The danger of putting dumb algorithms in charge of people's lives is here right now. The danger of smarter algorithms that do exactly what nefarious people tell them to do will be here soon Seems unlikely we'll even survive to get to the danger of AI acting on its own.

Hmm, I'm surprise no has mentioned that those who live in the city are not necessarily ALWAYS bombarded by the city's information overload. My home in the Bay Area is surrounded by trees and even has some wildlife. Working independently (at the moment), I can always retreat there and recuperate from any urban overload.

I would agree that a homeless person (or an overworked truck driver)who is constantly bombarded by the city's information would be driven insane by it - indeed, that's what we often see. But a resident who has a home to retreat to is not necessarily going to be crushed. Information overload, multitasking and similar stresses on the brain are no worse than physical stresses IF a person has proper rest and relaxation in between each experience. Recuperation is the difference between an athlete and a gallery slave and it is the difference between urbanite with a rich cultural life and a person crushed by urban existence.

And as far as the article, it seems like a collage of various more simplistic studies and perspectives, none of which look at the overall condition of life in cities or rural areas. One quoted scientist describes the brain as inherently limit and thus seems to have missed the unbelievable expansion of human intellectual activity in the last 100,000 years.

What it usually meaning to "throw hardware at a problem" is that an organization is going tolerate a bad design. The problem is an organization also requires highly paid people to manage a large hardware configuration. Throwing hardware at a problem often requires that your to tweak the basic program for the larger hardware configuration. This takes away from the time that a programming team could be spending on improving the basic design of the system.
Programmers may be expensive. But if you have a poor algorithm, one that does not scale, then you will throw an exponential amount of hardware at the problem.

This article seems like something of a step backwards to the attitudes of the 90's. One of the Really Good Things about modern lightweight methodologies like Scrum and XP is that they are getting away from seeing the programmer as a dollars-per-hour resource and realizing that lack of quality is always more expensive. Doing the job poorly always cost more in the long run. A management system that thinks otherwise will fail in any reasonably long run.

While he does a good job showing that science itself isn't going away, he actually lends credence to the position that cloud computing implies a lot of useful information will be generated outside of science. Moreover, he also might be supporting the position that science isn't necessarily going to catch-up and explain this data any time soon. So, the "strong" position, that Google makes science irrelevant, is naturally false. But the "weak" position, that Google represents a new kind of inquiry that is going to be increasingly used and relevant, seems intact and supported. So cheers to Google and science, HJS