How can algorithms predict human behavior, sometimes even better than we know ourselves? From shopping habits to potential health risks, what are the underlying principles that allow machines to seemingly understand the intricacies of the human condition?

Question

We often hear about algorithms that can forecast our preferences, suggest products, or even detect health issues before they become apparent. How can a machine, which doesn’t have consciousness or feelings, accurately predict something so complex as human behavior? I’m fascinated by this intersection of technology and psychology and would love to hear from anyone who can shed light on the mysterious ways these algorithms seem to ‘know’ us. What’s happening behind the scenes that makes this possible?

In: 10

Answer 1

Algorithms don’t understand the intricacies. They collect a lot of data from a lot of people, and when the data contain patterns algorithms can find them. So for example a woman might stop spending money on alcohol and nine months later start buying diapers (obvious pattern; pregnancies last 9 months and alcohol is counter indicated for pregnancy) – that’s a very common pattern, shows up in a lot of women, and you can use it to predict that someone might start buying diapers.

A very common pattern is going to be a very good predictor because it’s going to fit a lot of people because it’s common. If you want to use it to understand human behavior, you’ll need to actually interpret why the pattern exists.
Also note that the pattern is never going to be a perfect predictor: there are going to be people for whom it’s predicting incorrectly. Those are the cases where there are intricacies that break the pattern.