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Author Information: Kamili Posey, Kingsborough College, Kamili.Posey@kbcc.cuny.edu.

Posey, Kamili. “Scientism in the Philosophy of Implicit Bias Research.” Social Epistemology Review and Reply Collective 7, no. 10 (2018): 1-15.

Kamili Posey’s article was posted over two instalments. You can read the first here, but the pdf of the article includes the entire piece, and gives specific page references. Shortlink: https://wp.me/p1Bfg0-41k

Image by Rigoberto Garcia via Flickr / Creative Commons

 

In the previous piece, I outlined some concerns with philosophers, and particularly philosophers of social science, assuming the success of implicit interventions into implicit bias. Motivated by a pointed note by Jennifer Saul (2017), I aimed to briefly go through some of the models lauded as offering successful interventions and, in essence, “get out of the armchair.”

(IAT) Models and Egalitarian Goal Models

In this final piece, I go through the last two models, Glaser and Knowles’ (2007) and Blair et al.’s (2001) (IAT) models and Moskowitz and Li’s (2011) egalitarian goal model. I reiterate that this is not an exhaustive analysis of such models nor is it intended as a criticism of experiments pertaining to implicit bias. Mostly, I am concerned that the science is interesting but that the scientism – the application of tentative results to philosophical projects – is less so. It is from this point that I proceed.

Like Mendoza et al.’s (2010) implementation intentions, Glaser and Knowles’ (2007) (IMCP) aims to capture implicit motivations that are capable of inhibiting automatic stereotype activation. Glaser and Knowles measure (IMCP) in terms of an implicit negative attitude toward prejudice, or (NAP), and an implicit belief that oneself is prejudiced, or (BOP). This is done by retooling the (IAT) to fit both (NAP) and (BOP): “To measure NAP we constructed an IAT that pairs the categories ‘prejudice’ and ‘tolerance’ with the categories ‘bad’ and ‘good.’ BOP was assessed with an IAT pairing ‘prejudiced’ and ‘tolerant’ with ‘me’ and ‘not me.’”[1]

Study participants were then administered the Shooter Task, the (IMCP) measures, and the Race Prejudice (IAT) and Race-Weapons Stereotype (RWS) tests in a fixed order. They predicted that (IMCP) as an implicit goal for those high in (IMCP) “should be able to short-circuit the effect of implicit anti-Black stereotypes on automatic anti-Black behavior.”[2] The results seemed to suggest that this was the case. Glaser and Knowles found that study participants who viewed prejudice as particularly bad “[showed] no relationship between implicit stereotypes and spontaneous behavior.”[3]

There are a few considerations missing from the evaluation of the study results. First, with regard to the Shooter Task, Glaser and Knowles (2007) found that “the interaction of target race by object type, reflecting the Shooter Bias, was not statistically significant.”[4] That is, the strength of the relationship that Correll et al. (2002) found between study participants and the (high) likelihood that they would “shoot” at black targets was not found in the present study. Additionally, they note that they “eliminated time pressure” from the task itself. Although it was not suggested that this impacted the usefulness of the measure of Shooter Bias, it is difficult to imagine that it did not do so. To this, they footnote the following caveat:

Variance in the degree and direction of the stereotype endorsement points to one reason for our failure to replicate Correll et. al’s (2002) typically robust Shooter Bias effect. That is, our sample appears to have held stereotypes linking Blacks and weapons/aggression/danger to a lesser extent than did Correll and colleagues’ participants. In Correll et al. (2002, 2003), participants one SD below the mean on the stereotype measure reported an anti-Black stereotype, whereas similarly low scorers on our RWS IAT evidenced a stronger association between Whites and weapons. Further, the adaptation of the Shooter Task reported here may have been less sensitive than the procedure developed by Correll and colleagues. In the service of shortening and simplifying the task, we used fewer trials, eliminated time pressure and rewards for speed and accuracy, and presented only one background per trial.[5]

Glaser and Knowles claimed that the interaction of the (RWS) with the Shooter Task results proved “significant,” however, if the Shooter Bias failed to materialize (in the standard Correll et al. way) with study participants, it is difficult to see how the (RWS) was measuring anything except itself, generally speaking. This is further complicated by the fact that the interaction between the Shooter Bias and the (RWS) revealed “a mild reverse stereotype associating Whites with weapons (d = -0.15) and a strong stereotype associating Blacks with weapons (d = 0.83), respectively.”[6]

Recall that Glaser and Knowles (2007) aimed to show that participants high in (IMCP) would be able to inhibit implicit anti-black stereotypes and thus inhibit automatic anti-black behaviors. Using (NAP) and (BOP) as proxies for implicit control, participants high in (NAP) and moderate in (BOP) – as those with moderate (BOP) will be motivated to avoid bias – should show the weakest association between (RWS) and Shooter Bias. Instead, the lowest levels of Shooter Bias were seen in “low NAP, high BOP, and low RWS” study participants, or those who do not disapprove of prejudice, would describe themselves as prejudiced, and also showed lowest levels of (RWS).[7]

They noted that neither “NAP nor BOP alone was significantly related to the Shooter Bias,” but “the influence of RWS on Shooter Bias remained significant.”[8] In fact, greater bias was actually found with higher (NAP) and (BOP) levels.[9] This bias seemed to map on to the initial results of the Shooter Task results. It is most likely that (RWS) was the most important measure in this study for assessing implicit bias, not, as the study claimed, for assessing implicit motivation to control prejudice.

What Kind of Bias?

It is also not clear that the (RWS) was not capturing explicit bias instead of implicit bias in this study. At the point at which study participants were tasked with the (RWS), automatic stereotype activation may have been inhibited just in virtue of study participants involvement in the Shooter Task and (IAT) assessments regarding race-related prejudice. That is, race-sensitivity was brought to consciousness in the sequencing of the test process.

Although we cannot get into the heads of the study participants, this counter explanation seems a compelling possibility. That is, that the sequential tasks involved in the study captured study participants’ ability to increase focus and increase conscious attention to the race-related (IAT) test. Additionally, it is possible that some study participants could both cue and follow their own conscious internal commands, “If I see a black face, I won’t judge!” Consider that this is exactly how implementation intentions work.

Consider that this is also how Armageddon chess and other speed strategy games work. In Park et al.’s (2008) follow-up study on (IMCP) and cognitive depletion, they retreat somewhat from their initial claims about the implicit nature of (IMCP):

We cannot state for certain that our measure of IMCP reflects a purely nonconscious construct, nor that differential speed to “shoot” Black armed men vs. White armed men in a computer simulation reflects purely automatic processes. Most likely, the underlying stereotypes, goals, and behavioral responses represent a blend of conscious and nonconscious influences…Based on the results of the present study and those of Glaser and Knowles (2008), it would be premature to conclude that IMCP is a purely and wholly automatic construct, meeting the “four horsemen” criteria (Bargh, 1990). Specifically, it is not yet clear whether high IMCP participants initiate control of prejudice without intention; whether implicit control of prejudice can itself be inhibited, if for some reason someone wanted to; nor whether IMCP-instigated control of spontaneous bias occurs without awareness.[10]

If the (IMCP) potentially measures low-level conscious attention, this makes the question of what implicit measurements actually measure in the context of sequential tasks all the more important. In the two final examples, Blair et al.’s (2001) study on the use of counterstereotype imagery and Moskowitz and Li’s (2011) study on the use of counterstereotype egalitarian goals, we are again confronted with the issue of sequencing. In the study by Moskowitz and Li, study participants were asked to write down an example of a time when “they failed to live up to the ideal specified by an egalitarian goal, and to do so by relaying an event relating to African American men.”[11]

They were then given a series of computerized LDTs (lexicon decision tasks) and primes involving photographs of black and white faces and stereotypical and non-stereotypical attributes of black people (crime, lazy, stupid, nervous, indifferent, nosy). Over a series of four experiments, Moskowitz and Li found that when egalitarian goals were “accessible,” study participants were able to successfully generate stereotype inhibition. Blair et al. asked study participants to use counterstereotypical (CS) gender imagery over a series of five experiments, e.g., “Think of a strong, capable woman,” and then administered a series of implicit measures, including the (IAT).

Similar to Moskowitz and Li (2011), Blair et al. (2001) found that (CS) gender imagery was successful in reducing implicit gender stereotypes leaving “little doubt that the CS mental imagery per se was responsible for diminishing implicit stereotypes.”[12] In both cases, the study participants were explicitly called upon to focus their attention on experiences and imagery pertaining to negative stereotypes before the implicit measures, i.e., tasks, were administered. Again it is not clear that the implicit measures measured the supposed target.

In the case of Moskowitz and Li’s (2011) experiment, the study participants began by relating moments in their lives where they failed to live up to their goals. However, those goals can only be understood within a particular social and political framework where holding negatively prejudicial beliefs about African-American men is often explicitly judged harshly, even if not implicitly so. Given this, we might assume that the study participants were compelled into a negative affective state. But does this matter? As suggested by the study by Monteith (1993), and later study by Amodio et. al (2007), guilt can be a powerful tool.[13]

Questions of Guilt

If guilt was produced during the early stages of the experiment, it may have also participated in the inhibition of stereotype activation. Moskowitz and Li (2011) noted that “during targeted questioning in the debriefing, no participants expressed any conscious intent to inhibit stereotypes on the task, nor saw any of the tasks performed during the computerized portion of the experiment as related to the egalitarian goals they had undermined earlier in the session.”[14]

But guilt does not have to be conscious for it to produce effects. The guilt produced by recalling a moment of negative bias could be part and parcel of a larger feeling of moral failure. Moskowitz and Li needed to adequately disambiguate competing implicit motivations for stereotype inhibition before arriving at a definitive conclusion. This, I think, is a limitation of the study.

However, the same case could be made for (CS) imagery. Blair et al. (2001) noted that it is, in fact, possible that they too have missed competing motivations and competing explanations for stereotype inhibition. Particularly, they suggested that by emphasizing counterstereotyping the researchers “may have communicated the importance of avoiding stereotypes and increased their motivation to do so.”[15] Still, the researchers dismissed that this would lead to better (faster, more accurate) performance of the (IAT), but that is merely asserting that the (IAT) must measure exactly what the (IAT) claims that it does. Fast, accurate, and conscious measures are excluded from that claim. Complicated internal motivations are excluded from that claim.

But on what grounds? Consider Fielder et al.’s (2006) argument that the (IAT) is susceptible to faking and strategic processing, or Brendl et al.’s (2001) argument that it is not possible to infer a single cause from (IAT) results, or Fazio and Olson’s (2003) claim “the IAT has little to do with what is automatically activated in response to a given stimulus.”[16]

These studies call into question the claim that implicit measures like the (IAT) can measure implicit bias in the clear, problem-free manner that is often suggested in the literature. Implicit interventions into implicit bias that utilize the (IAT) are difficult to support for this reason. Implicit interventions that utilize sequential (IAT) tasks are also difficult to support for this reason. Of course, this is also live debate and the problems I have discussed here are far from the only ones that plague this type of research.[17]

That said, when it comes to this research we are too often left wondering if the measure itself is measuring the right thing. Are we capturing implicit bias or some other socially generated phenomenon? Are the measured changes we see in study results reflecting the validity of the instrument or the cognitive maneuverings of study participants? These are all critical questions that need sussing out. The temporary result is that the target conclusion that implicit interventions will lead to reductions in real-world discrimination will move further away.[18] We find evidence of this conclusion in Forscher et al.’s (2018) meta-analysis of 492 implicit interventions:

We found little evidence that changes in implicit measures translated into changes in explicit measures and behavior, and we observed limitations in the evidence base for implicit malleability and change. These results produce a challenge for practitioners who seek to address problems that are presumed to be caused by automatically retrieved associations, as there was little evidence showing that change in implicit measures will result in changes for explicit measures or behavior…Our results suggest that current interventions that attempt to change implicit measures will not consistently change behavior in these domains. These results also produce a challenge for researchers who seek to understand the nature of human cognition because they raise new questions about the causal role of automatically retrieved associations…To better understand what the results mean, future research should innovate with more reliable and valid implicit, explicit, and behavioral tasks, intensive manipulations, longitudinal measurement of outcomes, heterogeneous samples, and diverse topics of study.[19]

Finally, what I take to be behind Alcoff’s (2010) critical question at the beginning of this piece is a kind of skepticism about how individuals can successfully tackle implicit bias through either explicit or implicit practices without the support of the social spaces, communities, and institutions that give shape to our social lives. Implicit bias is related to the culture one is in and the stereotypes it produces. So instead of insisting on changing people to reduce stereotyping, what if we insisted on changing the culture?

As Alcoff notes: “We must be willing to explore more mechanisms for redress, such as extensive educational reform, more serious projects of affirmative action, and curricular mandates that would help to correct the identity prejudices built up out of faulty narratives of history.”[20] This is an important point. It is a point that philosophers who work on implicit bias would do well to take seriously.

Science may not give us the way out of racism, sexism, and gender discrimination. At the moment, it may only give us tools for seeing ourselves a bit more clearly. Further claims about implicit interventions appear as willful scientism. They reinforce the belief that science can cure all of our social and political ills. But this is magical thinking.

Contact details: Kamili.Posey@kbcc.cuny.edu

References

Alcoff, Linda. (2010). “Epistemic Identities,” in Episteme 7 (2), p. 132.

Amodio, David M., Devine, Patricia G., and Harmon-Jones, Eddie. (2007). “A Dynamic Model of Guilt: Implications for Motivation and Self-Regulation in the Context of Prejudice,” in Psychological Science 18(6), pp. 524-30.

Blair, I. V., Ma, J. E., & Lenton, A. P. (2001). “Imagining Stereotypes Away: The Moderation of Implicit Stereotypes Through Mental Imagery,” in Journal of Personality and Social Psychology, 81:5, p. 837.

Correll, Joshua, Bernadette Park, Bernd Wittenbrink, and Charles M. Judd. (2002). “The Police Officer’s Dilemma: Using Ethnicity to Disambiguate Potentially Threatening Individuals,” in Journal of Personality and Social Psychology, Vol. 83, No. 6, 1314–1329.

Devine, P. G., & Monteith, M. J. (1993). “The Role of Discrepancy-Associated Affect in Prejudice Reduction,” in Affect, Cognition and Stereotyping: Interactive Processes in Group Perception, eds., D. M. Mackie & D. L. Hamilton. San Diego: Academic Press, pp. 317–344.

Forscher, Patrick S., Lai, Calvin K., Axt, Jordan R., Ebersole, Charles R., Herman, Michelle, Devine, Patricia G., and Nosek, Brian A. (August 13, 2018). “A Meta-Analysis of Procedures to Change Implicit Measures.” [Preprint]. Retrieved from https://doi.org/10.31234/osf.io/dv8tu.

Glaser, Jack and Knowles, Eric D. (2007). “Implicit Motivation to Control Prejudice,” in Journal of Experimental Social Psychology 44, p. 165.

Kawakami, K., Dovidio, J. F., Moll, J., Hermsen, S., & Russin, A. (2000). “Just Say No (To Stereotyping): Effects Of Training in Negation of Stereotypic Associations on Stereotype Activation,” in Journal of Personality and Social Psychology, 78, 871–888.

Kawakami, K., Dovidio, J. F., and van Kamp, S. (2005). “Kicking the Habit: Effects of Nonstereotypic Association Training and Correction Processes on Hiring Decisions,” in Journal of Experimental Social Psychology 41:1, pp. 68-69.

Greenwald, Anthony G., Banaji, Mahzarin R., and Nosek, Brian A. (2015). “Statistically Small Effects of the Implicit Association Test Can Have Societally Large Effects,” in Journal of Personality and Social Psychology, Vol. 108, No. 4, pp. 553-561.

Mendoza, Saaid, Gollwitzer, Peter, and Amodio, David. (2010). “Reducing the Expression of Implicit Stereotypes: Reflexive Control through Implementation Intentions,” in Personality and Social Psychology Bulletin 36:4, p. 513-514.

Monteith, Margo. (1993). “Self-Regulation of Prejudiced Responses: Implications for Progress in Prejudice-Reduction Efforts,” in Journal of Personality and Social Psychology 65:3, p. 472.

Moskowitz, Gordon and Li, Peizhong. (2011). “Egalitarian Goals Trigger Stereotype Inhibition,” in Journal of Experimental Social Psychology 47, p. 106.

Oswald, F. L., Mitchell, G., Blanton, H., Jaccard, J., and Tetlock, P. E. (2013). “Predicting Ethnic and Racial Discrimination: A Meta-Analysis of IAT Criterion Studies,” in Journal of Personality and Social Psychology, Vol. 105, pp. 171-192

Oswald, F. L., Mitchell, G., Blanton, H., Jaccard, J., and Tetlock, P. E. (2015). “Using the IAT to Predict Ethnic and Racial Discrimination: Small Effect Sizes of Unknown Societal Significance,” in Journal of Personality and Social Psychology, Vol. 108, No. 4, pp. 562-571.

Saul, Jennifer. (2017). “Implicit Bias, Stereotype Threat, and Epistemic Injustice,” in The Routledge Handbook of Epistemic Injustice, eds. Ian James Kidd, José Medina, and Gaile Pohlhaus, Jr. [Google Books Edition] New York: Routledge.

Webb, Thomas L., Sheeran, Paschal, and Pepper, John. (2012). “Gaining Control Over Responses to Implicit Attitude Tests: Implementation Intentions Engender Fast Responses on Attitude-Incongruent Trials,” in British Journal of Social Psychology 51, pp. 13-32.

[1] Glaser, Jack and Knowles, Eric D. (2007). “Implicit Motivation to Control Prejudice,” in Journal of Experimental Social Psychology 44, p. 165.

[2] Glaser, Jack and Knowles, Eric D. (2007), p. 167.

[3] Glaser, Jack and Knowles, Eric D. (2007), p. 170.

[4] Glaser, Jack and Knowles, Eric D. (2007), p. 168.

[5] Glaser, Jack and Knowles, Eric D. (2007), p. 168.

[6] Glaser, Jack and Knowles, Eric D. (2007), p. 169.

[7] Glaser, Jack and Knowles, Eric D. (2007), p. 169. Of this “rogue” group, Glaser and Knowles note: “This group had, on average, a negative RWS (i.e., rather than just a low bias toward Blacks, they tended to associate Whites more than Blacks with weapons; see footnote 4). If these reversed stereotypes are also uninhibited, they should yield reversed Shooter Bias, as observed here” (169).

[8] Glaser, Jack and Knowles, Eric D. (2007), p. 169.

[9] Glaser, Jack and Knowles, Eric D. (2007), p. 169.

[10] Sang Hee Park, Jack Glaser, and Eric D. Knowles. (2008). “Implicit Motivation to Control Prejudice Moderates the Effect of Cognitive Depletion on Unintended Discrimination,” in Social Cognition, Vol. 26, No. 4, p. 416.

[11] Moskowitz, Gordon and Li, Peizhong. (2011). “Egalitarian Goals Trigger Stereotype Inhibition,” in Journal of Experimental Social Psychology 47, p. 106.

[12] Blair, I. V., Ma, J. E., & Lenton, A. P. (2001). “Imagining Stereotypes Away: The Moderation of Implicit Stereotypes Through Mental Imagery,” in Journal of Personality and Social Psychology, 81:5, p. 837.

[13] Amodio, David M., Devine, Patricia G., and Harmon-Jones, Eddie. (2007). “A Dynamic Model of Guilt: Implications for Motivation and Self-Regulation in the Context of Prejudice,” in Psychological Science 18(6), pp. 524-30

[14] Moskowitz, Gordon and Li, Peizhong (2011), p. 108.

[15] Blair, I. V., Ma, J. E., & Lenton, A. P. (2001), p. 838.

[16] Fielder, Klaus, Messner, Claude, Bluemke, Matthias. (2006). “Unresolved problems with the ‘I’, the ‘A’, and the ‘T’: A logical and Psychometric Critique of the Implicit Association Test (IAT),” in European Review of Social Psychology, 12, pp. 74-147. Brendl, C. M., Markman, A. B., & Messner, C. (2001). “How Do Indirect Measures of Evaluation Work? Evaluating the Inference of Prejudice in the Implicit Association Test,” in Journal of Personality and Social Psychology, 81(5), pp. 760-773. Fazio, R. H., and Olson, M. A. (2003). “Implicit Measures in Social Cognition Research: Their Meaning and Uses,” in Annual Review of Psychology 54, pp. 297-327.

[17] There is significant debate over the issue of whether the implicit bias that (IAT) tests measure translate into real-world discriminatory behavior. This is a complex and compelling issue. It is also an issue that could render moot the (IAT) as an implicit measure of anything full stop. Anthony G. Greenwald, Mahzarin R. Banaji, and Brian A. Nosek (2015) write: “IAT measures have two properties that render them problematic to use to classify persons as likely to engage in discrimination. Those two properties are modest test–retest reliability (for the IAT, typically between r = .5 and r = .6; cf., Nosek et al., 2007) and small to moderate predictive validity effect sizes. Therefore, attempts to diagnostically use such measures for individuals risk undesirably high rates of erroneous classifications. These problems of limited test-retest reliability and small effect sizes are maximal when the sample consists of a single person (i.e., for individual diagnostic use), but they diminish substantially as sample size increases. Therefore, limited reliability and small to moderate effect sizes are not problematic in diagnosing system-level discrimination, for which analyses often involve large samples” (557). However, Oswald et al. (2013) argue that “IAT scores correlated strongly with measures of brain activity but relatively weakly with all other criterion measures in the race domain and weakly with all criterion measures in the ethnicity domain. IATs, whether they were designed to tap into implicit prejudice or implicit stereotypes, were typically poor predictors of the types of behavior, judgments, or decisions that have been studied as instances of discrimination, regardless of how subtle, spontaneous, controlled, or deliberate they were. Explicit measures of bias were also, on average, weak predictors of criteria in the studies covered by this meta-analysis, but explicit measures performed no worse than, and sometimes better than, the IATs for predictions of policy preferences, interpersonal behavior, person perceptions, reaction times, and microbehavior. Only for brain activity were correlations higher for IATs than for explicit measures…but few studies examined prediction of brain activity using explicit measures. Any distinction between the IATs and explicit measures is a distinction that makes little difference, because both of these means of measuring attitudes resulted in poor prediction of racial and ethnic discrimination” (182-183). For further details about this debate, see: Oswald, F. L., Mitchell, G., Blanton, H., Jaccard, J., and Tetlock, P. E. (2013). “Predicting Ethnic and Racial Discrimination: A Meta-Analysis of IAT Criterion Studies,” in Journal of Personality and Social Psychology, Vol. 105, pp. 171-192 and Greenwald, Anthony G., Banaji, Mahzarin R., and Nosek, Brian A. (2015). “Statistically Small Effects of the Implicit Association Test Can Have Societally Large Effects,” in Journal of Personality and Social Psychology, Vol. 108, No. 4, pp. 553-561.

[18] See: Oswald, F. L., Mitchell, G., Blanton, H., Jaccard, J., and Tetlock, P. E. (2015). “Using the IAT to Predict Ethnic and Racial Discrimination: Small Effect Sizes of Unknown Societal Significance,” in Journal of Personality and Social Psychology, Vol. 108, No. 4, pp. 562-571.

[19] Forscher, Patrick S., Lai, Calvin K., Axt, Jordan R., Ebersole, Charles R., Herman, Michelle, Devine, Patricia G., and Nosek, Brian A. (August 13, 2018). “A Meta-Analysis of Procedures to Change Implicit Measures.” [Preprint]. Retrieved from https://doi.org/10.31234/osf.io/dv8tu.

[20] Alcoff, Linda. (2010). “Epistemic Identities,” in Episteme 7 (2), p. 132.

Author Information: Kamili Posey, Kingsborough College, Kamili.Posey@kbcc.cuny.edu.

Posey, Kamili. “Scientism in the Philosophy of Implicit Bias Research.” Social Epistemology Review and Reply Collective 7, no. 10 (2018): 1-16.

Kamili Posey’s article will be posted over two instalments. The pdf of the article gives specific page references, and includes the entire essay. Shortlink: https://wp.me/p1Bfg0-41m

Image by Walt Stoneburner via Flickr / Creative Commons

 

If you consider the recent philosophical literature on implicit bias research, then you would be forgiven for thinking that the problem of successful interventions into implicit bias fall into the category of things that are resolved. If you consider the recent social psychological literature on interventions into implicit bias, then you would come away with a similar impression. The claim is that implicit bias is epistemically harmful because we profess to believing one thing while our implicit attitudes tell a different story.

Strategy Models and Discrepancy Models

Implicit bias is socially harmful because it maps onto our real-world discriminatory practices, e.g., workplace discrimination, health disparities, racist police shootings, and identity-prejudicial public policies. Consider the results of Greenwald et al.’s (1998) Implicit Association Test. Consider also the results of Correll et. al’s (2002) “Shooter Bias.” If cognitive interventions are possible, and specifically implicit cognitive interventions, then they can help knowers implicitly manage automatic stereotype activation. Do these interventions lead to real-world reductions of bias?

Linda Alcoff (2010) notes that it is difficult to see how implicit, nonvolitional biases (e.g., those at the root of social and epistemic ills like race-based police shootings) can be remedied by explicit epistemic practices.[1] I would follow this by noting that it is equally difficult to see how nonvolitional biases can be remedied by implicit epistemic practices as well.

Jennifer Saul (2017) responds to Alcoff’s (2010) query by pointing to social psychological experiments conducted by Margo Monteith (1993), Jack Glaser and Eric D. Knowles (2007), Gordon B. Moskowitz and Peizhong Li (2011), Saaid A. Mendoza et al. (2010), Irene V. Blair et al. (2001), and Kerry Kawakami et al. (2005).[2] These studies suggest that implicit self-regulation of implicit bias is possible. Saul notes that philosophers with objections like Alcoff’s, and presumably like mine, should “not just to reflect upon the problem from the armchair – at the very least, one should use one’s laptop to explore the internet for effective interventions.”[3]

But I think this recrimination rings rather hollow. How entitled are we to extrapolate from social psychological studies in the manner that Saul advocates? How entitled are we to assumes the epistemic superiority of scientific research on racism, sexism, etc. over the phenomenological reporting of marginalized knowers? Lastly, how entitled are we to claims about the real-world applicability of these study results?[4] My guess is that the devil is in the details. My guess is also that social psychologists have not found the silver bullet for remedying implicit bias. But let’s follow Saul’s suggestion and not just reflect from the armchair.

A caveat: the following analysis is not intended to be an exhaustive or thorough refutation of what is ultimately a large body social psychological literature. Instead, it is intended to cast a bit of doubt on how these models are used by philosophers as successful remedies for implicit bias. It is intended to cast doubt a bit of doubt on the idea that remedies for racist, sexist, homophobic, and transphobic discrimination are merely a training session or reflective exercise away.

This type of thinking devalues the very real experiences of those who live through racism, sexism, homophobia, and transphobia. It devalues how pervasive these experiences are in American society and the myriad ways in which the effects of discrimination seep into marrow of marginalized bodies and marginalized communities. Worse still, it implies that marginalized knowers who claim, “You don’t understand my experiences!” are compelled to contend with the hegemonic role of “Science” that continues to speak over their own voices and about their own lives.[5] But again, back to the studies.

Four Methods of Remedy

I break up the above studies into four intuitive model types: (1) strategy models, (2) discrepancy models, (3) (IAT) models, and (4) egalitarian goal models. (I am not a social scientist, so the operative word here is “intuitive.”) Let’s first consider Kawakami et al. (2005) and Mendoza et al. (2010) as examples of strategy models. Kawakami et al. used Devine and Monteith’s (1993) notion of a negative stereotype as a “bad habit” that a knower needs to “kick” to model strategies that aid in the inhibition of automatic stereotype activation, or the inhibition of “increased cognitive accessibility of characteristics associated with a particular group.”[6]

In a previous study, Kawakami et al. (2000) asked research participants presented with photographs of black individuals and white individuals with stereotypical traits and non-stereotypical traits listed under each photograph to respond “No” to stereotypical traits and “Yes” to non-stereotypical traits.[7] The study found that “participants who were extensively trained to negate racial stereotypes initially also demonstrated stereotype activation, this effect was eliminated by the extensive training.

Furthermore, Kawakami et al. found that practice effects of this type lasted up to 24 h following the training.”[8] Kawakami et al. (2005) used this training model to ground an experiment aimed at strategies for reducing stereotype activation in the preference of men over women for leadership roles in managerial positions. Despite the training, they found that there was “no difference between Nonstereotypic Association Training and No Training conditions…participants were indeed attempting to choose the best candidate overall, in these conditions there was an overall pattern of discrimination against women relative to men in recommended hiring for a managerial position (Glick, 1991; Rudman & Glick, 1999)” [emphasis mine].[9]

Substantive conclusions are difficult to make by a single study but one critical point is how learning occurred in the training but improved stereotype inhibition did not occur. What, exactly, are we to make of this result? Kawakami et al. (2005) claimed that “similar levels of bias in both the Training and No Training conditions implicates the influence of correction processes that limit the effectiveness of training.”[10] That is, they attributed the lack of influence of corrective processes on a variety of contributing factors that limited the effectiveness of the strategy itself.

Notice, however, that this does not implicate the strategy as a failed one. Most notably Kawakami et al. found that “when people have the time and opportunity to control their responses [they] may be strongly shaped by personal values and temporary motivations, strategies aimed at changing the automatic activation of stereotypes will not [necessarily] result in reduced discrimination.”[11]

This suggests that although the strategies failed to reduce stereotype activation they may still be helpful in limited circumstances “when impressions are more deliberative.”[12] One wonders under what conditions such impressions can be more deliberative? More than that, how useful are such limited-condition strategies for dealing with everyday life and every day automatic stereotype activation?

Mendoza et al. (2010) tested the effectiveness of “implementation intentions” as a strategy to reduce the activation or expression of implicit stereotypes using the Shooter Task.[13] They tested both “distraction-inhibiting” implementation intentions and “response-facilitating” implementation intentions. Distraction-inhibiting intentions are strategies “designed to engage inhibitory control,” such as inhibiting the perception of distracting or biasing information, while “response-facilitating” intentions are strategies designed to enhance goal attainment by focusing on specific goal-directed actions.[14]

In the first study, Mendoza et al. asked participants to repeat the on-screen phrase, “If I see a person, then I will ignore his race!” in their heads and then type the phrase into the computer. This resulted in study participants having a reduced number of errors in the Shooter Task. But let’s come back to if and how we might be able to extrapolate from these results. The second study compared a simple-goal strategy with an implementation intention strategy.

Study participants in the simple-goal strategy group were asked to follow the strategy, “I will always shoot a person I see with a gun!” and “I will never shoot a person I see with an object!” Study participants in the implementation intention strategy group were asked to use a conditional, if-then, strategy instead: “If I see a person with an object, then I will not shoot!” Mendoza et al. found that a response-facilitating implementation intention “enhanced controlled processing but did not affect automatic stereotyping processing,” while a distraction-inhibiting implementation intention “was associated with an increase in controlled processing and a decrease in automatic stereotyping processes.”[15]

How to Change Both Action and Thought

Notice that if the goal is to reduce automatic stereotype activation through reflexive control that only a distraction-inhibiting strategy achieved the desired effect. Notice also how the successful use of a distraction-inhibiting strategy may require a type of “non-messy” social environment unachievable outside of a laboratory experiment.[16] Or, as Mendoza et al. (2010) rightly note: “The current findings suggest that the quick interventions typically used in psychological experiments may be more effective in modulating behavioral responses or the temporary accessibility of stereotypes than in undoing highly edified knowledge structures.”[17]

The hope, of course, is that distraction-inhibiting strategies can help dominant knowers reduce automatic stereotype activation and response-facilitated strategies can help dominant knowers internalize controlled processing such that negative bias and stereotyping can be (one day) reflexively controlled as well. But these are only hopes. The only thing that we can rightly conclude from these results is that if we ask a dominant knower to focus on an internal command, they will do so. The result is that the activation of negative bias fails to occur.

This does not mean that the knower has reduced their internalized negative biases and prejudices or that they can continue to act on the internal commands in the future (in fact, subsequent studies reveal the effects are short-lived[18]). As Mendoza et al. also note: “In psychometric terms, these strategies are designed to enhance accuracy without necessarily affecting bias. That is, a person may still have a tendency to associate Black people with violence and thus be more likely to shoot unarmed Blacks than to shoot unarmed Whites.”[19] Despite hope for these strategies, there is very little to support their real-world applicability.

Hunting for Intuitive Hypocrisies

I would extend a similar critique to Margot Monteith’s (1993) discrepancy model. Monteith’s (1993) often cited study uses two experiments to investigate prejudice related discrepancies in the behaviors of low-prejudice (LP) and high-prejudice (HP) individuals and the ability to engage in self-regulated prejudice reduction. In the first experiment, (LP) and (HP) heterosexual study participants were asked to evaluate two law school applications, one for an implied gay applicant and one for an implied heterosexual applicant. Study participants “were led to believe that they had evaluated a gay law school applicant negatively because of his sexual orientation;” they were tricked into a “discrepancy-activated condition” or a condition that was at odds with their believed prejudicial state.[20]

All of the study participants were then told that the applications were identical and that those who had rejected the gay applicant had done so because of the applicant’s sexual orientation. It is important to note that the applicants qualifications were not, in fact, identical. The gay applicant’s application materials were made to look worse than the heterosexual applicant’s materials. This was done to compel the rejection of the applicant.

Study participants were then provided a follow-up questionnaire and essay allegedly written by a professor who wanted to know (a) “why people often have difficulty avoiding negative responses toward gay men,” and (b) “how people can eliminate their negative responses toward gay men.”[21] Researchers asked study participants to record their reactions to the faculty essay and write down as much they could remember about what they read. They were then told about the deception in the experiment and told why such deception was incorporated into the study.

Monteith (1993) found that “low and high prejudiced subjects alike experienced discomfort after violating their personal standards for responding to a gay man, but only low prejudiced subjects experienced negative self-directed affect.”[22] Low prejudiced, (LP), “discrepancy-activated subjects,” also spent more time reading the faculty essay and “showed superior recall for the portion of the essay concerning why prejudice-related discrepancies arise.”[23]

The “discrepancy experience” generated negative self-directed affect, or guilt, for (LP) study participants with the hope that the guilt would (a) “motivate discrepancy reduction (e.g., Rokeach, 1973)” and (b) “serve to establish strong cues for punishment (cf. Gray, 1982).”[24] The idea here is that the experiment results point to the existence of a self-regulatory mechanism that can replace automatic stereotype activation with “belief-based responses;” however, “it is important to note that the initiation of self-regulatory mechanisms is dependent on recognizing and interpreting one’s responses as discrepant from one’s personal beliefs.”[25]

The discrepancy between what one is shown to believe and what one professes to believe (whether real or manufactured, as in the experiment) is aimed at getting knowers to engage in heightened self-focus due to negative self-directed affect. The goal of Monteith’s (1993) study is that self-directed affect would lead to a kind of corrective belief-making process that is both less prejudicial and future-directed.

But if it’s guilt that’s doing the psychological work in these cases, then it’s not clear that knowers wouldn’t find other means of assuaging such feelings. Why wouldn’t it be the case that generating negative self-directed affect would point a knower toward anything they deem necessary to restore a more positive sense of self? To this, Monteith made the following concession:

Steele (1988; Steele & Liu, 1983) contended that restoration of one’s self-image after a discrepancy experience may not entail discrepancy reduction if other opportunities for self-affirmation are available. For example, Steele (1988) suggested that a smoker who wants to quit might spend more time with his or her children to resolve the threat to the self-concept engendered by the psychological inconsistency created by smoking. Similarly, Tesser and Cornell (1991) found that different behaviors appeared to feed into a general “self-evaluation reservoir.” It follows that prejudice-related discrepancy experiences may not facilitate the self-regulation of prejudiced responses if other means to restoring one’s self-regard are available [emphasis mine].[26]

Additionally, she noted that even if individuals are committed to the reducing or “unlearning” automatic stereotyping, they “may become frustrated and disengage from the self-regulatory cycle, abandoning their goal to eliminate prejudice-like responses.”[27] Cognitive exhaustion, or cognitive depletion, can occur after intergroup exchanges as well. This may make it even less likely that a knower will continue to feel guilty, and to use that guilt to inhibit the activation of negative stereotypes when they find themselves struggling cognitively. Conversely, there is also the issue of a kind of lab-based, or experiment-based, cognitive priming. I pick up with this idea along with the final two models of implicit interventions in the next part.

Contact details: Kamili.Posey@kbcc.cuny.edu

References

Alcoff, Linda. (2010). “Epistemic Identities,” in Episteme 7 (2), p. 132.

Amodio, David M., Devine, Patricia G., and Harmon-Jones, Eddie. (2007). “A Dynamic Model of Guilt: Implications for Motivation and Self-Regulation in the Context of Prejudice,” in Psychological Science 18(6), pp. 524-30.

Blair, I. V., Ma, J. E., & Lenton, A. P. (2001). “Imagining Stereotypes Away: The Moderation of Implicit Stereotypes Through Mental Imagery,” in Journal of Personality and Social Psychology, 81:5, p. 837.

Correll, Joshua, Bernadette Park, Bernd Wittenbrink, and Charles M. Judd. (2002). “The Police Officer’s Dilemma: Using Ethnicity to Disambiguate Potentially Threatening Individuals,” in Journal of Personality and Social Psychology, Vol. 83, No. 6, 1314–1329.

Devine, P. G., & Monteith, M. J. (1993). “The Role of Discrepancy-Associated Affect in Prejudice Reduction,” in Affect, Cognition and Stereotyping: Interactive Processes in Group Perception, eds., D. M. Mackie & D. L. Hamilton. San Diego: Academic Press, pp. 317–344.

Forscher, Patrick S., Lai, Calvin K., Axt, Jordan R., Ebersole, Charles R., Herman, Michelle, Devine, Patricia G., and Nosek, Brian A. (August 13, 2018). “A Meta-Analysis of Procedures to Change Implicit Measures.” [Preprint]. Retrieved from https://doi.org/10.31234/osf.io/dv8tu.

Glaser, Jack and Knowles, Eric D. (2007). “Implicit Motivation to Control Prejudice,” in Journal of Experimental Social Psychology 44, p. 165.

Kawakami, K., Dovidio, J. F., Moll, J., Hermsen, S., & Russin, A. (2000). “Just Say No (To Stereotyping): Effects Of Training in Negation of Stereotypic Associations on Stereotype Activation,” in Journal of Personality and Social Psychology, 78, 871–888.

Kawakami, K., Dovidio, J. F., and van Kamp, S. (2005). “Kicking the Habit: Effects of Nonstereotypic Association Training and Correction Processes on Hiring Decisions,” in Journal of Experimental Social Psychology 41:1, pp. 68-69.

Greenwald, Anthony G., Banaji, Mahzarin R., and Nosek, Brian A. (2015). “Statistically Small Effects of the Implicit Association Test Can Have Societally Large Effects,” in Journal of Personality and Social Psychology, Vol. 108, No. 4, pp. 553-561.

Mendoza, Saaid, Gollwitzer, Peter, and Amodio, David. (2010). “Reducing the Expression of Implicit Stereotypes: Reflexive Control through Implementation Intentions,” in Personality and Social Psychology Bulletin 36:4, p. 513-514.

Monteith, Margo. (1993). “Self-Regulation of Prejudiced Responses: Implications for Progress in Prejudice-Reduction Efforts,” in Journal of Personality and Social Psychology 65:3, p. 472.

Moskowitz, Gordon and Li, Peizhong. (2011). “Egalitarian Goals Trigger Stereotype Inhibition,” in Journal of Experimental Social Psychology 47, p. 106.

Oswald, F. L., Mitchell, G., Blanton, H., Jaccard, J., and Tetlock, P. E. (2013). “Predicting Ethnic and Racial Discrimination: A Meta-Analysis of IAT Criterion Studies,” in Journal of Personality and Social Psychology, Vol. 105, pp. 171-192

Oswald, F. L., Mitchell, G., Blanton, H., Jaccard, J., and Tetlock, P. E. (2015). “Using the IAT to Predict Ethnic and Racial Discrimination: Small Effect Sizes of Unknown Societal Significance,” in Journal of Personality and Social Psychology, Vol. 108, No. 4, pp. 562-571.

Saul, Jennifer. (2017). “Implicit Bias, Stereotype Threat, and Epistemic Injustice,” in The Routledge Handbook of Epistemic Injustice, eds. Ian James Kidd, José Medina, and Gaile Pohlhaus, Jr. [Google Books Edition] New York: Routledge.

Webb, Thomas L., Sheeran, Paschal, and Pepper, John. (2012). “Gaining Control Over Responses to Implicit Attitude Tests: Implementation Intentions Engender Fast Responses on Attitude-Incongruent Trials,” in British Journal of Social Psychology 51, pp. 13-32.

[1] Alcoff, Linda. (2010). “Epistemic Identities,” in Episteme 7 (2), p. 132.

[2] Saul, Jennifer. (2017). “Implicit Bias, Stereotype Threat, and Epistemic Injustice,” in The Routledge Handbook of Epistemic Injustice, eds. Ian James Kidd, José Medina, and Gaile Pohlhaus, Jr. [Google Books Edition] New York: Routledge.

[3] Saul, Jennifer (2017), p. 466.

[4] See: Oswald, F. L., Mitchell, G., Blanton, H., Jaccard, J., and Tetlock, P. E. (2013). “Predicting Ethnic and Racial Discrimination: A Meta-Analysis of IAT Criterion Studies,” in Journal of Personality and Social Psychology, Vol. 105, pp. 171-192.

[5] I owe this critical point in its entirety to the work of Lacey Davidson and her presentation, “When Testimony Isn’t Enough: Implicit Bias Research as Epistemic Injustice” at the Feminist Epistemologies, Methodologies, Metaphysics, and Science Studies (FEMMSS) conference in Corvallis, Oregon in 2018. Davidson notes that the work of philosophers of race and critical race theorists often takes a backseat to the projects of philosophers of social science who engage with the science of racialized attitudes as opposed to the narratives and/or testimonies of those with lived experiences of racism. Davidson describes this as a type of epistemic injustice against philosophers of race and critical race theorists. She also notes that philosophers of race and critical race theorists are often people of color while the philosophers of social science are often white. This dimension of analysis is important but unexplored. Davidson’s work highlights how epistemic injustice operates within the academy to perpetuate systems of racism and oppression under the guise of “good science.” Her arguments was inspired by the work of Jeanine Weekes Schroer on the problematic nature of current research on stereotype threat and implicit bias in “Giving Them Something They Can Feel: On the Strategy of Scientizing the Phenomenology of Race and Racism,” Knowledge Cultures 3(1), 2015.

[6] Kawakami, K., Dovidio, J. F., and van Kamp, S. (2005). “Kicking the Habit: Effects of Nonstereotypic Association Training and Correction Processes on Hiring Decisions,” in Journal of Experimental Social Psychology 41:1, pp. 68-69. See also: Devine, P. G., & Monteith, M. J. (1993). “The Role of Discrepancy-Associated Affect in Prejudice Reduction,” in Affect, Cognition and Stereotyping: Interactive Processes in Group Perception, eds., D. M. Mackie & D. L. Hamilton. San Diego: Academic Press, pp. 317–344.

[7] Kawakami et al. (2005), p. 69. See also: Kawakami, K., Dovidio, J. F., Moll, J., Hermsen, S., & Russin, A. (2000). “Just Say No (To Stereotyping): Effects Of Training in Negation of Stereotypic Associations on Stereotype Activation,” in Journal of Personality and Social Psychology, 78, 871–888.

[8] Kawakami et al. (2005), p. 69.

[9] Kawakami et al. (2005), p. 73.

[10] Kawakami et al. (2005), p. 73.

[11] Kawakami et al. (2005), p. 74.

[12] Kawakami et al. (2005), p. 74.

[13] The Shooter Task refers to a computer simulation experiment where images of black and white males appear on a screen holding a gun or a non-gun object. Study participants are given a short response time and tasked with pressing a button, or “shooting” armed images versus unarmed images. Psychological studies have revealed a “shooter bias” in the tendency to shoot black, unarmed males more often than unarmed white males. See: Correll, Joshua, Bernadette Park, Bernd Wittenbrink, and Charles M. Judd. (2002). “The Police Officer’s Dilemma: Using Ethnicity to Disambiguate Potentially Threatening Individuals,” in Journal of Personality and Social Psychology, Vol. 83, No. 6, 1314–1329.

[14] Mendoza, Saaid, Gollwitzer, Peter, and Amodio, David. (2010). “Reducing the Expression of Implicit Stereotypes: Reflexive Control through Implementation Intentions,” in Personality and Social Psychology Bulletin 36:4, p. 513-514..

[15] Mendoza, Saaid, Gollwitzer, Peter, and Amodio, David (2010), p. 520.

[16] A “messy environment” presents additional challenges to studies like the one discussed here. As Kees Keizer, Siegwart Lindenberg, and Linda Steg (2008) claim in “The Spreading of Disorder,” people are more likely to violate social rules when they see that others are violating the rules as well. I can only imagine that this is applicable to epistemic rules as well. I mention this here to suggest that the “cleanliness” of the social environment of social psychological studies such as the one by Mendoza, Saaid, Gollwitzer, Peter, and Amodio, David (2010) presents an additional obstacle in extrapolating the resulting behaviors of research participants to the public-at-large. Short of mass hypnosis, how could the strategies used in these experiments, strategies that are predicated on the noninterference of other destabilizing factors, be meaningfully applied to everyday life? There is a tendency in the philosophical literature on implicit bias and stereotype threat to outright ignore the limited applicability of much of this research in order to make critical claims about interventions into racist, sexist, homophobic, and transphobic behaviors. Philosophers would do well to recognize the complexity of these issues and to be more cautious about the enthusiastic endorsement of experimental results.

[17] Mendoza, Saaid, Gollwitzer, Peter, and Amodio, David (2010), p. 520.

[18] Webb, Thomas L., Sheeran, Paschal, and Pepper, John. (2012). “Gaining Control Over Responses to Implicit Attitude Tests: Implementation Intentions Engender Fast Responses on Attitude-Incongruent Trials,” in British Journal of Social Psychology 51, pp. 13-32.

[19] Mendoza, Saaid, Gollwitzer, Peter, and Amodio, David (2010), p. 520.

[20] Monteith, Margo. (1993). “Self-Regulation of Prejudiced Responses: Implications for Progress in Prejudice-Reduction Efforts,” in Journal of Personality and Social Psychology 65:3, p. 472.

[21] Monteith (1993), p. 474.

[22] Monteith (1993), p. 475.

[23] Monteith (1993), p. 477.

[24] Monteith (1993), p. 477.

[25] Monteith (1993), p. 477.

[26] Monteith (1993), p. 482.

[27] Monteith (1993), p. 483.

Author Information: Adam Riggio, Royal Crown College, Social Epistemology Digital Editor, serrc.digital@gmail.com

Riggio, Adam. “The True Shape of a Society of Friends.” Social Epistemology Review and Reply Collective 7, no. 7 (2018): 40-45.

The pdf of the article gives specific page references. Shortlink: https://wp.me/p1Bfg0-3Zv

From the March for Justice for Police Violence in December 2014.
Sassower’s book does not directly touch on themes of institutional corruption, like the racialization of police forces as they act with undue violence and exploitation toward minority populations. But the communitarian moralities he thinks can overcome capitalism also has the potential to build progress here. More material for that sequel.
Image by All-Nite Images via Flickr / Creative Commons

 

As a work of philosophy, of political economy, of institutional analysis, Raphael Sassower’s The Quest for Prosperity has only one shortcoming. It makes for a tantalizing setup for his next work, and gives a reader the distinct impression that we are in store for a stunning sequel. Its title would be something like The Nature of Prosperity, or Remaking Prosperity. To the detriment of the actually existing book, reading The Quest for Prosperity makes you want desperately to read Remaking Prosperity, which unfortunately does not exist.

The Quest for Prosperity itself is a brilliant book, synthesizing many different concepts and images from several disciplines and traditions in the history of Western thought. It is a thoroughly researched and beautifully composed groundwork for a groundbreaking new philosophical approach to political economy.

The book drags a little in part three, which catalogues several hilariously inadequate new visions of prosperity that are unfortunately popular today. It would be news to someone who has only heard the hype of Silicon Valley and other ideologies similarly twisted to make working people desire their own slavery. But the average Washington Post, Manchester Guardian, or even Bloomberg News reader or fan of HBO’s Silicon Valley should already understand the toxic lifestyle PR of these moneyed industries.

As for that groundwork for the groundbreaking, the final two chapters offer a tantalizing glimpse of a work that explores the existence and revolutionary potential of the communitarian values underlying several disparate existing institutions. Unfortunately, it remains only a glimpse.

Economies of Scale

Sassower’s book revolves around an important ethical critique of contemporary capitalism and the culture of business and entrepreneurship that has grown so popular this century. In uncritically capitalist ways of thinking, there is only one set of terms in which people, social networks, technology, building and city architecture, institutions, organizations, ecologies, territories, and ideas are valued: their monetary potential. Such a morality of valuation reduces all that exists, including human identity itself, to a single dimension of ethical worth, and a petty-minded one at that.

The typical narratives to validate and venerate the contemporary economic order often appeal to images and concepts from Adam Smith’s The Wealth of Nations. Smith is a touchstone for Sassower as well, but he is wise not to linger on the image of the “invisible hand” that haunts the populist imagery of harmony through competition. Sassower instead focusses on how Smith describes the molecular connections of market exchanges – vendors and tradespeople buying and selling from each other in a town marketplace.

In the marketplaces where capitalist exchange begins, the individuals making money from each other are not themselves competitors. Their relationships are collegial friendships among professionals, and Smith describes their interaction as “the propensity to truck, barter, and exchange one thing for another.” So when a community’s prosperity flows from its markets and commercial exchanges, that prosperity is not a product of competition, but of friendliness. (Sassower 60-61)

In such a social atmosphere, a community of people constitutes itself easily from the everyday interactions of the marketplace, where people develop feelings of love at a low intensity for the neighbours who sustain their lives. Relationships of everyday economic exchange occur at such a personal level that the mutual benefit of such exchange is a straightforward fact, discovered through quotidian observation. They are, as Sassower describes them, “sympathetic neighbours.” (Sassower 90-91)

The rapaciousness and greed typical of contemporary business cultures could not arise from such relationship networks of friendly truck and barter. The network’s members connect by dynamics of mutual sympathy. Such a network would not be able to sustain business practices characterized by the greed and hostility into which many young professionals are socialized in the 21st century’s most intense economic hubs. Greed and cheating would result in your immediate expulsion from the marketplace, having betrayed the friendships of the others in the network.

Such sympathetic neighbourliness could most easily be overcome with an outside disturbance. For our case, that disturbance was the flow of massive economic income to those small marketplaces. This was the income of industrialization and colonialism. Speaking more descriptively, it was the income of exponential energy growth in domestic manufacturing, and a huge influx of many kinds of wealth from distant continents (raw materials, currency metals like gold and silver, agricultural goods, slaves).

These enormous flows of capital are too large for truck and barter, too massive to engage instinctual human sympathy. As the stakes of economic activity grow hugely higher, this depersonalization of economic activity leaves a person adrift in commercial exchange. Unable to form the same intimate connections as in the far less intense marketplace exchange, the alienated, angry approach to business as a zero-sum game. No longer sympathy and friendliness, but fear and aggression characterize the psychology of someone engaging with this sort of economic system in daily life. (Sassower 105)

Art by Shepard Fairey. Image by Wally Gobetz via Flickr / Creative Commons

What Would a Virtuous Oligarch Be?

In an economic system where capital flows massively overpower the capacity for everyday personal relationship networks to manage them, business life tends to condition people psychologically and morally into sociopaths. This problem of the depersonalized economy remains a wall in The Quest for Prosperity that, on its own terms, is insoluble. On its own terms, it likely is impossible to restore the virtue of sympathy to the psychological tendencies of people growing up in a high-intensity industrial capitalist economy. Sassower therefore forges an alternative image of the economic leader.

If capitalism can only express justice when the mega-rich are generally benevolent, community-minded people who care about their neighbours regardless of wealth, breeding, or class, then Sassower can at least describe how an oligarch could become kind. He identifies one economic principle, the recognition of which begins to transform an oligarch from a greedy sociopath to a personal ethic of rationally-justified sympathy. That principle is demand-centric economics.

This is a simple economic principle, fairly well-known in popular culture. If too many people in a society are in poverty, then the economy will stagnate from cratering demand; too few people will have enough money to spend, even for basic necessities. When a very wealthy person accepts this principle, he consents to submit a healthy portion of his income to taxation so that government services can close these poverty gaps. A business owner who accepts the principle of demand-centric economics will pay the workers in his business more, so that their spending can continue to drive economic development (Sassower 123-124).

Demand-centric thinking in economics has not been a major principle in how government policy on incomes and wealth inequality has developed over the last 40 years. The Reagan-Thatcher era of Western governance took the opposite principle, supply-side or trickle-down economics, as gospel. This is the notion that as the wealthy’s tax burden becomes lower and lower, they will spend more of that money in capital investment, backing new business ventures, and expanding private-sector employment.

Although the policy was widely mocked in popular culture from its first emergence, it has become the foundation of tax policy for all the largest political parties in the United States, United Kingdom, Canada, and among almost all conservative or centrist parties in Europe. Despite its success as legislature, the material consequences have been disastrous, as supply-side tax policies have decimated social democratic institutions throughout the West, intensifying economic precarity for millions across Europe and the Americas.

Why supply-side economics succeeded in becoming, until recently, uncontested common sense in popular culture and state-level politics is its intuitiveness in particular contexts. If an ordinary person’s annual income rises from $40,000 to $50,000, she will spend more money. The supply-side propagandist then derives a universal principle: If you have more money, you will spend more money. With that generality in hand, a principle that applies at middle-class incomes will be taken to hold at oligarchical incomes.

This is, of course, false, for three reasons that Sassower describes. One, personal consumption cannot proceed at an intensity of millions or billions of dollars each year. Two, most of that massive personal income never returns to their domestic economies anyway, and is instead burrowed in tax havens. Three, the capital investment industry no longer focusses on supplying startup funding for businesses. (Sassower 116)

Instead, global finance investment concentrates on the day-to-day trading of stocks in already existing companies, securities bundles, and speculation on the future value of stocks, securities, and currencies. High-frequency trading is a blatant sign that these investments are not for reinvestment into the productive economy. In this practice, a firm’s single algorithm will make millions of trades each day, based on its analyses of minute-to-minute market fluctuations. (Sassower 117)

Turning these massive fortunes away from the communities of non-rich people in their surroundings and around the world is a subtle but harrowing moral failure, considering the many hundreds of billions of dollars are wrapped entirely in these trading concerns.

A Fantastic Book That Falls Short of Its Potential

An economy of oligarchial inequality produces an elite for whom the purpose of living is cartoonishly grotesque personal self-enrichment. Such an economy as the one we live in today on Earth also deranges those who have virtually no wealth at all compared to these titans of mass ownership and securities gambling.

Anxiety over a precarious life of low pay and debt maintenance consumes all personal energy to help others. That anxiety encourages hatred of others as desperation and stress pervert any reflective capacity for long-term judgment into a paranoid social reflexivity. Reduced to egotistic, short-term thinking and habituated into distrust and hostility toward others, the poor become easy prey for financial fraud. The payday loan industry is built on this principle. Poverty does not breed virtue, but fear and rage.

This ties to what I think is the only notable flaw in The Quest for Prosperity. Stylistically, the book suffers from a common issue for many new research books in the humanities and social sciences. Its argument loses some momentum as it approaches the conclusion, and ends up in a more modest, self-restrained place than its opening chapters promised. How he does so reveals the far more profound shortcoming of Sassower’s book.

Sassower is admirable and innovative in his call to regenerate communitarian philosophy as a politically engaged popular intervention. His method is a philosophical examination of how four quite disparate civic institutions express effective communitarian ethics in their habitual structure and behavioural norms. The Catholic and some other Christian Churches socialize its dedicated members as “of one heart and soul” (Acts 4:32), whose primary economic concern is safeguarding people from the indignity of poverty. (Sassower 242-247)

The Israeli kibbutz movement governs distribution of goods and the financial results of their community’s work literally according to Marx’s principle of “from each according to his ability, to each according to his need.” Countercultural communes in North America operated according to similar rules of management as kibbutzim, but with quite different moral orientation. Kibbutz political philosophy is a secularized agrarian marxism organized around a utopian purpose of building a communal Zion where all oppressed people of the world can live in a Jewish homeland.

American counterculture communes sought to create a living alternative to the immanent political problem of rapacious capitalism’s continuation of genocidal imperialism. Sassower also offers a phenomenological exploration of how military training builds strong interpersonal bonds of solidarity, a communitarianism among soldiers.

All these templates for communitarian alternatives to the increasingly brutal culture of contemporary capitalism share an important common feature that is very dangerous for Sassower’s project. They are each rooted in civic institutions, material social structures for education and socialization. Contrary to how Sassower speaks of these four inspirations, civil rights and civic institutions alone are not enough to build and sustain a community each member of whom holds a communitarian ethical philosophy and moral sense deep in her heart.

The Impotence of Civil Rights

You may consider it a bit excessive that a book review would include a brief argument that civic institutions are not on their own adequate to ensure and maintain the freedom and dignity of the people who live in their domain. Nonetheless, Sassower wrote The Quest for Prosperity with an ambition of a similar scope, critiquing fundamental concepts of contemporary ideology and economic morality as part of an argument for communitarian alternatives. So I will maintain my own intensity of ambition with his.

There are two reasons why civic institutions alone, while needed, are not sufficient to overcome with communitarian values the ambitions of people to become oligarchs. Each of the two reasons is a different philosophical approach to the same empirical fact about human social capacities and institutions.

I first want to mention a logical reason. This is the simple fact that, conceptually speaking, law is not itself a material power. There is nothing about the law, as law, that compels your conformity to itself. There may be a moral motive to obey the law, whether that moral reason is a universal imperative or the injunction of social pressure. There may be a coercive motive to obey the law, as when you are under threat of police violence such as arrest, imprisonment, torture, or summary execution. Most often, people obey the law for practical reasons, as when a government’s legislation and regulations structure institutions we need to manage our techno-industrial society. But law alone is not justice, and so compels no obedience.

Law having no power to compel obedience, the existence of laws prohibiting violence against human rights does nothing to prevent such violence. If recognition of the law were all that was needed for obedience, then laws would never be violated. Only some material power, existing in addition to those laws, can ensure their application in managing the actions of a population.

The ultimate material power in the application of the law are state institutions, and any related institutions they support. Raising money through taxation, investment in industrial developments, and central bank mechanisms, states fund law enforcement institutions like courts, rehabilitation centres, prosecutors, and police. But even in institutions whose laws promise equal and fair treatment, individuals operating within those institutions can still use material power to give themselves unfair advantage over the less powerful.

Consider a civil suit whose defendant must make do with the cheapest legal representation in Albuquerque, but whose plaintiff walks into court with Alan Dershowitz at his side. Consider also the many instances where the power of institutions and institutionally-reinforced morality of solidarity encourages police abuse of citizens.

An individual officer may coerce sex from women under threat of arrest, or shoot a civilian with little or no cause; fellow officers or police unions will cover for him. An entire police department will prey on citizens as a matter of policy, as in many cities in the United States whose municipal police departments require a minimum (and growing) number of misdemeanor and bylaw violation fines for budgetary purposes. One of those such cities, incidentally, is Ferguson, Missouri.

The Impossibility of Prosperity?

I give these illustrations to emphasize the ethical importance of the fundamental purpose driving The Quest for Prosperity. Most of the book is taken up by Sassower’s clear and insightful argument for why contemporary capitalism is a moral and ethical disaster. The Quest for Prosperity is a stellar addition to this tradition of critical thought that has accompanied industrial development since its beginning.

Sassower takes a more noble stand than a critique, however, in proposing an alternative to capitalist practice for the domain most essential to resisting and overcoming industrial and economic injustice: public morality and personal ethics. His analysis of existing institutions and societies that foster communitarian moralities and ethics is detailed enough to show promise, but unfortunately so brief as to leave us without guidance or strategy to fulfill that promise.

My illustrations – deep pockets undermining a court’s fairness, police predation and corruption – describe real injustices rooted in the greed and hatred facilitated through capitalism and the racism that turns the exploited against each other. They are here to remind thinkers who are likewise against such injustice of the urgency of our challenges.

Sassower has offered communitarian approaches to morality and ethics as solutions to those challenges of injustice. I think his direction is very promising. But The Quest for Prosperity offers only a sign. If his next book is to fulfill the promise of this one, he must explore the possibilities opened up by the following questions.

Can communitarian values overcome the allure of greed? What kind of social, political, and economic structures would we need to achieve that utopian goal?

Contact details: serrc.digital@gmail.com

References

Sassower, Raphael. The Quest for Prosperity. London, UK: Rowman & Littlefield, 2017.

Author information: Moti Mizrahi, Florida Institute of Technology, mmizrahi@fit.edu

Mizrahi, Moti. “More in Defense of Weak Scientism: Another Reply to Brown.” Social Epistemology Review and Reply Collective 7, no. 4 (2018): 7-25.

The pdf of the article gives specific page references. Shortlink: https://wp.me/p1Bfg0-3W1

Please refer to:

Image by eltpics via Flickr / Creative Commons

 

In my (2017a), I defend a view I call Weak Scientism, which is the view that knowledge produced by scientific disciplines is better than knowledge produced by non-scientific disciplines.[1] Scientific knowledge can be said to be quantitatively better than non-scientific knowledge insofar as scientific disciplines produce more impactful knowledge–in the form of scholarly publications–than non-scientific disciplines (as measured by research output and research impact). Scientific knowledge can be said to be qualitatively better than non-scientific knowledge insofar as such knowledge is explanatorily, instrumentally, and predictively more successful than non-scientific knowledge.

Brown (2017a) raises several objections against my defense of Weak Scientism and I have replied to his objections (Mizrahi 2017b), thereby showing again that Weak Scientism is a defensible view. Since then, Brown (2017b) has reiterated his objections in another reply on SERRC. Almost unchanged from his previous attack on Weak Scientism (Brown 2017a), Brown’s (2017b) objections are the following:

  1. Weak Scientism is not strong enough to count as scientism.
  2. Advocates of Strong Scientism should not endorse Weak Scientism.
  3. Weak Scientism does not show that philosophy is useless.
  4. My defense of Weak Scientism appeals to controversial philosophical assumptions.
  5. My defense of Weak Scientism is a philosophical argument.
  6. There is nothing wrong with persuasive definitions of scientism.

In what follows, I will respond to these objections, thereby showing once more that Weak Scientism is a defensible view. Since I have been asked to keep this as short as possible, however, I will try to focus on what I take to be new in Brown’s (2017b) latest attack on Weak Scientism.

Is Weak Scientism Strong Enough to Count as Scientism?

Brown (2017b) argues for (1) on the grounds that, on Weak Scientism, “philosophical knowledge may be nearly as valuable as scientific knowledge.” Brown (2017b, 4) goes on to characterize a view he labels “Scientism2,” which he admits is the same view as Strong Scientism, and says that “there is a huge logical gap between Strong Scientism (Scientism2) and Weak Scientism.”

As was the case the first time Brown raised this objection, it is not clear how it is supposed to show that Weak Scientism is not “really” a (weaker) version of scientism (Mizrahi 2017b, 10-11). Of course there is a logical gap between Strong Scientism and Weak Scientism; that is why I distinguish between these two epistemological views. If I am right, Strong Scientism is too strong to be a defensible version of scientism, whereas Weak Scientism is a defensible (weaker) version of scientism (Mizrahi 2017a, 353-354).

Of course Weak Scientism “leaves open the possibility that there is philosophical knowledge” (Brown 2017b, 5). If I am right, such philosophical knowledge would be inferior to scientific knowledge both quantitatively (in terms of research output and research impact) and qualitatively (in terms of explanatory, instrumental, and predictive success) (Mizrahi 2017a, 358).

Brown (2017b, 5) does try to offer a reason “for thinking it strange that Weak Scientism counts as a species of scientism” in his latest attack on Weak Scientism, which does not appear in his previous attack. He invites us to imagine a theist who believes that “modern science is the greatest new intellectual achievement since the fifteenth century” (emphasis in original). Brown then claims that this theist would be an advocate of Weak Scientism because Brown (2017b, 6) takes “modern science is the greatest new intellectual achievement since the fifteenth century” to be “(roughly) equivalent to Weak Scientism.” For Brown (2017b, 6), however, “it seems odd, to say the least, that [this theist] should count as an advocate (even roughly) of scientism.”

Unfortunately, Brown’s appeal to intuition is rather difficult to evaluate because his hypothetical case is under-described.[2] First, the key phrase, namely, “modern science is the greatest new intellectual achievement since the fifteenth century,” is vague in more ways than one. I have no idea what “greatest” is supposed to mean here. Greatest in what respects? What are the other “intellectual achievements” relative to which science is said to be “the greatest”?

Also, what does “intellectual achievement” mean here? There are multiple accounts and literary traditions in history and philosophy of science, science studies, and the like on what counts as “intellectual achievements” or progress in science (Mizrahi 2013b). Without a clear understanding of what these key phrases mean here, it is difficult to tell how Brown’s intuition about this hypothetical case is supposed to be a reason to think that Weak Scientism is not “really” a (weaker) version of scientism.

Toward the end of his discussion of (1), Brown says something that suggests he actually has an issue with the word ‘scientism’. Brown (2017b, 6) writes, “perhaps Mizrahi should coin a new word for the position with respect to scientific knowledge and non-scientific forms of academic knowledge he wants to talk about” (emphasis in original). It should be clear, of course, that it does not matter what label I use for the view that “Of all the knowledge we have, scientific knowledge is the best knowledge” (Mizrahi 2017a, 354; emphasis in original). What matters is the content of the view, not the label.

Whether Brown likes the label or not, Weak Scientism is a (weaker) version of scientism because it is the view that scientific ways of knowing are superior (in certain relevant respects) to non-scientific ways of knowing, whereas Strong Scientism is the view that scientific ways of knowing are the only ways of knowing. As I have pointed out in my previous reply to Brown, whether scientific ways of knowing are superior to non-scientific ways of knowing is essentially what the scientism debate is all about (Mizrahi 2017b, 13).

Before I conclude this discussion of (1), I would like to point out that Brown seems to have misunderstood Weak Scientism. He (2017b, 3) claims that “Weak Scientism is a normative and not a descriptive claim.” This is a mistake. As a thesis (Peels 2017, 11), Weak Scientism is a descriptive claim about scientific knowledge in comparison to non-scientific knowledge. This should be clear provided that we keep in mind what it means to say that scientific knowledge is better than non-scientific knowledge. As I have argued in my (2017a), to say that scientific knowledge is quantitatively better than non-scientific knowledge is to say that there is a lot more scientific knowledge than non-scientific knowledge (as measured by research output) and that the impact of scientific knowledge is greater than that of non-scientific knowledge (as measured by research impact).

To say that scientific knowledge is qualitatively better than non-scientific knowledge is to say that scientific knowledge is explanatorily, instrumentally, and predictively more successful than non-scientific knowledge. All these claims about the superiority of scientific knowledge to non-scientific knowledge are descriptive, not normative, claims. That is to say, Weak Scientism is the view that, as a matter of fact, knowledge produced by scientific fields of study is quantitatively (in terms of research output and research impact) and qualitatively (in terms of explanatory, instrumental, and predictive success) better than knowledge produced by non-scientific fields of study.

Of course, Weak Scientism does have some normative implications. For instance, if scientific knowledge is indeed better than non-scientific knowledge, then, other things being equal, we should give more evidential weight to scientific knowledge than to non-scientific knowledge. For example, suppose that I am considering whether to vaccinate my child or not. On the one hand, I have scientific knowledge in the form of results from clinical trials according to which MMR vaccines are generally safe and effective.

On the other hand, I have knowledge in the form of stories about children who were vaccinated and then began to display symptoms of autism. If Weak Scientism is true, and I want to make a decision based on the best available information, then I should give more evidential weight to the scientific knowledge about MMR vaccines than to the anecdotal knowledge about MMR vaccines simply because the former is scientific (i.e., knowledge obtained by means of the methods of science, such as clinical trials) and the latter is not.

Should Advocates of Strong Scientism Endorse Weak Scientism?

Brown (2017b, 7) argues for (2) on the grounds that “once the advocate of Strong Scientism sees that an advocate of Weak Scientism admits the possibility that there is real knowledge other than what is produced by the natural sciences […] the advocate of Strong Scientism, at least given their philosophical presuppositions, will reject Weak Scientism out of hand.” It is not clear which “philosophical presuppositions” Brown is talking about here. Brown quotes Rosenberg (2011, 20), who claims that physics tells us what reality is like, presumably as an example of a proponent of Strong Scientism who would not endorse Weak Scientism. But it is not clear why Brown thinks that Rosenberg would “reject Weak Scientism out of hand” (Brown 2017d, 7).

Like other proponents of scientism, Rosenberg should endorse Weak Scientism because, unlike Strong Scientism, Weak Scientism is a defensible view. Insofar as we should endorse the view that has the most evidence in its favor, Weak Scientism has more going for it than Strong Scientism does. For to show that Strong Scientism is true, one would have to show that no field of study other than scientific ones can produce knowledge. Of course, that is not easy to show. To show that Weak Scientism is true, one only needs to show that the knowledge produced in scientific fields of study is better (in certain relevant respects) than the knowledge produced in non-scientific fields.

That is precisely what I show in my (2017a). I argue that the knowledge produced in scientific fields is quantitatively better than the knowledge produced in non-scientific fields because there is a lot more scientific knowledge than non-scientific knowledge (as measured by research output) and the former has a greater impact than the latter (as measured by research impact). I also argue that the knowledge produced in scientific fields is qualitatively better than knowledge produced in non-scientific fields because it is more explanatorily, instrumentally, and predictively successful.

Contrary to what Brown (2017b, 7) seems to think, I do not have to show “that there is real knowledge other than scientific knowledge.” To defend Weak Scientism, all I have to show is that scientific knowledge is better (in certain relevant respects) than non-scientific knowledge. If anyone must argue for the claim that there is real knowledge other than scientific knowledge, it is Brown, for he wants to defend the value or usefulness of non-scientific knowledge, specifically, philosophical knowledge.

It is important to emphasize the point about the ways in which scientific knowledge is quantitatively and qualitatively better than non-scientific knowledge because it looks like Brown has confused the two. For he thinks that I justify my quantitative analysis of scholarly publications in scientific and non-scientific fields by “citing the precedent of epistemologists who often treat all items of knowledge as qualitatively the same” (Brown 2017b, 22; emphasis added).

Here Brown fails to carefully distinguish between my claim that scientific knowledge is quantitatively better than non-scientific knowledge and my claim that scientific knowledge is qualitatively better than non-scientific knowledge. For the purposes of a quantitative study of knowledge, information and data scientists can do precisely what epistemologists do and “abstract from various circumstances (by employing variables)” (Brown 2017b, 22) in order to determine which knowledge is quantitatively better.

How Is Weak Scientism Relevant to the Claim that Philosophy Is Useless?

Brown (2017b, 7-8) argues for (3) on the grounds that “Weak Scientism itself implies nothing about the degree to which philosophical knowledge is valuable or useful other than stating scientific knowledge is better than philosophical knowledge” (emphasis in original).

Strictly speaking, Brown is wrong about this because Weak Scientism does imply something about the degree to which scientific knowledge is better than philosophical knowledge. Recall that to say that scientific knowledge is quantitatively better than non-scientific knowledge is to say that scientific fields of study publish more research and that scientific research has greater impact than the research published in non-scientific fields of study.

Contrary to what Brown seems to think, we can say to what degree scientific research is superior to non-scientific research in terms of output and impact. That is precisely what bibliometric indicators like h-index and other metrics are for (Rousseau et al. 2018). Such bibliometric indicators allow us to say how many articles are published in a given field, how many of those published articles are cited, and how many times they are cited. For instance, according to Scimago Journal & Country Rank (2018), which contains data from the Scopus database, of the 3,815 Philosophy articles published in the United States in 2016-2017, approximately 14% are cited, and their h-index is approximately 160.

On the other hand, of the 24,378 Psychology articles published in the United States in 2016-2017, approximately 40% are cited, and their h-index is approximately 640. Contrary to what Brown seems to think, then, we can say to what degree research in Psychology is better than research in Philosophy in terms of research output (i.e., number of publications) and research impact (i.e., number of citations). We can use the same bibliometric indicators and metrics to compare research in other scientific and non-scientific fields of study.

As I have already said in my previous reply to Brown, “Weak Scientism does not entail that philosophy is useless” and “I have no interest in defending the charge that philosophy is useless” (Mizrahi 2017b, 11-12). So, I am not sure why Brown brings up (3) again. Since he insists, however, let me explain why philosophers who are concerned about the charge that philosophy is useless should engage with Weak Scientism as well.

Suppose that a foundation or agency is considering whether to give a substantial grant to one of two projects. The first project is that of a philosopher who will sit in her armchair and contemplate the nature of friendship.[3] The second project is that of a team of social scientists who will conduct a longitudinal study of the effects of friendship on human well-being (e.g., Yang et al. 2016).

If Weak Scientism is true, and the foundation or agency wants to fund the project that is likely to yield better results, then it should give the grant to the team of social scientists rather than to the armchair philosopher simply because the former’s project is scientific, whereas the latter’s is not. This is because the scientific project will more likely yield better knowledge than the non-scientific project will. In other words, unlike the project of the armchair philosopher, the scientific project will probably produce more research (i.e., more publications) that will have a greater impact (i.e., more citations) and the knowledge produced will be explanatorily, instrumentally, and predictively more successful than any knowledge that the philosopher’s project might produce.

This example should really hit home for Brown, since reading his latest attack on Weak Scientism gives one the impression that he thinks of philosophy as a personal, “self-improvement” kind of enterprise, rather than an academic discipline or field of study. For instance, he seems to be saying that philosophy is not in the business of producing “new knowledge” or making “discoveries” (Brown 2017b, 17).

Rather, Brown (2017b, 18) suggests that philosophy “is more about individual intellectual progress rather than collective intellectual progress.” Individual progress or self-improvement is great, of course, but I am not sure that it helps Brown’s case in defense of philosophy against what he sees as “the menace of scientism.” For this line of thinking simply adds fuel to the fire set by those who want to see philosophy burn. As I point out in my (2017a), scientists who dismiss philosophy do so because they find it academically useless.

For instance, Hawking and Mlodinow (2010, 5) write that ‘philosophy is dead’ because it ‘has not kept up with developments in science, particularly physics’ (emphasis added). Similarly, Weinberg (1994, 168) says that, as a working scientist, he ‘finds no help in professional philosophy’ (emphasis added). (Mizrahi 2017a, 356)

Likewise, Richard Feynman is rumored to have said that “philosophy of science is about as useful to scientists as ornithology is to birds” (Kitcher 1998, 32). It is clear, then, that what these scientists complain about is professional or academic philosophy. Accordingly, they would have no problem with anyone who wants to pursue philosophy for the sake of “individual intellectual progress.” But that is not the issue here. Rather, the issue is academic knowledge or research.

Does My Defense of Weak Scientism Appeal to Controversial Philosophical Assumptions?

Brown (2017b, 9) argues for (4) on the grounds that I assume that “we are supposed to privilege empirical (I read Mizrahi’s ‘empirical’ here as ‘experimental/scientific’) evidence over non-empirical evidence.” But that is question-begging, Brown claims, since he takes me to be assuming something like the following: “If the question of whether scientific knowledge is superior to [academic] non-scientific knowledge is a question that one can answer empirically, then, in order to pose a serious challenge to my [Mizrahi’s] defense of Weak Scientism, Brown must come up with more than mere ‘what ifs’” (Mizrahi 2017b, 10; quoted in Brown 2017b, 8).

This objection seems to involve a confusion about how defeasible reasoning and defeating evidence are supposed to work. Given that “a rebutting defeater is evidence which prevents E from justifying belief in H by supporting not-H in a more direct way” (Kelly 2016), claims about what is actual cannot be defeated by mere possibilities, since claims of the form “Possibly, p” do not prevent a piece of evidence from justifying belief in “Actually, p” by supporting “Actually, not-p” directly.

For example, the claim “Hillary Clinton could have been the 45th President of the United States” does not prevent my perceptual and testimonial evidence from justifying my belief in “Donald Trump is the 45th President of the United States,” since the former does not support “It is not the case that Donald Trump is the 45th President of the United States” in a direct way. In general, claims of the form “Possibly, p” are not rebutting defeaters against claims of the form “Actually, p.” Defeating evidence against claims of the form “Actually, p” must be about what is actual (or at least probable), not what is merely possible, in order to support “Actually, not-p” directly.

For this reason, although “the production of some sorts of non-scientific knowledge work may be harder than the production of scientific knowledge” (Brown 2017b, 19), Brown gives no reasons to think that it is actually or probably harder, which is why this possibility does nothing to undermine the claim that scientific knowledge is actually better than non-scientific knowledge. Just as it is possible that philosophical knowledge is harder to produce than scientific knowledge, it is also possible that scientific knowledge is harder to produce than philosophical knowledge. It is also possible that scientific and non-scientific knowledge are equally hard to produce.

Similarly, the possibility that “a little knowledge about the noblest things is more desirable than a lot of knowledge about less noble things” (Brown 2017b, 19), whatever “noble” is supposed to mean here, does not prevent my bibliometric evidence (in terms of research output and research impact) from justifying the belief that scientific knowledge is better than non-scientific knowledge. Just as it is possible that philosophical knowledge is “nobler” (whatever that means) than scientific knowledge, it is also possible that scientific knowledge is “nobler” than philosophical knowledge or that they are equally “noble” (Mizrahi 2017b, 9-10).

In fact, even if Brown (2017a, 47) is right that “philosophy is harder than science” and that “knowing something about human persons–particularly qua embodied rational being–is a nobler piece of knowledge than knowing something about any non-rational object” (Brown 2017b, 21), whatever “noble” is supposed to mean here, it would still be the case that scientific fields produce more knowledge (as measured by research output), and more impactful knowledge (as measured by research impact), than non-scientific disciplines.

So, I am not sure why Brown keeps insisting on mentioning these mere possibilities. He also seems to forget that the natural and social sciences study human persons as well. Even if knowledge about human persons is “nobler” (whatever that means), there is a lot of scientific knowledge about human persons coming from scientific fields, such as anthropology, biology, genetics, medical science, neuroscience, physiology, psychology, and sociology, to name just a few.

One of the alleged “controversial philosophical assumptions” that my defense of Weak Scientism rests on, and that Brown (2017a) complains about the most in his previous attack on Weak Scientism, is my characterization of philosophy as the scholarly work that professional philosophers do. In my previous reply, I argue that Brown is not in a position to complain that this is a “controversial philosophical assumption,” since he rejects my characterization of philosophy as the scholarly work that professional philosophers produce, but he does not tell us what counts as philosophical (Mizrahi 2017b, 13). Well, it turns out that Brown does not reject my characterization of philosophy after all. For, after he was challenged to say what counts as philosophical, he came up with the following “sufficient condition for pieces of writing and discourse that count as philosophy” (Brown 2017b, 11):

(P) Those articles published in philosophical journals and what academics with a Ph.D. in philosophy teach in courses at public universities with titles such as Introduction to Philosophy, Metaphysics, Epistemology, Normative Ethics, and Philosophy of Science (Brown 2017b, 11; emphasis added).

Clearly, this is my characterization of philosophy in terms of the scholarly work that professional philosophers produce. Brown simply adds teaching to it. Since he admits that “scientists teach students too” (Brown 2017b, 18), however, it is not clear how adding teaching to my characterization of philosophy is supposed to support his attack on Weak Scientism. In fact, it may actually undermine his attack on Weak Scientism, since there is a lot more teaching going on in STEM fields than in non-STEM fields.

According to data from the National Center for Education Statistics (2017), in the 2015-16 academic year, post-secondary institutions in the United States conferred only 10,157 Bachelor’s degrees in philosophy and religious studies compared to 113,749 Bachelor’s degrees in biological and biomedical sciences, 106,850 Bachelor’s degrees in engineering, and 117,440 in psychology. In general, in the 2015-2016 academic year, 53.3% of the Bachelor’s degrees conferred by post-secondary institutions in the United States were degrees in STEM fields, whereas only 5.5% of conferred Bachelor’s degrees were in the humanities (Figure 1).

Figure 1. Bachelor’s degrees conferred by post-secondary institutions in the US, by field of study, 2015-2016 (Source: NCES)

 

Clearly, then, there is a lot more teaching going on in science than in philosophy (or even in the humanities in general), since a lot more students take science courses and graduate with degrees in scientific fields of study. So, even if Brown is right that we should include teaching in what counts as philosophy, it is still the case that scientific fields are quantitatively better than non-scientific fields.

Since Brown (2017b, 13) seems to agree that philosophy (at least in part) is the scholarly work that academic philosophers produce, it is peculiar that he complains, without argument, that “an understanding of philosophy and knowledge as operational is […] shallow insofar as philosophy and knowledge can’t fit into the narrow parameters of another empirical study.” Once Brown (2017b, 11) grants that “Those articles published in philosophical journals” count as philosophy, he thereby also grants that these journal articles can be studied empirically using the methods of bibliometrics, information science, or data science.

That is, Brown (2017b, 11) concedes that philosophy consists (at least in part) of “articles published in philosophical journals,” and so these articles can be compared to other articles published in science journals to determine research output, and they can also be compared to articles published in science journals in terms of citation counts to determine research impact. What exactly is “shallow” about that? Brown does not say.

A, perhaps unintended, consequence of Brown’s (P) is that the “great thinkers from the past” (Brown 2017b, 18), those that Brown (2017b, 13) likes to remind us “were not professional philosophers,” did not do philosophy, by Brown’s own lights. For “Socrates, Plato, Augustine, Descartes, Locke, and Hume” (Brown 2017b, 13) did not publish in philosophy journals, were not academics with a Ph.D. in philosophy, and did not teach at public universities courses “with titles such as Introduction to Philosophy, Metaphysics, Epistemology, Normative Ethics, and Philosophy of Science” (Brown 2017b, 11).

Another peculiar thing about Brown’s (P) is the restriction of the philosophical to what is being taught in public universities. What about community colleges and private universities? Is Brown suggesting that philosophy courses taught at private universities do not count as philosophy courses? This is peculiar, especially in light of the fact that, at least according to The Philosophical Gourmet Report (Brogaard and Pynes 2018), the top ranked philosophy programs in the United States are mostly located in private universities, such as New York University and Princeton University.

Is My Defense of Weak Scientism a Scientific or a Philosophical Argument?

Brown argues for (5) on the grounds that my (2017a) is published in a philosophy journal, namely, Social Epistemology, and so it a piece of philosophical knowledge by my lights, since I count as philosophy the research articles that are published in philosophy journals.

Brown would be correct about this if Social Epistemology were a philosophy journal. But it is not. Social Epistemology: A Journal of Knowledge, Culture and Policy is an interdisciplinary journal. The journal’s “aim and scope” statement makes it clear that Social Epistemology is an interdisciplinary journal:

Social Epistemology provides a forum for philosophical and social scientific enquiry that incorporates the work of scholars from a variety of disciplines who share a concern with the production, assessment and validation of knowledge. The journal covers both empirical research into the origination and transmission of knowledge and normative considerations which arise as such research is implemented, serving as a guide for directing contemporary knowledge enterprises (Social Epistemology 2018).

The fact that Social Epistemology is an interdisciplinary journal, with contributions from “Philosophers, sociologists, psychologists, cultural historians, social studies of science researchers, [and] educators” (Social Epistemology 2018) would not surprise anyone who is familiar with the history of the journal. The founding editor of the journal is Steve Fuller, who was trained in an interdisciplinary field, namely, History and Philosophy of Science (HPS), and is currently the Auguste Comte Chair in Social Epistemology in the Department of Sociology at Warwick University. Brown (2017b, 15) would surely agree that sociology is not philosophy, given that, for him, “cataloguing what a certain group of people believes is sociology and not philosophy.” The current executive editor of the journal is James H. Collier, who is a professor of Science and Technology in Society at Virginia Tech, and who was trained in Science and Technology Studies (STS), which is an interdisciplinary field as well.

Brown asserts without argument that the methods of a scientific field of study, such as sociology, are different in kind from those of philosophy: “What I contend is that […] philosophical methods are different in kind from those of the experimental scientists [sciences?]” (Brown 2017b, 24). He then goes on to speculate about what it means to say that an explanation is testable (Brown 2017b, 25). What Brown comes up with is rather unclear to me. For instance, I have no idea what it means to evaluate an explanation by inductive generalization (Brown 2017b, 25).

Instead, Brown should have consulted any one of the logic and reasoning textbooks I keep referring to in my (2017a) and (2017b) to find out that it is generally accepted among philosophers that the good-making properties of explanations, philosophical and otherwise, include testability among other good-making properties (see, e.g., Sinnott-Armstrong and Fogelin 2010, 257). As far as testability is concerned, to test an explanation or hypothesis is to determine “whether predictions that follow from it are true” (Salmon 2013, 255). In other words, “To say that a hypothesis is testable is at least to say that some prediction made on the basis of that hypothesis may confirm or disconfirm it” (Copi et al. 2011, 515).

For this reason, Feser’s analogy according to which “to compare the epistemic values of science and philosophy and fault philosophy for not being good at making testable predications [sic] is like comparing metal detectors and gardening tools and concluding gardening tools are not as good as metal detectors because gardening tools do not allow us to successfully detect for metal” (Brown 2017b, 25), which Brown likes to refer to (Brown 2017a, 48), is inapt.

It is not an apt analogy because, unlike metal detectors and gardening tools, which serve different purposes, both science and philosophy are in the business of explaining things. Indeed, Brown admits that, like good scientific explanations, “good philosophical theories explain things” (emphasis in original). In other words, Brown admits that both scientific and philosophical theories are instruments of explanation (unlike gardening and metal-detecting instruments). To provide good explanations, then, both scientific and philosophical theories must be testable (Mizrahi 2017b, 19-20).

What Is Wrong with Persuasive Definitions of Scientism?

Brown (2017b, 31) argues for (6) on the grounds that “persuasive definitions are [not] always dialectically pernicious.” He offers an argument whose conclusion is “abortion is murder” as an example of an argument for a persuasive definition of abortion. He then outlines an argument for a persuasive definition of scientism according to which “Weak Scientism is a view that has its advocates putting too high a value on scientific knowledge” (Brown 2017b, 32).

The problem, however, is that Brown is confounding arguments for a definition with the definition itself. Having an argument for a persuasive definition does not change the fact that it is a persuasive definition. To illustrate this point, let me give an example that I think Brown will appreciate. Suppose I define theism as an irrational belief in the existence of God. That is, “theism” means “an irrational belief in the existence of God.” I can also provide an argument for this definition:

P1: If it is irrational to have paradoxical beliefs and God is a paradoxical being, then theism is an irrational belief in the existence of God.

P2: It is irrational to have paradoxical beliefs and God is a paradoxical being (e.g., the omnipotence paradox).[4]

Therefore,

C: Theism is an irrational belief in the existence of God.

But surely, theists will complain that my definition of theism is a “dialectically pernicious” persuasive definition. For it stacks the deck against theists. It states that theists are already making a mistake, by definition, simply by believing in the existence of God. Even though I have provided an argument for this persuasive definition of theism, my definition is still a persuasive definition of theism, and my argument is unlikely to convince anyone who doesn’t already think that theism is irrational. Indeed, Brown (2017b, 30) himself admits that much when he says “good luck with that project!” about trying to construct a sound argument for “abortion is murder.” I take this to mean that pro-choice advocates would find his argument for “abortion is murder” dialectically inert precisely because it defines abortion in a manner that transfers “emotive force” (Salmon 2013, 65), which they cannot accept.

Likewise, theists would find the argument above dialectically inert precisely because it defines theism in a manner that transfers “emotive force” (Salmon 2013, 65), which they cannot accept. In other words, Brown seems to agree that there are good dialectical reasons to avoid appealing to persuasive definitions. Therefore, like “abortion is murder,” “theism is an irrational belief in the existence of God,” and “‘Homosexual’ means ‘one who has an unnatural desire for those of the same sex’” (Salmon 2013, 65), “Weak Scientism is a view that has its advocates putting too high a value on scientific knowledge” (Brown 2017b, 32) is a “dialectically pernicious” persuasive definition (cf. Williams 2015, 14).

Like persuasive definitions in general, it “masquerades as an honest assignment of meaning to a term while condemning or blessing with approval the subject matter of the definiendum” (Hurley 2015, 101). As I have pointed out in my (2017a), the problem with such definitions is that they “are strategies consisting in presupposing an unaccepted definition, taking a new unknowable description of meaning as if it were commonly shared” (Macagno and Walton 2014, 205).

As for Brown’s argument for the persuasive definition of Weak Scientism, according to which it “is a view that has its advocates putting too high a value on scientific knowledge” (Brown 2017b, 32), a key premise in this argument is the claim that there is a piece of philosophical knowledge that is better than scientific knowledge. This is premise 36 in Brown’s argument:

Some philosophers qua philosophers know that (a) true friendship is a necessary condition for human flourishing and (b) the possession of the moral virtues or a life project aimed at developing the moral virtues is a necessary condition for true friendship and (c) (therefore) the possession of the moral virtues or a life project aimed at developing the moral virtues is a necessary condition for human flourishing (see, e.g., the arguments in Plato’s Gorgias) and knowledge concerning the necessary conditions of human flourishing is better than any sort of scientific knowledge (see, e.g., St. Augustine’s Confessions, book five, chapters iii and iv) [assumption]

There is a lot to unpack here, but I will focus on what I take to be the points most relevant to the scientism debate. First, Brown assumes 36 without argument, but why think it is true? In particular, why think that (a), (b), and (c) count as philosophical knowledge? Brown says that philosophers know (a), (b), and (c) in virtue of being philosophers, but he does not tell us why that is the case.

After all, accounts of friendship, with lessons about the significance of friendship, predate philosophy (see, e.g., the friendship of Gilgamesh and Enkidu in The Epic of Gilgamesh). Did it really take Plato and Augustine to tell us about the significance of friendship? In fact, on Brown’s characterization of philosophy, namely, (P), (a), (b), and (c) do not count as philosophical knowledge at all, since Plato and Augustine did not publish in philosophy journals, were not academics with a Ph.D. in philosophy, and did not teach at public universities courses “with titles such as Introduction to Philosophy, Metaphysics, Epistemology, Normative Ethics, and Philosophy of Science” (Brown 2017b, 11).

Second, some philosophers, like Epicurus, need (and think that others need) friends to flourish, whereas others, like Diogenes of Sinope, need no one. For Diogenes, friends will only interrupt his sunbathing (Arrian VII.2). My point is not simply that philosophers disagree about the value of friendship and human flourishing. Of course they disagree.[5]

Rather, my point is that, in order to establish general truths about human beings, such as “Human beings need friends to flourish,” one must employ the methods of science, such as randomization and sampling procedures, blinding protocols, methods of statistical analysis, and the like; otherwise, one would simply commit the fallacies of cherry-picking anecdotal evidence and hasty generalization (Salmon 2013, 149-151). After all, the claim “Some need friends to flourish” does not necessitate, or even make more probable, the truth of “Human beings need friends to flourish.”[6]

Third, why think that “knowledge concerning the necessary conditions of human flourishing is better than any sort of scientific knowledge” (Brown 2017b, 32)? Better in what sense? Quantitatively? Qualitatively? Brown does not tell us. He simply declares it “self-evident” (Brown 2017b, 32). I take it that Brown would not want to argue that “knowledge concerning the necessary conditions of human flourishing” is better than scientific knowledge in the quantitative (i.e., in terms of research output and research impact) and qualitative (i.e., in terms of explanatory, instrumental, and predictive success) respects in which scientific knowledge is better than non-scientific knowledge, according to Weak Scientism.

If so, then in what sense exactly “knowledge concerning the necessary conditions of human flourishing” (Brown 2017b, 32) is supposed to be better than scientific knowledge? Brown (2017b, 32) simply assumes that without argument and without telling us in what sense exactly “knowledge concerning the necessary conditions of human flourishing is better than any sort of scientific knowledge” (Brown 2017b, 32).

Of course, philosophy does not have a monopoly on friendship and human flourishing as research topics. Psychologists and sociologists, among other scientists, work on friendship as well (see, e.g., Hojjat and Moyer 2017). To get an idea of how much research on friendship is done in scientific fields, such as psychology and sociology, and how much is done in philosophy, we can use a database like Web of Science.

Currently (03/29/2018), there are 12,334 records in Web of Science on the topic “friendship.” Only 76 of these records (0.61%) are from the Philosophy research area. Most of the records are from the Psychology (5,331 records) and Sociology (1,111) research areas (43.22% and 9%, respectively). As we can see from Figure 2, most of the research on friendship is done in scientific fields of study, such as psychology, sociology, and other social sciences.

Figure 2. Number of records on the topic “friendship” in Web of Science by research area (Source: Web of Science)

 

In terms of research impact, too, scientific knowledge about friendship is superior to philosophical knowledge about friendship. According to Web of Science, the average citations per year for Psychology research articles on the topic of friendship is 2826.11 (h-index is 148 and the average citations per item is 28.1), and the average citations per year for Sociology research articles on the topic of friendship is 644.10 (h-index is 86 and the average citations per item is 30.15), whereas the average citations per year for Philosophy research articles on friendship is 15.02 (h-index is 13 and the average citations per item is 8.11).

Quantitatively, then, psychological and sociological knowledge on friendship is better than philosophical knowledge in terms of research output and research impact. Both Psychology and Sociology produce significantly more research on friendship than Philosophy does, and the research they produce has significantly more impact (as measured by citation counts) than philosophical research on the same topic.

Qualitatively, too, psychological and sociological knowledge about friendship is better than philosophical knowledge about friendship. For, instead of rather vague statements about how “true friendship is a necessary condition for human flourishing” (Brown 2017b, 32) that are based on mostly armchair speculation, psychological and sociological research on friendship provides detailed explanations and accurate predictions about the effects of friendship (or lack thereof) on human well-being.

For instance, numerous studies provide evidence for the effects of friendships or lack of friendships on physical well-being (see, e.g., Yang et al. 2016) as well as mental well-being (see, e.g., Cacioppo and Patrick 2008). Further studies provide explanations for the biological and genetic bases of these effects (Cole et al. 2011). This knowledge, in turn, informs interventions designed to help people deal with loneliness and social isolation (see, e.g., Masi et al. 2010).[7]

To sum up, Brown (2017b, 32) has given no reasons to think that “knowledge concerning the necessary conditions of human flourishing is better than any sort of scientific knowledge.” He does not even tell us what “better” is supposed to mean here. He also ignores the fact that scientific fields of study, such as psychology and sociology, produce plenty of knowledge about human flourishing, both physical and mental well-being. In fact, as we have seen, science produces a lot more knowledge about topics related to human well-being, such as friendship, than philosophy does. For this reason, Brown (2017b, 32) has failed to show that “there is non-scientific form of knowledge better than scientific knowledge.”

Conclusion

At this point, I think it is quite clear that Brown and I are talking past each other on a couple of levels. First, I follow scientists (e.g., Weinberg 1994, 166-190) and philosophers (e.g., Haack 2007, 17-18 and Peels 2016, 2462) on both sides of the scientism debate in treating philosophy as an academic discipline or field of study, whereas Brown (2017b, 18) insists on thinking about philosophy as a personal activity of “individual intellectual progress.” Second, I follow scientists (e.g., Hawking and Mlodinow 2010, 5) and philosophers (e.g., Kidd 2016, 12-13 and Rosenberg 2011, 307) on both sides of the scientism debate in thinking about knowledge as the scholarly work or research produced in scientific fields of study, such as the natural sciences, as opposed to non-scientific fields of study, such as the humanities, whereas Brown insists on thinking about philosophical knowledge as personal knowledge.

To anyone who wishes to defend philosophy’s place in research universities alongside academic disciplines, such as history, linguistics, and physics, armed with this conception of philosophy as a “self-improvement” activity, I would use Brown’s (2017b, 30) words to say, “good luck with that project!” A much more promising strategy, I propose, is for philosophy to embrace scientific ways of knowing and for philosophers to incorporate scientific methods into their research.[8]

Contact details: mmizrahi@fit.edu

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Ashton, Z., and M. Mizrahi. “Intuition Talk is Not Methodologically Cheap: Empirically Testing the “Received Wisdom” about Armchair Philosophy.” Erkenntnis (2017): DOI 10.1007/s10670-017-9904-4.

Ashton, Z., and M. Mizrahi. “Show Me the Argument: Empirically Testing the Armchair Philosophy Picture.” Metaphilosophy 49, no. 1-2 (2018): 58-70.

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[1] I thank Adam Riggio for inviting me to respond to Brown’s second attack on Weak Scientism.

[2] On why appeals to intuition are bad arguments, see Mizrahi (2012), (2013a), (2014), (2015a), (2015b), and (2015d).

[3] I use friendship as an example here because Brown (2017b, 31) uses it as an example of philosophical knowledge. I will say more about that in Section 6.

[4] For more on paradoxes involving the divine attributes, see Mizrahi (2013c).

[5] “Friendship is unnecessary, like philosophy, like art, like the universe itself (for God did not need to create)” (Lewis 1960, 71).

[6] On fallacious inductive reasoning in philosophy, see Mizrahi (2013d), (2015c), (2016), and (2017c).

[7] See also “The Friendship Bench” project: https://www.friendshipbenchzimbabwe.org/.

[8] For recent examples, see Ashton and Mizrahi (2017) and (2018).