Social sciences suffer from social drsirability bias, very noisy data, difficult to formalize concepts/abstractions too leaky, and difficulties with controls. Additionally, many people have strong (and often false) intuitions about social reality overriding scientific judgement.
One could call the social world more “complex” than physical realm but “complex” is a tricky word… A human is arguably more complex than an atom; yet the models that social scientists use are much less complex than used by physicists.
Although I wouldn’t dispute the stats that you are citing here, John, I would guess these might be downstream from above difficulties.
Although I wouldn’t dispute the stats that you are citing here, John, I would guess these might be downstream from above difficulties.
I think that’s the right counterargument to make (kudos :) ). Building on it, I’d say: ok, the causal arrows go both ways here. The field draws less impressive people, who do kinda junk research, which draws less impressive people. So the different sciences end up in different equilibria, with different levels of competence among the scientists. But then, what determines the equilibrium? Why did physics end up with more competent people doing more competent work, and psychology with less competent people doing less competent work, rather than vice-versa? Unless we want to claim that it was luck of the draw, there has to be something endogenous to the underlying territories of physics and psychology which cause their sciences to end up in these different equilibria.
Once the question is framed that way, it suggests different answers.
One could maybe tell a story like “psychology is more complex than physics, so physics had more impressive work earlier on, which drew in smarter people...”. That could explain the different equilibria. But also, it feels like a just-so story; one could just as easily argue that smarter people tend to be drawn to more complex systems, where they can properly show off their merit.
Explanations like noisy data or difficulties with controls seem similar. Like, any explanation of the form “psychology is harder for reason X, so physics had more impressive work earlier on, which drew in smarter people...” feels like a just-so story; it seems at least as plausible that more competent people will be drawn to more difficult problems. (Note that both the hypotheses put forward in the OP are of this form, so this is also a response to the OP.)
Feedback loops look a little more plausible as an explanation: “insofar as it’s harder to get clear feedback on models in psychology compared to physics, it’s easier for bullshit to thrive in psychology, so smarter people go to physics where success is relatively more a function of smarts rather than academic politics, …”. I don’t really buy that explanation, since getting feedback on models seems-to-me comparably difficult in physics and in psychology; it’s a core hard part of any science. But it’s at least plausible.
The infiltration of “social reality” is another plausible explanation, which I personally find much more probable. The model would be roughly: “insofar as psychology is largely about modeling social reality and adjacent topics, psychology itself becomes a relevant battleground for social-reality-level competitions, and also people predisposed to thinking in social reality will find psychology more appealing than physics. Alas, both focus on social-reality-level competitions and predisposition for thinking in social reality are extremely strong negative predictors of one’s competence as a scientist, so psychology ends up with a lot more incompetent people than physics, …”. I probably wouldn’t endorse that exact model as worded, but I’d put a fair bit of probability on something in roughly that ballpark.
This comment by Carl Feynman has a very crisp formulation of the main problem as I see it.
They’re measuring a noisy phenomenon, yes, but that’s only half the problem. The other half of the problem is that society demands answers. New psychology results are a matter of considerable public interest and you can become rich and famous from them. In the gap between the difficulty of supply and the massive demand grows a culture of fakery. The same is true of nutrition— everyone wants to know what the healthy thing to eat is, and the fact that our current methods are incapable of discerning this is no obstacle to people who claim to know.
For a counterexample, look at the field of planetary science. Scanty evidence dribbles in from occasional spacecraft missions and telescopic observations, but the field is intellectually sound because public attention doesn’t rest on the outcome.
So, the recipe for making a broken science you can’t trust is
The public cares a lot about answers to questions that fall within the science’s domain.
The science currently has no good attack angles on those questions.
As you say, if a field is exposed to these incentives for a while, you get additional downstream problems like all the competent scientist who care about actual progress leaving. But I think that’s a secondary effect. If you replaced all the psychology grads with physics and electrical engineering grads overnight, I’d expect you’d at best get a very brief period of improvement before the incentive gradient brought the field back to the status quo. On the other hand, if the incentives suddenly changed, I think reforming the field might become possible.
This suggests that if you wanted to found new parallel fields of nutrition, psychology etc. you could trust, you should consider:
Making it rare for journalists to report on your new fields. Maybe there’s just a cultural norm against talking to the press and publishing on Twitter. Maybe people have to sign contracts about it if they want to get grants. Maybe the research is outright siloed because it is happening inside some company.
Finding funders who won’t demand answers if answers can’t be had. Seems hard. This might exclude most companies. The usual alternative is government&charity, but those tend to care too much about what the findings are. My model of how STEM manages to get useful funding out of them is that funding STEM is high-status, but STEM results are mostly too boring and removed from the public interest for the funders to get invested in them.
Like, any explanation of the form “psychology is harder for reason X, so physics had more impressive work earlier on, which drew in smarter people...” feels like a just-so story; it seems at least as plausible that more competent people will be drawn to more difficult problems. (Note that both the hypotheses put forward in the OP are of this form, so this is also a response to the OP.)
Thanks, John. I want to clarify how our hypotheses differ from the “just-so story” pattern you described.
Our hypotheses don’t claim “psychology is harder for reason X, which led to physics attracting smarter people.” Rather, we propose structural factors that may contribute to the *perception* of different disciplines’ difficulty, independent of the researchers’ capabilities.
I share your skepticism of just-so stories, which typically:
Highlight compatibility between evidence and a hypothesis
Fail to consider alternative explanations
Don’t generate novel, testable predictions
Often lack explicit calibration about confidence
We’ve tried to avoid these pitfalls in several ways:
First, we’re explicit about our confidence levels. We present these as partial explanations among many factors that likely contribute to perceived disciplinary difficulty, not as comprehensive accounts.
Second, our hypotheses can generate testable predictions. For example:
The Rigid Demands hypothesis makes it more likely that self-reported pre-commitment to specific questions should correlate with lower R² values across fields
The Fruit in the Hand hypothesis makes it more likely that the something like the Kolmogorov complexity of algorithms that solve “impressive” tasks in evolved social domains (like facial recognition) should be greater than those for non-evolved physical domains (like calculating rocket trajectories)
Third, we’ve formalized our reasoning mathematically, which helps expose assumptions and clarify the scope of our claims.
Clearly, these are speculative conjectures regarding very hard questions. That said, we think our formal approach can help move us toward more structured hypotheses about a fascinating question—something we hope is marginally better than just-so stories. :)
My model is that early on physics had very impressive & novel math, which attracted people who like math, who did more math largely with the constraint the math had to be trying to model something in the real world, which produced more impressive & novel math, which attracted more people who like math, etc etc, and this is the origin of the equilibrium.
Note a similar argument can be made for economics, though the nice math came much later on, and obviously was much less impactful than literally inventing calculus.
Social sciences suffer from social drsirability bias, very noisy data, difficult to formalize concepts/abstractions too leaky, and difficulties with controls. Additionally, many people have strong (and often false) intuitions about social reality overriding scientific judgement.
One could call the social world more “complex” than physical realm but “complex” is a tricky word… A human is arguably more complex than an atom; yet the models that social scientists use are much less complex than used by physicists.
Although I wouldn’t dispute the stats that you are citing here, John, I would guess these might be downstream from above difficulties.
I think that’s the right counterargument to make (kudos :) ). Building on it, I’d say: ok, the causal arrows go both ways here. The field draws less impressive people, who do kinda junk research, which draws less impressive people. So the different sciences end up in different equilibria, with different levels of competence among the scientists. But then, what determines the equilibrium? Why did physics end up with more competent people doing more competent work, and psychology with less competent people doing less competent work, rather than vice-versa? Unless we want to claim that it was luck of the draw, there has to be something endogenous to the underlying territories of physics and psychology which cause their sciences to end up in these different equilibria.
Once the question is framed that way, it suggests different answers.
One could maybe tell a story like “psychology is more complex than physics, so physics had more impressive work earlier on, which drew in smarter people...”. That could explain the different equilibria. But also, it feels like a just-so story; one could just as easily argue that smarter people tend to be drawn to more complex systems, where they can properly show off their merit.
Explanations like noisy data or difficulties with controls seem similar. Like, any explanation of the form “psychology is harder for reason X, so physics had more impressive work earlier on, which drew in smarter people...” feels like a just-so story; it seems at least as plausible that more competent people will be drawn to more difficult problems. (Note that both the hypotheses put forward in the OP are of this form, so this is also a response to the OP.)
Feedback loops look a little more plausible as an explanation: “insofar as it’s harder to get clear feedback on models in psychology compared to physics, it’s easier for bullshit to thrive in psychology, so smarter people go to physics where success is relatively more a function of smarts rather than academic politics, …”. I don’t really buy that explanation, since getting feedback on models seems-to-me comparably difficult in physics and in psychology; it’s a core hard part of any science. But it’s at least plausible.
The infiltration of “social reality” is another plausible explanation, which I personally find much more probable. The model would be roughly: “insofar as psychology is largely about modeling social reality and adjacent topics, psychology itself becomes a relevant battleground for social-reality-level competitions, and also people predisposed to thinking in social reality will find psychology more appealing than physics. Alas, both focus on social-reality-level competitions and predisposition for thinking in social reality are extremely strong negative predictors of one’s competence as a scientist, so psychology ends up with a lot more incompetent people than physics, …”. I probably wouldn’t endorse that exact model as worded, but I’d put a fair bit of probability on something in roughly that ballpark.
This comment by Carl Feynman has a very crisp formulation of the main problem as I see it.
So, the recipe for making a broken science you can’t trust is
The public cares a lot about answers to questions that fall within the science’s domain.
The science currently has no good attack angles on those questions.
As you say, if a field is exposed to these incentives for a while, you get additional downstream problems like all the competent scientist who care about actual progress leaving. But I think that’s a secondary effect. If you replaced all the psychology grads with physics and electrical engineering grads overnight, I’d expect you’d at best get a very brief period of improvement before the incentive gradient brought the field back to the status quo. On the other hand, if the incentives suddenly changed, I think reforming the field might become possible.
This suggests that if you wanted to found new parallel fields of nutrition, psychology etc. you could trust, you should consider:
Making it rare for journalists to report on your new fields. Maybe there’s just a cultural norm against talking to the press and publishing on Twitter. Maybe people have to sign contracts about it if they want to get grants. Maybe the research is outright siloed because it is happening inside some company.
Finding funders who won’t demand answers if answers can’t be had. Seems hard. This might exclude most companies. The usual alternative is government&charity, but those tend to care too much about what the findings are. My model of how STEM manages to get useful funding out of them is that funding STEM is high-status, but STEM results are mostly too boring and removed from the public interest for the funders to get invested in them.
To return to LessWrong’s favorite topic, this doesn’t bode well for alignment.
Thanks, John. I want to clarify how our hypotheses differ from the “just-so story” pattern you described.
Our hypotheses don’t claim “psychology is harder for reason X, which led to physics attracting smarter people.” Rather, we propose structural factors that may contribute to the *perception* of different disciplines’ difficulty, independent of the researchers’ capabilities.
I share your skepticism of just-so stories, which typically:
Highlight compatibility between evidence and a hypothesis
Fail to consider alternative explanations
Don’t generate novel, testable predictions
Often lack explicit calibration about confidence
We’ve tried to avoid these pitfalls in several ways:
First, we’re explicit about our confidence levels. We present these as partial explanations among many factors that likely contribute to perceived disciplinary difficulty, not as comprehensive accounts.
Second, our hypotheses can generate testable predictions. For example:
The Rigid Demands hypothesis makes it more likely that self-reported pre-commitment to specific questions should correlate with lower R² values across fields
The Fruit in the Hand hypothesis makes it more likely that the something like the Kolmogorov complexity of algorithms that solve “impressive” tasks in evolved social domains (like facial recognition) should be greater than those for non-evolved physical domains (like calculating rocket trajectories)
Third, we’ve formalized our reasoning mathematically, which helps expose assumptions and clarify the scope of our claims.
Clearly, these are speculative conjectures regarding very hard questions. That said, we think our formal approach can help move us toward more structured hypotheses about a fascinating question—something we hope is marginally better than just-so stories. :)
My model is that early on physics had very impressive & novel math, which attracted people who like math, who did more math largely with the constraint the math had to be trying to model something in the real world, which produced more impressive & novel math, which attracted more people who like math, etc etc, and this is the origin of the equilibrium.
Note a similar argument can be made for economics, though the nice math came much later on, and obviously was much less impactful than literally inventing calculus.