Role of individual differences for development and manifestation of wisdom, approaches to wisdom development and training, & cultural, subcultural, and social-contextual differences

Grossmann, Igor, Nic M. Weststrate, Monika Ardelt, Justin P. Brienza, Mengxi Dong, Michel Ferrari, Marc A. Fournier, et al. 2020. “The Science of Wisdom in a Polarized World: Knowns and Unknowns.” PsyArXiv. May 26. doi:10.1080/1047840X.2020.1750917

Abstract: Interest in wisdom in the cognitive sciences, psychology, and education has been paralleled by conceptual confusions about its nature and assessment. To clarify these issues and promote consensus in the field, wisdom researchers met in Toronto in July of 2019, resolving disputes through discussion. Guided by a survey of scientists who study wisdom-related constructs, we established a common wisdom model, observing that empirical approaches to wisdom converge on the morally-grounded application of metacognition to reasoning and problem-solving. After outlining the function of relevant metacognitive and moral processes, we critically evaluate existing empirical approaches to measurement and offer recommendations for best practices. In the subsequent sections, we use the common wisdom model to selectively review evidence about the role of individual differences for development and manifestation of wisdom, approaches to wisdom development and training, as well as cultural, subcultural, and social-contextual differences. We conclude by discussing wisdom’s conceptual overlap with a host of other constructs and outline unresolved conceptual and methodological challenges.

Character strengths as wisdom in disguise?

The last several decades have not only seen the emergence of the psychometric base to the wisdom construct, but also a proliferation of potentially related constructs. Psychological scientists so far have not considered the conceptual and psychometric relationship of such constructs to wisdom. Below we provide two examples. This list is not exhaustive and questions below may be applied broadly.

Intellectual humility. Several constructs have recently emerged under the umbrella rubric of character strengths and virtues (e.g., Bleidorn & Denissen, 2015; Fleeson, Furr, Jayawickreme, Meindl, & Helzer, 2014; Peterson & Seligman, 2004) , which include a range of characteristics such as courage, gratitude (e.g., DeSteno, Li, Dickens, & Lerner, 2014; McCullough, Kilpatrick, Emmons, & Larson, 2001) , compassion (Goetz, Keltner, & Simon-Thomas, 2010) and forgiveness (McCullough, 2000) . Some of these constructs have their roots in the virtue theory and Christian theology, and have become popular within the positive psychology movement (Seligman & Csikszentmihalyi, 2014) . One character strength that has received a great deal of attention concerns (intellectual) humility (e.g., Leary et al., 2017; Stellar et al., 2018; Van Tongeren, Davis, Hook, & Witvliet, 2019) , defined as the “ability to accurately acknowledge one’s limitations and abilities and (b) an interpersonal stance that is other-oriented rather than self-focused” (Van Tongeren et al., 2019) . Intellectual humility was the focus of Socrates' definition of wisdom and the overlap of this conceptual definition with the common wisdom model is striking, raising the question about the distinctiveness of humility from wisdom, and the discriminant validity of the extant measures. Indeed, several of the most common measures aiming to capture the common wisdom model (Table 1) include intellectual humility as a central facet. Moreover, features of humility and wisdom are listed among the 28 measurable character strengths (Peterson & Seligman, 2004) . Undoubtedly, intellectual humility is an important concept in a time of ever increasing political polarization (Haidt & Lukianoff, 2018; Leary et al., 2017) . The question that remains open concerns its uniqueness beyond the PMC components it shares with the common wisdom model advanced in the present target article. If it is just a facet of the same broader construct, researchers studying humility and wisdom may benefit from insights from respective fields, including concerns with measurement levels and usability of the self-report scales (see Section 3). After all, most humility instruments so far appear to involve abstract self-ratings, even though the process they arguably aim to capture concern is meta-cognitive and thereby is not easily amendable to abstract self-beliefs (Brienza et al., 2018; Grossmann, Dorfman, et al., 2020) . Abstract self-beliefs may be self-deceiving or used for purposes of impression management (Dunning, Heath, & Suls, 2004; Kihlstrom, Eich, Sandbrand, & Tobias, 2000; T. D. Wilson & Bar-Anan, 2008) , raising questions whether a person claiming that they are “much more humble than you would understand” accurately expresses their humility.

Open-mindedness. A related characteristic that has experienced a resurgence in scientific interest concerns open-mindedness. The construct itself is not new and can be traced to theories by Carl Rogers and others (e.g., Rogers, 1954) . Indeed, the initial intent of the openness factor of the OCEAN model of personality has included open-mindedness (for review, John, Naumann, & Soto, 2008 , esp. Table 4.2). However, whereas openness/open-mindedness in personality research has been conceptually defined as a description of “the breadth, depth, originality, and complexity of an individual’s mental and experiential life” (John et al., 2008) , there appears to be no unified definition of open-mindedness neither as a character strength nor as a thinking disposition. Some scholars define and proceed to measure it as intellectual flexibility and openness to diverse viewpoints in the process of making a decision (Fujita, Gollwitzer, & Oettingen, 2007; Price, Ottati, Wilson, & Kim, 2015) . Others define it almost identically to the definition of humility above, as “an intellectual quality displayed by someone who recognizes that her belief could be wrong, so her mind is subject to change” (Spiegel, 2012) . And yet others define open-minded thinking as “the disposition to weigh new evidence against a favored belief heavily (or lightly), the disposition to spend a great deal of time (or very little) on a problem before giving up, or the disposition to weigh heavily the opinions of others in forming one's own” (Baron, 1985 , p. 15; also see Stanovich & West, 1997). The conceptual confusion concerning open-mindedness is particularly evident in the puzzling observations that open-minded thinking appears to be positively related to political polarization about climate change (Kahan & Corbin, 2016) : If the definition of open-mindedness involves openness to diverse viewpoints and a potential of one being wrong, one ought to expect less polarization among more open-minded individuals! Similar to the concept of humility, this conceptual confusion raises questions about the meaning of the term, as well as the overlap with the definition of wisdom as a morally-grounded PMC. Researchers on open-mindedness may benefit from the present discussion of the common wisdom model, which may provide a roadmap for conceptual and methodological clarification of the open-mindedness construct, as well.

Overall, bodies of research on character strength and thinking dispositions have not sufficiently clarified the relationship to psychological characteristics of wisdom. Is wisdom one of many virtues linked to creativity, open-mindedness, perspective, and innovation, and distinct from humility, prudence, or justice (Peterson & Seligman, 2004) ? Both the common wisdom model advanced here and the relevant psychometric evidence are inconsistent with this perspective: The common wisdom model involves psychological characteristics of humility, prudence, as well as moral aspirations concerning justice and fairness. An alternative possibility advanced in Aristotelian and Thomistic virtue ethics is that wisdom (or prudence) represents a cardinal meta-virtue allowing one to discern which actions to pursue in concrete circumstances one may be experiencing (e.g., Darnell et al., 2019; Schwartz & Sharpe, 2006) . In relationship to thinking dispositions or character strengths, wisdom may be represented as a tool allowing one to figure out which of the character traits are more relevant in a given situation. This perspective is consistent with the common wisdom framework advanced here, with PMC oriented towards discerning the fit between one’s dispositions, one’s goals, and the features of a given situation. However, this “cardinal virtue” perspective requires measurement of the fit between one’s tendencies and the situational demands across multiple diagnostic situations, to estimate whether PMC indeed allows one to flexibly switch between different behaviors to optimally fit the context of a new situation. No psychometric instruments for the assessment of character strengths (e.g., Fleeson, Furr, Jayawickreme, Meindl, & Helzer, 2014) , thinking dispositions (e.g., Baron, 2019; Perkins, Jay, & Tishman, 1993; Stanovich & West, 2002) or wisdom (Staudinger & Glück, 2011) have so far even attempted to assess relevant characteristics within such “strategy-situation fit” framework.

Toward a psychological and cognitive science of wisdom

Beyond individual differences in character strengths and thinking dispositions, the common wisdom model as morally-grounded PMC also has implications for research on consciousness and artificial intelligence. We review possible connections and a range of unanswered questions below.

Consciousness. Within the body of research on consciousness, some researchers have suggested three different levels of awareness (e.g., Pinard, 1992; Schooler, 2002), including unconscious processes, basic conscious processes, and meta-conscious processes. At the implicit or enacted level of consciousness, experience is embedded in the actions one is experiencing. At the explicit level of consciousness, the person engages in conscious processing of the phenomena. At the third, meta-conscious level, the person deliberately and consciously takes charge of their cognitive functioning (Damasio, 1999; Pinard, 1992; Proust, 2013; Winkielman & Schooler, 2011) -- i.e., one becomes aware of the content of one’s conscious processes in ways that become increasingly transparent. The concept of meta-consciousness shares a great deal in common with the meta-cognitive components central to the empirical conceptualizations of wisdom (see Figure 1). Both require a perspectival appreciation of one’s conscious experience (e.g., experience of the inadequacy of one’s explanations of a given concept). Moreover, theoretical and empirical work on meta-consciousness suggests that the processes triggering meta-consciousness (Winkielman & Schooler, 2011) may be relevant for boosting wisdom as well. At the same time, the lack of moral grounding for the concept of meta-consciousness, compared to its centrality to the common wisdom model, raises the questions about the limits of the conceptual overlap. Is meta-consciousness a necessary, but not sufficient aspect of wisdom? If meta-consciousness is necessary for wisdom, can wisdom ever become habitual or automatic? Are the individuals prone to mind-wandering more or less likely to think wisely? Answers to these questions can help better understand the concept of wisdom from a cognitive science perspective, including the role of implicit, automatic, and physiological processes.

Artificial intelligence. Artificial intelligence (AI) research typically aims to develop “rational,” intelligent agents, a quality attributed to devices that adaptively react to the environment and take actions that maximize their chances of successfully achieving their goals (Russell & Norvig, 2016) . Notably, AI is often attributed to those qualities that machine devices have not yet mastered – an observation often described as the Tesler’s Theorem (Hofstadter, 1980 , p. 601) or the AI effect (McCorduck, 2004) . Given the steady AI advances in the domains of speech comprehension, language translations, and human-superior performance on strategic games such as chess or Go, a question arises: Will AI at some point be able to acquire wisdom? The development of “wise” AI systems is of special relevance in the time of ethical debates concerning the use of AI and machine-learning approaches to human-machine interactions, autonomous cars, political advertising, and criminal court decisions. For some time, AI researchers have recognized the hierarchy of Data, Information, Knowledge, and Wisdom (DIKW), in which data represent measurements or symbols, information is the application of data to answer questions, knowledge depends on the context of question and answer, and wisdom depends on values. Indeed, there is a growing recognition that values need to be incorporated into the development of AI (Conn, 2017) . On the surface, advances in AI-based knowledge representation, expert systems, and planning suggest that some aspects of human wisdom may be approximated via the AI. At the same time, the ideal of a goal-oriented, rational agent central to the AI research (Russell & Norvig, 2016) can be idiosyncratic to the common characteristics of a wise person: Under many circumstances, a wise person may choose a socially conscious, reasonable option, rather than preference-maximizing rational option (Rawls, 1971; Toulmin, 2001) . This characterization of a wise person is not idiosyncratic, as it is shared among laypeople across a range of contemporary societies (Grossmann, Eibach, et al., 2020) . Whether AI researchers can go beyond the maxim of goal-oriented optimization and to simulate psychological characteristics of wisdom in the context of ill-defined problems remains an open question. How will AI be able to integrate the influx of multi-model streams of information with moral aspirations as suggested by Asimov’s zeroth law or robotics (1986) ? Without doubt, “wise” AI requires discerning where, when, and to what degree to apply different rules for processing information, but it also requires optimization towards resolution of certain trade-offs (e.g., trade-offs between general and context-specific strategies). Perhaps a first step in testing the viability of a “wise” AI will be contingent on the development of systems capable to effectively simulate PMC common to psychological wisdom in the context of complex, social issues.