How minds differ
Planning far ahead or living close
In shortSome people plan far ahead and others live close to now, and both bring costs and strengths.
The idea
Some people plan far ahead and want to know about next week now; others live close to the present, and ‘in half an hour’ means little. Both are differences in how far ahead the brain predicts. A long horizon can bring worry about many possible futures; a short one can bring surprise at things everyone else saw coming.
What to try
- For short horizons, make the future concrete: a picture timetable, a timer, ‘after lunch’ rather than ‘at two’.
- For long horizons, give enough of the plan to rest on, and say which parts are not decided yet.
- Match the length of the plan to how far ahead the person can use it.
The common mistake
Giving long verbal plans to someone who lives close to the present, and then calling the result forgetfulness.
Want to know more?
Start here
Short, plain pieces by the researchers and good writers.
Books
How the predictive brain shapes what we see, feel and do, with many everyday examples.
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The science behind itHow strong the evidence is, the model, videos and references.
How strong the evidence is
A way of thinking A lens for interpreting what a child does, not a rule from trials.
Deep temporal models nest slower processes over faster ones, so that plans unfold as sequences of sequences (Kiebel et al., 2008; Friston et al., 2017). Planning depth, the number of future steps considered in policy selection, varies between people and with load. Shallow depth predicts little anticipation of delayed consequences and surprise at transitions; deep planning with low precision over distant outcomes predicts worry about many branches. For formulation: notice how far ahead the person spontaneously talks, and compare external temporal supports (timers, now-and-next boards) with verbal plans.
More technical books
The technical textbook on active inference, for those who want the formal model.
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References
- Kiebel, S. J., Daunizeau, J., & Friston, K. J. (2008). A hierarchy of time-scales and the brain. PLoS Computational Biology, 4(11), e1000209.
- Friston, K. J., Rosch, R., Parr, T., Price, C., & Bowman, H. (2017). Deep temporal models and active inference. Neuroscience & Biobehavioral Reviews, 77, 388–402.
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