I don't know how to classify this phenomena but its characteristics are: lofty, haughty, condescending, dismissive language - a desire to be "right" about the "true boring nature of the world - high cynicism paired with disgust for optimism - absolute conviction even lacking more than a trickle of experimental evidence.
In the case of the solar roads, people were "promising" me that it would never be a viable solution not because of any good thermodynamics calculations or anything, but merely because the roads were pretty expensive right now, and kinda slippery right now, and because it seems to make more sense right now to just build solar panels in the Mojave desert or whatever.
Never mind that freeways are arteries across the nation, never mind that maybe someone will whip up some crazy asphalt mixture that you can plug a cord into, nope, it's not ever going to be a thing, TRUUUUST USSSS.
https://www-cs-faculty.stanford.edu/~knuth/smullyan.html
> Once upon a time there was a universe. In this universe there was a planet. On this planet there was virtually no laughter. Nothing like ``humor'' was really known. People never laughed, nor jested, nor kidded, nor joked, nor anything like that. The inhabitants were extremely serious, conscientious, sincere, hard-working, studious, well wishing, and moral. But of humor they knew nothing. All except for a small minority who had some feeling for what humor was. These people occasionally laughed and joked. Their behavior was extremely alarming to everyone else and was regarded as an obviously pathological phenomenon. These few people were called ``laughers,'' and they were promptly hospitalized.
The most annoying are the many who claim to be approaching thins with reason who immediately flee to the worst flaws in thinking there are, ad hominem and arguments from authority. Rather than focus on substantive issues, they point out that those putting forward the ideas don't have the right credentials or similar. Which, if you're just dealing with "am I personally going to accept this idea", that's fine. But it's a pragmatic dodge that is guaranteed to fail quite often. Identity of the speaker can't influence truth of what is spoken, it's that simple.
Then you've got things like the issues you mention, like the expense. So tackle the expense problem! WHY is it expensive? Things are only expensive for a few reasons. Either they require rare materials, extremely precise engineering, or they're being produced for an extremely small destination market. It's not magic. If the things can be made at scale, and they can be made with commodity components, they can be made cheap, end of story. That's just a matter of scale. Whether that scale could ever be achieved is one of those "you have to grant the hypothetical" situations. The slipperiness might be a bigger sticking point. What physical properties lead to stickiness and how do they affect light transmission through a medium? That might be the killer right there, but you have to actually pursue it before you can write something off.
Being intellectually adventurous isn't for everybody. Many people can't take an idea like "maybe it would be best if we ate people" and then just take it apart and determine what the consequences would be and whether they accomplish a desired goal. They just can't bring themselves to do it. Or once they hear about prion diseases, they bail instantly without looking for workarounds. You have to WANT an idea to work to ever have a chance of proving whether its possible. Then you can define the conditions under which it WOULD be possible. And if it's not possible, then you actually know why. Which means you probably know far more about the original problem you were trying to solve and that might generate some great ideas going forward.
"I can't have people that unlucky working for me."
Like virtually everything else in biology and learning theory the optimum is not at either "edge" of the parameter space but somewhere in between. Willingness to entertain model-breaking ideas and data is a compromise between the need to avoid falsehood and error and the need to learn and update models when needed.