I think it goes without saying that more data is good. But the quality or strength of the data is important too. I think some debates over stereotypes rest on if they count as good quality data, or data that should override other data (firsthand experience) on how to update your prior. For instance, if you get data from mass media that “all women like chocolate more than men” but get data from most of the men and women you know that both like chocolate equally, which trumps which in if you are more likely to consider chocolate as gift to male or female friends?
You could say the societal stereotype is better data—after all stereotypes have been built up over generations, are “common knowledge”. You could say your personal, thoughtful experience is better (I trust my own people around me, not secondhand, thirdhand, or mass media cultural tropes—but what if I’m in an unrepresentative bubble, what if my friends, knowing the stereotypes are ashamed to fulfil them and say the opposite, in which case I should downweigh their claims and actually follow the stereotype more).
Also in adversarial settings you want to know if stereotypes are accurate data or are created with an agenda (e.g. in wartime many stereotypes about the enemy’s traits are not based on accurate understanding of the enemy; okay in a less obviously conflict-driven setting you might get this still—like stereotypes exaggerated to sell a product “get this for dad” even though your dad doesn’t fit the stereotypes, or “this city has friendly people” obviously sponsored by the tourism industry). They could be accurate however and in your best interest (e.g. the stereotype of citizens of this city being mean and unfriendly might be unflattering but your friend might generally care and tell you the stereotype (against the fear of generalizing) because if you’re stranded there, it’s good to know how much help you can expect from friendly strangers in borrowing a phone).
Sometimes there are clever things you could try, for example find out whether female chimpanzees like chocolate more than male chimpanzees… but of course there are situations where the rational answer is simply “I don’t know”.
That doesn’t necessarily mean no data, but could mean data that you strongly suspect are filtered or fake, without being able to sort out this mess. In other words, all evidence you have is very weak evidence: personal evidence may be weak because it is likely to be a result of your bubble (you are more likely to associate with people who like chocolate as much as you do), media evidence may be weak because media do not have sufficient incentives to say true things.
EDIT: Of course, saying “I don’t know” can make both sides angry that you don’t see how the stereotype of obviously true/false. Sometimes it is smarter to not say what you actually believe, even if the actual belief is “I don’t know”.
I think it goes without saying that more data is good. But the quality or strength of the data is important too. I think some debates over stereotypes rest on if they count as good quality data, or data that should override other data (firsthand experience) on how to update your prior. For instance, if you get data from mass media that “all women like chocolate more than men” but get data from most of the men and women you know that both like chocolate equally, which trumps which in if you are more likely to consider chocolate as gift to male or female friends?
You could say the societal stereotype is better data—after all stereotypes have been built up over generations, are “common knowledge”. You could say your personal, thoughtful experience is better (I trust my own people around me, not secondhand, thirdhand, or mass media cultural tropes—but what if I’m in an unrepresentative bubble, what if my friends, knowing the stereotypes are ashamed to fulfil them and say the opposite, in which case I should downweigh their claims and actually follow the stereotype more).
Also in adversarial settings you want to know if stereotypes are accurate data or are created with an agenda (e.g. in wartime many stereotypes about the enemy’s traits are not based on accurate understanding of the enemy; okay in a less obviously conflict-driven setting you might get this still—like stereotypes exaggerated to sell a product “get this for dad” even though your dad doesn’t fit the stereotypes, or “this city has friendly people” obviously sponsored by the tourism industry). They could be accurate however and in your best interest (e.g. the stereotype of citizens of this city being mean and unfriendly might be unflattering but your friend might generally care and tell you the stereotype (against the fear of generalizing) because if you’re stranded there, it’s good to know how much help you can expect from friendly strangers in borrowing a phone).
Sometimes there are clever things you could try, for example find out whether female chimpanzees like chocolate more than male chimpanzees… but of course there are situations where the rational answer is simply “I don’t know”.
That doesn’t necessarily mean no data, but could mean data that you strongly suspect are filtered or fake, without being able to sort out this mess. In other words, all evidence you have is very weak evidence: personal evidence may be weak because it is likely to be a result of your bubble (you are more likely to associate with people who like chocolate as much as you do), media evidence may be weak because media do not have sufficient incentives to say true things.
EDIT: Of course, saying “I don’t know” can make both sides angry that you don’t see how the stereotype of obviously true/false. Sometimes it is smarter to not say what you actually believe, even if the actual belief is “I don’t know”.