Hi Paul. I reject the reasonableness of defining an "association" as a bias. Indeed, defining "bias" is pretty tricky. Sometimes, it is mere preference. Other times it is deviation from normative stat model. Yet other times it, it is some sort of systematic error. Yet other times, it is two people judging the same stimuli differently. Associations are none of these things. Associations may predict some of these things some of the time, but: 1. That is an empirical question each time; 2. If A (associations) predict B (preferences, behavior, judgments) then A and B must be different things. Put differently, I associate ham with cheese. To refer to this as any sort of bias (not that you did, but it is an association which you did state is a bias) strikes me as unjustified. Then you get the nasty downstream effects, where by A is amply demonstrated (association) and then simply presumed to constitute some sort of nasty bias (e.g., racial prejudice or stereotypes). Very motte (there is an association!) and bailey (look how racist they all are!).
It then goes downhill from there. Even when associations predict some outcome, it does not necessarily constitute the bailey. Say IAT scores predict discrim, r=.2 or so. This can occur because high racism iat scores correspond to racist behavior, 0 corresponds to egalitarian behavior and negative scores to anti-White behavior. Or it can occur because high "racism" IAT scores correspond to egalitarian behavior and ones near zero to anti-White behavior. For a real example, see Blanton et al 2009 JAP.
I'm having a tough time connecting your comments with my post. I say that implicit biases are associations we have with groups, often with some sort of positive or negative feelings. So, no, you're wrong -- for me, the association between ham and cheese isn't a bias.
I don't say or imply that biases are nasty or racist (though I think some are). I mean, I have a section called "Does implicit bias mean that we are all, in general, racist?" and then write "My answer is: No". Hard to be more clear than that. And since I argue _against_ the predictive power of IATs and say that they don't predict discrimination, I don't get the point of your last paragraph at all.
I'm very interested in your views on this topic, and would love your feedback, but I worry that you wrote your comment without actually reading my post.
I read the whole thing carefully, Paul. I was responding to this, which strikes me as the definitional glue holding together much of the post. You wrote
"What are implicit biases?"
"They are the associations that we have with human groups, often with some sort of positive or negative feelings. Some examples are associating elderly people with incompetence, men with violence, women with nurturance, and Jews with finance."
So you answer to the q, "What are implicit biases" is associations with human groups. My comment addresses that head-on and says, "not so fast."
You then continue:
"These studies have been done with millions of people and have found that people have negative associations on the basis of race, age, sexual orientation, body weight, disability, and other factors."
Well, maybe. They show differently reaction times to various double paired-then-inverted-double-pairs of concepts. But the entire point of my comment (and, really Blanton et al's paper) is that 0 does not necessarily correspond to egalitarian beliefs, judgments or behaviors. Indeed, they found that IAT scores much higher than 0 (typically interpreted as "negative associations") correspond to egalitarian-ness. If scores much higher than 0 typically or even intermittently correspond to egalitarian-ness, then it is not justified to interpret the many studies showing IAT>0 as "negative associations" in any meaningful way with respect to any sort of bias.
I decided to comment because, though I do think you did a good job here capturing some of the limitations and interpretive problems with IAT research, the post understates known limitations to the IAT that undercut justifications for interpreting findings as bias (as defined in any of the ways listed in my first comment).
Hi Lee. You say that IAT scores don't reliably connect how "egalitarian" people are. Are you sure we disagree about this? Maybe we're using the word in different ways, but I certainly wouldn't say that the IAT measures how egalitarian we are!
But, yes, I do think the IAT can detect (roughly) "negative associations". If you are quicker to connect terms like "bad" to the elderly (vs. positive terms like "good"), say, this suggests that we have a negative association with elderly people. I guess we disagree about this?
It is a reaction time difference, not a bias. Whether any particular score, including a faster response to elderly-bad/young-good than to elderly-good/young-bad reflects a "negative association" in any sense other than "speed-of-reaction-time" is precisely what is at issue. And yes, I am saying that a faster response on the iat to e-b/y-g than to e-g/y-b does not necessarily mean "negative association" in any conventional meaning of the word "negative."
Relatedly, you did define implicit bias as an association involving human groups, so that would exclude my ham and cheese example (though, cognitively, I do not see why it should, but its your definition, so I'll go with it). I associate the French with wine, pro baseball players with athleticism, and rural dwellers in the U.S. with Trump support. I do not see how any of these would constitute bias for any conventional meaning of the term bias. If one agrees that some associations are not bias, then bias cannot be defined as associations of concepts with human groups. It remains possible that some associations of concepts with human groups are some sort of bias, but one would then need to define bias as something other than mere associations.
My definition of "implicit bias" doesn't include ham and cheese because nobody would think of ham and cheese as a bias. I'm not sure why you're confused about this definitional choice--shouldn't a good definition match the usual meaning of a term? And I agree that associating French with wine, etc. isn't a bias either. But I did also mention valence -- "often with some sort of positive or negative feelings". If I took out "often" (which I probably should), would we be on the same page?
If we get a faster response to elderly-bad/young-good than to elderly-good/young-bad, there has to be a reason for this. I think it's because we associate elderly with bad and young with good. You disagree, which is fine, but what's your alternative?
No, that's not really the point. The point is that the IAT is so filled with measurement artifacts that a simple interpretation of "reaction time diff" as "association" is not necessarily justified. See Fiedler et al, 2006; Blanton et al 2015 (Towards a meaningful metric...); Sherman's various papers on The Quad Model; Machery's work on IAT anamolies or Gawronski et al, 2022, Psych Inq, title: "Reflections on the difference between implicit bias and bias on implicit measures." Great exchange there. Quoting G et al: "Our rejection of BIM as an indicator of unconscious biases raises the question of whether implicit measures still have any value for research on social biases. Some commentators seemed rather skeptical about that, noting that the research program on BIM has lost considerable momentum over the last years—partly due to unresolved debates about the predictive validity of BIM and meta-analytic evidence questioning the presumed causal role of BIM in discriminatory behavior." [BIM=Bias on implicit measures]. And also: "Expanding on the debate about the meaning of the term implicit, we discourage using the term implicit in reference to bias. Use of the term implicit is just too flexible and inconsistent to ensure conceptual precision."
Or one stop shop: https://osf.io/74whk/, >40 sources critical of the IAT in particular or the concept of implicit bias in general.
How to disabiguate a measure of received wisdom from one measuring prejudice? It's really the same question.
One should look at the anomalies produced by the theory.
The important one I NEVER see Banaji et al discuss in reference to the IAT is that of "Slow learning". (except perhaps Lee Dunham)
This is the major difference between the RACE: GOOD-BAD IAT and the GENDER: GOOD-BAD IAT. They failed to find any potentially causal slow learning effects for the Black:White, even though they were forced to create measures for younger and younger age groups. (as low as 5)
This could mean that part of the RACE IAT construct measures the same type of categorisation effect of boys pulling on different coloured football shirts. (i.e. Team White and Team Black)
However, the Harvard Implict study shows clear longitudinal affects for Gender with increasing shifts towards Male: Bad, Female:Good for BOTH sexes. One might therefore conclude that a slow learning effect is present, which would not be surprising due to current messaging to boys and girls as they go from adolescence to adulthood.
If that is the case then the IAT must be separated into two components - Instantaneous and Slow Learning (Speculating a bit but perhaps corresponding to System 1 and 2 related evaluations).
Lastly, in terms of Stereotype forms of the IAT, how to disambiguate between stereotypes are on the whole are true and ones that are a product of bias.
This could be the problem of "Systematizer" vs "Empathiser" perceptions.
Systematizers might assess the world as it happens to be where as empathisers might assess the world as it ought to be. (Akin to Jungian Thinking and Feeling types).
e.g. If an IAT result shows Men: Violent, Women: Passive, then are you measuring actual bias or Subjective perception of a Stereotype?
Fascinating, thank you
Hi Paul. I reject the reasonableness of defining an "association" as a bias. Indeed, defining "bias" is pretty tricky. Sometimes, it is mere preference. Other times it is deviation from normative stat model. Yet other times it, it is some sort of systematic error. Yet other times, it is two people judging the same stimuli differently. Associations are none of these things. Associations may predict some of these things some of the time, but: 1. That is an empirical question each time; 2. If A (associations) predict B (preferences, behavior, judgments) then A and B must be different things. Put differently, I associate ham with cheese. To refer to this as any sort of bias (not that you did, but it is an association which you did state is a bias) strikes me as unjustified. Then you get the nasty downstream effects, where by A is amply demonstrated (association) and then simply presumed to constitute some sort of nasty bias (e.g., racial prejudice or stereotypes). Very motte (there is an association!) and bailey (look how racist they all are!).
It then goes downhill from there. Even when associations predict some outcome, it does not necessarily constitute the bailey. Say IAT scores predict discrim, r=.2 or so. This can occur because high racism iat scores correspond to racist behavior, 0 corresponds to egalitarian behavior and negative scores to anti-White behavior. Or it can occur because high "racism" IAT scores correspond to egalitarian behavior and ones near zero to anti-White behavior. For a real example, see Blanton et al 2009 JAP.
HI, Lee.
I'm having a tough time connecting your comments with my post. I say that implicit biases are associations we have with groups, often with some sort of positive or negative feelings. So, no, you're wrong -- for me, the association between ham and cheese isn't a bias.
I don't say or imply that biases are nasty or racist (though I think some are). I mean, I have a section called "Does implicit bias mean that we are all, in general, racist?" and then write "My answer is: No". Hard to be more clear than that. And since I argue _against_ the predictive power of IATs and say that they don't predict discrimination, I don't get the point of your last paragraph at all.
I'm very interested in your views on this topic, and would love your feedback, but I worry that you wrote your comment without actually reading my post.
I read the whole thing carefully, Paul. I was responding to this, which strikes me as the definitional glue holding together much of the post. You wrote
"What are implicit biases?"
"They are the associations that we have with human groups, often with some sort of positive or negative feelings. Some examples are associating elderly people with incompetence, men with violence, women with nurturance, and Jews with finance."
So you answer to the q, "What are implicit biases" is associations with human groups. My comment addresses that head-on and says, "not so fast."
You then continue:
"These studies have been done with millions of people and have found that people have negative associations on the basis of race, age, sexual orientation, body weight, disability, and other factors."
Well, maybe. They show differently reaction times to various double paired-then-inverted-double-pairs of concepts. But the entire point of my comment (and, really Blanton et al's paper) is that 0 does not necessarily correspond to egalitarian beliefs, judgments or behaviors. Indeed, they found that IAT scores much higher than 0 (typically interpreted as "negative associations") correspond to egalitarian-ness. If scores much higher than 0 typically or even intermittently correspond to egalitarian-ness, then it is not justified to interpret the many studies showing IAT>0 as "negative associations" in any meaningful way with respect to any sort of bias.
I decided to comment because, though I do think you did a good job here capturing some of the limitations and interpretive problems with IAT research, the post understates known limitations to the IAT that undercut justifications for interpreting findings as bias (as defined in any of the ways listed in my first comment).
Hi Lee. You say that IAT scores don't reliably connect how "egalitarian" people are. Are you sure we disagree about this? Maybe we're using the word in different ways, but I certainly wouldn't say that the IAT measures how egalitarian we are!
But, yes, I do think the IAT can detect (roughly) "negative associations". If you are quicker to connect terms like "bad" to the elderly (vs. positive terms like "good"), say, this suggests that we have a negative association with elderly people. I guess we disagree about this?
It is a reaction time difference, not a bias. Whether any particular score, including a faster response to elderly-bad/young-good than to elderly-good/young-bad reflects a "negative association" in any sense other than "speed-of-reaction-time" is precisely what is at issue. And yes, I am saying that a faster response on the iat to e-b/y-g than to e-g/y-b does not necessarily mean "negative association" in any conventional meaning of the word "negative."
Relatedly, you did define implicit bias as an association involving human groups, so that would exclude my ham and cheese example (though, cognitively, I do not see why it should, but its your definition, so I'll go with it). I associate the French with wine, pro baseball players with athleticism, and rural dwellers in the U.S. with Trump support. I do not see how any of these would constitute bias for any conventional meaning of the term bias. If one agrees that some associations are not bias, then bias cannot be defined as associations of concepts with human groups. It remains possible that some associations of concepts with human groups are some sort of bias, but one would then need to define bias as something other than mere associations.
My definition of "implicit bias" doesn't include ham and cheese because nobody would think of ham and cheese as a bias. I'm not sure why you're confused about this definitional choice--shouldn't a good definition match the usual meaning of a term? And I agree that associating French with wine, etc. isn't a bias either. But I did also mention valence -- "often with some sort of positive or negative feelings". If I took out "often" (which I probably should), would we be on the same page?
If we get a faster response to elderly-bad/young-good than to elderly-good/young-bad, there has to be a reason for this. I think it's because we associate elderly with bad and young with good. You disagree, which is fine, but what's your alternative?
No, that's not really the point. The point is that the IAT is so filled with measurement artifacts that a simple interpretation of "reaction time diff" as "association" is not necessarily justified. See Fiedler et al, 2006; Blanton et al 2015 (Towards a meaningful metric...); Sherman's various papers on The Quad Model; Machery's work on IAT anamolies or Gawronski et al, 2022, Psych Inq, title: "Reflections on the difference between implicit bias and bias on implicit measures." Great exchange there. Quoting G et al: "Our rejection of BIM as an indicator of unconscious biases raises the question of whether implicit measures still have any value for research on social biases. Some commentators seemed rather skeptical about that, noting that the research program on BIM has lost considerable momentum over the last years—partly due to unresolved debates about the predictive validity of BIM and meta-analytic evidence questioning the presumed causal role of BIM in discriminatory behavior." [BIM=Bias on implicit measures]. And also: "Expanding on the debate about the meaning of the term implicit, we discourage using the term implicit in reference to bias. Use of the term implicit is just too flexible and inconsistent to ensure conceptual precision."
Or one stop shop: https://osf.io/74whk/, >40 sources critical of the IAT in particular or the concept of implicit bias in general.
How to disabiguate a measure of received wisdom from one measuring prejudice? It's really the same question.
One should look at the anomalies produced by the theory.
The important one I NEVER see Banaji et al discuss in reference to the IAT is that of "Slow learning". (except perhaps Lee Dunham)
This is the major difference between the RACE: GOOD-BAD IAT and the GENDER: GOOD-BAD IAT. They failed to find any potentially causal slow learning effects for the Black:White, even though they were forced to create measures for younger and younger age groups. (as low as 5)
This could mean that part of the RACE IAT construct measures the same type of categorisation effect of boys pulling on different coloured football shirts. (i.e. Team White and Team Black)
However, the Harvard Implict study shows clear longitudinal affects for Gender with increasing shifts towards Male: Bad, Female:Good for BOTH sexes. One might therefore conclude that a slow learning effect is present, which would not be surprising due to current messaging to boys and girls as they go from adolescence to adulthood.
If that is the case then the IAT must be separated into two components - Instantaneous and Slow Learning (Speculating a bit but perhaps corresponding to System 1 and 2 related evaluations).
Lastly, in terms of Stereotype forms of the IAT, how to disambiguate between stereotypes are on the whole are true and ones that are a product of bias.
This could be the problem of "Systematizer" vs "Empathiser" perceptions.
Systematizers might assess the world as it happens to be where as empathisers might assess the world as it ought to be. (Akin to Jungian Thinking and Feeling types).
e.g. If an IAT result shows Men: Violent, Women: Passive, then are you measuring actual bias or Subjective perception of a Stereotype?