Mindware
February 23, 2010
On Thursday [25FEB] I'm heading over to the City College of New York to be the inaugural speaker for their MCA Ad/PR lecture series.
I shall be talking about some of the things I've been thinking about recently to do with the effect of what we call technology on the advertising industry, and the larger media ecosystem it lives in.
I've been lucky enough to be asked to speak at various universities over the last few years, from the University of Westminster in the UK, to MIT, USC and CCNY over here.
[And the Minneapolis College of Art and Design in a couple of weeks as part of the Conversations about the Future of Advertising series].
It's always really interesting for me since normally I talk to advertising and marketing people about this kind of thing, but I'm usually stealing chunks of excellent academic thinking, some of which is [hopefully] new to the audience.
Whereas with a student audience, the academic stuff is usually more familiar, but the real-life advertising stuff is less familiar.
And it's that mix of things you are familiar with and things that you aren't, things both establish and then disrupt expectations, that is one of the awesome features of recombinance.
In some ways, this line of thought is itself a function of a false opposition that we set up in reference to education systems - the division between 'academic' and 'vocational' learning.
I think there is another interesting distinction to be made that works perhaps along the same lines.
Let's say that there are only two kinds of learning.
Learning things [putting entries into a database] and learning skills or toolsets, that can be applied to different things - installing different pieces of software.
I've always been in love with trivia and enjoyed looking for similarities across broad reference sets - since I don't follow sports it's probably one of my more masculine qualities. But the corpus of knowledge has long since extended beyond the means of any mind to retain.
So the new kind of digitally enhanced intelligence that we are supposed to getting thanks to Google will have to be about learning to absorb and deal with new information quickly - which requires robust toolsets - abstract conceptualizations - that can be applied to brand new situations and problems.