Written in Philadelphia and despatched to TechRepublic at 30Mbps over an open wi-fi hub in my Pittsburgh hotel later the same day.

Almost everything I learned at college and university has been used at some time during my professional career – and I still lean on that seminal education when faced with new and challenging problems today. But by degree, the speed of change has seen many technologies and techniques sidelined by progress during my years in industry.

To probe the rate of change I recently asked an engineering class for a show of hands on a series of topics to get a feel for the knowledge evaporation rate. Out of a class of about 100 mature students the count went like this:

  • Who has seen a thermionic tube? = 5
  • Does anyone know how they work? =0
  • Has anyone know how a cathode ray tube works? = 1
  • Does anyone know how a transistor works? = 1
  • Who knows how a laser works? = 3
  • Who knows how an LED works? = 2
  • Who knows how an LED display works? = 3
  • Who understands Maxwell’s equations? = 0
  • Who knows how an antenna works? = 0
  • Has anyone heard of the radar range equation? = 0
  • Who has heard about the Schrödinger equation? = 11
  • Who knows what a compiler is? = 15

I won’t go on as I’m sure you get the idea. The big question is: does this lack of fundamental knowledge matter? Perhaps not. So long as someone somewhere does understand, the tech world will keep on spinning. But should the last one with knowledge die, we could quickly be in trouble.

For many of us, keeping abreast or ahead of the game is now an accelerating challenge driven by technologies that span every sector and aspect of companies and society.

We can no longer read all the R&D publications or attend all the conferences and courses to get a filtered and distilled view of progress.

Putting all these issues into some quantified context using the best practice I have come across involves the concept of knowledge half-life. The calculation methods are varied and hardly comprehensive, or indeed fully justified, but it is all we have as a guide to the challenge we now face.

The simplest technique is to reference the citation rates of scientific, technology and engineering publications. On this basis, I have to put together the following graphic for a broad selection of disciplines.

The most interesting observation to make here is that the medical and marine biology students are out of date before they can even graduate, while the physicists have about 11 years of grace.

What does this tell us? The education system as it stands is no longer doing its job and can’t possibly work as we move forward and the situation gets worse.

It is obvious that we have to move on, and it all has to be online and available anywhere, anytime, and in a form fit for purpose. But perhaps the biggest leap will be delegating the role of tutor to some disembodied entity – some machine – able to rapidly access, filter and format what is required well, or just, in time.

In addition, individuals will have to assume a greater responsibility for their own course of study. They will have to choose what they follow as wholly prescriptive education paths fall by the wayside. Moreover, education will be full time from cradle to grave for those in the fastest-moving sectors.

In many respects the world is demanding that students grow up and mature far faster than ever before. They will have to assume greater responsibility and achieve greater authority earlier than any previous generation, and they have to do it in concert with a world of machines and escalating complexity.

Will our young people be able to rise to this change and challenge? We’ll soon see, but I certainly intend running with them and giving it go.