You can’t escape the bias by simply making a decision to go to system II
System 2 is not enough. But if there is a straw of hope to mitigate the bias in a particular situation where finding a correct solution is important, the only chance to find it is to search for it using your System 2. Suppose have to decide the foreseeable probability of flooding, you know about hindsight bias and you actually care about finding the correct estimate. How should you proceed? Perhaps you have to devise a method that you will use to make estimation in advance of looking at the date. Or perhaps you will make a decision to obtain data from various cities in the same region and use logistic regression to make an estimate. Or perhaps you will use some other estimator. What I am trying to say is that all these methods of deliberate reasoning (decision making algorithms, statistical analysis, etc.) are executed by System 2 and not System 1. I am not trying to say that System 2 guarantees that we will avoid bias. Firstly, in my understanding, System 2 and System 1 aren’t separate systems, they are merely two ends of the continuum. Secondly, just because an algorithm is executed by System 2 doesn’t mean that that algorithm is good.
As I have said, System 2 seems to be close to necessary, but obviously it is not sufficient (for example, rolling a dice to “determine” the probability of flooding doesn’t rely on intuition). Algorithms that are executed by System 2 are usually somewhat more transparent, therefore it is easier to detect their mistakes and biases. This means that it is easier to fix them. Thus there is a chance that at least some of those algorithms are good enough to be good estimators and avoid biases.
Transparency is what makes System 2 preferable to System 1 in this particular situation. In other types of situations or other types of questions, as dthunt noted, feedback loops can be useful to train your intuition to achieve greater accuracy even though intuitive reasoning itself is not necessarily transparent.
System 2 is not enough. But if there is a straw of hope to mitigate the bias in a particular situation where finding a correct solution is important, the only chance to find it is to search for it using your System 2.
No, you can also take a good night sleep to give your System I more time to anaylse the situation to improve it’s output.
You can also do exercises to calibrate your credence. Calibration training for probability estimates is probably one of the best ways to get them right.
System 2 is not enough. But if there is a straw of hope to mitigate the bias in a particular situation where finding a correct solution is important, the only chance to find it is to search for it using your System 2. Suppose have to decide the foreseeable probability of flooding, you know about hindsight bias and you actually care about finding the correct estimate. How should you proceed? Perhaps you have to devise a method that you will use to make estimation in advance of looking at the date. Or perhaps you will make a decision to obtain data from various cities in the same region and use logistic regression to make an estimate. Or perhaps you will use some other estimator. What I am trying to say is that all these methods of deliberate reasoning (decision making algorithms, statistical analysis, etc.) are executed by System 2 and not System 1. I am not trying to say that System 2 guarantees that we will avoid bias. Firstly, in my understanding, System 2 and System 1 aren’t separate systems, they are merely two ends of the continuum. Secondly, just because an algorithm is executed by System 2 doesn’t mean that that algorithm is good.
As I have said, System 2 seems to be close to necessary, but obviously it is not sufficient (for example, rolling a dice to “determine” the probability of flooding doesn’t rely on intuition). Algorithms that are executed by System 2 are usually somewhat more transparent, therefore it is easier to detect their mistakes and biases. This means that it is easier to fix them. Thus there is a chance that at least some of those algorithms are good enough to be good estimators and avoid biases.
Transparency is what makes System 2 preferable to System 1 in this particular situation. In other types of situations or other types of questions, as dthunt noted, feedback loops can be useful to train your intuition to achieve greater accuracy even though intuitive reasoning itself is not necessarily transparent.
No, you can also take a good night sleep to give your System I more time to anaylse the situation to improve it’s output.
You can also do exercises to calibrate your credence. Calibration training for probability estimates is probably one of the best ways to get them right.