The Creator Engine

The role of Technology in Creator Ecosystems

A few years ago, when I was still possessed by visions of how crypto might change the calculus for creators, I read a book by Eliezer Yudkowsky called, ‘Inadequate Equilibria’, and became obsessed with proving it was secretly written about the music industry.

The book suggests that though we often see opportunities in the world where it seems we can do much better than the status quo, the people involved seem incapable of improving. I was pretty interested, having read lots of Yudkowsky’s blog, so I read through the book in a day or so.

Thoroughly convinced of the book’s arguments, I thought it would be a great idea to try to illustrate how this problem manifested in the music industry using a toy model and set about imagining the creative industries as a game.

This approach, of reducing a complex system into something that resembles a toy or a game so you can find a solution, became popular in the late 1920s when John Von Neumann published ‘On the Theory of Games of Strategy’, birthing the field of game theory.

The clever insight in this approach is best explained by a quote from Ken Binmore in his book, ‘Playing For Real’, which reads:

Nobody ever solved a genuinely difficult problem without trying out their ideas on easy problems first. The crucial step in solving a real-life strategic problem nearly always consists of locating a toy game that lies at its heart.

So, out came the whiteboard, and I spent a few hours sketching out a toy game that approximated the way things tend to work in the creative industries. My experience of the music industry had a fairly large influence on the process but I made it as general as I could.

Game Designer

tl;dr: it’s a continuous auction where artists sell fans their creations, both want to make sure the auctions continue forever but artists risk running out of resources and exiting the game if they consistently produce creations fans don’t value

In this game, creators and fans take on the role of our main players, who form two teams: Creation and Consumption.

Points are distributed randomly to each player, from 1-100. Gameplay proceeds as a series of repeated mini-games, each with three rounds. The goal of the game is simply to make sure the game never ends.

Oh, so like an auction?

1. In round 1, creators spend points to make a creation. We assign each creation a value of 1, 3, or 10 at random. The more points, the higher the chance of a higher value.

2. In round 2, Fans place a bid on creations they want to consume. Fans, conversely, want the best creative experiences they can find for the lowest price.

3. In round 3, we exchange all creations where the bid price is higher than the sell price. To conclude, creators receive the bids as points in their balance and fans receive the creations. We convert the creations into their bid price and update their balance. Failed bids cost fans the assigned value of the creation, i.e., 1, 3, or 10.

As an example:

1. a single creator with a balance of 50 points at the beginning spends 1 point and makes a creation worth 3 points

2. A fan with a balance of 50 points bids 5 points and the bid is accepted, awarding both players 5 points.

3. The creator’s new balance is 54 points and the fan’s balance remains the same. We grew the pie!

Now, over time, both sides realise that they can use their points (or a share of their future points) to employ an army of secondary players to help them maximise their gains, including financiers who can increase the chance of high value creations, retailers who can offer creations to multiple fans per round, and technology providers who can do both. This quickly becomes the dominant strategy and a powerful class of secondary players emerges. We’ve finally arrived at a game that looks a lot like the industry we started with.

With the design complete, I tried to understand why secondary players were able to hold the game in an inadequate equilibria. Even though everyone agrees that the current state of the industry is worse than what they know is achievable, they also wouldn’t change their strategy. Artist streaming payouts could be said to be in an inadequate equilibrium, where it appears obvious to many people that streaming services should just increase their prices and pay artists more yet, year-after-year, they decline to. The strategies of secondary players, in effect, exalts them to the role of primary players—the only players in the game that matter.

The game described above is clearly flawed but a more complete explanation of the game is, conveniently, beyond the scope of this post. However, the process of designing it yielded two useful insights.

The first was that, for all my white-boarding, this game was far too complex for me to learn anything useful about equilibria. The second, was that a far simpler model could be useful for explaining how to think about creativity and technology, especially for new players.

The Creator Engine

After that humbling experience, I chose the more modest goal of illustrating how creators, such as artists, writers, illustrators, video creators, and digital artists use technology to cultivate and broaden relationships with their audience or consumers. It’s called The Creator Engine, and it attempts to provide a framework for understanding the impact of technology on creators and their ecosystem of fans over time.

The Creator Engine

Engine Components

Capital is the fuel that powers the engine and Relationships are the product. The Creator Engine has four components:

• 'Creation' which involves generating content or creative products. This requires time and data, both of which are essential inputs to all creative processes

• 'Consumption', which captures fan engagement with the creator's creation. This part requires attention from the audience and generates revenue.

• 'Environment', which accounts for various external factors that can influence the creator's capacity to create and the audience's propensity to consume. For instance, the creator's ability to create can be regulated by environmental factors, and likewise, the culture of the audience can regulate their consumption habits.

• 'Technology', this part plays a critical role in mediating the number of relationships the engine can sustain. It does this by applying capital to alter the relationships between the other components and their inputs.

Capital & Technology

The engine provides a return on capital which can be used to fund further creation or increase the number of relationships a single creator or creation can support through investments in technology.

For example, capital can be invested in technology to alter:

• The amount of labour required to sustain the attention of a fan. For example, technology has made it increasingly cheaper to serve fans anywhere in the world, at any point in time.

• The rate at which capital investments return revenue. For example, recorded music was originally distributed by radio which returned ad revenue against all listening, CDs allowed for sales of copies of each recording to consumers.

• The rate at which attention converts to revenue. For example, Digital Ads convert attention into small payments per impression, click, or install. NFT sales capture huge upfront payments against the lifetime attention a creation may generate.

• The ratios of data, labour, and capital required to produce, sustain, or expand fan relationships. For example, merchandise through which a fan might maintain a connection with a creator typically requires significant upfront investment to produce whereas a YouTube Follow is essentially free for both artists and fans and can be scaled infinitely.

Carrying Capacity

Now we come to the most important point, carrying capacity. We can imagine that an ecosystem of fans orbits each creator engine as they forge relationships with a creator. At any point in time, each engine has a fixed relationship carrying capacity.

Simply put, each creator, on average, can support a limited number of fan relationships before each fan begins receiving a worse experience—a Dunbar Number for entertainment.

Should a startup, like TikTok, introduce technology that increases the carrying capacity of the average creator ecosystem without also increasing the consumption of resources required to serve more fans or decreasing the value of whatever it is each fan receives, the technology has a good chance of survival.

If the technology increases carrying capacity and reduces the consumption of resources, increases the value of outputs, or both, the startup has an opportunity to disrupt the status quo, ushering in a new dominant paradigm.

YouTube is the perfect example of a startup that used technology to increase the number of fans that can consume video plus the number of video creators that can serve fans, all at much, much lower costs than before it existed.

By investing in technology, Youtube modulated the relationships in the Creator Engine between data, labour, and capital. Paired with other technologies such as smartphones and software, the average creator can now cheaply sustain a vast number of fan relationships anywhere in the world through video. Many have built entire livelihoods entirely on YouTube.

Unsurprisingly, the world now uploads just under 4 million videos to YouTube everyday. In the near future, a single DIY creator will maintain billions of deep connections with fans around the world in real-time using technology alone.

Kevin might need to update his 1000 true fan theory a couple more times.