Mason Majszak

While the term ‘flood’ may elicit clear images of rushing water or overflowing river banks, genuine concerns around formally demarcating this phenomenon remain. In this paper, we investigate the phenomenon’s conceptual space, discussing its physical and social components. We highlight key features of the term, as it is commonly used, while illustrating existing conceptual challenges, including the lack of direct reference to the assumptions about how things ought to be, what the philosophical literature calls normativity, involved in setting relevance parameters and the rarity threshold. We propose defining the flood phenomenon by referencing both its physical and normative properties. Within this demarcation framework, physical floods constitute pools or fluxes of water beyond a normatively-specified rarity threshold. A second demarcation occurs when a notion of desirability is used to identify if the presence of water is bad or good. Anthropocentric floods are then physical floods deemed undesirable or desirable. Recognizing the uncertainty present in identifying and adopting notions of desirability can then help explain instances of lack of consensus in communities, what we call interventional ambiguity, on whether to seek engineered solutions to specific flood-related problems. Our demarcation framework can facilitate cross-disciplinary communication and motivate further refinement of flood-related concepts.

In this paper, we investigate the use of non-epistemic values in the communication of scientific information. We examine how values, by way of the precautionary principle, have been used to move from a deeply uncertain scientific concept, climate tipping points, to a metaphor which promotes political action. We argue that the precautionary principle has been used to produce a metaphor which idealizes the tipping point context. The idealization highlights specific features that are relevant for decision-making, including the potential for catastrophe, while omitting others, such as the deep uncertainty related to specific climate tipping points. We discuss the negative impacts of using precautionary principle-like reasoning when communicating about tipping points, highlighting the potential to (1) mischaracterize the uncertainty present within the decision-making context, and (2) further politicize a scientific debate to the point of hyperpolarization. We conclude that when communicating about deeply uncertain events the precautionary principle ought to be used as a meta-principle directed at the research community, the more-research-needed argument, rather than as a decision-making principle for policy.

Within the philosophical literature, there has been a trend to discuss subjectivity, and its impacts on science, from the perspective of value judgments. While this discussion is necessary and has proven to be fruitful, I contend that the type of subjectivity referenced in this discussion extends beyond the use of values. In this paper, I argue that the type of subjectivity of concern in this literature is regarding some personal aspect of the individual and the use of this aspect in addressing the uncertainty present within scientific decision-making contexts. I begin by arguing that, while it is not explicitly stated, the current discussions of this subjectivity within the literature actually focus on instances of normative uncertainty present within these decision-making contexts, where I claim that values are used to address this uncertainty. In this way, I identify a connection between the use of values in science and the presence of normative uncertainty. However, other forms of uncertainty are also present in scientific decision-making contexts, modal and empirical uncertainty, which must also be addressed. Using examples from climate science, I show how these uncertainties are addressed by other means, specifically through a scientist’s tacit knowledge and intuition. Subsequently, tacit knowledge and intuition are shown to maintain the same type of subjectivity as value judgments, where the use of this subjectivity is a necessary part of decision-making. In this way, I highlight additional vehicles of subjectivity and novel contexts of uncertainty where this subjectivity can be introduced into science. Thus, when someone recognizes the type of subjectivity, which is historically only associated with values, to be present in science they should no longer assume that the introduction was due to a value judgment. Ultimately, I conclude by discussing these other vehicles of subjectivity and their impact on epistemic reliability.

Parameterization and parameter tuning are central aspects of climate modeling, and there is widespread consensus that these procedures involve certain subjective elements. Even if the use of these subjective elements is not necessarily epistemically problematic, there is an intuitive appeal for replacing them with more objective (automated) methods, such as machine learning. Relying on several case studies, we argue that, while machine learning techniques may help to improve climate model parameterization in several ways, they still require expert judgment that involves subjective elements not so different from the ones arising in standard parameterization and tuning. The use of machine learning in parameterizations is an art as well as a science and requires careful supervision.

Like any science marked by high uncertainty, climate science is characterized by a widespread use of expert judgment. In this paper, we first show that, in climate science, expert judgment is used to overcome uncertainty, thus playing a crucial role in the domain and even at times supplanting models. One is left to wonder to what extent it is legitimate to assign expert judgment such a status as an epistemic superiority in the climate context, especially as the production of expert judgment is particularly opaque. To begin answering this question, we highlight the key components of expert judgment. We then argue that the justification for the status and use of expert judgment depends on the competence and the individual subjective features of the expert producing the judgment since expert judgment involves not only the expert's theoretical knowledge and tacit knowledge, but also their intuition and values. This goes against the objective ideal in science and the criteria from social epistemology which largely attempt to remove subjectivity from expertise.

Expert judgment can be seen throughout climate science and even more prominently when discussing climate tipping points. To provide an accurate characterization of expert judgment we begin by evaluating the existing literature on expertise as it relates to climate science as a whole, before then focusing the literature review on the role of expert judgment in the unique context of climate tipping points. From this we turn our attention to the structured expert elicitation protocols specifically developed for producing expert judgments about tipping points. We highlight that expert elicitation is not only used for the quantification of uncertainty in this context, but also for the very identification and characterization of tipping points and their interactions, making expert judgment in itself a genuine scientific output. The central role of expert judgment in this domain raises several epistemic issues that require careful attention. Among other topics, we discuss the relationship between expert judgment and modeling, as well as the nonepistemic values that are involved in the production of expert judgments, highlighting how the elicitation protocols can be used to manage these values. In the perspective of climate change, clarifying the epistemic foundations of expert judgment in this context can help to navigate the epistemic situation between self-defeating alarmism and blind dismissal, thus contributing to a better understanding of the challenges related to climate (and Earth system) tipping points.