Erroneous thinking on climate change

This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details. Author(s): Title: Year: Version: Copyright: Rights: Rights url: Please cite the original version: CC BY 4.0 https://creativecommons.org/licenses/by/4.0/ Erroneous thinking on climate change © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group Published version Myllylä, Mari; Saariluoma, Pertti Myllylä, M., & Saariluoma, P. (2024). Erroneous thinking on climate change. Journal of Environmental Planning and Management, Early online. https://doi.org/10.1080/09640568.2024.2389158 2024 Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=cjep20 Journal of Environmental Planning and Management ISSN: (Print) (Online) Journal homepage: www.tandfonline.com/journals/cjep20 Erroneous thinking on climate change Mari Myllylä & Pertti Saariluoma To cite this article: Mari Myllylä & Pertti Saariluoma (30 Aug 2024): Erroneous thinking on climate change, Journal of Environmental Planning and Management, DOI: 10.1080/09640568.2024.2389158 To link to this article: https://doi.org/10.1080/09640568.2024.2389158 © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. Published online: 30 Aug 2024. Submit your article to this journal View related articles View Crossmark data Erroneous thinking on climate change Mari Myllyl€ aand Pertti Saariluoma Faculty of Information Technology, University of Jyv€ askyl€ a, Jyv€ askyl€ a, Finland (Received 5 December 2023; final version received 1 August 2024) The ultimate source of the ongoing human-induced climate change must be found within the thinking that guides actions. This human aspect goes outside the laws of natural science. Human thinking as a cause of anthropogenic or industrial climate change is still an under-researched topic. Here, we focus on how humans think about climate change. We use a content-based analysis of the mind to analyze comments in a Finnish online forum, Suomi24. Our immediate findings are that people have errors in reviewing knowledge and constructing information in their mental representations. Discussions are colored by illusions, false claims, incorrect interpretations, mistakes, and opinions to deny facts. Understanding erroneous thinking is crucial, as it helps to identify ways to correct risky thinking and to understand why people do what they do. Ultimately, erroneous thinking is the root cause of the modern climate crisis. Keywords: climate change thinking; erroneous thinking; mental content; contentbased analysis of mind 1. Introduction The ongoing human-induced climate change is a conceptually and theoretically challenging multidisciplinary problem and finding effective tools to meet its consequences is vital. The present climate change did not exist before the birth of industrial society. Its speed has also increased with the development of that society and especially due to the use of fossil fuels (IPCC (Intergovernmental Panel on Climate Change) 2023a, 2023b). Consequently, the ultimate reason for the climate crisis must be searched for in human individual and institutional actions. The explanation for actions is in human information processing and especially in thinking. Human deeds are consequences of their thinking. Although they are not always able to do what they think, everything they have done, they have thought. Despite this, little attention has been paid by researchers to human thinking on climate, which is the root cause of climate problems. Science searches for causes and reasons because knowledge of them enables researchers to look for solutions that help to mitigate the negative effects of the phenomenon in question. Knowing that the carburetor broke because water turned into ice and expanded made it possible to solve the problem by using glycol to change the freezing temperature (Hempel and Oppenheim 1948). Finding the reason for the broken carburetor made it possible to eliminate the harm. Corresponding author. Email: [email protected] ß2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons. org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. Journal of Environmental Planning and Management, 2024 https://doi.org/10.1080/09640568.2024.2389158 The above is a classic example of scientific explanation and its functions in design thinking. Its logic is clear, which may call attention away from one of its highly interesting aspects, which is the relationship between human action and mind and a natural phenomenon. Hempel and Oppenheim (1948) did not pay attention to the human aspect of their example, although it was obvious (Saariluoma, Ca~ nas, and Leikas 2016). People looked for an explanation, and people discovered it as well as the means to eliminate the harm. Harm, of course, is also a human phenomenon. If animal minds are not counted, harm or finding some issues harmful have had hardly any relevance. In the example given above, it seems to make sense not only to think of it as a carburetor problem but also as a human research issue. Traditionally, human research and natural science have been separate ways of rational thinking. Snow (1959) spoke of two cultures. Brentano ([1924] 1955) and Dilthey (1970), for example, adopted the idea of Geist from Kant ([1781] 1976) and other German idealists and developed Geistenwissenschaften or human research on very different grounds from natural science. Positivism pursued the unity of science and, at the same time, hermeneutics and phenomenology sought to establish new grounds for human research (Heidegger [1926] 1992; Husserl [1913] 2004; Radnitsky 1968;Stegm € uller 1969). The explanations of human actions differ from natural scientific explanations (Saariluoma, Ca~ nas, and Leikas 2016; Von Wright 1971). Natural phenomena are causal, which means that the explanatory ground is something that happened before the phenomenon to be explained. For example, the climate becomes warmer after the increase in fossil emissions. However, explaining human actions is different. Nature follows deterministic laws but, as in the analysis presented, human actions organize a specific combination of the laws of nature. However, the action also has its human side, which is essential to analyzing the event as a whole. If a person throws a stone at the head of another person, as in the case of David and Goliath in the biblical story, the issue has two sides: naturalistic and human. The trajectory of the stone follows the laws of nature, but David’s thinking happens in his mind and follows the laws of human mental processes. Thus, the analysis of events having a hard scientific core must often be joined with human research grounded on analysis of what happened in reality outside of the laws of nature. People are intentional (Brentano [1924] 1955; Von Wright 1971). Their actions are pursued toward some definite goal. They construct a representation of the situation in their mind, set a goal, and pursue that goal. It is quite possible that the way to the goal is open when the goal has been set, and therefore, no causal link can explain what people do. The explanation is to be found in some future situation (Von Wright 1971). It is also human to err. One reason is the selectivity of human thinking. People need not search for all the alternative action paths, but they can concentrate on the relevant ones (Newell and Simon 1972; Saariluoma 1995; Saariluoma, Ca~ nas, and Leikas 2016). The selection process enables people to live in an infinitely complex world, since they can represent it in a rational manner. They can represent the information that makes sense when thinking and guiding their actions. Selective information processing is a necessary precondition for rational information content, but it is at the same time a source of human error. The things people see as essential are not necessarily the ones that are essential. It is also common for people to misinterpret the information they acquire and, consequently, they construct biased mental representations of situations. For thousands of years people saw how masts became visible before their ships on the horizon, but they did not find a correct 2M. Myllyl€ a and P. Saariluoma interpretation for this perceived information (Hanson 1958). Thus, both paying attention to irrelevant states of affairs and misinterpreting the facts can lead to serious errors or erroneous thinking (de Groot 1965; Evans 2013; Kahneman 2011; Newell and Simon 1972; Pohl 2017; Tversky and Kahneman 1974; Van Eemeren and Grootendorst 2004; Wason 1968). Thinking is often organized around thought models, which are information schemas around which people structure the construction of the information content of their mental representations (Chase and Simon 1973; Myllyl€ a and Saariluoma 2022; Saariluoma 1995). The mind integrates situation-specific information, which is partly perceivable but often has non-perceivable content elements (Myllyl€ a and Saariluoma 2022; Saariluoma 1995). It is not always evident that people are thinking correctly, which is a cause for concern. In mental representations, it is possible to have incorrect elements. Such elements have been termed as cognitive illusions (Pohl 2017), cognitive biases (Kahneman 2011), or fallacies (Van Eemeren and Grootendorst 2004). Fallacies refer to illusory argumentation, biases to systematically disfocused thoughts, and, finally, cognitive illusions to systematic thought errors. These conceptual classes are not necessarily sharply differentiable but can refer to similar phenomena in discourse. 1.1. Human thinking and mental content Thinking guides human actions. It also enables people to find new lines of action and to find new ways to achieve their action goals. Therefore, understanding thinking is key to explaining why people plan and act in particular ways (Ho, Saxe, and Cushman 2022; Saariluoma, Ca~ nas, and Leikas 2016). Especially informative is the analysis of the information content of mental representations or, in brief, mental content (Allport 1980; Fodor 1992; Myllyl€ a and Saariluoma 2022; Newell and Simon 1972). People do not just think, they think of something specific and the specific is expressed in mental content. If the properties of relevant mental content are used to explain what people do, the approach can be called content-based mental research, content-based psychology, or content-based cognitive science (Myllyl€ a and Saariluoma 2022; Saariluoma 1995). The core concept of content-based analysis of human thinking is mental representation. People create in their minds descriptions of their ongoing actions, goals, and physical and social environments. These descriptions can be called mental representations of the situation (Allport 1980; Fodor 1992; Newell and Simon 1972). Apperception is the process in which situationand action-relevant pieces of information, e.g. mental models, are combined into information contents of active mental representations guiding human action (Johnson-Laird 2008; Kant [1781] 1976; Myllyl€ a and Saariluoma 2022; Saariluoma 1995,2001). It is good to notice here, that our focus is not in the capacity required by mental models (Johnson-Laird and Byrne 1991), but in their information or mental content. Thinking is thus a process that constructs and modifies the information content in mental representations. At the beginning of a thought process, one cannot know how to achieve the goal of an action, but in the course of the modification of current representation, one can find a solution (K€ ohler [1917] 1957; Newell and Simon 1972). Lifelong experiences and some basic biological systems have made it possible for people to have thought models in apperception utilized when encoding active mental Journal of Environmental Planning and Management 3 representations. Inbuilt and information content-wise specialized neural tracts, such as the ones specialized in encoding specific colors (Zeki 1993) or object locations, comprise the lowest information levels in mental models (Lindsay and Norman [1972] 2013). Biologically embedded instinctual programs give outlines for action tendencies (Eibel-Eibesfeldt 1989). However, experiences and learning give concrete information content to the thought models in human minds. Within cognitive psychology, various representational concepts have been developed, including schemas, mental or thought models (Johnson-Laird 1983,2008), plans (Miller et al.1960; Schanck and Abelson 1977), mental maps (Tobler 1976), concepts, and associative or neural networks (Kohonen 1977). In the way we conceptualize mental representations, the term mental representation is reserved for information in the mind that describes the representation of an ongoing action and relevant related information. The other terms from mental models and schemas to associative networks we see as long-term memory information. The line between active and stored information is not clear, as many actions can take not only days or weeks but years. Thus, actions are not only active but also stored in memory over a period of time. Also, as Ericsson and Kintsch (1995) showed, active representations have parts in working memory as well as in long-term memory. However, from our point of view, what is essential is the information content of representations. Content-based analysis of thinking can be applied to investigating various types of practical actions, since understanding the content of thoughts can help to explain why people behave in certain ways. A good example is content-based analysis of climate thinking. Climate change is undoubtedly one of the foremost problems of mankind (World Economic Forum 2022). The phenomenon has its geophysical and chemical roots, but it is caused by human thinking, and the risks and harms it causes should be eliminated by human thinking (see e.g. Hulkkonen 2023; Jamieson 2014). At the end of the day, ordinary people decide how they think about climate change. If thinking in this matter is not operating correctly and reliably, it is a source of social risk. Therefore, the analysis of the mental content of climate change thinking becomes relevant. 2. Methods Today, social media is important on a practical level when people form their opinions. Internet and social media online forums can also be an alternative source of information for some people (Harju 2018; Seuri et al.2021; Zwaan 2022). Qualitative methods such as observations, interviews, discourse, and social media analyses, or ethnographic analyses can offer information about how people think when they think about climate change and its effects on living (Denzin and Lincoln 1994). 2.1. Participants and procedure To investigate climate change thinking, we analyzed data from a popular Finnish online social networking website called Suomi24 (Vaahensalo 2018), where the content of discussions presented at the paragraph level is stored in the Suomi24 Sentences Corpus 2018–2020 open data repository (City Digital Group 2021). It does not contain any personal data and it is publicly available in the Kielipankki [Language bank], Korp service. According to the Finnish National Board on Research Integrity TENK 4M. Myllyl€ a and P. Saariluoma (Finnish National Board on Research Integrity) (2019) guidelines, research that is based on registry such as Kielipankki material does not require an ethical review statement from the ethics committee. The Corpus is restricted with CC-BY-NC license which makes it available for academic, non-commercial use. Active users of the Suomi24 forum have been described as middle-aged men, who live in the city alone or with their partners, and a third are retired (Harju 2018). Suomi24 has over 11 million threads (City Digital Group 2022) and at the end of the last decade it was estimated to have over 2 million monthly users (Reinikainen 2019). However, according to Statistics Finland (2020), in 2020 Suomi24 was followed by a modest 3% of the total population. We searched content with a keyword “ilmastonmuutos”(climate change) in discussions written only in the year 2020. This resulted in 3,816 messages being retrieved. Data were saved in Microsoft Word TM . 2.2. Materials and methods We carried out a qualitative content-based analysis (Krippendorf 2019; Myllyl€ a, Ca~ nas Delgado, and Saariluoma 2023; Myllyl€ a and Saariluoma 2022) of the data following the principles of the heterophenomenological approach (Dennett 2017). Thus, empirical third-person perspectives about mental contents are directly based on the content of the first-person perspective in protocols (Ericsson and Simon 1993). The analysis proceeded in two iterations. First, we read through all the messages to analyze what types of contents were present and what observations we can make out of it. Our immediate observation was that people have errors in reviewing knowledge and constructing information in their mental representations. Instead, they rely on illusions, misinformation, and denial. Misinformation can be defined as misleading or false information, such as erroneous opinions which are created and spread, regardless of whether deceit was intentional or not (Saariluoma and Maksimainen 2012). We focused on this topic. We then classified the related contents under different themes. Our other findings arising from the same corpus material, which focus on denialism and conspiracy thinking, have been discussed in more detail elsewhere (Myllyl€ a, Ca~ nas Delgado, and Saariluoma 2023). This time we wanted to abstract how people’s thinking is faulty from the point of view of information criticism. 3. Results We categorized content about erroneous thinking and thought models regarding reviewing knowledge and information criticism in six themes: (1) errors in criterion of knowledge, (2) errors in criterion of truth, (3) errors in relationships and compatibilities of facts, (4) errors in assessing future impacts in practice, (5) errors in assessing different factors, causes and scales, and (6) errors in understanding the nature of scientific reasoning. Due to licensing restrictions, we have omitted all direct quotes. 3.1. Errors in criterion of knowledge One important starting point for information criticism is the basic structure of knowledge and knowing. It has long been believed that knowledge is a justified true belief (de Grefte 2023; Hilpinen 1970; Cooper and Hutchinson 1997). This is called the Journal of Environmental Planning and Management 5 classic concept of knowledge. For this concept to apply, (1) one must believe that the matter exists in some way, (2) the matter must be true, and (3) the matter must be well justified. If someone does not believe it, of course they cannot know it. If, on the other hand, it is not true, it cannot be knowledge either. Finally, the person must have a good argument that the matter is true. A simplified roulette winner example can illustrate what knowledge is about. Suppose Person A has a big win in roulette and says he knew it would happen. In this case, on the basis of the above criteria, it can be claimed that Person A knew he would win if: (1) He believed he would win. Placing a chip, of course, guarantees that he believes he will win. If he also wins, the matter is true and meets (2) the second information criterion. The last criterion (3) is problematic, because it is difficult to find a good reason why the roulette number can be predicted. However, in the case of a roulette spin influenced by magnets, for example, the outcome of which can be predicted, and the person being aware of it, he would have a good reason for his initial claim. The same classical information criteria can be applied to climate discourse. It is possible to look at climate opinions through the criteria of information and think about the extent to which knowledge-based societal debates really are. For example, some Suomi24 debaters believe that it is not possible to state with certainty the role of humans as the current cause of climate change (1). According to them, the matter has not been scientifically studied by appropriate expertise (2), but speculation is based mainly on interpretative presuppositions, unexplored hypotheses, or “climate faith”(3). Some debaters may have thought that the results of human research were one-sided, biased, and unreliable (2), as the researchers and related research were either unprofessional or manipulated in the interests of politicians, businessmen, or the mainstream media (3), illustrating an underlying conspiracy thought model. However, the examples described above are in no way true, at least in the light of today’s scientific facts, and, thus, do not meet the criteria for knowledge. In reality, the contribution of humans to ongoing climate change has undoubtedly been shown to be significant, based on comprehensive, high-quality, and impartial research accepted by the scientific community (IPCC (Intergovernmental Panel on Climate Change) 2023a,2023b; United Nations 2019; World Economic Forum 2022). In contrast, the few published studies that deny mainstream climate science have contained critical flaws and errors, such as inaccurately insisting cooling or low climate sensitivity, using unsuitable statistical methods or misunderstanding physics (Cook 2020). 3.2. Errors in criterion of truth One of the key criteria in classical information analysis is truth. This usually means that a true claim matches up to the reality (Niiniluoto 1999). For example, it is true that the average global temperature has risen. On the basis of statistical monitoring, it can also be elicited that the statement corresponds to how things are. An overview of measurement statistics describing changes in various physical phenomena, such as an increase in the global surface temperature, sea level altitude, or the carbon cycle, can be found, for instance, in the report of Working Group I of the Intergovernmental Panel on Climate Change (IPCC (Intergovernmental Panel on Climate Change) 2023a). The report summarizes the results of more than 14,000 peer-reviewed studies, which 6M. Myllyl€ a and P. Saariluoma were re-evaluated by a panel of 234 experts. In addition, 517 other experts were involved in compiling the report. The correspondence between truth and state of affairs is the most important criterion of truth (David 2022; Niiniluoto 1999). Claims that do not correspond to the truth are false and untrue. As a result, the latter cannot be taken as a basis for information. For example, it was quite common in Suomi24 to claim that it has not been possible to measure climate change, particularly temperature changes, for a long enough period, so no convincing conclusions can be drawn from the effects of human activity on climate change. Some believed that previous modeling and predictions of climate change had been proven to be incorrect, or that the changes predicted in them had been drastically exaggerated. In reality, climate change has been extensively studied over a very long period (IPCC (Intergovernmental Panel on Climate Change) 2023a). Developments related to climate change have largely followed previous forecasts, if not advanced even more strongly (IPCC (Intergovernmental Panel on Climate Change) 2023a,2023b). As the understanding of, for instance, climate sensitivity advances, and the amount of observational data and the computing power of computers increases, climate models and the predictions derived from them have become increasingly comprehensive and accurate (IPCC (Intergovernmental Panel on Climate Change) 2023a,2023b; Ruosteenoja and Jylh€ a2021; but see also Simpson et al.2021; Urban et al.2016). 3.3. Errors in relationships and compatibilities of facts The truth of the matter can also be established on the basis of other facts. In this case, there is usually talk of compatibility of truths (Niiniluoto 1999; Young 2018). Such a network of truths usually improves reliability. However, if there are mistakes in the interrelated system of truths, in its data or how it is understood, it can lower the credibility of the claim or take the base away from it altogether. Climate and weather are complex concepts. Terms can be confused and oversimplified. People may imagine false cause-and-effect relationships and make incorrect interpretations of reality and the climate system, which was also found in Suomi24 discussions. Cold and snowy weather in winter may be mistaken as proof that climate change is not happening. Similarly, severe summer heat can be viewed, erroneously, as a direct sign of global warming. However, the local climate is not about individual weather observations but the average of 30-year weather statistics for a wider area (IPCC (Intergovernmental Panel on Climate Change) 2023a; Ruosteenoja and Jylh€ a 2021). With the current climate change, average temperatures have risen globally and extreme high temperature incidences have increased. Some of the heat has also been transferred to the oceans (Cheng et al.2023; IPCC (Intergovernmental Panel on Climate Change) 2023a,2023b; World Meteorological Organization 2022). Another example of errors in compatibility of truths in Suomi24 was to associate the public debate on climate change with previous historical, similar debates. For example, since the societal worries and fears of running out of oil that followed the oil crisis of the 1970s did not materialize, climate change and the debate about it must be a similar exaggeration or “sham.”Although the debate on the oil crisis of the 1970s and on climate change today may give rise to similar emotions and thoughts, they are not compatible as phenomena in terms of their facts—that is, they cannot be compared to make reliable claims about climate change. 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