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The main problem seems to be that computer scientists don't care about history. That seems a bit strange to me, since there is no lack of people to analyse the historical parts of mathematics of physics. Maybe the problem is that computer science history doesn't seem like history yet since it is relatively recent?

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Because a lot of CS history are only relevant in a larger/humanities context. In terms of absolute technical value, the historical contributions are not necessarily as valuable. Russell and Whitehead's Principia Mathematica has next to no practical use in modern day software engineering. Their existence helped induce Church and Turing to create modern computer science theory but the discrete mathematics in that book itself holds little value for your average computer scientist outside of being an intellectual exercise.

Another issue is that CS is a branch of applied math that also happens to be extremely profitable. Math operates on much larger timescales than other domains. But business and economics demands immediate attribution. McCulloch and Pitts had their Hebbian neural network almost a century ago. Kleene of the Regex fame designed his neural network in 1951 [0]. These vast timescales are quite normal for advanced mathematics. But in 2010 GPUs became cheap and the obscure theories of the pre-GOFAI age are suddenly immensely profitable. Of course the names and associations would be with their most recent implementors. The ones who actually applied and made it possible, rather than those whom dreamt it up a century ago.

[0] https://news.ycombinator.com/item?id=25882079

Re first paragraph: Do you think mathematics and physics are different? It isn't like the old papers are relevant after hundreds of years, others have written the same things in more distilled and easier to read formats.

Well, most students in (contemporary) math programs don't learn to derive their axioms from Euclid (construction of naturals are usually done via Peano), their Calculus from Newton's Principia, and nor do they learn their set theory from Cantor's original papers. Instead they learn from modern textbooks that make only a passing reference to the original authors.

Yeah, that was my point. I wondered what your point was.

I had the impression that there was a fair amount of CS history that only shined much later when CPU, IO, memory, etc, was big enough or fast enough for it to become practical.

Edit: Meaning there are pretty straightforward reasons to care about history.

You can definitely come up with ideas that are too early for the hardware. When I was doing proof of correctness work in the early 1980s, it took 45 minutes to run something that now runs in a second. I had a nice ragdoll physics system in the late 1990s, and on a 100 MIPS machine it was about a quarter of real time speed. Now games have ragdolls. Around 1970, I was working on 3D graphics with hidden surface elimination. I had it working, but I had to monopolize a million dollar UNIVAC mainframe in the middle of the night to do it at 2 FPS. Usually I just ran batch jobs and used a pen plotter. Asked to figure out a way to create drawings of parts from tool paths, I thought of what are now called octrees, figured out how memory would be needed, knew I had 64K of 36 bit words, and abandoned that approach. At a million dollars a megabyte, it was unaffordable. TCP was at one time considered too much compute for PC-sized machines. This produced a decade of now-forgotten "PC LAN" systems.

Some ideas just need a big engine.

People don't want to look back at

- how far we came in each decade

- how brilliant people had to be to invent ideas that feel obvious to us

- how much people got done with previous decades' technology

- how many times history the consensus of expert opinion mis-predicted the next development

because we want to believe

- the current state of the art is close to perfection than it is to the last generation

- we only have to embrace the obvious

- people who are one step behind the times are at an insurmountable disadvantage to us who are up-to-date

- the future will bring nothing more than a higher perfection of the ideas we embrace now

It's intellectual millennialism. We want to think that the new ideas we receive at the beginning of our career are the final piece of the puzzle, that there's no point in generations beyond us. Our ideas give us special powers to accomplish things that no previous generation could accomplish, and no subsequent generation will accomplish much more, or the same things much easier, than we did. We are standing at the end of history. We are the generation that left the desert and entered the promised land.

History upsets all that. History teaches us that the future will stand in relation to us as we stand in relation to the past, whereas we want to believe that we are equals with the future and superior to the past.

The main problem is that computer researchers don't always write up their ideas in papers. And source code is hard to read, system dependent - you can't understand it without being familiar with hardware which may not even exist any more - and may be impossible to access.

This isn't really about history. This is about ideas which could still be useful today but which have been forgotten, for a variety of reasons.

Most CS departments don't have anyone who specialises in this. And academic historians have other priorities.

Calling this dumbing down doesn't help. It's not about historians "dumbing down" CS, it's about not understanding the difference between what historians do - create narratives - and what archivists and researchers do, which is more closely related to continuing research and development.

Physics actually has the same problem. Anything outside a limited mainstream is forgotten very quickly. Math seems less prone to it, perhaps because math is made of academic papers and nothing else, and there's more of a tradition of open exploration and communication.

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