Associative System
A mental system that encodes and processes statistical regularities, using similarity and temporal relations to make predictions, as opposed to a symbolic rule-based system.
THE IDEA
The associative system encodes and processes statistical regularities of its environment, frequencies and correlations amongst the various features of the world. Generally speaking, associative systems are able to divide perceptions into reasonable clusters on the basis of statistical (or at least quasi-statistical) regularities. They treat objects in similar ways to the extent the objects are perceived as similar (e.g., Rumelhart & Zipser, 1985). The primary reason for this is that the degree to which an association is operative is proportional to the similarity between the current stimulus and previously associated stimuli. On this view, associative thought uses temporal and similarity relations to draw inferences and make predictions that approximate those of a sophisticated statistician. Rather than trying to reason on the basis of an underlying causal or mechanical structure, it constructs estimates based on underlying statistical structure. (Lacking highly predictive causal models, this is the preferred mode of analysis for many forecasters.)
When to use it
Forecasting economic trends when causal models are unavailable
Medical diagnosis based on pattern recognition of symptoms and test results
User recommendation systems (e.g., Netflix, Amazon) that leverage similarity and co-occurrence
Learning a language through exposure to statistical regularities (e.g., implicit learning of grammar)
FROM THEORY TO EVERYDAY LIFE
In practice
Forecasting without causal models
A simple rainfall predictor uses historical combinations of temperature and pressure to estimate the chance of rain. It relies on statistical associations without modeling the physical mechanisms that produce the weather.
Categorizing objects by similarity
When you see a new fruit that looks like an apple and feels like an apple, your associative system classifies it as an apple based on similarity to past apples, even if you have no rule-based definition.
A MOMENT TO REFLECT
Put it to work.
Can you think of a decision you made recently that relied on statistical associations rather than causal understanding? How might that have affected the outcome?
In what situations might an associative system be more reliable than a rule-based approach? When might it lead to errors?
How does the associative system relate to the concept of 'thin-slicing' or rapid cognition?
Often confused with
References
- Rumelhart & Zipser, 1985 — Rumelhart, D. E. & Zipser, D. (1985)
CONTINUE THE CONVERSATION
Source texts
- Heuristics and Biases The Psychology of Intuitive Judgment (Thomas Gilovich, Dale Griffin, Daniel Kahneman)