So no. This is not a war between our corporate overlords.

(I couldn’t remember the title or the author. So I asked claude for it of course)

The lawnmower exists, you might disagree, but it’s not your lawnmower, you can’t uncreate it. But you can and should take care never to put your hand near it.

I'd say compared to just typing the code on a disconnected computer: Not worth it.

I like the law because you can quite easily formulate it without bias.

Large enough orgs will indeed get people whose job is more closely aligned with the goal vs people whose job is more closely aligned with the existence of the org. _Because_ you need to keep investing energy to keep the org in existence. You can’t just do the goal only.

But being responsible for keeping the org in existence is not the same as responsible for the goals that the org was created for in the first place.

_and_ I can see how the people whose job it is to ensure the org keeps existing will gain the majority vote.

It’s like a law of nature: the way things fall out if you’re not consciously working to have them fall out differently.

(So it can be good for google to fire them from a “let’s keep existing standpoint” even though it might be contrary to having the easiest/optimal to use product. And if that is so, the keep existing vote will have the power) I don’t use google products really that much so I can’t speak to the merits of this example.

Json-ld says: if you want to know whether the “title” property means the schema.org or the dublin core variant then you can find out which it is by

So you’d always use json-ld _with_ schema.org or something.

Which can outperform a generic solution like this of course, but it’s not less work to make faster for most cases.

Also duckdb can give you access to an in memory representation (e.g. `fetch_arrow_table()`) so you have less “language data structure wrapping” overhead. And you can do filtering yourself on that. In most cases the “where” statements will win though.

Is it easier to build or repair a radio now than it was when they were first sold? A computer? A car? A washing machine? A vacuum cleaner?

The main thing they do is stack the market to be very favourable for a given industry and then have extreme competition between the companies.

When estinating a loan default, even of 99 people with a purple skin color default on a loan, the hundredth should not be expected to default on the loan just because of the skin color. Both because this is scientifically wrong (it’s not the skin color that causes them to default. There’s a confounding variable) and because it would put someone in a position that they can never get out of.

So the answer to your question is simple: you make a model where the attributes are causal factors for loan default. And you might need to special case attributes that are an accident of birth but that list is finite (listed in the law) and short and generally constructed to exclude strong causal variables.

> In September 2025 the Lorentz Center at Leiden University in the Netherlands hosted a conference entitled Mechanization and Mathematical Research. The around 60 participants from 10 countries comprised mathematicians, computer scientists, philosophers, historians and social scientists, including those with experience in industry and in government.

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