Learning about place and scale

How do we know what we say is true?

Some people, in some conditions, are good at the prediction game. I will pick out a few lessons under two headings: the people and the process.

Can we predict? What are the rules of predicting? How do we know whether something is true?

Being clearer about the decisions we make, finding out if those decisions helped us get to where we wanted to go, and using the learning to make better decisions in the future. Is this core to how we want to think about learning?

In Era 3. What do we mean by data? What do we mean by outcomes? What do we mean change and change mechanism?

To me, the machine is able to analyse the world as it is. Not a world with linear progression from bad to good on a single variable, but a world where some things are good, somethings are bad, and there is a lot of fluctuation from one moment to another.

The machine was picking up on context not directly relevant to the therapy that strongly influenced the young person’s progress. Some examples.

I want to draw out what the machine says about how we learn.

The machine will see things we don’t see. We will see things the machine doesn’t see. Ergo. Let’s make friends with a machine.

When I was studying evidence based programmes, I kept coming across an interesting phenomenon.