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"...a language of description (programming language) that serves as an interface between the models in the human mind and those in computing hardware"

We do know what the models in our computing hardware look like, but do we actually know the models in the human mind?

Don't get me wrong, I love everything about this document. But I can't help but feel like that conceit is really dangerous. And seems common in this era of work.

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I don't think he means the models of the human mind at the implementation level. Rather he's referring to the mental conception of a specific problem or task, or even a natural language description of the problem, and how that is translated to a computer program that models that problem.

People are associate not procedural so objects do map somewhat better than functions. Many of the hardest problems in computer science are very short term. Navigating a car across the country is not that hard, not hitting anything or breaking any laws in the next 10 seconds and every 10 seconds along the way is vastly more difficult.

It's easy to calculate a trajectory to toss a ball into a hoop, it's much harder to get a robotic arm to do so.

At a molecular level, we could argue that everything is procedural in humans as well. Of course things get complicated at biological neural networks where parallel processing becomes more important.

In the end, both humans and machines have to follow the laws of nature (physics) in order to process information. There is nothing magic about it, at a certain point of abstraction we both (all) work in the same information processing way.

When trying to come up with hard problems in computer science I would think np hard, not robotics.

Building a robot to toss the ball is still hard but that is an engineering and physics problem. The calculations remain simple.

In what way is it dangerous? It's a good description of what programming languages do, even if we don't know exactly how our minds work.

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