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

Mizrahi, Moti. “Why Scientific Knowledge Is Still the Best.” Social Epistemology Review and Reply Collective 7, no. 9 (2018): 18-32.

The pdf of the article gives specific page references. Shortlink: https://wp.me/p1Bfg0-40I

For context, see also:

Image by Specious Reasons via Flickr / Creative Commons

 

It is common knowledge among scholars and researchers that the norms of academic research dictate that one must enter an academic conversation by properly acknowledging, citing, and engaging with the work done by other scholars and researchers in the field, thereby showing that a larger conversation is taking place.[1] See, for example, Graff and Birkenstein (2018, 1-18) on “entering the conversation.” Properly “entering the conversation” is especially important when one aims to criticize the work done by other scholars and researchers in the field.

In my previous reply to Bernard Wills’ attack on Weak Scientism (Wills 2018a), I point out that Wills fails in his job as a scholar who aims to criticize work done by other scholars and researchers in the field (Mizrahi 2018b, 41), since Wills does not cite or engage with the paper in which I defend Weak Scientism originally (Mizrahi 2017a), the very thesis he seeks to attack. Moreover, he does not cite or engage with the papers in my exchange with Christopher Brown (Mizrahi 2017b; 2018a), not to mention other works in the literature on scientism.

In his latest attack, even though he claims to be a practitioner of “close reading” (Wills 2018b, 34), it appears that Wills still has not bothered to read the paper in which I defend the thesis he seeks to attack (Mizrahi 2017a), or any of the papers in my exchange with Brown (Mizrahi 2017b; 2018a), as evidenced by the fact that he does not cite them at all. To me, these are not only signs of lazy scholarship but also an indication that Wills has no interest in engaging with my arguments for Weak Scientism in good faith. For these reasons, this will be my second and final response to Wills. I have neither the time nor the patience to debate lazy scholars who argue in bad faith.

On the Quantitative Superiority of Scientific Knowledge

In response to my empirical data on the superiority of scientific knowledge over non-scientific knowledge in terms of research output and research impact (Mizrahi 2017a, 357-359; Mizrahi 2018a, 20-22; Mizrahi 2018b, 42-44), Wills (2018b, 34) claims that he has “no firm opinion at all as to whether the totality of the sciences have produced more ‘stuff’ than the totality of the humanities between 1997 and 2017 and the reason is that I simply don’t care.”

I would like to make a few points in reply. First, the sciences produce more published research, not just “stuff.” Wills’ use of the non-count noun ‘stuff’ is misleading because it suggests that research output cannot be counted or measured. However, research output (as well as research impact) can be counted and measured, which is why we can use this measure to determine that scientific research (or knowledge) is better than non-scientific research (or knowledge).

Second, my defense of Weak Scientism consists of a quantitative argument and a qualitative argument, thereby showing that scientific knowledge is superior to non-scientific knowledge both quantitatively and qualitatively, which are the two ways in which one thing can be said to be better than another (Mizrahi 2017a, 354). If Wills really does not care about the quantitative argument for Weak Scientism, as he claims, then why is he attacking my defense of Weak Scientism at all?

After all, showing that “scientific knowledge is [quantitatively] better – in terms of research output (i.e. more publications) and research impact (i.e. more citations) – than non-scientific knowledge” is an integral part of my defense of Weak Scientism (Mizrahi 2017a, 358). To know that, however, Wills would have to read the paper in which I make these arguments for Weak Scientism (Mizrahi 2017a). In his (2018a) and (2018b), I see no evidence that Wills has read, let alone read closely, that paper.

Third, for someone who says that he “simply [doesn’t] care” about quantity (Wills 2018b, 34), Wills sure talks about it a lot. For example, Wills claims that a “German professor once told [him] that in the first half of the 20th Century there were 40,000 monographs on Franz Kafka alone!” (Wills 2018a, 18) and that “Shakespeare scholars have all of us beat” (Wills 2018a, 18). Wills’ unsupported claims about quantity turn out to be false, of course, as I show in my previous reply (Mizrahi 2018b, 42-44). Readers will notice that Wills does not even try to defend those claims in his (2018b).

Fourth, whether Wills cares about quantity or has opinions on the matter is completely beside the point. With all due respect, Wills’ opinions about research output in academic disciplines are worthless, especially when we have data on research output in scientific and non-scientific disciplines. The data show that scientific disciplines produce more research than non-scientific disciplines and that scientific research has a greater impact than non-scientific research (Mizrahi 2017a, 357-359; Mizrahi 2018a, 20-22; Mizrahi 2018b, 42-44).

Wills (2018b, 35) thinks that the following is a problem for Weak Scientism: “what if it were true that Shakespeare scholars produced more papers than physicists?” (original emphasis) Lacking in good arguments, as in his previous attack on Weak Scientism, Wills resorts to making baseless accusations and insults, calling me “an odd man” for thinking that literature would be better than physics in his hypothetical scenario (Wills 2018b, 35). But this is not a problem for Weak Scientism at all and there is nothing “odd” about it.

What Wills fails to understand is that Weak Scientism is not supposed to be a necessary truth. That is, Weak Scientism does not state that scientific knowledge must be quantitatively and qualitatively better than non-scientific knowledge. Rather, Weak Scientism is a contingent fact about the state of academic research. As a matter of fact, scientific disciplines produce better research than non-scientific disciplines do.

Moreover, the data we have (Mizrahi 2017a, 357-359; Mizrahi 2018a, 20-22; Mizrahi 2018b, 42-44) give us no reason to think that these trends in research output and research impact are likely to change any time soon. Of course, if Wills had read my original defense of Weak Scientism (Mizrahi 2017a), and my replies to Brown, he would have known that I have discussed all of this already (Mizrahi 2017b, 9-10; 2018a, 9-13).

Likewise, contrary to what Wills (2018b, 36, footnote 2) seems to think, there is nothing odd about arguing for a thesis according to which academic research produced by scientific disciplines is superior to academic research produced by non-scientific disciplines, “while leaving open the question whether non-scientific knowledge outside the academy may be superior to science” (original emphasis). If Wills were familiar with the literature on scientism, he would have been aware of the common distinction between “internal scientism” and “external scientism.”

See, for example, Stenmark’s (1997, 16-18) distinction between “academic-internal scientism” and “academic-external scientism” as well as Peels (2018, 28-56) on the difference between “academic scientism” and “universal scientism.” Again, a serious scholar would have made sure that he or she is thoroughly familiar with the relevant literature before attacking a research paper that aims to make a contribution to that literature (Graff and Birkenstein 2018, 1-18).

Wills also seems to be unaware of the fact that my quantitative argument for Weak Scientism consists of two parts: (a) showing that scientific research output is greater than non-scientific research output, and (b) showing that the research impact of scientific research is greater than that of non-scientific research (Mizrahi 2017a, 356-358). The latter is measured, not just by publications, but also by citations. Wills does not address this point about research impact in his attacks on Weak Scientism. Since he seems to be proud of his publication record, for he tells me I should search for his published papers on Google (Wills 2018b, 35), let me to illustrate this point about research impact by comparing Wills’ publication record to a colleague of his from a science department at his university.

According to Google Scholar, since completing his doctorate in Religious Studies at McMaster University in 2003, Wills has published ten research articles (excluding book reviews). One of his research articles was cited three times, and three of his research articles were cited one time each. That is six citations in total.

On the other hand, his colleague from the Physics program at Memorial University, Dr. Svetlana Barkanova, has published 23 research articles between 2003 and 2018, and those articles were cited 53 times. Clearly, in the same time, a physicist at Wills’ university has produced more research than he did (130% more research), and her research has had a greater impact than his (783% more impact). As I have argued in my (2017a), this is generally the case when research produced by scientific disciplines is compared to research produced by non-scientific disciplines (Table 1).

Table 1. H Index by subject area, 1999-2018 (Source: Scimago Journal & Country Rank)

H Index
Physics 927
Psychology 682
Philosophy 161
Literature 67

Reflecting on One’s Own Knowledge

In his first attack on Weak Scientism, Wills (2018a, 23) claims that one “can produce a potential infinity of knowledge simply by reflecting recursively on the fact of [one’s] own existence.” In response, I pointed out that Wills (2018a, 23) himself admits that this reflexive procedure applies to “ANY fact” (original capitalization), which means that it makes no difference in terms of the quantity of knowledge produced in scientific versus non-scientific disciplines.

As I have come to expect from him, Wills (2018b, 35) resorts to name-calling again, rather than giving good arguments, calling my response “sophism,” but he seems to miss the basic logical point, even though he admits again that extending one’s knowledge by reflexive self-reflection “can be done with any proposition at all” (Wills 2018b, 35). Of course, if “it can be done with any proposition at all” (Wills 2018b, 35; emphasis added), then it can be done with scientific propositions as well, for the set of all propositions includes scientific propositions.

To illustrate, suppose that a scientist knows that p and a non-scientist knows that q. Quantitatively, the amount of scientific and non-scientific knowledge is equal in this instance (1 = 1). Now the scientist reflects on her own knowledge that p and comes to know that she knows that p, i.e., she knows that Kp. Similarly, the non-scientist reflects on her knowledge that q and comes to know that she knows that q, i.e., she knows that Kq. Notice that, quantitatively, nothing has changed, i.e., the amount of scientific versus non-scientific knowledge is still equal: two items of scientific knowledge (p and Kp) and two items of non-scientific knowledge (q and Kq).

Wills might be tempted to retort that p may be an item of scientific knowledge but Kp is not because it is not knowledge that is produced by scientific procedures. However, if Wills were to retort in this way, then it would be another indication of sloppy scholarship on his part. In my original paper (Mizrahi 2017a, 356), and in my replies to Brown (Mizrahi 2017b, 12-14; Mizrahi 2018a, 14-15), I discuss at great length my characterization of disciplinary knowledge as knowledge produced by practitioners in the field. I will not repeat those arguments here.

Baseless Accusations of Racism and Colonialism

After raising questions about whether I am merely rationalizing my “privilege” (Wills 2018a, 19), Wills now says that his baseless accusations of racism and colonialism are “not personal” (Wills 2018b, 35). His concern, Wills (2018b, 35) claims, is “systemic racism” (original emphasis). As a white man, Wills has the chutzpah to explain (or white-mansplain, if you will) to me, an immigrant from the Middle East, racism and colonialism.

My people were the victims of ethnic cleansing and genocide, lived under British colonial rule, and are still a persecuted minority group. Since some of my ancestors died fighting the British mandate, I do not appreciate using the term ‘colonialism’ to describe academic disputes that are trifle in comparison to the atrocities brought about by racism and colonialism.

Perhaps Wills should have used (or meant to use) the term ‘imperialism’, since it is sometimes used to describe the expansion of a scientific theory into new domains (Dupré 1994). This is another sign of Wills’ lack of familiarity with the literature on scientism. Be that as it may, Wills continues to assert without argument that my “defense of weak-scientism is ideologically loaded,” that it implies “the exclusion of various others such as women or indigenous peoples from the socially sanctioned circle of knowers,” and that I make “hegemonic claims for science from which [I] stand to benefit” (Wills 2018b, 36).

In response, I must admit that I have no idea what sort of “ideologies” Weak Scientism is supposed to be loaded with, since Wills does not say what those are. Wills (2018b, 36) asserts without argument that “the position [I] take on scientism has social, political and monetary implications,” but he does not specify those implications. Nor does he show how social and political implications (whatever those are) are supposed to follow from the epistemic thesis of Weak Scientism (Mizrahi 2017a, 353). I am also not sure why Wills thinks that Weak Scientism implies “the exclusion of various others such as women or indigenous peoples from the socially sanctioned circle of knowers” (Wills 2018b, 36), since he provides no arguments for these assertions.

Of course, Weak Scientism entails that there is non-scientific knowledge (Mizrahi 2018b, 41). If there is non-scientific knowledge, then there are non-scientific knowers. In that case, on Weak Scientism, non-scientists are not excluded from “the circle of knowers.” In other words, on Weak Scientism, the circle of knowers includes non-scientists, which can be women and people of color, of course (recall Dr. Svetlana Barkanova). Contrary to what Wills seems to think, then, Weak Scientism cannot possibly entail “the exclusion of various others such as women or indigenous peoples from the socially sanctioned circle of knowers” (Wills 2018b, 36).

In fact, if it is “the exclusion of various others” that Wills (2018b, 36) is genuinely concerned about, then he is undoubtedly aware of the fact that it is precisely white men like him who are guilty of systematically excluding “various others,” such as women (Paxton et al. 2012) and people of color (Botts et al. 2014), from the academic discipline of philosophy (American Philosophical Association 2014). As anyone who is familiar with the academic discipline of philosophy knows, “philosophy faces a serious diversity problem” (Van Norden 2017b, 5). As Amy Ferrer (2012), Executive Director of the American Philosophical Association (APA), put it on Brian Leiter’s blog, Leiter Reports:

philosophy is one of the least diverse humanities fields, and indeed one of the least diverse fields in all of academia, in terms of gender, race, and ethnicity. Philosophy has a reputation for not only a lack of diversity but also an often hostile climate for women and minorities (emphasis added).

In light of the lack of diversity in academic philosophy, some have gone as far as arguing that contemporary philosophy is racist and xenophobic; otherwise, argues Bryan Van Norden (2017a), it is difficult to explain “the fact that the rich philosophical traditions of China, India, Africa, and the Indigenous peoples of the Americas are completely ignored by almost all philosophy departments in both Europe and the English-speaking world.”

In fact, Wills’ attacks on Weak Scientism illustrate how white men like him attempt to keep philosophy white and “foreigner-free” (Cherry and Schwitzgebel 2016). They do so by citing and discussing the so-called “greats,” which are almost exclusively Western men. Citations are rather scarce in Wills’ replies, but when he cites, he only cites “the greats,” like Aristotle and Augustine (see Schwitzgebel et al. 2018 on the “Insularity of Anglophone Philosophy”).

As for his claim that I “stand to benefit” (Wills 2018b, 36) from my defense of Weak Scientism, I have no idea what Wills is talking about. I had no idea that History and Philosophy of Science (HPS) and Science and Technology Studies (STS) “can often assert hegemony over other discourses” (Wills 2018b, 36). I bet this will come as a surprise to other HPS and STS scholars and researchers. They will probably be shocked to learn that they have that kind of power over other academic disciplines.

More importantly, even if it were true that I “stand to benefit” (Wills 2018b, 36) from my defense of Weak Scientism, nothing about the merit of my defense of Weak Scientism would follow from that. That is, to argue that Weak Scientism must be false because I stand to benefit from it being true is to argue fallaciously. In particular, it is an informal fallacy of the circumstantial ad hominem type known as “poisoning the well,” which “alleges that the person has a hidden agenda or something to gain and is therefore not an honest or objective arguer” (Walton and Krabbe 1995, 111).

It is as fallacious as arguing that climate change is not real because climate scientists stand to benefit from climate research or that MMR vaccines are not safe (e.g., cause autism) because medical researchers stand to benefit from such vaccines (Offit 2008, 213-214). These are the sort of fallacious arguments that are typically made by those who are ignorant of the relevant science or are arguing in bad faith.

In fact, the same sort of fallacious reasoning can be used to attack any scholar or researcher in any field of inquiry whatsoever, including Wills. For instance, just as my standing to benefit from defending Weak Scientism is supposed to be a reason to believe that Weak Scientism is false, or Paul Offit’s standing to gain from MMR vaccines is supposed to be a reason to believe that such vaccines are not safe, Wills’ standing to benefit from his attacks on Weak Scientism (e.g., by protecting his position as a Humanities professor) would be a reason to believe that his attacks on Weak Scientism are flawed.

Indeed, the administrators at Wills’ university would have a reason to dismiss his argument for a pay raise on the grounds that he stands to benefit from it (Van Vleet 2011, 16). Of course, such reasoning is fallacious no matter who is the target. Either MMR vaccines are safe and effective or they are not regardless of whether Offit stands to benefit from them. Climate change is real whether climate scientists stand to benefit from doing climate research. Likewise, Weak Scientism is true or false whether or not I stand to benefit from defending it.

Image by Maia Valenzuela via Flickr / Creative Commons

 

Revisiting the Joyce Scholar

Wills (2018b, 36) returns to his example of the Joyce scholar as an example of non-scientific knowledge “that come[s] from an academic context.” As I have already pointed out in my previous reply (Mizrahi 2018b, 41-42), it appears that Wills fails to grasp the difference between Strong Scientism and Weak Scientism. Only Strong Scientism rules out knowledge that is not scientific. On Weak Scientism, there is both scientific and non-scientific knowledge. Consequently, examples of non-scientific knowledge from academic disciplines other than scientific ones do not constitute evidence against Weak Scientism.

Relatedly, Wills claims to have demonstrated that I vacillate between Strong Scientism and Weak Scientism and cites page 22 of his previous attack (Wills 2018a, 22). Here is how Wills (2018a, 22) argues that I vacillate between Strong Scientism and Weak Scientism:

Perhaps it is the awareness of such difficulties that leads Mizhari [sic] to his stance of ‘Weak Scientism’. It is not a stance he himself entirely sticks to. Some of his statements imply the strong version of scientism as when he tells us the [sic] knowledge is “the scholarly work or research produced in scientific fields of study, such as the natural sciences, as opposed to non-scientific fields, such as the humanities” [Mizrahi 2018a, 22].

However, the full passage Wills cites as evidence of my vacillation between Strong Scientism and Weak Scientism is from the conclusion of my second reply to Brown (Mizrahi 2018a) and it reads as follows:

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.

Clearly, in this passage, I am talking about how ‘knowledge’ is understood in the scientism debate, specifically, that knowledge is the published research or scholarship produced by practitioners in academic disciplines (see also Mizrahi 2017a, 353). I am not saying that non-scientific disciplines do not produce knowledge. How anyone can interpret this passage as evidence of vacillation between Strong Scientism and Weak Scientism is truly beyond me. To me, this amounts to “contextomy” (McGlone 2005), and thus further evidence of arguing in bad faith on Wills’ part.

Wills also misunderstands, as in his previous attack on Weak Scientism, the epistemic properties of unity, coherence, simplicity, and testability, and their role in the context of hypothesis testing and theory choice. For he seems to think that “a masterful exposition of Portrait of the Artist as Young Man will show the unity, coherence and simplicity of the work’s design to the extent that these are artistically desired features” (Wills 2018b, 36). Here Wills is equivocating on the meaning of the terms ‘unity’, ‘coherence’, and ‘simplicity’.

There is a difference between the epistemic and the artistic senses of these terms. For example, when it comes to novels, such as A Portrait of the Artist as Young Man, ‘simplicity’ may refer to literary style and language. When it comes to explanations or theories, however, ‘simplicity’ refers to the number of entities posited or assumptions taken for granted (Mizrahi 2016). Clearly, those are two different senses of ‘simplicity’ and Wills is equivocating on the two. As far as Weak Scientism is concerned, it is the epistemic sense of these terms that is of interest to us. Perhaps Wills fails to realize that Weak Scientism is an epistemic thesis because he has not read my (2017a), where I sketch the arguments for this thesis, or at least has not read it carefully enough despite claiming to be a practitioner of “close reading” (Wills 2018b, 34).

When he says that the Joyce scholar “tests [what he says] against the text,” Wills (2018b, 37) reveals his misunderstanding of testability once again. On Wills’ description of the work done by the Joyce scholar, what the Joyce scholar is doing amounts to accommodation, not novel prediction. I have already discussed this point in my previous reply to Wills (Mizrahi 2018b, 47) and I referred him to a paper in which I explain the difference between accommodation and novel prediction (Mizrahi 2012). But it appears that Wills has no interest in reading the works I cite in my replies to his attacks. Perhaps a Stanford Encyclopedia of Philosophy entry on the difference between accommodation and prediction would be more accessible (Barnes 2018).

Wills finds it difficult to see how the work of the Joyce scholar can be improved by drawing on the methods of the sciences. As Wills (2018b, 37) writes, “What in this hermeneutic process would be improved by ‘scientific method’ as Mizrahi describes it? Where does the Joyce scholar need to draw testable consequences from a novel hypothesis and test it with an experiment?” (original emphasis)

Because he sees no way the work of the Joyce scholar can benefit from the application of scientific methodologies, Wills thinks it follows that I have no choice but to say that the work of the Joyce scholar does not count as knowledge. As Wills (2018b, 37) writes, “It seems to me that only option for Mizrahi here is to deny that the Joyce scholar knows anything (beyond the bare factual information) and this means, alas, that his position once again collapses into strong scientism.”

It should be clear, however, that this is a non sequitur. Even if it is true that scientific methodologies are of no use to the Joyce scholar, it does not follow that the work of the Joyce scholar does not count as knowledge. Again, Weak Scientism is the view that scientific knowledge is better than non-scientific knowledge. This means that scientists produce knowledge using scientific methods, whereas non-scientists produce knowledge using non-scientific methods, it’s just that scientists produce better knowledge using scientific methods that are superior to non-scientific methods in terms of the production of knowledge. Non-scientists can use scientific methods to produce knowledge in their fields of inquiry. But even if they do not use scientific methods in their work, on Weak Scientism, the research they produce still counts as knowledge.

Moreover, it is not the case that scientific methodologies are of no use to literary scholars. Apparently, Wills is unaware of the interdisciplinary field in which the methods of computer science and data science are applied to the study of history, literature, and philosophy known as the “Digital Humanities.” Becoming familiar with work in Digital Humanities will help Wills understand what it means to use scientific methods in a literary context. Since I have already discussed all of this in my original paper (Mizrahi 2017a) and in my replies to Brown (Mizrahi 2017b; 2018a), I take this as another reason to think that Wills has not read those papers (or at least has not read them carefully enough).

To me, this is a sign that he is not interested in engaging with Weak Scientism in good faith, especially since my (2017a) and my replies to Brown are themselves instances of the use of methods from data science in HPS, and since I have cited two additional examples of work I have done with Zoe Ashton that illustrates how philosophy can be improved by the introduction of scientific methods (Ashton and Mizrahi 2018a and 2018b). Again, it appears that Wills did not bother to read (let alone read closely) the works I cite in my replies to his attacks.

Toward the end of his discussion of the Joyce scholar, Wills (2018b, 37) says that using scientific methods “may mean better knowledge in many cases.” If he accepts that using scientific methods “may mean better knowledge in many cases” (Wills 2018b, 37), then Wills thereby accepts Weak Scientism as well. For to say that using scientific methods “may mean better knowledge in many cases” (Wills 2018b, 37) is to say that scientific knowledge is generally better than non-scientific knowledge.

Of course, there are instances of bad science, just as there are instances of bad scholarship in any academic discipline. Generally speaking, however, research done by scientists using the methods of science will likely be better (i.e., quantitatively better in terms of research output and research impact as well as qualitatively better in terms of explanatory, predictive, and instrumental success) than research done by non-scientists using non-scientific methods. That is Weak Scientism and, perhaps unwittingly, Wills seems to have accepted it by granting that using scientific methods “may mean better knowledge in many cases” (Wills 2018b, 37).

Inference to the Best Explanation

In my (2017a), as well as in my replies to Brown (Mizrahi 2017b; 2018a) and to Wills (Mizrahi 2018b), I have argued that Inference to the Best Explanation (IBE) is used in both scientific and non-scientific disciplines. As McCain and Poston (2017, 1) put it:

Explanatory reasoning is quite common. Not only are rigorous inferences to the best explanation (IBE) used pervasively in the sciences, explanatory reasoning is virtually ubiquitous in everyday life. It is not a stretch to say that we implement explanatory reasoning in a way that is “so routine and automatic that it easily goes unnoticed” [Douven 2017].

Once this point is acknowledged, it becomes clear that, when judged by the criteria of good explanations, such as unity, coherence, simplicity, and testability, scientific IBEs are generally better than non-scientific IBEs (Mizrahi 2017a, 360; Mizrahi 2017b, 19-20; Mizrahi 2018a, 17; Mizrahi 2018b, 46-47).

In response, Wills tells the story of his daughter who has attempted to reason abductively in class once. Wills (2018b, 38) begins by saying “Let me go back to my daughter,” even though it is the first time he mentions her in his (2018b), and then goes on to say that she once explained “how Scriabin created [the Prometheus] chord” to the satisfaction of her classmates.

But how is this supposed to be evidence against Weak Scientism? In my (2017a), I discuss how IBE is used in non-scientific disciplines and I even give an example from literature (Mizrahi 2017a, 361). Apparently, Wills is unaware of that, which I take to be another indication that he has not read the paper that defends the thesis he seeks to criticize. Again, to quote Wills (2018b, 38) himself, “All disciplines use abduction,” so to give an example of IBE from a non-scientific discipline does nothing at all to undermine Weak Scientism. According to Weak Scientism, all academic disciplines produce knowledge, and many of them do so by using IBE, it’s just that scientific IBEs are better than non-scientific IBEs.

Wills asserts without argument that, in non-scientific disciplines, there is no need to test explanations even when IBE is used to produce knowledge. As Wills (2018b, 38) writes, “All disciplines use abduction, true, but they do not all arrive at the ‘best explanation’ by the same procedures.” For Wills (2018b, 38), his daughter did not need to test her hypothesis about “how Scriabin created [the Prometheus] chord.” Wills does not tell us what the hypothesis in question actually is, so it is hard to tell whether it is testable or not. To claim that it doesn’t need to be tested, however, even when the argument for it is supposed to be an IBE, would be to misuse or abuse IBE rather than use it.

That is, if one were to reason to the best explanation without judging competing explanations by the criteria of unity, coherence, simplicity, testability, and the like, then one would not be warranted in concluding that one’s explanation is the best among those considered. That is just how IBE works (Psillos 2007). To say that an explanation is the best is to say that, among the competing explanations considered, it is the one that explains the most, leaves out the least, is consistent with background knowledge, is the least complicated, and yields independently testable predictions (Mizrahi 2017a, 360-362).

Wills (2018b, 39) seems to grant that “unity, simplicity and coherence” are good-making properties of explanations, but not testability. But why not testability? Why an explanation must be simple in order to be a good explanation, but not testable? Wills does not say. Again (Mizrahi 2018b, 47), I would urge Wills to consult logic and reasoning textbooks that discuss IBE. In those books, he will find that, in addition to unity, coherence, and simplicity, testability is one of the “characteristics that are necessary conditions for any explanation to qualify as being a reasonable empirical explanation” (Govier 2010, 300).

In other words, IBE is itself the procedure by which knowledge is produced. This procedure consists of “an inference from observations and a comparison between competing hypotheses to the conclusion that one of those hypotheses best explains the observations” (Mizrahi 2018c). For example (Sinnott-Armstrong and Fogelin 2015, 196):

  • Observation: Your lock is broken and your valuables are missing.
  • Explanation: The hypothesis that your house has been burglarized, combined with previously accepted facts and principles, provides a suitably strong explanation of observation 1.
  • Comparison: No other hypothesis provides an explanation nearly as good as that in 2.
  • Conclusion: Your house was burglarized.

As we can see, the procedure itself requires that we compare competing hypotheses. As I have mentioned already, “common standards for assessing explanations” (Sinnott-Armstrong and Fogelin 2015, 195) include unity, coherence, simplicity, and testability. This means that, if the hypothesis one favors as the best explanation for observation 1 cannot be tested, then one would not be justified in concluding that it is the best explanation, and hence probably true. That is simply how IBE works (Psillos 2007).

Contrary to what Wills (2018b, 39) seems to think, those who reason abductively without comparing competing explanations by the criteria of unity, coherence, simplicity, and testability are not using IBE, they are misusing or abusing it (Mizrahi 2017a, 360-361). To reason abductively without testing your competing explanations is as fallacious as reasoning inductively without making sure that your sample is representative of the target population (Govier 2010, 258-262).

Image by Specious Reasons via Flickr / Creative Commons

 

The Defense Rests

Fallacious reasoning, unfortunately, is what I have come to expect from Wills after reading and replying to his attacks on Weak Scientism. But this is forgivable, of course, given that we all fall prey to mistakes in reasoning on occasion. Even misspelling my last name several times (Wills 2018a, 18, 22, 24) is forgivable, so I accept Wills’ (2018b, 39) apology. What is unforgivable, however, is lazy scholarship and arguing in bad faith. As I have argued above, Wills is guilty of both because, despite claiming to be a practitioner of “close reading” (Wills 2018b, 34), Wills has not read the paper in which I defend the thesis he seeks to attack (Mizrahi 2017a), or any of the papers in my exchange with Brown (Mizrahi 2017b; 2018a), as evidenced by the fact that he does not cite them at all (not to mention citing and engaging with other works on scientism).

This explains why Wills completely misunderstands Weak Scientism and the arguments for the quantitative superiority (in terms of research output and research impact) as well as qualitative superiority (in terms of explanatory, predictive, and instrumental success) of scientific knowledge over non-scientific knowledge. For these reasons, this is my second and final response to Wills. I have neither the time nor the patience to engage with lazy scholarship that was produced in bad faith.

Contact details: mmizrahi@fit.edu

References

Ashton, Zoe and Moti Mizrahi. “Intuition Talk is Not Methodologically Cheap: Empirically Testing the ‘Received Wisdom’ About Armchair Philosophy.” Erkenntnis 83, no. 3 (2018a): 595-612.

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

American Philosophical Association. “Minorities in Philosophy.” Data and Information on the Field of Philosophy. Accessed on August 13, 2018. http://c.ymcdn.com/sites/www.apaonline.org/resource/resmgr/data_on_profession/minorities_in_philosophy.pdf.

Barnes, Eric Christian. “Prediction versus Accommodation.” In The Stanford Encyclopedia of Philosophy (Fall 2018 Edition), edited by E. N. Zalta. Accessed on August 14, 2018. https://plato.stanford.edu/archives/fall2018/entries/prediction-accommodation/.

Botts, Tina Fernandes, Liam Kofi Bright, Myisha Cherry, Guntur Mallarangeng, and Quayshawn Spencer. “What Is the State of Blacks in Philosophy?” Critical Philosophy of Race 2, no. 2 (2014): 224-242.

Cherry, Myisha and Eric Schwitzgebel. “Like the Oscars, #PhilosophySoWhite.” Los Angeles Times, March 04, 2016. Accessed on August 13, 2018. http://www.latimes.com/opinion/op-ed/la-oe-0306-schwitzgebel-cherry-philosophy-so-white-20160306-story.html.

Douven, Igor. “Abduction.” In The Stanford Encyclopedia of Philosophy, edited by E. N. Zalta (Summer 2017 Edition). Accessed on August 14, 2018. https://plato.stanford.edu/archives/sum2017/entries/abduction/.

Dupré, John. “Against Scientific Imperialism.” PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1994, no. 2 (1994): 374-381.

Ferrer, Amy. “What Can We Do about Diversity?” Leiter Reports: A Philosophy Blog, December 04, 2012. Accessed on August 13, 2018. http://leiterreports.typepad.com/blog/2012/12/what-can-we-do-about-diversity.html.

Govier, Trudy. A Practical Study of Argument. Seventh Edition. Belmont, CA: Wadsworth, 2010.

Graff, Gerald and Cathy Birkenstein. They Say/I Say: The Moves that Matter in Academic Writing. Fourth Edition. New York: W. W. Norton & Co., 2018.

Haack, Susan. Defending Science–within Reason: Between Scientism and Cynicism. New York: Prometheus Books, 2007.

Hawking, Stephen and Leonard Mlodinow. The Grand Design. New York: Bantam Books, 2010.

Kidd, I. J. “How Should Feyerabend Have Defended Astrology? A Reply to Pigliucci.” Social Epistemology Review and Reply Collective 5, no. 6 (2016): 11-17.

McCain, Kevin and Ted Poston. “Best Explanations: An Introduction.” In Best Explanations: New Essays on Inference to the Best Explanation, edited by K. McCain and T. Poston, 1-6. Oxford: Oxford University Press, 2017.

McGlone, Matthew S. “Contextomy: The Art of Quoting out of Context.” Media, Culture & Society 27, no. 4 (2005): 511-522.

Mizrahi, Moti. “Why the Ultimate Argument for Scientific Realism Ultimately Fails.” Studies in the History and Philosophy of Science 43, no. 1 (2012): 132-138.

Mizrahi, Moti. “Why Simpler Arguments are Better.” Argumentation 30, no. 3 (2016): 247-261.

Mizrahi, Moti. “What’s So Bad about Scientism?” Social Epistemology 31, no. 4 (2017a): 351-367.

Mizrahi, Moti. “In Defense of Weak Scientism: A Reply to Brown.” Social Epistemology Review and Reply Collective 6, no. 11 (2017b): 9-22.

Mizrahi, Moti. “More in Defense of Weak Scientism: Another Reply to Brown.” Social

Epistemology Review and Reply Collective 7, no. 4 (2018a): 7-25.

Mizrahi, Moti. “Weak Scientism Defended Once More.” Social Epistemology Review and Reply Collective 7, no. 6 (2018b): 41-50.

Mizrahi, Moti. “The ‘Positive Argument’ for Constructive Empiricism and Inference to the Best Explanation. Journal for General Philosophy of Science (2018c): https://doi.org/10.1007/s10838-018-9414-3.

Offit, Paul A. Autism’s False Prophets: Bad Science, Risky Medicine, and the Search for a Cure. New York: Columbia University Press, 2008.

Paxton, Molly, Carrie Figdor, and Valerie Tiberius. “Quantifying the Gender Gap: An Empirical Study of the Underrepresentation of Women in Philosophy.” Hypatia 27, no. 4 (2012): 949-957.

Peels, Rik. “The Empirical Case Against Introspection.” Philosophical Studies 17, no. 9 (2016): 2461-2485.

Peels, Rik. “A Conceptual Map of Scientism.” In Scientism: Prospects and Problems, edited by J. De Ridder, R. Peels, and R. Van Woudenberg, 28-56. New York: Oxford University Press, 2018.

Psillos, Stathis. “The Fine Structure of Inference to the Best Explanation. Philosophy and Phenomenological Research 74, no. 2 (2007): 441-448.

Rosenberg, Alexander. The Atheist’s Guide to Reality: Enjoying Life Without Illusions. New York: W. W. Norton, 2011.

Scimago Journal & Country Rank. “Subject Bubble Chart.” SJR: Scimago Journal & Country Rank. Accessed on August 13, 2018. http://www.scimagojr.com/mapgen.php?maptype=bc&country=US&y=citd.

Schwitzgebel, Eric, Linus Ta-Lun Huang, Andrew Higgins, Ivan Gonzalez-Cabrera. “The Insularity of Anglophone Philosophy: Quantitative Analyses.” Philosophical Papers 47, no. 1 (2018): 21-48.

Sinnott-Armstrong, Walter and Robert Fogelin. Understanding Arguments. Ninth Edition. Stamford, CT: Cengage Learning, 2015.

Stenmark, Mikael. “What is Scientism?” Religious Studies 33, no. 1 (1997): 15-32.

Van Norden, Bryan. “Western Philosophy is Racist.” Aeon, October 31, 2017a. Accessed on August 12, 2018. https://aeon.co/essays/why-the-western-philosophical-canon-is-xenophobic-and-racist.

Van Norden, Bryan. Taking Back Philosophy: A Multicultural Manifesto. New York: Columbia University Press, 2017b.

Van Vleet, Jacob E. Informal Logical Fallacies: A Brief Guide. Lahman, MD: University Press of America, 2011.

Walton, Douglas N. and Erik C. W. Krabbe. Commitment in Dialogue: Basic Concepts of Interpersonal Reasoning. Albany: State University of New York Press, 1995.

Weinberg, Steven. Dreams of a Final Theory: The Scientist’s Search for the Ultimate Laws of Nature. New York: Random House, 1994.

Wills, Bernard. “Why Mizrahi Needs to Replace Weak Scientism With an Even Weaker Scientism.” Social Epistemology Review and Reply Collective 7, no. 5 (2018a): 18-24.

Wills, Bernard. “On the Limits of any Scientism.” Social Epistemology Review and Reply Collective 7, no. 7 (2018b): 34-39.

[1] I would like to thank Adam Riggio for inviting me to respond to Bernard Wills’ second attack on Weak Scientism.

Author Information: Saana Jukola and Henrik Roeland Visser, Bielefeld University, sjukola@uni-bielefeld.de and rvisser@uni-bielefeld.de.

Jukola, Saana; and Henrik Roland Visser. “On ‘Prediction Markets for Science,’ A Reply to Thicke” Social Epistemology Review and Reply Collective 6, no. 11 (2017): 1-5.

The pdf of the article includes specific page numbers. Shortlink: https://wp.me/p1Bfg0-3Q9

Please refer to:

Image by The Bees, via Flickr

 

In his paper, Michael Thicke critically evaluates the potential of using prediction markets to answer scientific questions. In prediction markets, people trade contracts that pay out if a certain prediction comes true or not. If such a market functions efficiently and thus incorporates the information of all market participants, the resulting market price provides a valuable indication of the likelihood that the prediction comes true.

Prediction markets have a variety of potential applications in science; they could provide a reliable measure of how large the consensus on a controversial finding truly is, or tell us how likely a research project is to deliver the promised results if it is granted the required funding. Prediction markets could thus serve the same function as peer review or consensus measures.

Thicke identifies two potential obstacles for the use of prediction markets in science. Namely, the risk of inaccurate results and of potentially harmful unintended consequences to the organization and incentive structure of science. We largely agree on the worry about inaccuracy. In this comment we will therefore only discuss the second objection; it is unclear to us what really follows from the risk of harmful unintended consequences. Furthermore, we consider another worry one might have about the use of prediction markets in science, which Thicke does not discuss: peer review is not only a quality control measure to uphold scientific standards, but also serves a deliberative function, both within science and to legitimize the use of scientific knowledge in politics.

Reasoning about imperfect methods

Prediction markets work best for questions for which a clearly identifiable answer is produced in the not too distant future. Scientific research on the other hand often produces very unexpected results on an uncertain time scale. As a result, there is no objective way of choosing when and how to evaluate predictions on scientific research. Thicke identifies two ways in which this can create harmful unintended effects on the organization of science.

Firstly, projects that have clear short-term answers may erroneously be regarded as epistemically superior to basic research which might have better long-term potential. Secondly, science prediction markets create a financial incentive to steer resources towards research with easily identifiable short-term consequences, even if more basic research would have a better epistemic pay-off in the long-run.

Based on their low expected accuracy and the potential of harmful effects on the organization of science, Thicke concludes that science prediction markets might be a worse ‘cure’ than the ‘disease’ of bias in peer review and consensus measures. We are skeptical of this conclusion for the same reasons as offered by Robin Hanson. While the worry about the promise of science prediction markets is justified, it is unclear how this makes them worse than the traditional alternatives.

Nevertheless, Thicke’s conclusion points in the right direction: instead of looking for a more perfect method, which may not become available in the foreseeable future, we need to judge which of the imperfect methods is more palatable to us. Doing that would, however, require a more sophisticated evaluation of the different strengths and weakness of the different available methods and how to trade those off, which goes beyond the scope of Thicke’s paper.

Deliberation in Science

An alternative worry, which Thicke does not elaborate on, is the fact that peer review is not only expected to accurately determine the quality of submissions and conclude what scientific work deserves to be funded or published, but it is also valued for its deliberative nature, which allows it to provide reasons to those affected by the decisions made in research funding or the use of scientific knowledge in politics. Given that prediction markets function through market forces rather than deliberative procedure, and produce probabilistic predictions rather than qualitative explanations, this might be (another) aspect on which the traditional alternative of peer review outperforms science prediction markets.

Within science, peer review serves two different purposes. First, it functions as a gatekeeping mechanism for deciding which projects deserve to be carried out or disseminated – an aim of peer review is to make sure that good work is being funded or published and undeserving projects are rejected. Second, peer review is often taken to embody the critical mechanism that is central to the scientific method. By pointing out defects and weaknesses in manuscripts or proposals, and by suggesting new ways of approaching the phenomena of interest, peer reviewers are expected to help authors improve the quality of their work. At least in an ideal case, authors know why their manuscripts were rejected or accepted after receiving peer review reports and can take the feedback into consideration in their future work.

In this sense, peer review represents an intersubjective mechanism that guards against the biases and blind spots that individual researchers may have. Criticism of evidence, methods and reasoning is essential to science, and necessary for arriving at trustworthy results.[1] Such critical interaction thus ensures that a wide variety of perspectives in represented in science, which is both epistemically and socially valuable. If prediction markets were to replace peer review, could they serve this second, critical, function? It seems that the answer is No. Prediction markets do not provide reasons in the way that peer review does, and if the only information that is available are probabilistic predictions, something essential to science is lost.

To illustrate this point in a more intuitive way: imagine that instead of writing this comment in which we review Thicke’s paper, there is a prediction market on which we, Thicke and other authors would invest in bets regarding the likelihood of science prediction markets being an adequate replacement of the traditional method of peer review. From the resulting price signal we would infer whether predictions markets are indeed an adequate replacement or not. Would that allow for the same kind of interaction in which we now engage with Thicke and others by writing this comment? At least intuitively, it seems to us that the answer is No.

Deliberation About Science in Politics

Such a lack of reasons that justify why certain views have been accepted or rejected is not only a problem for researchers who strive towards getting their work published, but could also be detrimental to public trust in science. When scientists give answers to questions that are politically or socially sensitive, or when controversial science-based recommendations are given, it is important to explain the underlying reasons to ensure that those affected can – at least try to – understand them.

Only if people are offered reasons for decisions that affect them can they effectively contest such decisions. This is why many political theorists regard the ability of citizens to demand an explanation, and the corresponding duty of decision-makers to be responsive to such demands, as a necessary element of legitimate collective decisions.[2] Philosophers of science like Philip Kitcher[3] rely on very similar arguments to explain the importance of deliberative norms in justifying scientific conclusions and the use of scientific knowledge in politics.

Science prediction markets do not provide substantive reasons for their outcome. They only provide a procedural argument, which guarantees the quality of their outcome when certain conditions are fulfilled, such as the presence of a well-functioning market. Of course, one of those conditions is also that at least some of the market participants possess and rely on correct information to make their investment decisions, but that information is hidden in the price signal. This is especially problematic with respect to the kind of high-impact research that Thicke focuses on, i.e. climate change. There, the ability to justify why a certain theory or prediction is accepted as reliable, is at least as important for the public discourse as it is to have precise and accurate quantitative estimates.

Besides the legitimacy argument, there is another reason why quantitative predictions alone do not suffice. Policy-oriented sciences like climate science or economics are also expected to judge the effect and effectiveness of policy interventions. But in complex systems like the climate or the economy, there are many different plausible mechanisms simultaneously at play, which could justify competing policy interventions. Given the long-lasting controversies surrounding such policy-oriented sciences, different political camps have established preferences for particular theoretical interpretations that justify their desired policy interventions.

If scientists are to have any chance of resolving such controversies, they must therefore not only produce accurate predictions, but also communicate which of the possible underlying mechanisms they think best explains the predicted phenomena. It seems prediction markets alone could not do this. It might be useful to think of this particular problem as the ‘underdetermination of policy intervention by quantitative prediction’.

Science prediction markets as replacement or addition?

The severity of the potential obstacles that Thicke and we identify depends on whether science prediction markets would replace traditional methods such as peer review, or would rather serve as addition or even complement to traditional methods. Thicke provides examples of both: in the case of peer review for publication or funding decisions, prediction markets might replace traditional methods. But in the case of resolving controversies, for instance concerning climate change, it aggregates and evaluates already existing pieces of knowledge and peer review. In such a case the information that underlies the trading behavior on the prediction market would still be available and could be revisited if people distrust the reliability of the prediction market’s result.

We could also imagine that there are cases in which science prediction markets are used to select the right answer or at least narrow down the range of alternatives, after which a qualitative report is produced which provides a justification of the chosen answer(s). Perhaps it is possible to infer from trading behavior which investors possess the most reliable information, a possibility explored by Hanson. Contrary to Hanson, we are skeptical of the viability of this strategy. Firstly, the problem of the underdetermination of theory by data suggests that different competing justifications might be compatible with the observation trading behavior. Secondly, such justifications would be post-hoc rationalizations, which sound plausible but might lack power to discriminate among alternative predictions.

Conclusion

All in all, we are sympathetic to Michael Thicke’s critical analysis of the potential of prediction markets in science and share his skepticism. However, we point out another issue that speaks against prediction markets and in favor of peer review: Giving and receiving reasons for why a certain view should be accepted or rejected. Given that the strengths and weaknesses of these methods fall on different dimensions (prediction markets may fare better in accuracy, while in an ideal case peer review can help the involved parties understand the grounds why a position should be approved), it is important to reflect on what the appropriate aims in particular scientific and policy context are before making a decision on what method should be used to evaluate research.

References

Hanson, Robin. “Compare Institutions To Institutions, Not To Perfection,” Overcoming Bias (blog). August 5, 2017. Retrieved from: http://www.overcomingbias.com/2017/08/compare-institutions-to-institutions-not-to-perfection.html

Hanson, Robin. “Markets That Explain, Via Markets To Pick A Best,” Overcoming Bias (blog), October 14, 2017 http://www.overcomingbias.com/2017/10/markets-that-explain-via-markets-to-pick-a-best.html

[1] See, e.g., Karl Popper, The Open Society and Its Enemies. Vol 2. (Routledge, 1966) or Helen Longino, Science as Social Knowledge. Values and Objectivity in Scientific Inquiry (Princeton University Press, 1990).

[2] See Jürgen Habermas, A Theory of Communicative Action, Vols1 and 2. (Polity Press, 1984 & 1989) & Philip Pettit, “Deliberative democracy and the discursive dilemma.” Philosophical Issues, vol. 11, pp. 268-299, 2001.

[3] Philip Kitcher, Science, Truth, and Democracy (Oxford University Press, 2001) & Philip Kitcher, Science in a democratic society (Prometheus Books, 2011).

Author Information: Adam Riggio, New Democratic Party of Canada, adamriggio@gmail.com

Riggio, Adam. “Subverting Reality: We Are Not ‘Post-Truth,’ But in a Battle for Public Trust.” Social Epistemology Review and Reply Collective 6, no. 3 (2017): 66-73.

The PDF of the article gives specific page numbers. Shortlink: http://wp.me/p1Bfg0-3vZ

Image credit: Cornerhouse, via flickr

Note: Several of the links in this article are to websites featuring alt-right news and commentary. This exists both as a warning for offensive content, as well as a sign of precisely how offensive the content we are dealing with actually is.

An important purpose of philosophical writing for public service is to prevent important ideas from slipping into empty buzzwords. You can give a superficial answer to the meaning of living in a “post-truth” world or discourse, but the most useful way to engage this question is to make it a starting point for a larger investigation into the major political and philosophical currents of our time. Post-truth was one of the many ideas American letters haemorrhaged in the maelstrom of Trumpism’s wake, the one seemingly most relevant to the concerns of social epistemology.

It is not enough simply to say that the American government’s communications have become propagandistic, or that the Trump Administration justifies its policies with lies. This is true, but trivial. We can learn much more from philosophical analysis. In public discourse, the stability of what information, facts, and principles are generally understood to be true has been eroding. General agreement on which sources of information are genuinely reliable in their truthfulness and trustworthiness has destabilized and diverged. This essay explores one philosophical hypothesis as to how that happened: through a sustained popular movement of subversion – subversion of consensus values, of reliability norms about information sources, and of who can legitimately claim the virtues of subversion itself. The drive to speak truth to power is today co-opted to punch down at the relatively powerless. This essay is a philosophical examination of how that happens.

Subversion as a Value and an Act

A central virtue in contemporary democracy is subversion. To be a subversive is to progress society against conservative, oppressive forces. It is to commit acts that transgress popular morality while providing a simultaneous critique of it. As new communities form in a society, or as previously oppressed communities push for equal status and rights, subversion calls attention to the inadequacy of currently mainstream morality to the new demands of this social development. Subversive acts can be publications, artistic works, protests, or even the slow process of conducting your own life publicly in a manner that transgresses mainstream social norms and preconceptions about what it is right to do.

Values of subversiveness are, therefore, politically progressive in their essence. The goal of subversion values is to destabilize an oppressive culture and its institutions of authority, in the name of greater inclusiveness and freedom. This is clear when we consider the popular paradigm case of subversive values: punk rock and punk culture. In the original punk and new wave scenes of 1970s New York and Britain, we can see subversion values in action. Punk’s embrace of BDSM and drag aesthetics subvert the niceties of respectable fashion. British punk’s embrace of reggae music promotes solidarity with people oppressed by racist and colonialist norms. Most obviously, punk enshrined a morality of musical composition through simplicity, jamming, and enthusiasm. All these acts and styles subverted popular values that suppressed all but vanilla hetero sexualities, marginalized immigrant groups and ethnic minorities, denigrated the poor, and esteemed an erudite musical aesthetic.

American nationalist conservatism today has adopted the form and rhetoric of subversion values, if not the content. The decadent, oppressive mainstream the modern alt-right opposes and subverts is a general consensus of liberal values – equal rights regardless of race or gender, an imperative to build a fair economy for all citizens, end police oppressive of marginalized communities, and so on. Alt-right activists push for the return of segregation and even ethnic cleansing of Hispanics from the United States. Curtis Yarvin, the intellectual centre of America’s alt-right, openly calls for an end to democratic institutions and their replacement with government by a neo-cameralist state structure that replaces citizenship with shareholds and reduces all public administration and foreign policy to the aim of profit. Yet because these ideas are a radical front opposing a broadly liberal democratic mainstream culture, alt-right activists declare themselves punk. They claim subversiveness in their appropriation of punk fashion in apparel and hair, and their gleeful offensiveness to liberal sensibilities with their embrace of public bigotry.

Subversion Logics: The Vicious Paradox and Trolling

Alt-right discourse and aesthetic claim to have inherited subversion values because their activists oppose a liberal democratic mainstream whose presumptions include the existence of universal human rights and the encouragement of cultural, ethnic, and gender diversity throughout society. If subversion values are defined entirely according to the act of subverting any mainstream, then this is true. But this would decouple subversion values from democratic political thought. At question in this essay – and at this moment in human democratic civilization – is whether such decoupling is truly possible.

If subversion as an act is decoupled from democratic values, then we can understand it as the act of forcing an opponent into a vicious paradox. One counters an opponent by interpreting their position as implying a hypocritical or self-contradictory logic. The most general such paradox is Karl Popper’s paradox of tolerance. Alt-right discourse frames their most bigoted communications as subversive acts of total free speech – an absolutism of freedom that decries as censorship any critique or opposition to what they say. This is true whether they write on a comment thread, through an anonymous Twitter feed, or on a stage at UC Berkeley. We are left with the apparent paradox that a democratic society must, if we are to respect our democratic values without being hypocrites ourselves, accept the rights of the most vile bigots to spread racism, misogyny, anti-trans and heterosexist ideas, Holocaust denial, and even the public release of their opponents’ private information. As Popper himself wrote, the only response to such an argument is to deny its validity – a democratic society cannot survive if it allows its citizens to argue and advocate for the end of democracy. The actual hypocritical stance is free speech absolutism: permitting assaults on democratic society and values in the name of democracy itself.

Trolling, the chief rhetorical weapon of the alt-right, is another method of subversion, turning an opponent’s actions against herself. To troll is to communicate with statements so dripping in irony that an opponent’s own opposition can be turned against itself. In a simple sense, this is the subversion of insults into badges of honour and vice versa. Witness how alt-right trolls refer to themselves as shitlords, or denounce ‘social justice warriors’ as true fascists. But trolling also includes a more complex rhetorical strategy. For example, one posts a violent, sexist, or racist meme – say, Barack Obama as a witch doctor giving Brianna Wu a lethal injection. If you criticize the post, they respond that they were merely trying to bait you, and mock you as a fragile fool who takes people seriously when they are not – a snowflake. You are now ashamed, having fallen into their trap of baiting earnest liberals into believing in the sincerity of their racism, so you encourage people to dismiss such posts as ‘mere trolling.’ This allows for a massive proliferation of racist, misogynist, anti-democratic ideas under the cover of being ‘mere trolling’ or just ‘for the lulz.’

No matter the content of the ideology that informs a subversive act, any subversive rhetoric challenges truth. Straightforwardly, subversion challenges what a preponderant majority of a society takes to be true. It is an attack on common sense, on a society’s truisms, on that which is taken for granted. In such a subversive social movement, the agents of subversion attack common sense truisms because of their conviction that the popular truisms are, in fact, false, and their own perspective is true, or at least acknowledges more profound and important truths than what they attack. As we tell ourselves the stories of our democratic history, the content of those subversions were actually true. Now that the loudest voices in American politics claiming to be virtuous subversives support nationalist, racist, anti-democratic ideologies, we must confront the possibility that those who speak truth to power have a much more complicated relationship with facts than we often believe.

Fake News as Simply Lies

Fake news is the central signpost of what is popularly called the ‘post-truth’ era, but it quickly became a catch-all term that refers to too many disparate phenomena to be useful. When preparing for this series of articles, we at the Reply Collective discussed the influence of post-modern thinkers on contemporary politics, particularly regarding climate change denialism. But I don’t consider contemporary fake news as having roots in these philosophies. The tradition is regarded in popular culture (and definitely in self-identified analytic philosophy communities) as destabilizing the possibility of truth, knowledge, and even factuality.

This conception is mistaken, as any attentive reading of Jacques Derrida, Michel Foucault, Gilles Deleuze, Jean-Francois Lyotard, or Jean Beaudrillard will reveal that they were concerned – at least on the question of knowledge and truth – with demonstrating that there were many more ways to understand how we justify our knowledge and the nature of facticity than any simple propositional definition in a Tarskian tradition can include. There are more ways to understand knowledge and truth than seeing whether and how a given state of affairs grounds the truth and truth-value of a description. A recent article by Steve Fuller at the Institute of Art and Ideas considers many concepts of truth throughout the history of philosophy more complicated than the popular idea of simple correspondence. So when we ask whether Trumpism has pushed us into a post-truth era, we must ask which concept of truth had become obsolete. Understanding what fake news is and can be, is one productive probe of this question.

So what are the major conceptions of ‘fake news’ that exist in Western media today? I ask this question with the knowledge that, given the rapid pace of political developments in the Trump era, my answers will probably be obsolete, or at least incomplete, by publication. The proliferation of meanings that I now describe happened in popular Western discourse in a mere two months from Election Day to Inauguration Day. My account of these conceptual shifts in popular discourse shows how these shifts of meaning have acquired such speed.

Fake news, as a political phenomenon, exists as one facet of a broad global political culture where the destabilization of what gets to count as a fact and how or why a proposition may be considered factual has become fully mainstream. As Bruno Latour has said, the destabilization of facticity’s foundation is rooted in the politics and epistemology of climate change denialism, the root of wider denialism of any real value for scientific knowledge. The centrepiece of petroleum industry public relations and global government lobbying efforts, climate change denialism was designed to undercut the legitimacy of international efforts to shift global industry away from petroleum reliance. Climate change denial conveniently aligns with the nationalist goals of Trump’s administration, since a denialist agenda requires attacking American loyalty to international emissions reduction treaties and United Nations environmental efforts. Denialism undercuts the legitimacy of scientific evidence for climate change by countering the efficacy of its practical epistemic truth-making function. It is denial and opposition all the way down. Ontologically, the truth-making functions of actual states of affairs on climatological statements remain as fine as they always were. What’s disappeared is the popular belief in the validity of those truth-makers.

So the function of ‘fake news’ as an accusation is to sever the truth-making powers of the targeted information source for as many people who hear the accusation as possible. The accusation is an attempt to deny and destroy a channel’s credibility as a source of true information. To achieve this, the accusation itself requires its own credibility for listeners. The term ‘fake news’ first applied to the flood of stories and memes flowing from a variety of dubious websites, consisting of uncorroborated and outright fabricated reports. The articles and images originated on websites based largely in Russia and Macedonia, then disseminated on Facebook pages like Occupy Democrats, Eagle Rising, and Freedom Daily, which make money using clickthrough-generating headlines and links. Much of the extreme white nationalist content of these pages came, in addition to the content mills of eastern Europe, from radical think tanks and lobby groups like the National Policy Institute. These feeds are a very literal definition of fake news: content written in the form of actual journalism so that their statements appear credible, but communicating blatant lies and falsehoods.

The feeds and pages disseminating these nonsensical stories were successful because the infrastructure of Facebook as a medium incentivizes comforting falsehoods over inconvenient truths. Its News Feed algorithm is largely a similarity-sorting process, pointing a user to sources that resemble what has been engaged before. Pages and websites that depend on by-clickthrough advertising revenue will therefore cater to already-existing user opinions to boost such engagement. A challenging idea that unsettles a user’s presumptions about the world will receive fewer clickthroughs because people tend to prefer hearing what they already agree with. The continuing aggregation of similarity after similarity reinforces your perspective and makes changing your mind even harder than it usually is.

Trolling Truth Itself

Donald Trump is an epically oversignified cultural figure. But in my case for the moment, I want to approach him as the most successful troll in contemporary culture. In his 11 January 2017 press conference, Trump angrily accused CNN and Buzzfeed of themselves being “fake news.” This proposition seems transparent, at first, as a clear act of trolling, a President’s subversive action against critical media outlets. Here, the insulting meaning of the term is retained, but its reference has shifted to cover the Trump-critical media organizations that first brought the term to ubiquity shortly after the 8 November 2016 election. The intention and meaning of the term has been turned against those who coined it.

In this context, the nature of the ‘post-truth’ era of politics appears simple. We are faced with two duelling conceptions of American politics and global social purpose. One is the Trump Administration, with its propositions about the danger of Islamist terror and the size of this year’s live Inauguration audience. The other is the usual collection of news outlets referred to as the mainstream media. Each gives a presentation of what is happening regarding a variety of topics, neither of which is compatible, both of which may be accurate to greater or lesser degrees in each instance. The simple issue is that the Trump Administration pushes easily falsified transparent propaganda such as the lie about an Islamist-led mass murder in Bowling Green, Kentucky. This simple issue becomes an intractable problem because significantly large spaces in the contemporary media economy constitutes a hardening of popular viewpoints into bubbles of self-reinforcing extremism. Thanks to Facebook’s sorting algorithms, there will likely always be a large group of Trumpists who will consider all his administration’s blatant lies to be truth.

This does not appear to be a problem for philosophy, but for public relations. We can solve this problem of the intractable audience for propaganda by finding or creating new paths to reach people in severely comforting information bubbles. There is a philosophical problem, but it is far more profound than even this practically difficult issue of outreach. The possibility conditions for the character of human society itself is the fundamental battlefield in the Trumpist era.

The accusation “You are fake news!” of Trump’s January press conference delivered a tactical subversion, rendering the original use of the term impossible. The moral aspects of this act of subversion appeared a few weeks later, in a 7 February interview Trump Administration communications official Sebastian Gorka did with Michael Medved. Gorka’s words first appear to be a straightforward instance of authoritarian delegitimizing of opposition, as he equates ‘fake news’ with opposition to President Trump. But Gorka goes beyond this simple gesture to contribute to a re-valuation of the values of subversion and opposition in our cultural discourse. He accuses Trump-critical news organizations of such a deep bias and hatred of President Trump and Trumpism that they themselves have failed to understand and perceive the world correctly. The mainstream media have become untrustworthy, says Gorka, not merely because many of their leaders and workers oppose President Trump, but because those people no longer understand the world as it is. That conclusion is, as Breitbart’s messaging would tell us, the reason to trust the mainstream media no longer is their genuine ignorance. And because it was a genuine mistake about the facts of the world, that accusation of ignorance and untrustworthiness is actually legitimate.

Real Failures of Knowledge

Donald Trump, as well as the political movements that backed his Presidential campaign and the anti-EU side of the Brexit referendum, knew something about the wider culture that many mainstream analysts and journalists did not: they knew that their victory was possible. This is not a matter of ideology, but a fact about the world. It is not a matter of interpretive understanding or political ideology like the symbolic meanings of a text, object, or gesture, but a matter of empirical knowledge. It is not a straightforward fact like the surface area of my apartment building’s front lawn or the number of Boeing aircraft owned by KLM. Discovering such a fact as the possibility conditions and likelihood of an election or referendum victory involving thousands of workers, billions of dollars of infrastructure and communications, and millions of people deliberating over their vote or refusal to vote is a massively complicated process. But it is still an empirical process and can be achieved to varying levels of success and failure. In the two most radical reversals of the West’s (neo)liberal democratic political programs in decades, the press as an institution failed to understand what is and is not possible.

Not only that, these organizations know they have failed, and know that their failure harms their reputation as sources of trustworthy knowledge about the world. Their knowledge of their real inadequacy can be seen in their steps to repair their knowledge production processes. These efforts are not a submission to the propagandistic demands of the Trump Presidency, but an attempt to rebuild real research capacities after the internet era’s disastrous collapse of the traditional newspaper industry. Through most of the 20th century, the news media ecology of the United States consisted of a hierarchy of local, regional, and inter/national newspapers. Community papers reported on local matters, these reports were among the sources for content at regional papers, and those regional papers in turn provided source material for America’s internationally-known newsrooms in the country’s major urban centres. This information ecology was the primary route not only for content, but for general knowledge of cultural developments beyond those few urban centres.

With the 21st century, it became customary to read local and national news online for free, causing sales and advertising revenue for those smaller newspapers to collapse. The ensuing decades saw most entry-level journalism work become casual and precarious, cutting off entry to the profession from those who did not have the inherited wealth to subsidize their first money-losing working years. So most poor and middle class people were cut off from work in journalism, removing their perspectives and positionality from the field’s knowledge production. The dominant newspaper culture that centred all content production in and around a local newsroom persisted into the internet era, forcing journalists to focus their home base in major cities. So investigation outside major cities rarely took place beyond parachute journalism, visits by reporters with little to no cultural familiarity with the region. This is a real failure of empirical knowledge gathering processes. Facing this failure, major metropolitan news organizations like the New York Times and Mic have begun building a network of regional bureaus throughout the now-neglected regions of America, where local independent journalists are hired as contractual workers to bring their lived experiences to national audiences.

America’s Democratic Party suffered a similar failure of knowledge, having been certain that the Trump campaign could never have breached the midwestern regions – Michigan, Wisconsin, Pennsylvania – that for decades have been strongholds of their support in Presidential elections. I leave aside the critical issue of voter suppression in these states to concentrate on a more epistemic aspect of Trump’s victory. This was the campaign’s unprecedented ability to craft messages with nuanced detail. Cambridge Analytica, the data analysis firm that worked for both Trump and leave.eu, provided the power to understand and target voter outreach with almost individual specificity. This firm derives incredibly complex and nuanced data sets from the Facebook behaviour of hundreds of millions of people, and is the most advanced microtargeting analytics company operating today. They were able to craft messages intricately tailored to individual viewers and deliver them through Facebook advertising. So the Trump campaign has a legitimate claim to have won based on superior knowledge of the details of the electorate and how best to reach and influence them.

Battles Over the Right to Truth

With this essay, I have attempted an investigation that is a blend of philosophy and journalism, an examination of epistemological aspects of dangerous and important contemporary political and social phenomena and trends. After such a mediation, I feel confident in proposing the following conclusions.

1) Trumpist propaganda justifies itself with an exclusive and correct claim to reliability as a source of knowledge: that the Trump campaign was the only major information source covering the American election that was always certain of the possibility that they could win. That all other media institutions at some point did not understand or accept the truth of Trump’s victory being possible makes them less reliable than the Trump team and Trump personally.

2) The denial of a claim’s legitimacy as truth, and of an institution’s fidelity to informing people of truths, has become such a powerful weapon of political rhetoric that it has ended all cross-partisan agreement on what sources of information about the wider world are reliable.

3) Because of the second conclusion, journalism has become an unreliable set of knowledge production techniques. The most reliable source of knowledge about that election was the analysis of mass data mining Facebook profiles, the ground of all Trump’s public outreach communications. Donald Trump became President of the United States with the most powerful quantitative sociology research program in human history.

4) This is Trumpism’s most powerful claim to the mantle of the true subversives of society, the virtuous rebel overthrowing a corrupt mainstream. Trumpism’s victory, which no one but Trumpists themselves thought possible, won the greatest achievement of any troll. Trumpism has argued its opponent into submission, humiliated them for the fact of having lost, then turned out to be right anyway.

The statistical analysis and mass data mining of Cambridge Analytica made Trump’s knowledge superior to that of the entire journalistic profession. So the best contribution that social epistemology as a field can make to understanding our moment is bringing all its cognitive and conceptual resources to an intense analysis of statistical knowledge production itself. We must understand its strengths and weaknesses – what statistical knowledge production emphasizes in the world and what escapes its ability to comprehend. Social epistemologists must ask themselves and each other: What does qualitative knowledge discover and allow us to do, that quantitative knowledge cannot? How can the qualitative form of knowledge uncover a truth of the same profundity and power to popularly shock an entire population as Trump’s election itself?