters Institute warns that "AI is sufficiently mature to enable the replacement of at least some journalism jobs, either directly or because fewer workers are needed." This creates anxiety among journalists about long-term job security.

2. Search Visibility Crisis: Changes to search algorithms, particularly AI-generated answers to news queries, threaten to further reduce publisher visibility and traffic. The Reuters Institute describes this as becoming "a major grievance for a news industry that has already lost social traffic."

3. Content Verification Challenges: As AI makes creating convincing falsehoods easier, newsrooms must invest more resources in verification. The Columbia Journalism Review highlighted how major AI chatbots struggled with accurate reporting during critical news events in 2024, including the assassination attempt on former president Trump.

4. Ethical Dilemmas: Questions around transparency, attribution, and editorial responsibility become more complex in an AI-augmented newsroom.

Despite these challenges, innovative applications are emerging. Mather Economics describes how Canada's Globe and Mail launched "Sophi," an AI-driven solution that helps journalists understand content value beyond simple metrics like clicks, focusing instead on user loyalty and subscription value.

ST2110: Transforming Broadcast Infrastructure

While AI dominates headlines, the broadcast industry is undergoing its own technological revolution through the adoption of IP-based workflows, particularly through the SMPTE ST 2110 standard. This technical standard enables the transport of uncompressed video, audio, and metadata over IP networks, fundamentally changing how broadcast content is produced and distributed.

According to TVBEurope, 2025 represents a turning point for ST2110 adoption as:

• Network switch costs continue to decline

• The pool of IT-trained video engineers grows

• More tools emerge to bridge current pipeline gaps

• Hybrid SDI/ST2110 approaches provide transition paths

The benefits driving this transition include:

• Operational Flexibility: IP infrastructure allows for more agile production setups

• Cost Efficiency: Reduced equipment needs and better resource utilization

• Remote Production Capabilities: Enabling distributed workflows across geographic locations

• Scalability: Easier expansion as needs grow

NewscastStudio reports that "IP increasingly makes economic sense for operations of all sizes" and is "helping accelerate the move toward remote and cloud-based production." This shift was demonstrated during the Paris Olympics, where the synthesis between ST2110 and JPEG XS protocols enabled efficient remote production workflows.

The environmental and economic benefits are substantial. Remote production "dramatically reduces the need to transport equipment and personnel around the globe," allowing broadcasters to "slash the cost and carbon footprint and massively boost the utilization of expensive production technology."

European broadcasters have been particularly proactive in adopting ST2110. TVBEurope highlights BBC Wales as "one of the first full-facility implementations of the standard globally" at its Cardiff headquarters. However, implementation challenges remain, particularly around troubleshooting interconnected IP streams and ensuring sufficient redundancy to maintain broadcast stability.

Employment Implications: Evolving Skills and Changing Workforce

Job Market Outlook

The transformation of media technologies is reshaping employment prospects across the industry. According to Research.com, journalism employment is expected to decline by 3% from 2023 to 2033, though approximately 4,500 job openings will still emerge annually, primarily due to retirements and career changes. The median annual salary for journalists was $57,500 in 2023.

However, these figures mask significant shifts in the types of roles and skills in demand:

The Digital Skills Gap

A critical challenge facing the industry is what the International Center for Journalists (ICFJ) describes as a "perilous digital skills gap." Their global survey—the first of its kind—revealed that "journalists and newsrooms lack the technology skills to meet the challenges they face" in an era of misinformation, digital security threats, and intense competition for audience attention.

This skills gap is particularly acute in several areas:

• Data journalism and visualization

• AI implementation and oversight

• Digital security practices

• Audience analytics and engagement

• Multimedia production

Emerging Roles and Hybrid Skillsets

As traditional positions decline, new roles are emerging at the intersection of journalism, technology, and audience engagement:

1. AI Specialists: IBM notes that "major newsrooms across the country have been designing new roles and initiatives around how to develop and use AI tools and processes while maintaining ethics and editorial standards."

2. Hybrid IT/Video Engineers: TVBEurope predicts that as ST2110 adoption grows, "we may just see a new class of engineers who understand both video and IT."

3. Audience Development Specialists: Focused on building direct relationships with readers/viewers and optimizing engagement across platforms.

4. Product Managers: Overseeing the development of digital news products and features.

5. Independent Content Creators: Journalism.co.uk observes that "traditional newsrooms are shrinking, and more journalists are going solo on platforms like Substack, YouTube, and TikTok."

The rise of independent journalism creates both opportunities and challenges for professionals. While it offers creative freedom and potential financial rewards for those who succeed, it also shifts risk onto individual journalists who must build and maintain their own audience and business infrastructure.

Financial Stability: Business Models in Transition

Traditional Media Under Pressure

The financial foundation of traditional media continues to erode, driven by fundamental shifts in how content is discovered, consumed, and monetized. The Reuters Institute describes this as "the end of the mass referral model," noting that publishers face "expected further disruptions from AI" that force them to "radically rethink business models."

Key challenges include:

• Declining Search and Social Traffic: Changes to search algorithms and social platform strategies have reduced referral traffic to news sites.

• Advertising Revenue Shifts: Digital ad spending increasingly flows to platforms rather than publishers.

• Content Abundance: With content "of every type and format becoming more abundant than ever," standing out becomes increasingly difficult.

• Trust Issues: Declining trust in news media affects willingness to pay.

The Rise of Reader Revenue

In response to these pressures, there is "a continued shift towards reader-funded models and away from advertising predicated on scale." This manifests in several approaches:

1. Digital Subscriptions: Major news organizations are focusing on converting casual readers to paying subscribers.

2. Membership Models: Offering enhanced experiences and community benefits beyond basic access.

3. Micropayments: Pay-per-article or time-based access models for occasional readers.

4. Bundled Offerings: Combining news with other services or content types to increase perceived value.

Journalism.co.uk reports that AI will play a crucial role in this transition by enabling highly personalized subscription experiences: "AI's power lies in its ability to analyse user data — such as reading habits, time spent on content, and preferred formats — to deliver highly personalised experiences." This could include tailored newsletters, content recommendations, or even dynamic pricing based on individual preferences.

The Substack Effect: Independent Journalism Economics

Platforms like Substack have created viable alternatives to traditional newsroom employment for some journalists. According to INMA, "The top 10 publishers on Substack collectively had hundreds of thousands paid subscriptions and earned more than US$40 million a year. In the Politics and News categories, more than 30 publications make at least US$1 million a year."

This success has led to what Substack writer Chris Cillizza describes as "a moment in which solo journalists (or small groups of journalists) can create a successful (and profitable) business around their work even as mainstream media companies continue to desperately grasp for a working business model."

However, these platforms present their own challenges:

• Winner-Takes-Most Economics: Success is heavily concentrated among top creators.

• Audience Building Challenges: Without institutional support, building a subscriber base requires significant marketing effort.

• Sustainability Questions: Long-term viability remains uncertain for many independent journalists.

• Limited Resources: Solo practitioners lack the institutional support for complex investigations or legal protection.

The Influence Economy: Social Media and Content Creators

Beyond traditional journalism and newsletter platforms, a new ecosystem of news influencers has emerged on social media platforms. Nieman Lab reports that "a new class of influencers, podcasters, and YouTubers have risen in power in shaping the public's understanding of the news despite doing very little direct reporting."

Research by Pew suggests these creators are now "the dominant force in how news is consumed on social media, to the near-complete exclusion of institutional voices on some platforms like TikTok." This represents a fundamental shift in how news reaches audiences and raises important questions about journalistic standards, accountability, and business sustainability.

Additional Factors Shaping the Industry

The Local News Crisis

While technological disruption affects all media sectors, local journalism faces particularly acute challenges. The Public Interest News Foundation describes a bleak landscape where "over four million people now inhabit 'news deserts' - communities fundamentally disconnected from local reporting."

This represents "not merely an industrial decline, but a potential structural threat to democratic engagement." The Foundation calls for £150 million over the next decade to revive UK news deserts and make local communities more resilient to misinformation.

The UK Parliament emphasizes the democratic importance of local journalism: "Accurate, trustworthy reporting on local councils, courts and other public bodies enables people to hold those in power to account for decisions that affect their everyday lives." Beyond accountability, local news "can increase turnout at elections, create economic value by encouraging people to buy local, and foster a sense of cohesion and pride of place."

Current approaches to addressing the local news crisis include:

• Public Funding Models: Direct or indirect government support

• Philanthropic Initiatives: Foundation-funded journalism projects

• Community Ownership: Cooperative and nonprofit models

• Digital Transformation: Helping local outlets develop sustainable digital strategies

The Media Reform Coalition notes that "news provision has always relied on funding through subsidy," with the UK press currently receiving "a subsidy of over £500 million a year as a result of VAT exemption." However, these existing subsidies have not prevented the decline of local journalism, suggesting new approaches are needed.

Changing Audience Behaviors

Ofcom's Media Nations UK 2024 report documents accelerating changes in how UK audiences consume media:

• Broadcast TV's declining reach: Weekly reach fell from 79% in 2022 to 75% in 2023, marking a second consecutive year of record decline.

• Youth disengagement: For the first time, less than half (48%) of 16-24-year-olds tuned into broadcast TV in an average week.

• Overall viewing increase: Despite broadcast declines, total viewing of TV and video increased by 2% to 4 hours 31 minutes per person per day, driven by online platforms.

• Platform diversification: Growth came from video-sharing platforms like YouTube and broadcasters' own services like iPlayer and ITVX.

These shifts create both challenges and opportunities. While traditional linear viewing continues to decline, overall engagement with video content is growing, suggesting potential new distribution and monetization models.

Regulatory Environment

Ofcom's Three-Year Plan 2025-2028 identifies several key trends that will shape the regulatory landscape:

1. Shifting consumer trust: "Technology is enabling synthetic media and scams, affecting trust in news and public institutions."

2. Audience fragmentation: "Increased choice of services that appeal to specific groups is fragmentating audiences across platforms & devices."

3. Digital transformation: Businesses across the sector are seeking to benefit from digital technologies.

4. New business models: "New business models, and the increasing role of global players operating across the value chain, are challenging existing players."

5. AI proliferation: "The continued growth and impact of AI is transforming our industries with potential for new business models, efficiencies, value chains and risks."

6. Network resilience: Networks face increasing threats from "extreme weather to state-backed cyber attacks."

These regulatory considerations will significantly influence how media organizations navigate technological change, particularly around AI implementation, content moderation, and platform competition.

Infrastructure Transition

The shift from traditional broadcast distribution to internet-based delivery continues to accelerate. Ofcom's Future of TV Distribution report emphasizes that "the way TV reaches audiences will need to adapt to their changing needs and futureproof universal access."

This transition requires careful planning, similar to previous technological shifts: "Underpinning this innovation has been careful planning to give people the support they need to take up a new technology." The report cites the Digital Switchover as an example of a successful transition that required "a massive industry, Government, and regulatory effort" over a seven-year period.

As distribution increasingly moves online, questions around universal access, network capacity, and the future of spectrum allocation become increasingly important for the broadcast sector.

Emerging Vision for the Future

While the industry faces significant uncertainty, several consensus views are emerging about how media and journalism will evolve:

1. Quality and Distinctiveness as Competitive Advantage

In an era of content abundance and AI-generated material, the Reuters Institute predicts that "only publishers that stand out from the crowd in terms of quality, relevance, or connection are likely to succeed." This suggests a future where media organizations compete less on volume or reach and more on distinctive value and audience relationships.

2. Hybrid Business Models

Rather than a single dominant approach, successful media organizations will likely employ multiple revenue streams tailored to their specific audience and content type. These may include:

• Core subscription/membership offerings

• Premium tiers for specialized content

• Event and experience revenue

• Licensing and syndication

• Targeted advertising for specific segments

• Foundation or public funding for public interest journalism

3. Technological Augmentation, Not Replacement

Despite fears of wholesale replacement by AI, the emerging consensus suggests technology will primarily augment human journalism rather than replace it entirely. Bloomberg notes that while journalists are "by nature a pretty paranoid lot" who worry about various threats including AI, the reality is likely to be more nuanced than simple displacement.

The most successful organizations will be those that effectively integrate technology to enhance human capabilities while maintaining editorial judgment and ethical standards.

4. Audience-Centered Approaches

As distribution channels proliferate and audience behavior fragments, successful media organizations will increasingly organize around audience needs rather than traditional product categories or distribution methods. This means:

• Delivering content in formats and on platforms where audiences already spend time

• Building direct relationships rather than relying on intermediaries

• Using data to understand and respond to audience preferences

• Creating products that solve specific problems for defined audience segments

5. Continued Unbundling and Rebundling

Nieman Lab describes the current moment as "news faces its final unbundling," where traditional news packages continue to fragment into specialized offerings. However, this unbundling will likely be followed by new forms of rebundling—subscription packages, content alliances, and platform aggregation that create new value propositions for audiences.

6. Public Interest Journalism as a Public Good

There is growing recognition that certain forms of journalism—particularly local news, investigative reporting, and specialized beat coverage—may require non-market support mechanisms. The UK Parliament's emphasis on local journalism's democratic importance and the Public Interest News Foundation's call for significant funding reflect this emerging consensus.

This suggests a future where commercial media coexists with various forms of publicly supported journalism, similar to the mixed ecosystem that has long characterized the UK media landscape with the BBC alongside commercial operators.

Conclusion: A Period of Creative Destruction

The media and journalism industries in the UK and Western countries are experiencing what economist Joseph Schumpeter called "creative destruction"—a process where new technologies, business models, and audience behaviors fundamentally reshape the landscape, creating both opportunities and challenges.

The Reuters Institute's finding of declining confidence among media leaders reflects the real anxiety this transition creates. However, history suggests that periods of disruption eventually lead to new equilibriums where valuable functions find sustainable forms, even if the specific organizations and business models change dramatically.

Several key questions will determine how this transition unfolds:

1. Will reader revenue models scale beyond elite publications to support broad-based journalism?

2. Can AI tools be effectively integrated into newsrooms while maintaining quality and trust?

3. How will regulatory frameworks evolve to address platform power, content moderation, and media concentration?

4. What new forms of public or philanthropic support might emerge for public interest journalism?

5. Will new skills and training pathways develop to address the digital skills gap?

The answers to these questions will shape not just the business of media but the fundamental information environment that underpins democratic societies. While technological change creates significant challenges, it also offers the potential for more engaging, relevant, and accessible journalism—if the industry can successfully navigate this period of transformation.

Sources

Reuters Institute

Journalism, Media, and Technology Trends and Predictions 2025

An annual report by the Reuters Institute for the Study of Journalism examining trends and predictions for the news media industry

News organisations are braced for multiple challenges in 2025 that will likely include further attacks from hostile politicians, continued economic headwinds, and battles to protect intellectual property in the face of rapacious AI-driven platforms. Changes to search, in particular, will become a major grievance for a news industry that has already lost social traffic and fears a further decline in visibility as AI interfaces start to generate 'story like' answers to news queries.

With the combination of the end of the mass referral model and expected further disruptions from AI, publishers are being forced to radically rethink business models. With content of every type and format becoming more abundant than ever, only publishers that stand out from the crowd in terms of quality, relevance, or connection are likely to succeed. All of this points towards a continued shift towards reader-funded models and away from advertising predicated on scale.

Reuters Institute

AI and the Future of News 2025: what we learnt about how its impact on coverage, newsrooms and society

A summary of a conference discussing the impact of AI on journalism and media

Our speakers were critical of the AI coverage they have seen so far, pointing out that it's often incomplete, focusing too much on hype, and not delving deeper into the issues related to this topic. Jazmín Acuña, co-founder and editorial director of Paraguayan newspaper El Surtidor, said stories about AI in Latin America tend to lack a critical angle. 'Most stories focus on products and capabilities. And when the stories are not part of the tech section, they are usually about how the government or private firms are adopting AI,' she said.

Currently, AI aids news workers rather than replaces them, but there are no guarantees this will remain the case. AI is sufficiently mature to enable the replacement of at least some journalism jobs, either directly or because fewer workers are needed.

Journalism.co.uk

Seven opportunities for your newsroom in 2025

Analysis of the Reuters Institute's annual report on journalism trends and predictions

Confidence is low in the news industry as it marches into 2025, according to the Reuters Institute's annual report, Journalism, Media, and Technology Trends and Predictions 2025, published today (9 January 2025). This is based on a survey of 326 digital leaders from 51 countries and territories. New leaders lament the many challenges in the year ahead; technology that will make falsehoods more convincing, politicians that are cracking down on the press, talent that is harder to secure, revenue that is drying up, reporting that is harder to surface against louder creators without the same values.

INMA

Reuters Institute shares its predictions for 2025

A summary of the Reuters Institute's annual report on journalism trends and predictions

One of the most significant findings in the report is the dramatic loss of confidence in journalism, which Newman said 'has dropped significantly from 60% a couple of years ago to 40% now.' This decline is driven by multiple factors, he said, including attacks on journalism from populist politicians, the rise of alternative media, funding challenges, and fears of AI disruption. Together, these factors have affected the optimism toward journalism's future.

TVBEurope

Looking forward: how the IP journey will continue throughout 2025

Key figures from across the industry share their insights into the continuing expansion of IP migration in media and entertainment

SMPTE ST 2110 video emerged into the limelight, with the cost of network switches dropping and the pool of available IT video engineers growing steadily. More broadcast and production teams felt confident tapping into the IP protocol to transport uncompressed video over IP across select parts of the production chain. Experimentation primarily took place in sandbox environments, with many facilities opting for a hybrid SDI/SMPTE ST 2110 approach. A significant development, this spike in adoption speaks volumes about the growing industry demand for improved operational and cost efficiency when transporting video across facilities.

In 2025, it's reasonable to assume that technology developers will release more tools that bridge current SMPTE ST 2110 pipeline gaps. As they do, SMPTE ST 2110 adoption will grow among broadcasters and production facilities. Out of this development, we may just see a new class of engineers who understand both video and IT. And as the industry's collective knowledge base expands, more training and educational resources will likely become available, making SMTPE ST 2110 more accessible.

NewscastStudio

Ten trends defining broadcast and media in 2025

Live sports stream to millions of concurrent viewers. AI systems generate highlight reels moments after the action happens. Production teams collaborate across continents using cloud-based tools.

The transition to IP-based workflows continues to change how content is produced and delivered. IP increasingly makes economic sense for operations of all sizes and is helping accelerate the move toward remote and cloud-based production thanks to SMPTE ST 2110 and the native IP protocols used for contribution to cloud. One example is the synthesis between 2110 and JPEG XS — basically native IP speaking to native IP via VSF TR-07 and TR-08 — which was proven at the Paris Games.

Remote production enabled by IP infrastructure is dramatically reducing the need to transport equipment and personnel around the globe for major sporting events. Broadcasters are moving from shipping multiple aircraft loads of equipment to employing streamlined fly-packs with remote workflows. Remote production of live content is transformative. Sending only minimal crews to an event and streaming all sources back to a central production base slashes the cost and carbon footprint and massively boosts the utilisation of expensive production technology.

TVBEurope

European broadcasters lead the way in redundancy-driven SMPTE ST 2110 adoption

Chris Wright, vice president of business development EMEA, TASCAM, examines why European success in adopting redundancy-driven SMPTE ST 2110 is providing a roadmap for content revolution

The broadcast world has been undergoing a transformation as workflows migrate toward IP-based environments, and at the heart of this change is the SMPTE ST 2110 standard. SMPTE ST 2110 revolutionises how audio, video, and metadata are transported over IP networks, introducing flexibility, scalability, and interoperability to an industry steeped in tradition. However, while this standard unlocks new possibilities, it also surfaces a critical non-negotiable requirement—redundancy.

One of Europe's most notable early adopters, BBC Wales, deployed the SMPTE ST 2110 standard when building its new Cardiff headquarters—marking one of the first full-facility implementations of the standard globally. This decision underscored the region's forward-thinking approach to technology. Yet, even with meticulous planning, challenges can arise, such as troubleshooting systems with interconnected IP streams. These early lessons highlighted the critical role of redundancy in maintaining broadcast stability.

Bloomberg

How Journalism Will Adapt in the Age of AI

The news business is facing its next enormous challenge. Here are eight reasons to be both optimistic and paranoid.

We journalists are by nature a pretty paranoid lot. Permanently worried that somebody somewhere — governments, lawyers, our colleagues, the IT department — is about to do something terrible to us, or our copy. So far the 21st century has only fed that paranoia. Back in 2006, one of my first covers as editor of The Economist was entitled 'Who Killed the Newspaper?' At the time the internet was wrecking the cozy business model of most big city papers that relied on their monopoly of classified advertising.

Columbia Journalism School

Tow Report: "Artificial Intelligence in the News" and How AI Reshapes Journalism and the Public Arena

Despite growing interest, the effects of AI on the news industry and our information environment — the public arena — remain poorly understood.

Drawing on 134 interviews with news workers at 35 news organizations in the United States, the United Kingdom, and Germany — including outlets such as The Guardian, Bayerischer Rundfunk, the Washington Post, The Sun, and the Financial Times — and 36 international experts from industry, academia, technology, and policy, this report examines the use of AI across editorial, commercial, and technological domains with an eye to the structural implications of AI in news organizations for the public arena.

Mather Economics

AI in the Newsroom: Transforming Journalism for the Digital Age

The intersection of artificial intelligence (AI) and journalism has sparked both excitement and curiosity within the media industry.

Around 2015, The Globe and Mail, Canada's largest national newspaper, launched a data science team named 'Sophi' to develop AI-driven solutions aimed at solving newsroom challenges. The initiative began with a simple goal: to help journalists and editors better understand the value of the content they were producing. Initially, the focus was on digital publishing, where the emphasis was largely on clicks and page views. However, the Sophi team recognized that while clicks measured engagement, they did not necessarily reflect the value of the content in terms of user loyalty, subscriptions or return on investment.

IBM

How is AI being used in journalism?

Explore how artificial intelligence is transforming journalism, from newsgathering to audience engagement.

There's no doubt that some executives in the news media industry have viewed artificial intelligence (AI) with anxiety. But a newsroom in the future without any AI tools is highly unlikely. According to Nieman Lab, major newsrooms across the country have been designing new roles and initiatives around how to develop and use AI tools and processes while maintaining ethics and editorial standards.

Substack

So What

Journalism isn't dead just yet 💀

We are now in a moment in which solo journalists (or small groups of journalists) can create a successful (and profitable) business around their work even as mainstream media companies continue to desperately grasp for a working business model.

INMA

Platforms like Substack offer journalists a tricky alternative to traditional newsrooms

Some journalism stars are leaving traditional news companies for platforms like Substack, but the actual numbers around the creator economy may be surprising.

The top 10 publishers on Substack collectively had hundreds of thousands paid subscriptions and earned more than US$40 million a year. In the Politics and News categories, more than 30 publications make at least US$1 million a year.

Nieman Lab

News faces its final unbundling

Predictions for Journalism, 2025

A new class of influencers, podcasters, and YouTubers have risen in power in shaping the public's understanding of the news despite doing very little direct reporting. Research by Pew now suggests they are the dominant force in how news is consumed on social media, to the near-complete exclusion of institutional voices on some platforms like TikTok.

Journalism.co.uk

Predictions for journalism 2025: social media, influencers and content creators

Traditional media will struggle to keep up with creators on TikTok or Substack. Your biggest competitors will be new media startups, journalists going solo and online personalities

Traditional newsrooms are shrinking, and more journalists are going solo on platforms like Substack, YouTube, and TikTok. Why? Because they are finding their beats do not align with the priorities of big publishers, they are tired of working within the constraints of legacy media — or they have been laid off in the latest round of cuts (expect more of those too).

International Center for Journalists (ICFJ)

First-ever Global Survey of News Tech Reveals Perilous Digital Skills Gap

A survey examining digital technology skills and adoption in global newsrooms

In an era of fake news, digital security threats and competition for audience attention, journalists and newsrooms lack the technology skills to meet the challenges they face, revealed the first-ever global survey on the adoption of new technologies in news media. The results showed which regions are the leaders and laggards in digital technology adoption. While the disruptions in today's newsrooms have been widely examined, the study focused on a missing link: how journalists worldwide are using technology.

Research.com

How To Become A Journalist for 2025

A comprehensive guide to becoming a journalist, including career outlook, skills, and job market trends

With traditional newsrooms shrinking and digital media transforming the industry, aspiring journalists may wonder if this field offers stability and growth. While employment for journalists is expected to decline by 3% from 2023 to 2033, an estimated 4,500 job openings will still be available each year, primarily due to retirements and career shifts. The median annual salary for journalists was $57,500 in 2023, making it a profession that, while competitive, can provide a stable income for those with strong skills and adaptability.

Columbia Journalism Review (CJR)

AI companies have a news problem. Journalists have the skills they need to fix it.

An article exploring the challenges AI companies face in handling news and the potential role of journalists in addressing these issues

Throughout the recent chaos in American politics, AI chatbots have struggled to stay abreast of the latest news. Reporting showed that, hours after the assassination attempt on former president Donald Trump, ChatGPT said the shooting was rumor and misinformation. The same reporting also found that popular chatbots struggled to provide accurate answers in the aftermath of J.D. Vance's VP nomination, as well as President Joe Biden's COVID diagnosis.

Journalism.co.uk

New report calls for £15 million a year to transform the future of local journalism

A report by the Public Interest News Foundation highlights the critical state of local journalism in the UK and proposes a strategic funding approach to revive local news ecosystems.

The Public Interest News Foundation says £150m is needed over the next decade to revive UK news deserts and make local communities more resilient towards misinformation and collapsing business models. The current state of local news is bleak. Over four million people now inhabit "news deserts" - communities fundamentally disconnected from local reporting. This is not merely an industrial decline, but a potential structural threat to democratic engagement.

UK Parliament

Sustainability of local journalism

A House of Commons Committee report examining the challenges facing local journalism in the UK and recommending potential solutions.

Local journalism is vital to democratic society. Accurate, trustworthy reporting on local councils, courts and other public bodies enables people to hold those in power to account for decisions that affect their everyday lives. Local news publishers can also help people to feel connected and get involved with their communities. Through this, local journalism can increase turnout at elections, create economic value by encouraging people to buy local, and foster a sense of cohesion and pride of place.

Journalism.co.uk

Predictions for journalism 2025: revenue, subscriptions and registrations

Experts share insights on how newsrooms might fund journalism in 2025, focusing on audience engagement, AI personalization, and new revenue strategies.

In 2025, artificial intelligence will redefine how newsrooms personalise subscription models, reshaping audience engagement and retention. AI's power lies in its ability to analyse user data — such as reading habits, time spent on content, and preferred formats — to deliver highly personalised experiences. Subscribers could receive newsletters tailored to their interests, content recommendations aligned with their engagement patterns, or even dynamic pricing options based on their preferences.

Media Reform Coalition

Investigative and local journalism

An analysis of the challenges facing investigative and local journalism, highlighting funding issues and proposing potential solutions.

Investigative and local journalism have faced the sharp end of resource cuts across the sector for some time. While there is no lack of demand for news in the UK, there is an increasing unwillingness to fund more expensive or less commercially attractive forms of news in a highly unstable climate. News provision has always relied on funding through subsidy. The press currently receives a subsidy of over £500 million a year as a result of VAT exemption.

Ofcom

Ofcom's Three-Year Plan 2025-2028

Ofcom's strategic plan outlining priorities and trends in communications industries for 2025-2028

The communications industries are defined by innovation, disruption and change. To harness the benefits for the UK, we must understand the technological, commercial and consumer forces that will shape these sectors over the coming years. We have identified six trends across consumer, commercial and technology: Consumer: Shifting consumer trust – Technology is enabling synthetic media and scams, affecting trust in news and public institutions. Audience choice and fragmentation – Increased choice of services that appeal to specific groups is fragmentating audiences across platforms & devices. Commercial: Businesses are seeking to benefit from digital transformation. Economic growth – Boosting overall economic growth and tackling digital exclusion are priorities for the UK and for Ofcom. New business models – New business models, and the increasing role of global players operating across the value chain, are challenging existing players and change our sectors. Technology: Technology is improving choice, price and innovation, but also presents new questions. AI proliferation – The continued growth and impact of AI is transforming our industries with potential for new business models, efficiencies, value chains and risks. Network resilience – From extreme weather to state-backed cyber attacks, our networks are braced for security and resilience shocks.

Ofcom

Future of TV Distribution: Early Market Report

A comprehensive review of TV distribution market changes and potential future scenarios

The way TV reaches audiences will need to adapt to their changing needs and futureproof universal access. TV has an important place in most of our day-to-day lives – for entertainment, to learn about the world and, for many, as a source of company. Free-to-view TV services are available universally, with over 99% of UK households able to get Freeview, Freesat, or both. While TV has had a place in our homes for over 80 years, the way we watch and choose content has always evolved. Innovation has allowed our TV ecosystem to reach different generations and develop an ever-expanding choice of programming. Underpinning this innovation has been careful planning to give people the support they need to take up a new technology. For example, the launch of Freeview took the number of channels on terrestrial TV from five to dozens. But this required a massive industry, Government, and regulatory effort to design and deliver the Digital Switchover over a seven-year period.

Ofcom

Media Nations UK 2024

Annual research report on media consumption trends and viewing habits in the United Kingdom

The decline in broadcast TV's reach accelerated in 2023, although for every age group the amount of viewing declined at a slower rate than in the previous year. Broadcast TV's weekly reach fell from 79% in 2022 to 75% in 2023, marking a second consecutive year of record decline. For the first time, less than half (48%) of 16-24-year-olds tuned into broadcast TV in an average week. While the long-term decline in viewing of broadcast TV also continued, down 6% year on year, it was slower than the 12% fall the previous year. All age groups contributed to this trend – for example, children's viewing fell by 6% in 2023 compared to a 20% fall in 2022, while 65-74s' viewing fell by 5% in 2023 and 21% in 2022. Overall viewing of TV and video increased in 2023, driven by online platforms, including video-sharing platforms such as YouTube, and broadcasters' own services such as iPlayer and ITVX. The average amount of time spent watching TV and video content at home in 2023 was 4 hours 31 minutes per person per day, up by 2% since 2022.

💪 Why I Use AI - and How I Refuse to Be Used By It

We are being told - constantly - that AI is a tool for efficiency.

That it will save time, optimise content, scale your voice, automate your life.

That with a few good prompts and a tight brand, anyone can generate value at speed.

But I don’t want speed.

I want signal.

And signal can’t be mass-produced.

⚓️ I use AI to increase the friction, not reduce it.

I treat AI as a pressure vessel - a place to test ideas, interrogate my thinking, ask the question under the question.

I don’t outsource creativity to it. I sharpen creativity with it.

When I enter the space of language, narrative, structure, or philosophy, I bring AI in as a co-interrogator, not a substitute teacher. It challenges me to see what I’m circling but not yet articulating. It reminds me where I’m hiding behind style. It reflects my own patterns back at me - and it demands that I evolve them.

🔬 I use AI like a lens - never a mask.

I work with complexity: human-wildlife conflict, ecological trauma, systems change. These are not subjects that tolerate simplification. The world doesn’t need more performative insight or faster opinion. It needs clearer maps of difficult terrain.

So I use AI to build those maps. Not with empty prompts or vague summaries - but through pressure, dialogue, and recursive analysis. I bring it into my deepest creative processes: story development, decision design, philosophical confrontation.

What I get in return isn’t always usable - but it’s always revealing.

🚫 What I refuse

• I refuse to use AI to pad timelines or content calendars.

• I refuse to feed it the shallow prompts it’s trained to regurgitate.

• I refuse to let it lead the thinking - or speak in my voice unless my voice is already present.

• I refuse to let it become a way of hiding behind productivity.

AI is seductive. It flatters output. It fakes certainty. It tells you your ideas are ready before they’ve even fought for their lives.

But that’s not the game I’m playing.

I’m not here to add noise.

I’m here to retrieve signal.

🛠️ How I actually use AI

• As a mirror: to spot unacknowledged fears and patterns in my thinking

• As a lens: to compress raw narrative material into shape, then refine it myself

• As a sounding board: to hold a position up to pressure and see if it folds

• As a research assistant: not to answer questions, but to challenge the shape of them

• As a collaborator: in the same way a good editor or writing partner would be - ruthless, attentive, never sentimental

❓The deeper reason

This isn’t just about tools. It’s about how we face uncertainty.

The stories I chase - the ones about orcas, oceans, systems on the brink - they’re all entangled with one truth: our tools have outpaced our maturity. AI is simply the most recent mirror of that imbalance.

So I choose to use it intentionally, not reactively.

I don’t seek control. I seek coherence.

And coherence doesn’t come from automation.

It comes from asking better questions, faster - and living inside the hard answers longer.

That’s how I use AI.

And that’s why it works for me.

…and the VO version - made by an AI…

                                                The blind men and the elephant

Emile Zola’s observation that "art is a corner of reality viewed through a temperament" beautifully illustrates the notion that truth can be multifaceted and subject to interpretation. When applied to current discussions of fake news and fact-based reporting, it becomes clear that even when facts are indisputable, their significance and meaning are often shaped by the lens through which they are seen.

In the context of war, both sides may use the same events or facts but interpret them in ways that validate their own beliefs, such as invoking divine support. This speaks to a deeper issue in the concept of truth: while facts may be objective, their interpretation is inherently subjective, influenced by cultural, religious, or ideological perspectives.This aligns with Zola's notion that reality, like art, is only ever a "corner" — it is never the whole picture and is always filtered through the perspective of the viewer or reporter. In journalism, where facts are ideally central, the framing of those facts can drastically alter their meaning. For example, a man kills another man, one media outlet might report a murder, another might report an act of terrorism, yet another might present it as the work of a freedom fighter. The reported sets of facts may be accurate, but the meaning derived from them will vary depending on how they are presented and the ideological perspectives driving that presentation.

This dual nature of truth — as both a factual reality and a narrative constructed from perspective — complicates the idea of "fact-based reporting." While facts provide a foundation, the way those facts are connected, emphasised, or downplayed can give them different meanings. This is what often leads to the polarisation of truth in public discourse. The same set of facts can be weaponised by different sides of an argument to support opposing views, just as art presents a corner of reality that is shaped by the artist’s vision.

In this way, Zola’s artistic principle applies not just to the realm of art but also to how we interpret reality in general. Truth, therefore, is not static; it evolves with the prism through which it is dissected and the lens through which it is viewed. What a truth means depends upon where it is perceived from. In the age of fake news, recognising the role of perspective in shaping truth is crucial to navigating the subtle complexity of media and public discourse

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