Abstract
In this paper we investigate ignorance in relation to our capacity to justify our beliefs. To achieve this aim we specifically address scientific misconceptions, i.e. beliefs that are considered to be false in light of accepted scientific knowledge. The hypothesis we put forward is that misconceptions are not isolated false beliefs, but rather form part of a system of inferences—an explanation—which does not match current scientific theory. We further argue that, because misconceptions are embedded in a system, they cannot be rectified simply by replacing false beliefs with true ones. To address our misconceptions, we must rather act on the system of beliefs that supports them. In the first step of our analysis, we distinguish between misconceptions that are easy to dispel because they represent simple errors that occur against the background of a correct explanatory apparatus and misconceptions that are, on the contrary, very difficult to dispel because they are the product of pseudo explanations. We show that, in the latter case, misconceptions constitute an integral part of an incorrect explanation and the reasons that support such misconceptions are deeply misleading. In the second step, we discuss various approaches that have been adopted to address the problem of misconceptions. Challenging the notion that directly addressing and criticizing specific misconceptions is an effective approach, we propose that critical thinking is the most fruitful means to deal with misconceptions. We define the core competences and knowledge relevant for the practice of critical thinking and discuss how they help us avoid misconceptions that arise from accepting beliefs that form part of a mistaken explanation.
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Notes
In the literature, the approach to ignorance that considers the possession of true justified beliefs as a necessary condition for having knowledge and, by contrast, the absence of one of these conditions as sufficient to establish ignorance is called the Standard View of Ignorance (Le Morvan 2011, 2012, 2013; Le Morvan and Peels 2016). Recently, epistemological research has developed a new approach called the New View of Ignorance in which the role assigned to justification and to the capacity to explicitly offer reasons in support of our beliefs has been weakened and in which a person is considered to be ignorant primarily in the case in which s/he holds false beliefs. (On the so-called New View see Peels 2010, 2011, 2012; Le Morvan and Peels 2016). On the one hand, the New View denies—contrary to what we suggest—that justification plays a central function in determining whether we are or are not ignorant about some topic. However, on the other hand, it takes a step towards our approach: it not only places stronger emphasis on the cognizing powers of the subject than the "standard view" but also considers the possibility of distinguishing between various degrees of ignorance. In fact, by discussing the impossibility of providing a complete justification for a belief, it makes it possible to consider ignorance as a continuum rather than in a categorical manner, distinguishing between various degrees in which a person can be said to be ignorant as for the reasons s/he has to hold his/her beliefs (for a conception of ignorance as an epistemic status that comes in degrees and ignorance as the incapacity to adequately and completely answer questions concerning our beliefs cf. Nottelmann 2016). Of course, we cannot expect that people are able to provide a complete justification for their beliefs and even the issue of what an acceptable justification should look like is controversial. However, especially when considering beliefs concerning (relatively simple) phenomena that have a widely accepted , we can take a practical stance and assume that scientific theories which are commonly accepted by the scientific community at a given time provide us a measure for which beliefs should be considered to be true or false at that time and what a justification of them would ideally look like. On this basis, we can also assess (or approximate) the distance between scientific knowledge and individual beliefs as well as the distance between the way scientific theories justify specific pieces of knowledge and the way in which people justify their beliefs about the same phenomena.
In fact, it is not impossible for an individual to hold a belief that is inconsistent with other beliefs s/he holds, and yet it would be irrational for him/her to do so. As Davidson argues: “Strictly speaking, then, the irrationality consists not in any particular belief but in inconsistency within a set of beliefs.” (Davidson 1985/2004, p. 192) According to a widely shared view in psychology developed by Leon Festinger (1957), inconsistencies cannot be psychologically accepted by the subject who will make every possible effort to rationalize and thus resolve them. In the same vein, Davidson (1982/2004, 1986/2004) points out how the inconsistencies we are sometimes victim of can be explained only by postulating a kind of compartmentalization of the mind. However, generally people seek internal congruency among their beliefs and coherence plays a pivotal role in the way we interpret human thinking (on this cf. also Thagard 2000).
In epistemology, justification has been viewed in various ways. Justification might be conceived as being linear: in this case an individual belief is proven to be true by a set of other beliefs and those other beliefs are proven to be true by another set and so on, until we reach some beliefs that are based on experience and are therefore considered—if not indisputable—at least well-grounded: as BonJour (1985, p. 26) formulates it, “sufficient by itself to satisfy the adequate justification condition for knowledge”. Alternatively, justification can be viewed holistically as an interferential network of beliefs that are interconnected within a system and providing mutual support but are supported by experience only altogether as a whole. In this case, what justifies a belief is primarily its coherence with the system (this form of holism is commonly discussed in relation to Quine 1951; for a discussion of different justification models cf. Elgin 2005; van Cleve 2005). While strong forms of holism would consider a belief to be justified only if it is coherent with the whole system of beliefs that includes it, more moderate forms of holism support the view that justification depends on some chunks of this system. Typically, they also embrace some weak form of foundationalism in which some beliefs are considered more basic than others because they are closer to experience, i.e. observational, and thus serve as a foundation for others. (On moderate vs. strong holism from the point of view of Quine’s philosophy and on Quine’s later arguments in favor of a moderate form of holism cf. De Rosa and Lepore 2004). To numerous epistemologists, the idea that we can always apply linear models of justification that lead us to some fundamental beliefs appeared to be implausible in the light of the complexity of our system of knowledge. For this reason, they argued for a holist picture of knowledge in which beliefs are connected to each other within an inferential network and mutually sustain each other (cf. van Quine and Ullian 1970; Bonjour 1985; Harman 1993; Thagard 2007). At the same time, the view that all the beliefs of a complex beliefs system are also involved in the justification of each appeared to be too extreme as well as problematic from an epistemological point of view. In fact, this implies that, when even one single belief in the system is changed, all others must be modified accordingly. This excessive interdependence of beliefs makes the system as a whole too instable (cf. Fodor and Lepore 1992, chap. 2). For this reason, many epistemologists have considered a moderate form of holism as the most plausible option. And yet, independently of which view of the structure of knowledge we favor and thus of which is the specific model of justification we prefer, at least some principles of inferential justification can be considered to be shared by all these models. Indeed, independently of whether we think that our beliefs are structured “like a building that rests upon a foundation” or "like a web where the strength of any given area depends on the strength of the surrounding areas" (Steup 2018), we always presuppose that beliefs form a congruent structure and that their relationships are somehow explanatory. We will say something more on this last factor below, but—since we will consider scientific theory as a benchmark to assess misconceptions—we will mainly just assume that the inferential relationships presupposed by scientific theories are explanatory, i.e. that they are form part of an appropriate explanation.
Even though this remains implicit in his paper, Reichenbach’s analysis is inspired by a specific model of explanations, i.e. by the Hempel and Oppenheim’s (1948) Deductive-Nomological Model. However, his description is general enough to also be compatible with other positions on what a consists of. The Deductive-Nomological Model of explanation does not explicitly rely on the notion of causation. But many advocates of this model argue that it still captures the causal component of explanations since “all causal claims imply the existence of some corresponding regularity (a “law”) linking cause to effect” (Woodward 2017, cf. this article also for a brief discussion of the main modes of explanation that are currently under debate).
Reichenbach suggests that—when people do not have the means to develop an actual explanation—they try to account for phenomena by analogy with something else they understand better: since human experience is something everybody has firsthand knowledge of, people usually resort to analogies with human experience. Reichenbach intuition on this is confirmed by a number of contemporary, empirical studies showing that people with a poor understanding of the physical word have a strong tendency to anthropomorphize. They tend to explain physical phenomena using the same principles they would use to explain the behavior of human agents and thus they project human-like characteristics onto non-human things (Epley et al. 2007; Willard and Norenzayan 2013; Lindeman and Svedholm-Häkkinen 2016). And yet, the opposite also occurs, even if more rarely: people who exhibit a poor knowledge of the human mind and of social dynamics, but have a better comprehension of mechanisms and physical systems tend to interpret human phenomena according to non-human but better known mechanical principles (Lindeman and Svedholm-Häkkinen 2016).
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Dellantonio, S., Pastore, L. Ignorance, misconceptions and critical thinking. Synthese 198, 7473–7501 (2021). https://doi.org/10.1007/s11229-019-02529-7
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DOI: https://doi.org/10.1007/s11229-019-02529-7