There's a good reason why humans had to invent maps to find the shortest path between two points: our brains couldn't be bothered to figure it out on its own.
New research from the Massachusetts Institute of Technology (MIT), published this week in the journal Nature Computational Science, looked at how the human brain tries to navigate through city streets and found that rather than look for the shortest possible path – and thus the more efficient one – it instead settles for the "pointiest path" because it was easier.
Calculating the shortest path between two points is a fairly computationally expensive task, both for a computer and for our brains. But while our GPS navigators or logistics software needs to calculate the truly shortest path between A and B, our brains are wired to simply pick a path that is "good enough" to get us there in a reasonable time, rather than the fastest.
"Vector-based navigation does not produce the shortest path, but it’s close enough to the shortest path, and it’s very simple to compute it," said Carlo Ratti, a professor of urban technologies in MIT’s Department of Urban Studies and Planning and director of the Senseable City Laboratory and lead author of the new study.
"There appears to be a tradeoff that allows computational power in our brain to be used for other things — 30,000 years ago, to avoid a lion, or now, to avoid a perilious SUV," Ratti added.
By settling on a pointiest path that more or less keeps our destination in front of us, our brains only have to keep track of a single point on the map, so to speak, rather than a series of points in a mental graph that we'd need to constantly reference and update as we progress towards our destination.
By sacrificing the efficiency of the truly shortest path, our brains can focus their attention on other things, like keeping an eye out for dangers or performing other tasks requiring more active attention. Besides, our brains aren't capable of having logging the kind of detailed maps necessary for shortest path computation.
“You can’t have a detailed, distance-based map downloaded into the brain, so how else are you going to do it? The more natural thing might be use information that’s more available to us from our experience,” said Joshua Tenenbaum, a professor of computational cognitive science at MIT and co-author of the study.
“Thinking in terms of points of reference, landmarks, and angles is a very natural way to build algorithms for mapping and navigating space based on what you learn from your own experience moving around in the world.”
- Is the human mind made of fractals?
- Have our brains just not evolved for social media?
- The world’s largest chip is creating AI networks larger than the human brain
Analysis: lazy or efficient? For the human brain, there isn't much difference
The amount of energy needed to operate the human brain is actually rather staggering. Of all the calories used by the human body in a day, the brain uses up about 20% of that energy, and it has been built over millions of years of evolution to make the best use of that energy possible.
In most cases, this means that it can behave like a mediocre student in college making a rough calculation of how little work they can do in order to graduate and not one bit of effort more than is necessary.
In a lot of ways, this makes perfect sense. If that student's survival in the world really only depends on their graduating college rather than the quality grades they achieve, the extra effort spent to get an A+ rather than a C+ is actually a waste of energy that could be put towards other activities.
The brain does pretty much the same thing, even if it means we're all C+ students in the school of survival – but hey, at least we passed, right?
- Stay up to date on all the latest tech news with the TechRadar newsletter