Psychology links the subjective and objective
Psychology studies the subjective, but we try to do so in a way that creates objective measurements.
You hear ostensible criticisms like, "self-report is subjective".
Yes, of course it is, but self-report is also constrained. Those constraints are part of what builds toward making an objective science.
Our goal as researchers is not to treat human brains like rocks that we can measure and know all about without asking them anything. One of the great things about humans is that we can ask them about their experience! We can ask a participant, "When we objectively did X, what happened in your subjective experience?" and the participant can tell us. We write down their response and that subjective report becomes a measurement that can be treated scientifically.
Objectifying the Subjective
Statistics are objective. They're math.
We apply statistical methods to data.
That data comes from, in many cases, a subjective source.
Lets take "response times" as an example.
Response time measurements seem objective: we measure how long it takes a human to respond to some stimulus. Maybe we display something on a computer screen and the participant sees it, then the participant presses a button. That is, the human subjectively sees the stimulus, then reports their subjective experience by moving their finger, which we record as an objective measurement of time passing. We researchers then apply statistical methods to the objective measurement, all too easily forgetting that the foundation was the person's subjectivity.
We link the person's subjective experience (seeing the stimulus) to the objective measurement (response time).
The foundation of psychology is "subjective" because we're studying the human experience, which is subjective.
As part of the scientific process, we measure that subjective experience with questionnaires, behavioural tasks, and neuroimaging, then try to create objective mathematical models based on the measurements that we call "data". Our models are not perfect by any stretch and it is useful to remember that they exist in a mutable social environment and should be expected to change as time marches on.
Imagine we had an AI helmet: you put on the helmet, then the helmet tells you how you feel. The helmet uses a statistical model (objective) and reports on your state of mind (subjective).
If the helmet says, "You are happy", but you don't feel happy, do you believe the helmet?
You don't, right? Even though the helmet is objective, that won't override your subjective experience of your state of mind.
In all likelihood, such an AI helmet would be trained on subjective self-report data!
A typical way to make such a device would be to put it on people, then ask "how do you feel?", then they say, "happy", then the helmet records that data-point as "happy". After a million data-points and statistical modelling with deep learning, the helmet has a very good model of when people are going to say "happy".
Even still, statistical models can be wrong. Statistical models aren't perfect and generally cannot become perfect. There are limits to our ability to model reality.
Whatever the helmet says, you should still believe yourself over the helmet.
Your subjective experience is still primary.
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