Can't say whether I agree or not but I'm reminded of Werner Herzog's interview with GQ[1]:
"I think psychology and self-reflection is one of the major catastrophes of the twentieth century. A major, major mistake. And it’s only one of the mistakes of the twentieth century, which makes me think that the twentieth century in its entirety was a mistake...
There’s something profoundly wrong-as wrong as the Spanish Inquisition was. The Spanish Inquisition had one goal, to eradicate all traces of Muslim faith on the soil of Spain, and hence you had to confess and proclaim the innermost deepest nature of your faith to the commission. And almost as a parallel event, explaining and scrutinizing the human soul, into all its niches and crooks and abysses and dark corners, is not doing good to humans. We have to have our dark corners and the unexplained. We will become uninhabitable in a way an apartment will become uninhabitable if you illuminate every single dark corner and under the table and wherever-you cannot live in a house like this anymore. And you cannot live with a person anymore-let’s say in a marriage or a deep friendship-if everything is illuminated, explained, and put out on the table. There is something profoundly wrong. It’s a mistake. It’s a fundamentally wrong approach toward human beings."
Counterpoint: valid statistical methods and good experimental design has produced good psychological science. Most notably, the predictive power of various theories has been demonstrated in the various social media and advertising algorithms that target different categories of people.
Most of psychology is borderline religious bunkum, but not all. It will eventually converge with a theory of biological intelligence and neuroscience, and until then, will likely not improve much from broad statistical tools and observations.
The understated point is "valid" in "valid statistical methods".
Frequently, social sciences (and even a lot of medicine: basically, anything involving humans where applying valid statistical methods can quickly become unethical) rely on too small a sample set to eradicate the noise.
You do not have to model all factors, because it is impossible to do so, you just need to have a large enough sample to ensure statistical significance that's not out of "statistics in a week" course.
I've seen one too many 50-subjects study, that claims to have extremely high confidence.
> Most notably, the predictive power of various theories has been demonstrated in the various social media and advertising algorithms that target different categories of people.
Can you be more specific? I’m not sure what the field of psychology has to do with algorithms that predict relevance and engagement based on their own data on clicks and other user actions.
