Is Taste personal or shared? Taste may begin as personal experience. But if we view Taste as a system, then its measurable shape appears through the handshaking of signals between at least two cybernetic systems. It becomes understood through interaction among environment, phenomena, process, and observer. Taste can therefore be understood as a shared dyadic process. It is not only a biological judgment about sensory experience, but also a feedback loop: a pattern-matching game in which people organize concepts into constructs, constructs into aesthetics, and aesthetics into observations that can be tested by another participant. ...

After a few tests, it appears that biological faces are not a strict requirement. Instead, other visual elements are proving to be much stronger candidates for wider algorithmic distribution: Abstract, complicated and hand-drawn lines are preferred by Stage B’s system Abstract, complicated and hand-drawn lines with some patterns are liked more often by other players Photo art without clear contrast between lines and colors do not perform well We can see the initial outline of this on the second most recent data collection: ...

In this latest set of tests for the series, I focused on a different strategy involving multiple photo art images in a single post on Stage B, each showing the step-by-step breakdown of how the illustration came together. I suspect the combination of showing the process of the artwork provides more proof of human work versus automation. The reverse order of final output to an earlier version was also something I wanted to test, as most content showing process tends to be in order from oldest to newest versus newest to oldest. ...

After a week of testing and recording the data, there’s a clearer picture of what these bots are doing with these public commits or at least according to my tests in this particular setup. Listed below are each day’s set of total and unique clones, and what changing factor I made on each repository if any. Strategy Alpha: Normal code with license This test involved including a standard AGPL-v3 license file along with a small coded script with no comments. Each daily change involved superficial edits to the codebase sent as one commit per day. ...

The first time I tried this experiment was last year, when I made my source code public on GitHub after many years of keeping repositories private. At the time, their Insights page (where repository traffic and cloning stats are displayed) was updating the analytics roughly every couple of hours. I noticed when I would make a commit and then have it broadcasted on my public feed, I would receive views and clones regardless of what I published. Here are a handful of tests I tried during this period: ...

The new test turned out as I had expected — more views and engagement on photo art only with emphasis on color saturation and complex linework. What was most interesting was that Stage A did not really respond the way I had assumed, but Stage B definitely fed the content to the generalized feed. Content Id Format Line Complexity Saturation Level 1 photo art high high 2 photo art high high 3 photo art high high Content in reverse order. ...

Comparing the algorithmic results of Stage A versus Stage B in the black box of social media games shows some diverging results. While most of the content testing was similar, I did add some text replies to other players in Stage B and also reacted to a comment on Stage A. These may have affected the outcomes somewhat but I’ll assume they aren’t substantial for this analysis. In terms of the responses, here are the results after a few days: ...

Is it art, a game or technology? Clean games contain the presupposition that phenomenological documentation of lived pattern recognition is not about objective truth but instead about hybrid interpretations within performed frames of thinking. That is, we write subjective observations of our experiences based on our biases of experience within stages of rules that existed prior to us being aware of them. While the rules were made before we entered the stage as players, we inevitably mutate their composition by being inside of this stage. ...

Applying clean game experiments on social media accounts (which I refer to as “stages”) is an interesting way to explore systems and their algorithms within a black box (the “stage”). Social media is a black box game stage. What do I mean by “clean game”? I am defining it in this lens as having a somewhat newer account with very few followers in the double digits. It’s enough of a set to observe patterns of feedback loops and not enough to create additional noise that makes it difficult to discern the minimum observed rules within a stage. ...

Fairness is defined by voluntary, revocable participation under evolving Unspoken Rules, not equality of data. Asymmetry is intentional, not accidental Open-endedness reflects the quality of shared commitment to the process, not a specific outcome. Communication happens through meta-moves and frame alignment. Continuous observation and participation matter more than fixed scorekeeping. There is no financial incentive in these interactions. The goal is continual collaborative world-building across asymmetric perspectives.