I think if anything, the suburbs/exurbs are what is preventing what you're describing.
Right now it's too costly to blanket a city with public transportation, for example, because the density isn't there. The same issue happened when electricity was invented, and when the telephone was invented - to build the infrastructure in less dense areas, the taxpayer had to subsidize.
Houston and LA have worse air quality and worse traffic than NYC does, despite having less than half the population. Yes, NYC and SF are very expensive, and they also happen to have very strict zoning laws that prevent the suburbs from adding density.
> I don't think we should be striving to turn the entire Earth into Kowloon.
Oh of course not, that's an absolutely extreme example.
Yes, advanced societies tend to have a decrease in birth rates. Yet, they still keep getting denser, as people move to cities. Density, if done thoughtfully, can lead to increased economic output, better health, better environmental outcomes, less traffic (holding population constant, anyways), etc.
Why should we avoid density? Societies get more urban as they progress. Density is the way of progress. That doesn't mean we shouldn't be smart and thoughtful about it, but ultimately density should be the goal.
I just think that you're focusing on the wrong things here. Towards the top of the article they say:
> One of the difficult tasks was to schedule a meeting room in a scheduling application, using information contained in several email messages. This was difficult because the problem statement was implicit and involved multiple steps and multiple constraints. It would have been much easier to solve the explicitly stated problem of booking room A for Wednesday at 3pm, but having to determine the ultimate need based on piecing together many pieces of info from across separate applications made this a difficult job for many users.
This task isn't overly complicated. It's a task that computer-savvy people do on a regular basis, but it complex enough that it might trip up someone who can't use a computer well.
I have to agree with the other commenter, I think you're definitely overthinking it. A keyword search is clearly what they meant for the user to do.
They're not expecting 5% of the population to train a word2vec model and produce prediction interval estimates. Just a simple back-of-the-envelope check.
In Bayesian analysis, it's possible to actually accept the null, rather than just the reject/not reject that is common to frequentist statistical inference.
Right now it's too costly to blanket a city with public transportation, for example, because the density isn't there. The same issue happened when electricity was invented, and when the telephone was invented - to build the infrastructure in less dense areas, the taxpayer had to subsidize.
Houston and LA have worse air quality and worse traffic than NYC does, despite having less than half the population. Yes, NYC and SF are very expensive, and they also happen to have very strict zoning laws that prevent the suburbs from adding density.