“…the program “The Brain,” in which Dr David Eagleman, neuroscientist, NYT bestselling author and Guggenheim Fellow shared a fascinating but little known secret…our brains are specifically designed so that we learn on the job – by doing.
Dr Eagleman explained that this is why human babies do not have anywhere near the survival skills possessed by animal babies. While a giraffe calf can stand and walk within 30 minutes of being born, a human baby is a fragile and helpless thing that doesn’t begin walking until several months after birth.
But this lack of ‘pre-programming’ in a human baby’s brain does gives humans a bigger, blanker ‘canvas’ to paint on and an extraordinary advantage: we are able to adapt to and survive in vastly different environments, even if it’s one our ancestors would have been completely unfamiliar with – because we just learn all we need, when required, on the job.
By contrast, a giraffe could not learn to survive in the Antarctic or in an environment unfamiliar to its species or where its natural food source does not exist. Its brain is simply not designed to quickly learn the new skills it needs to find food or shelter in an alien environment and so it will perish.
Dr Eagleman says this unique design feature of the human brain is obviously a significant factor in why humans are the planet’s dominant species – and from what I’ve witnessed, tapping into this ability to learn what we need as we go is a huge advantage at work where products, processes and systems are changing more rapidly than ever.
And it’s one more reason why the 70:20:10 framework for learning and development makes practical good sense. Why try to train employees on new things in a training room far from the field of work if humans are pre-programmed to learn from experience? It’s little wonder that employees struggle to absorb the information or instructions they receive in such settings because their brain, which is primarily designed to learn on the job, is unable to attach meaningful context to all this new data.”
Ted Gannan, here on Panviva’s blog.
OSS can be extraordinarily complex beasts. Even vendors have multiple sets of contributors, so therefore multiple sets of intelligence contributing to the vendor’s total acquired knowledge, so what chance do operators have of learning all the nuances of our products?
Overlay this with the fact that our customers (eg CSPs) have their own detailed processes, some of which an operator will use very infrequently. An operator can’t be trained for every process. Even if they could, it’s highly likely that they will forget the less common ones by the time they’re asked to use them.
On the plus side, OSS are traditionally quite good at building workflows for an operator to follow. However, those workflow tools are generally not set up to show operators what data (and data conventions) they should be populating on any given user interface within a workflow step. There are also often multiple side-chains, processes that aren’t captured in the workflow, to get around some of the rare situations that arise.
This leaves a functionality gap for many OSS vendors – to augment the user experience with decision support.
Unfortunately, building all this knowledge into a static decision support tool is time-consuming and prone to mistakes, particularly as products evolve. This makes the decision support a prime candidate for machine-learning based assistance of the type described in this earlier post.Read the Passionate About OSS Blog for more or Subscribe to the Passionate About OSS Blog by Email