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Out of curiosity, does anyone have any examples of scientific books (or papers) that are the exact opposite: influential or famous at the time but completely an

Out of curiosity, does anyone have any examples of scientific books (or papers) that are the exact opposite: influential or famous at the time but completely and utterly destroyed by the test of time. Like, that seem silly to us in how completely and utterly wrong they turned out to be in their every single conclusion. I'm thinking about research versions of Lord Kevin's favorite edict: "Heavier than air flying machines impossible" or the patent person (examiner? head of patent office?) who in the nineteenth century said everything that can be invented has been invented.

dekhn 9y ago
Any paper about the luminiferous aether from before the Michelson Morley experiment?
Houshalter 9y ago
Sure fields of research go obsolete all the time. E.g. much of the computer vision stuff from 2006 is basically dead now. If you go further back, a lot of early AI research was exciting at the time, but is entirely forgotten about now.
- Finnucane 9y ago
  There's some difference between obsolete--a method that gets replaced by an improved method later on--and just plain wrong.
- mindcrime 9y ago
  If you go further back, a lot of early AI research was exciting at the time, but is entirely forgotten about now. Interesting that you would use that example. I suspect, although I can't prove, that this is largely a mistake. Or maybe not so much a mistake as a choice that will wind up being revisited. That is, I think there is still a lot of "meat on the bone" for many of the AI techniques that were being explored in the 70's and 80's, and we will see another round of things suddenly coming back into favor at some point. It's happened before... remember when ANN's were completely out of vogue, and the computing power and data availability caused a sudden resurgence in interest in those? I would not be surprised to see similar things happening w/r/t various aspects of GOFAI. More likely, I think we'll see additional integration / hybridization of probabilistic / pattern matching systems (using ANN's / Deep Learning / etc.) and symbolic processing and automated reasoning. 'course, I might be totally wrong, but that's my feeling ATM.
ferdterguson 9y ago
Not a field, but a person who everyone thought was Nobel prize bound and it turned out to be all BS. You may think that it's just one person, but the amount of research dollars that got allocated to try and prove or disprove all of this work would be staggering. https://en.wikipedia.org/wiki/Schön_scandal https://en.wikipedia.org/wiki/Schön_scandal

dekhn 9y ago

Any paper about the luminiferous aether from before the Michelson Morley experiment?

Houshalter 9y ago

Sure fields of research go obsolete all the time. E.g. much of the computer vision stuff from 2006 is basically dead now. If you go further back, a lot of early AI research was exciting at the time, but is entirely forgotten about now.

Finnucane 9y ago
There's some difference between obsolete--a method that gets replaced by an improved method later on--and just plain wrong.
mindcrime 9y ago
If you go further back, a lot of early AI research was exciting at the time, but is entirely forgotten about now. Interesting that you would use that example. I suspect, although I can't prove, that this is largely a mistake. Or maybe not so much a mistake as a choice that will wind up being revisited. That is, I think there is still a lot of "meat on the bone" for many of the AI techniques that were being explored in the 70's and 80's, and we will see another round of things suddenly coming back into favor at some point. It's happened before... remember when ANN's were completely out of vogue, and the computing power and data availability caused a sudden resurgence in interest in those? I would not be surprised to see similar things happening w/r/t various aspects of GOFAI. More likely, I think we'll see additional integration / hybridization of probabilistic / pattern matching systems (using ANN's / Deep Learning / etc.) and symbolic processing and automated reasoning. 'course, I might be totally wrong, but that's my feeling ATM.

ferdterguson 9y ago

Not a field, but a person who everyone thought was Nobel prize bound and it turned out to be all BS. You may think that it's just one person, but the amount of research dollars that got allocated to try and prove or disprove all of this work would be staggering. https://en.wikipedia.org/wiki/Schön_scandal https://en.wikipedia.org/wiki/Schön_scandal