I’m starting work this week on a new body of work covering two large topics in Learning Transformation: Big Data and Artificial Intelligence. My specific focus in this work will be threefold: firstly, to present a coherent and comprehensive state of play with current technologies and research, secondly, to build out case studies of how these areas are influencing and changing Organisations globally, across a range of sectors, and finally, to identify specific actionable insights and areas for individual (and Organisational) experimentation.
In the Learning Science module, which i have just about finished, i included a whole section on the ‘Hyperbole Filter’, alongside sections on ‘What Science Can Do For Us’, and ‘What Science Cannot Do For Us’. I will attempt a similar stance for this piece.
I anticipate that i will develop this over the next six months or so, alongside some other work, and will #WorkOutLoud as i do so.
As an aside, the Learning Science work is taking shape into the Learning Science Guidebook, which i intend to publish as a full free eBook before the end of this year. I am working through a final edit this week.
My pace of work is quite high at the moment, because of the approach i am taking overall to the Modern Learning Capability work: i intend to get the whole thing to a workable draft fast (ok, a year is not ‘fast’, but fast enough!), and iterate it rapidly. Some of the modules build directly out of previous work (and books), so are relatively easy (e.g. Learning Methodology, Social Learning, Community Building, etc), but others (like Learning Science, and Big Data) are entirely new.
That’s one of the things i am enjoying most: this work is taking me into new areas, which are proving fascinating, if tough!