This article is about migration of Bantu-speaking people 5000 years ago, not innovation in general, and isn't really applicable to scientific/technological discoveries. Perhaps link to the original paper without the clickbaity title:

"Bantu expansion shows that habitat alters the route and pace of human dispersals" http://www.pnas.org/content/early/2015/09/09/1503793112

Wow, good catch—that's worse than average even for a press release farm.

We've changed the title (from "Human innovation more trial-and-error than 'lightbulb' moments"), but have left the URL because the popular article, distorting as it is, provides more background. Also, the researchers themselves are pushing this interpretation, to judge by the quotes in the article, so it isn't just spin by a headline writer. Anyone who wants to read the paper can follow the link you've helpfully provided.

"The most exciting phrase to hear in science, the one that heralds new discoveries, is not 'Eureka!' but 'That's funny...'"

Isaac Asimov

And then, in by far the majority of cases, after much head scratching and scribbling, the "That's funny" turns into "Doh!"

But in an extreme minority of cases, when the "That's funny" remains ...

Absolutely. Like the handful of cases we "discovered" room temperature superconductivity. Until we tracked down something shorting somewhere in our system :-)

It is said that true fundamental innovation in a technological sense takes 15+years... stable ecosystems (govt policies, strong economies etc) are needed to foster this innovation. Fundamental innovation also creates new methodologies in two or three areas, whether it be tech, market or implementation.

Everything else is incremental innovation (new tech enhancing products in a known market), this can be achieved in 1 to 3 years.

Genuinely interested in where those figures come from. Do you have any sources I could read?

Yup, my MIT professor Eugene Fitzgerald's book, "Inside Real Innovation". Enjoy the read!

Like how evolution is supposed to work then. Mutations are the 'ideas' and natural selection decides if they're worthwhile or not.

I can see this pattern in other areas, like startups. Founders have ideas, users/market decide if they're worthwhile or not.

Indeed! What you describe is the basic message of memetics field: evolutionary passage of packages of information through our brains.

"""Watt's engine was more a redesign more than an invention. Edison's notebook reveals that he tried thousands of filament materials before alighting by chance on his favoured material. """

Why isn't Edison's Light bulb not considered a redesign as well? Edison himself called it "Improvement In Electric Lights" in the patent he filed in 1878.

Because beyond using electricity lightbulbs and carbon arc lights have little in common.

Once you have electricity, you will soon discover two things. First that a thin conductor will be heated when you pass electricity through resistive heating, and secondly, that it will soon burn, melt or vaporize after a short time if you heat it enough to produce any significant amount of light.

In other words, the initial idea came from a quite basic fact about electricity, and Humphry Davy experimented with it already around 1800, but a lot of trial and failure had to be done before it could be used for practical lighting.

Edison did enough research to come up with a practical one. He was not the only one, and others, including Joseph Swan made practical light bulbs at about the same time. Even this seemingly revolutionary idea was really more trial and failure than anything else.

I believe it is considered a redesign, or incremental improvement by most people, and the article is trying to imply that but without just repeating the phrase it just used.

And I believe the these incremental improvements are being stifled by the current patent situation, unfortunately.

Human innovation is 'lightbuld' moment first, then lot of trial-and-error.

Is it? For me, it's generally the opposite. I do a bunch of trial and error as I explore the problem space and the solution space. Small details gradually accumulate. Then, finally, things shift into a new pattern and I say, "Aha!"

After that I'll still have a fair bit of experimentation as I tune. But that feels much less trial-and-error-ish to me; before I was wandering; after I have a direction.

It is called "understanding", not "inventing".

An undiscovered understanding IS (novel discovering and therefore) an invention.

My level of English is low, so I cannot beat you in word game, so I cease fire, but let me explain my position better.

About decade ago, I played engineering game written in Flash (I cannot remember it name), where player must solve various tasks, e.g lift ball or stop ball which is dropped from high altitude. Unique idea of that game was fixed amount of money for whole game, which player need to spend wisely to pass all levels, or redo some levels again but with better efficiency, to save money. My first implementations in this game were simple: I understood problem and implemented most obvious solution, to advance quickly. Second solutions were improvements or optimization, to save money, to advance further. I beat game, but then my brother started to play same game and beat my score, so we started competition. Third solutions, made during competition, were true innovations: they are non-obvious and highly efficient, but each of such innovative solution had "lightbulb" moment first, and then sometimes hours of tweaking to implement it. So my gradation is: understanding of problem leads to obvious non-optimal solution first, then understanding of problem with first solution leads to improved solution (local optimum), then "lightbulb" moment leads to non-obvious efficient solution (global optimum).

Good news for artificial intelligence. Computers are a lot better at trial and error than "thinking" through a solution.

I also thought of AI while reading this title. Many people assess that strong AI will not be possible until will figure out how the brain works. Yet it's very much possible that we create a machine that exhibits human-like behavior before we understand how it works.

Trial and error exists, it's called 'genetic programming'

The trial in genetic programming is too random, compared to what a human researcher would try.

Doesn't this tear down the entire premise of the article? "Just trial & error" dismisses all the thought that goes into designing experiments and analyzing the data.

Human trial and error is more like a hill-climbing algorithm or a localized graph search algorithm, things which computers can do quite well.

You'd be surprised at how directed forces applied to "random" values yields surprising solutions.

We only need a way to tell the computer "hey, this random result/behavior could be useful for this and/or that specific purpose!"...

A missing piece inhere is the Maslow's hierarchy of needs. Discovery usually occurs only at the highest levels, not when the mind is busy obsessing with that pain in the stomach or fear of being eaten or whatnot! Life in Africa was (and still is) tough.