I love that the most unhinged of them all is the water king, when water is usually portrayed as the most serene element.

The specific number 7 hasn’t actually been well studied or reinforced; rather, it’s the chunking aspect of Miller’s work that was salient.

This paper talks about how people just accepted the number seven as a given for forty years after Miller published and didn’t explore it further. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4486516/

That seven is the magic number thing wasn’t much supported since it was first published in the 50s, instead it is more task-dependent https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4486516/

Always important to remember that a lot of laws of anything depend on the situation.

The paradigm shift will be us sliding down to second place on the “food chain” as AI takes over. Most of humanity will be relegated and only a rich few ogliarchs who control the automated systems for their own benefit.

AI is still an interpreter of data; there is no perfectly “true” interpretation of raw data. There is always a process of interpreting data to have some meaning. Interpretation is prone to bias.

If the machine learning model makes interpretations based on prior interpretations made (eg “historically only white or male candidates have been successfully hired in this role”) then this can perpetuate existing bias. Until recently the engineers building these models have not been thinking to build in safeguards against bias. Laws like these ensure that these kinds of biases are safeguarded against.

Think of this like building codes in architecture/structural engineering.