The thing is, in some cases, all the productivity ends up costing a lot more. For small shops it will not be evident, but for bigger ones trying to scale, it'll be a major area of improvement (to use less cycles).
And that's OK... comes down to using the right tool for the right job, matching the skills of your developers with the challenge, how fast you want things delivered, etc, etc, etc.
I think the major issue people see is that when all of that slow programs are looked from a 10,000 feet view as a single thing, it looks like a damn waste of resources. Thus comments like "computing (as a whole) in the last X years has been terrible", etc. We can delve into programmer culture, lack of skills, people not caring about wasting resources, etc, etc, etc.
I think the solution is better tooling. Let the programmer be productive, deliver things fast, etc, but build something more intelligent that will strip it down to only the necessary bits and deploy.
Performance is always important. If you can solve a problem in 10% more time using a performant language, then it makes sense to do so, and I've seen few problems that I can express in Python or Ruby (painfully slow) that I cannot express in C++ (highly performant) or Scala (moderately performant) in roughly that amount of extra time.
In most cases, when you are a professional developer, you are not the end-user of your product. In these cases, deliberately choosing a less performant language for the sake of developer productivity can mean you end up penalizing the end user.
My opinion is that investing the modest effort to select a high-performance platform and framework gives you the freedom to write inefficient application code first and to optimize later. It is the process that allows you to avoid the most expensive kind of premature optimization I've seen by postponing optimization until well after an application's concept has been vetted by its first several thousand users.