In this first week of the E-Learning 3.0 MOOC, Stephen Downes has shared a video introduction to the course (see https://el30.mooc.ca/course_activity_centre.htm ) and also recorded a video of a conversation he had with George Siemens. This was really enjoyable to watch.
It has been ten years since Stephen and George offered the first ever MOOC on connectivism, which for me (without wanting to sound too dramatic) was a life-changing experience. On the back of that course I established myself as an independent education consultant and researcher, which ultimately led to a PhD by publication. More important than this was that it led to connections with people with whom I am still in contact and who are now personal friends. As George said, that first MOOC, CCK08, The Connectivism and Connective Knowledge Course came at a time of mass explosion of technology, extensive innovation and the emergence of shared intelligence. But, as George said, after this initial excitement, the last five years has felt a bit like a wilderness and many of the initial aspirations for a democratic open web have not been realised.
However, neither George nor Stephen has given up on their initial aspirations to democratise learning. Both think we are now entering an era of deepening understanding of learning. Each has approached this differently, although they both feel that connectivism continues to be relevant, if not even more relevant, to how we learn in a technological age, as technology becomes more prominent.
Stephen asked George to tell us what is his current work focus. What are the issues that concern him? This was where the discussion became fascinating. It centred around what it means to be human and what is human intelligence in a world where machines can learn just as we do. For Stephen there isn’t anything that is uniquely human. Anything organised in the right way can learn. If we can learn, machines can too; if we can come up with ethics so can computers. Computers can always learn more than we can. Unlike us, they don’t get tired and improve with more data. Machines are equally as smart as us. So, George asked, why are we teaching in a counter-intuitive way when systems/machines can do it so much more efficiently and in 50 years time we will all be working with robots?
Grappling with these questions, George is looking for what is uniquely human. He sees this as ‘being-ness’. I have heard him talk about this before to Neil Selwyn, and earlier this year wrote a blog post about their discussion – Skills for ‘Being’ in a Digital Age . Stephen thinks ‘being’ is too fuzzy a concept to be useful, although ‘being’ seems to have exercised the minds of many a past philosopher, not least Heidegger. Despite this, I think Stephen nailed it when he said, ‘the most consequential things can’t be measured’. Perhaps, as Stephen suggested, ‘being’ can be recognised (without being measured, defined or articulated) in such qualities as ‘goodness’. We can probably think of similar qualities that it is hard to imagine a machine learning. George suggested that to understand ‘being’ we might need to return to traditional contemplative practices.
My current thinking is that ‘being’ is one of those ideas that cannot be made explicit without losing its meaning. It is something that we ‘know’, intuitively and empathically, without having to articulate it, and this knowledge is unique to each and every one of us. It is this that makes us different from machines.
This was a great discussion to have at the start of the course.