Part the First

With my colleague JC Couture, I am teaching at the University of Alberta a course focused on using strategic foresight as a key component of leadership. Small group – ten students. Smart group with energy for the work.

What is striking about planning this work and exploring the growing (but very messy) literature related to foresight in education is just how bad a lot of this work is. For example, many who write so-called foresight pieces are really speculating about futures based on superficial analysis and not a lot of detailed work. This is a key point made by a number of research centre leaders working in this space.

For example, what is the future of AI in education? Is it going to be the disrupter the “market” imagines (doubtful) or another tool (like programmed learning, adaptive learning, MOOCs, Khan Academy) which will have niche impact but overall lead to many small changes rather than a major re-imagining of schooling. The Gartner hype-cycle helps us understand all this – the hype right now is big, but when we get to the platform of reality we will see just how the lie of the land looks. My job is to support serious foresight endeavours by using tools like causal layer analysis, trend analysis and other similar tools to help get some rigour into this work.

I wrote a book called How to Rethink the Future so as to share some of these tools. Maybe I need a second edition!

Part the Second

There is an interesting question, raised in an article from The Atlantic – who is able to predict the future? The article looks at a series of studies done over time which compares experts and specialists versus non-experts and generalists. The latter do better than the former.

One of the keys is to find people whose interests cross-boundaries and run deep. That is an expert in macro-economics who has studied growth curves in depth is less likely to predict the future than someone with an interest in photography, art, economics, literature, biology and politics. Makes sense to me.

The thing is, though, future studies are less about accurate predictions of specific things (X will happen at Y time because of A) but more concerned with the shape of things to come in more general terms.