May 31, 2022

pitching a new series to you

caleb gamman’s


Everyones mad at tech right now. But instead of undermining the tech companies, we create fictions that reinforce their power. Y’know: “Facebook can change your beliefs,” “AI will replace us,” “Twitter bots determine elections,” “the police can do Minority Report,” “TikTok knows you better than you know yourself”

But really, online advertising is on the brink of collapse, progress in AI has plateaued, data collection doesn’t work, and the algorithms are stuck in feedback loops. This isn’t a story of evil overlords puppeteering society, it’s one of global stagnation, an unregulated industry, and some losers failing over and over, but receiving an incredible amount of power in the process.

This isn’t your dad’s Netflix/Black Mirror are-you-scared-of-your-phone-yet tech critique. This aims to be something genuinely deconstructive, that attacks (and doesn’t hype up) the power of tech. It’s a lot like those Netflix docs actually, but obviously, with no commercial future.

Welcome to CyberGunk.

The Style

CyberGunk consists of 15 minute episodes consisting primarily of a monologue delivered straight to camera, with some really slick backdrops. Basically my current YouTube videos, with slightly more deliberate direction. There is possible room for more fleshed out overlays, montages, and “scenes” (Visual demonstrations, GPT generated bits, deepfaked act-outs, fake mid-rolls, juxtaposing interview clips, text-to-speech voices, cinematic outros), but only if that content feels tight, appropriate and natural.

Note: I won’t be doing that, I want to reduce my scope and since the content is a bit of a departure, with the style, as much as possible im trying to stay in my lane. One thing at a time

The Tone

This is going into relatively uncharted territory, covering topics that are generally sealed off in academia, and usually considered too dry or complex to be fully understood. So it’s important that while everything should be exhaustively researched and thought out, by the time it gets to delivery it’s always light, snappy, understandable and conversational. Everything is throwaway. This series isn’t about the detail, it’s about the broad strokes.

Sort of an embarrassing insight into what I’m trying to do here. 

The Structure

Structurally each episode should be fairly straightforward, opening with punchy/jokey material, going into all the informational setup, crescendoing into a big “woah” moment/reveal, before ending on a more subdued note. They should be filled with callbacks/factual links tying different threads together and, less strictly, the same goes for the series as a whole. 

The Jokes

Priority #1 here is to get some jokes off. Don’t let this dry sketching-out-my-ideas writing fool you. Ah see this was never meant to be said aloud. Don’t let this dry sketching-out-my-ideas writing fool you, this is going to be the most joke-dense thing I’ve ever done, I may even include some proper jokes, and not just meta-deconstruction. Dense pieces of information or obscure fact should be stripped down and reworked into joke form, or entirely replaced. There’s plenty of material in the denigration of the most powerful figures in society, but also Caleb Gamman should always be a low-status idiot owning himself.

The Smuggle

It’s important that this series is strongly ideological, as any media about tech will be. But as much as possible it needs to be smuggled in. It’s pointing towards ideas like: regulation of tech companies, publicly-owned media, arts funding, antitrust law, rejection of “AI,” the complete destruction of neoliberal capitalism… But I won’t actually be saying these things. Really your average viewer should watch this and think it’s apolitical. Much like they would watch The Social Dilemma or The Great Hack. Idiots.



  1. a wistful or excessively sentimental yearning for return to (or of) some past period or irrecoverable condition

We live in a weird time, and it’s hard to imagine a different future. So instead our mass culture seems to dig up the past and reconfigure it to shore up the present. 

This video is about nostalgia, and how it became a defining force in the modern world (By which I mean “how come there’s so many dang Marvel movies,” or “K-pop is just pop from 20 years ago,” or “what’s the deal with Stranger Things”). This video examines why we are culturally stuck in time, why our media is increasingly nostalgic. But also the inherent nostalgia of using tech: the stress of being always on, the inability to escape your past, and strangely, because the algorithms are nostalgic.

Nostalgia can be a destructive, regressive force. But it can also be powerfully restorative. 


supervised learning

  1. an approach to creating artificial intelligence where an algorithm is trained on input data that has been labeled for a particular output; through trial and error, the model approximates a function to correctly match output values, enabling it to make predictions when presented with novel input

Current machine learning boils down to one pattern recognition algorithm, and while powerful, it’s a far cry from our dreams of learning computers.

This video is about automation and technophobia. From Ancient Greece to Tesla; the mechanical turk to Amazon Go; the birth of modern AI in the 1950’s and the following waves of hype and disappointment. The fundamental technology remains unchanged, and we find out over and over that no, the computer cannot learn to love. 

The tech companies don’t have the power we imagine, and comparatively, ours is not an age of technological innovation, but one of stagnation.

Note: This is actually two separate videos now.


programmatic advertising

  1. the real-time buying and selling of ad inventory through automated bidding systems

Targeted programmatic advertising is the dominant business model of the internet. But recent research shows that it may not actually work at all.

This video is about how the internet was commodified, and based on the financial markets. This system was sold on lies, and its flaws (inaccurate data, fraud, dark pools, perverse incentives) have allowed it to spiral out of control. With online advertising so integral to the internet, what happens if it crashes?

While the collapse of today’s internet would have some extreme, far-reaching consequences, there may be a path to a better future. 



  1. one that creates usually by bringing something new or original into being; especially, capitalized (‘God’)

“YouTuber” and “influencer” are now dream careers, while employment in traditional creative industries becomes increasingly precarious.

This video is about Facebook’s pivot to video, streaming’s race to the bottom, and the lack of money in advertising. Tech has played a major part in tanking the creative industries, while public funding has slipped away. Individuals are increasingly turning to online platforms and crowdfunding to support their work, but the actual success stories are unfathomably rare.

The tools are so much more accessible, anyone can build a fanbase of thousands, but for a creative to make a living, it’s less attainable than ever.



  1. the deceptive practice of presenting an orchestrated marketing or public relations campaign in the guise of unsolicited comments from members of the public

With the failure of programmatic advertising, those in power have turned back to a more traditional form of marketing: Public Relations. 

This video is about the increasing reach of media manipulation: How Netflix went from impersonating DVD forum users, to manipulating social media algorithms; how press releases dominate the news media; and how a new, more insidious version of PR has emerged, and what it has to do with stan culture.

However, despite these large campaigns to bombard us with secret marketing, they may not work at all. While machines can manipulate machines, we may be stronger than we think.


personal data

  1. any information relating to an identified or identifiable natural person (‘data subject’); an identifiable natural person is one who can be identified, directly or indirectly, in particular by reference to an identifier

In a world where data collection doesn’t do what they say it can, are there still reasons not to want it?

This video is about the shady world of data brokers and surveillance capitalism, how these systems work, and how they don’t actually work at all, they’re filled with errors and racism. Amazon wants to track the entire world, and they’re incidentally working with the police. The FBI’s job is to show up at people’s houses for posting. Algorithms are used for predictive policing, which is where you find a vulnerable individual, make them do a crime and then arrest them for it. There are steps you can take to disappear, but it’s bigger than any one person. 

The worry isn’t that this powerful tech will destroy us, the worry is that it doesn’t work and is being used anyway.