We argue that concerns about double-counting—using the same evidence both to calibrate or tune climate models and also to confirm or verify that the models are adequate—deserve more careful scrutiny in climate modelling circles. It is widely held that double-counting is bad and that separate data must be used for calibration and confirmation. We show that this is far from obviously true, and that climate scientists may be confusing their targets. Our analysis turns on a Bayesian/relative-likelihood (...) approach to incremental confirmation. According to this approach, double-counting is entirely proper. We go on to discuss plausible difficulties with calibrating climate models, and we distinguish more and less ambitious notions of confirmation. Strong claims of confirmation may not, in many cases, be warranted, but it would be a mistake to regard double-counting as the culprit. 1 Introduction2 Remarks about Models and Adequacy-for-Purpose3 Evidence for Calibration Can Also Yield Comparative Confirmation3.1 Double-counting I3.2 Double-counting II4 Climate Science Examples: Comparative Confirmation in Practice4.1 Confirmation due to better and worse best fits4.2 Confirmation due to more and less plausible forcings values5 Old Evidence6 Doubts about the Relevance of Past Data7 Non-comparative Confirmation and Catch-Alls8 Climate Science Example: Non-comparative Confirmation and Catch-Alls in Practice9 Concluding Remarks. (shrink)

Philosophy of science has witnessed substantial recent debate over the existence of a structural analogue of chaos, which is alleged to spell trouble for certain uses of climate models. The debate over the analogy can and should be separated from its alleged epistemic implications: chaos-like behavior is neither necessary nor sufficient for small dynamical misrepresentations to generate erroneous results. The kind of sensitivity that matters in epistemology is one that induces unsafe beliefs, and the existence of a structural analogue (...) to chaos is better seen as an explanation for known safety failures than as providing evidence for unknown ones. (shrink)

Today, a major challenge for climate science is to overcome what is called the “usability gap” between the projections derived from climate models and the needs of the end-users. Regional Climate Models (RCMs) are expected to provide usable information concerning a variety of impacts and for a wide range of end-users. It is often assumed that the development of more accurate, more complex RCMs with higher spatial resolution should bring process understanding and better local projections, thus overcoming (...) the usability gap. In this paper, I rather assume that the credibility of climate information should be pursued together with two other criteria of usability, which are salience and legitimacy. Based on the Swiss climate change scenarios, I study the attempts at meeting the needs of end-users and outline the trade-off modellers and users have to face with respect to the cascade of uncertainty. A conclusion of this paper is that the trade-off between salience and credibility sets the conditions under which RCMs can be deemed adequate for the purposes of addressing the needs of end-users and gearing the communication of the projections toward direct use and action. (shrink)

The continued development of General Circulation Models (GCMs) towards increasing resolution and complexity is a predominantly chosen strategy to advance climate science, resulting in channelling of research and funding to meet this aspiration. Yet many other modelling strategies have also been developed and can be used to understand past and present climates, to project future climates and ultimately to support decision-making. We argue that a plurality of climate modelling strategies and an equitable distribution of funding among (...) them would be an improvement on the current predominant strategy for informing policy making. To support our claim, we use a philosophy of science approach to compare increasing resolution and complexity of General Circulation Models with three alternate examples: the use of machine learning techniques, the physical climate storyline approach, and Earth System Models of Intermediate Complexity. We show that each of these strategies prioritises a particular set of methodological aims, among which are empirical agreement, realism, comprehensiveness, diversity of process representations, inclusion of the human dimension, reduction of computational expense, and intelligibility. Thus, each strategy may provide adequate information to support different specific kinds of research and decision questions. We conclude that, because climate decision-making consists of different kinds of questions, many modelling strategies are all potentially useful, and can be used in a complementary way. (shrink)

Recent philosophical attention to climate models has highlighted their weaknesses and uncertainties. Here I address the ways that models gain support through observational data. I review examples of model fit, variety of evidence, and independent support for aspects of the models, contrasting my analysis with that of other philosophers. I also investigate model robustness, which often emerges when comparing climate models simulating the same time period or set of conditions. Starting from Michael Weisberg’s analysis of robustness, I conclude (...) that his approach involves a version of reasoning from variety of evidence, enabling this robustness to be a confirmatory virtue.. (shrink)

I propose a distinct type of robustness, which I suggest can support a confirmatory role in scientific reasoning, contrary to the usual philosophical claims. In model robustness, repeated production of the empirically successful model prediction or retrodiction against a background of independentlysupported and varying model constructions, within a group of models containing a shared causal factor, may suggest how confident we can be in the causal factor and predictions/retrodictions, especially once supported by a variety of evidence framework. I present (...) class='Hi'>climate models of greenhouse gas global warming of the 20th Century as an example, and emphasize climate scientists’ discussions of robust models and causal aspects. The account is intended as applicable to a broad array of sciences that use complex modeling techniques. (shrink)

To study climate change, scientists employ computer models, which approximate target systems with various levels of skill. Given the imperfection of climate models, how do scientists use simulations to generate knowledge about the causes of observed climate change? Addressing a similar question in the context of biological modelling, Levins (1966) proposed an account grounded in robustness analysis. Recent philosophical discussions dispute the confirmatory power of robustness, raising the question of how the results of computer modelling (...) studies contribute to the body of evidence supporting hypotheses about climate change. Expanding on Staley’s (2004) distinction between evidential strength and security, and Lloyd’s (2015) argument connecting variety-of-evidence inferences and robustness analysis, I address this question with respect to recent challenges to the epistemology robustness analysis. Applying this epistemology to case studies of climate change, I argue that, despite imperfections in climate models, and epistemic constraints on variety-of-evidence reasoning and robustness analysis, this framework accounts for the strength and security of evidence supporting climatological inferences, including the finding that global warming is occurring and its primary causes are anthropogenic. (shrink)

Non-epistemic values pervade climate modelling, as is now well documented and widely discussed in the philosophy of climate science. Recently, Parker and Winsberg have drawn attention to what can be termed “epistemic inequality”: this is the risk that climate models might more accurately represent the future climates of the geographical regions prioritised by the values of the modellers. In this paper, we promote value management as a way of overcoming epistemic inequality. We argue that value management (...) can be seriously considered as soon as the value-free ideal and inductive risk arguments commonly used to frame the discussions of value influence in climate science are replaced by alternative social accounts of objectivity. We consider objectivity in Longino's sense as well as strong objectivity in Harding's sense to be relevant options here, because they offer concrete proposals that can guide scientific practice in evaluating and designing so-called multi-model ensembles and, in fine, improve their capacity to quantify and express uncertainty in climate projections. (shrink)

Climate change adaptation is largely a local matter, and adaptation planning can benefit from local climate change projections. Such projections are typically generated by accepting climate model outputs in a relatively uncritical way. We argue, based on the IPCC’s treatment of model outputs from the CMIP5 ensemble, that this approach is unwarranted and that subjective expert judgment should play a central role in the provision of local climate change projections intended to support decision-making.

Understanding climate change is becoming an urgent requirement for those in education. The normative values of education have long been closely aligned with the global, modernised world. The industrial model has underpinned the hidden and overt curriculum. Increasingly though, a new eco-centric orientation to economics, technology, and social organisation is beginning to shape up the post-carbon world. Unless education is up to date with the issues of climate change, the estate of education will be unable to meet its (...) task of knowledge transfer. This paper covers the basic science and ethical policy debates, and begins to outline the questions that will necessarily entangle education as we orientate ourselves to the new world that is upon us. (shrink)

Climate change mitigation has become a paradigm case both for externalities in general and for the game-theoretic model of the Tragedy of the Commons (ToC) in particular. This situation is worrying, as we have reasons to suspect that some models in the social sciences are apt to be performative to the extent that they can become self-fulfilling prophecies. Framing climate change mitigation as a hardly solvable coordination problem may force us into a worse situation, by changing real-world behaviour (...) to fit our model, rather than the other way around. But while this problem of the performativity of the ToC has been noted in a recent paper in this journal by Matthew Kopec, his proposed strategies for dealing with their self-fulfilling nature fall short of providing an adequate solution. Instead of relying on the idea that modelling assumptions are always strictly speaking false, this paper shows that the problem may be better framed as a problem of underdetermination between competing explanations. Our goal here is to provide a framework for choosing between this set of competing models that allows us to avoid a ‘Russian Roulette’-like situation in which we gamble with existential risk. (shrink)

A number of authors, including me, have argued that the output of our most complex climate models, that is, of global climate models and Earth system models, should be assessed possibilistically. Worries about the viability of doing so have also been expressed. I examine the assessment of the output of relatively simple climate models in the context of discovery and point out that this assessment is of epistemic possibilities. At the same time, I show that the concept (...) of epistemic possibility used in the relevant studies does not fit available analyses of this concept. Moreover, I provide an alternative analysis that does fit the studies and broad climate modelling practices as well as meshes with my existing view that climate model assessment should typically be of real possibilities. On my analysis, to assert that a proposition is epistemically possible is to assert that it is not known to be false and is consistent with at least approximate knowledge of the basic way things are. I, finally, consider some of the implications of my discussion for available possibilistic views of climate model assessment and for worries about such views. I conclude that my view helps to address worries about such assessment and permits using the full range of climate models in it. (shrink)

The Intergovernmental Panel on Climate Change has developed a novel framework for assessing and communicating uncertainty in the findings published in their periodic assessment reports. But how should these uncertainty assessments inform decisions? We take a formal decision-making perspective to investigate how scientific input formulated in the IPCC’s novel framework might inform decisions in a principled way through a normative decision model.

Recently a number of scientists have proposed substantial changes to the practice of climate modeling, though they disagree over what those changes should be. We provide an overview and critical examination of three leading proposals: the unified approach, the hierarchy approach and the pluralist approach. The unified approach calls for an accelerated development of high-resolution models within a seamless prediction framework. The hierarchy approach calls for more attention to the development and systematic study of hierarchies of related models, with (...) the aim of advancing understanding. The pluralist approach calls for greater diversity in modeling efforts, including, on some of its variants, more attention to empirical modeling. After identifying some of the scientific and institutional challenges faced by these proposals, we consider their expected gains and costs, relative to a business-as-usual modeling scenario.We find the proposals to be complementary, having valuable synergies. But since resource limitations make it unlikely that all three will be pursued, we offer some reflections on more limited changes in climate modeling that seem well within reach and that can be expected to yield substantial benefits. (shrink)

Given that mitigating climate change is a large-scale global issue, what obligations do individuals have to lower their personal carbon emissions? I survey recent suggestions by Walter Sinnott-Armstrong and Dale Jamieson and offer models for thinking about their respective approaches. I then present a third model based on the notion of structural violence. While the three models are not mutually incompatible, each one suggests a different focus for mitigating climate change. In the end, I agree with Sinnott-Armstrong that (...) people have limited moral obligations to directly lower personal emissions, but I offer different reasons for this conclusion, namely that the structural arrangements of our lives place a limit on how much individuals can restrict their own emissions. Thus, individuals should focus their efforts on changing the systems instead (e.g., the design of cities, laws and regulation, etc.), which will lead to lower emissions on a larger scale. (shrink)

Anthropogenic climate change poses some difficult ethical quandaries for non-anthropocentrists. While it is hard to deny that climate change is a substantial moral ill, many types of non-human organisms stand to benefit from climate change. Modelling studies provide evidence that net primary productivity (NPP) could be substantially boosted, both regionally and globally, as a result of warming from increased concentrations of greenhouse gases. The same holds for deployment of certain types of climate engineering, or large-scale, (...) technological modifications of the global environment in order to prevent or slow anthropogenic climate change. For example, solar radiation management with stratospheric aerosol injections could benefit plant life by promoting enhanced photosynthesis, increasing diffuse radiation, and reducing heat stress. This has a surprising implication: from some non-anthropocentric perspectives, certain scenarios of climate change and climate engineering might bring about morally better states of affairs when compared to emission-mitigation baselines. (shrink)

Climate change – and its most dangerous consequence, the rapid overheating of the planet – is not the offspring of a natural procedure; instead, it is human-induced. It is only the aftermath of a specific pattern of conomic development, one that focuses mainly on economic growth rather than on quality of life and sustainability. Since climate change is a major threat not only to millions of humans, but also to numerous non-human species and other forms of life, as (...) well as to the equilibrium and the viability of the very planet, addressing it is of dire importance. In this chapter it will be argued that addressing the threat of climate change is primarily a task and a challenge for ethics, since the stabilization and gradual amelioration of the situation requires abandoning an up to now dominant model of life, longestablished customs and a so far cogent system of moral values. It will be further maintained that this for ethics might – or, even, should – become a new categorical imperative, since preserving the viability of the planet is a fundamental moral duty not only towards the existing members of the moral community, but also towards future generations. (shrink)

Climate change as a social issue challenged the disciplinary and methodological traditions of research. Moreover, climate change becomes more problematic as schools must be able to engage learners in learning situations that are challenging and rooted in geographical pedagogical traditions. Though it is present in the curriculum, the present study systematically reviews the teaching of climate change from selected literature from 2019 to 2021. The objective of this study is to investigate approaches and strategies in the teaching (...) and learning of climate change as well as its integration across different learning areas in the basic education curriculum within a global continuum and the conception and operationalization of climate change education. Of the accessed meaningful related literature, the researchers selected one hundred fifty (150) pieces of literature further trimmed down into fifty-seven (57) and then to nineteen (19) from the year 2019 to 2021. The selection of literature is based on the following criteria set by the researcher: educational approach and implication, the methodology employed, and perspectives about climate change. Much of the present literature stressed science as a potent subject for discussing climate change, but others were covered as well, including climate education, arts, primary and middle school, after-school activities, and professional development. A systematic study of climate change, a model, computer games, classroom instructions, and learning capacities were all aims of the review. Teaching and learning approaches and strategies were identified. Methodology, perspectives, inferences, and recommendations were thematically discussed. (shrink)

ABSTRACT: It will be argued that Eric Winsberg has created a problem where nobody is in the position to rationally support the Anthropogenic Climate Change hypothesis, since he demands the normal lay public defer to experts but, from Winsberg’s philosophical commitments, experts are precluded from having the ability to rationally conclude that a hypothesis is superior to an alternative. Winsberg’s difficulties can be resolved with a little help from Bayesian Confirmation Theory. A Bayesian analysis will be provided which allows (...) for the evaluation of climate models that uses Winsberg’s analysis of robustness. (shrink)

Climate change assessments rely upon scenarios of socioeconomic developments to conceptualize alternative outcomes for global greenhouse gas emissions. These are used in conjunction with climate models to make projections of future climate. Specifically, the estimations of greenhouse gas emissions based on socioeconomic scenarios constrain climate models in their outcomes of temperatures, precipitation, etc. Traditionally, the fundamental logic of the socioeconomic scenarios—that is, the logic that makes them plausible—is developed and prioritized using methods that are very subjective. (...) This introduces a fundamental challenge for climate change assessment: The veracity of projections of future climate currently rests on subjective ground. We elaborate on these subjective aspects of scenarios in climate change research. We then consider an alternative method for developing scenarios, a systems dynamics approach called ‘Cross-Impact Balance’ (CIB) analysis. We discuss notions of ‘objective’ and ‘objectivity’ as criteria for distinguishing appropriate scenario methods for climate change research. We distinguish seven distinct meanings of ‘objective,’ and demonstrate that CIB analysis is more objective than traditional subjective approaches. However, we also consider criticisms concerning which of the seven meanings of ‘objective’ are appropriate for scenario work. Finally, we arrive at conclusions regarding which meanings of ‘objective’ and ‘objectivity’ are relevant for climate change research. Because scientific assessments uncover knowledge relevant to the responses of a real, independently existing climate system, this requires scenario methodologies employed in such studies to also uphold the seven meanings of ‘objective’ and ‘objectivity.’. (shrink)

Climate change temperature prediction plays a crucial role in effective environmental planning. This study introduces an innovative approach that harnesses the power of Artificial Neural Networks (ANNs) within the Just Neural Network (JustNN) framework to enhance temperature forecasting in the context of climate change. By leveraging historical climate data, our model achieves exceptional accuracy, redefining the landscape of temperature prediction without intricate preprocessing. This model sets a new standard for precise temperature forecasting in the context of (...) class='Hi'>climate change. Moreover, our research provides valuable insights into the pivotal factors influencing temperature variations, making significant contributions to environmental science and climate mitigation strategies. (shrink)

Climatology is a paradigmatic complex systems science. Understanding the global climate involves tackling problems in physics, chemistry, economics, and many other disciplines. I argue that complex systems like the global climate are characterized by certain dynamical features that explain how those systems change over time. A complex system's dynamics are shaped by the interaction of many different components operating at many different temporal and spatial scales. Examining the multidisciplinary and holistic methods of climatology can help us better understand (...) the nature of complex systems in general. -/- Questions surrounding climate science can be divided into three rough categories: foundational, methodological, and evaluative questions. "How do we know that we can trust science?" is a paradigmatic foundational question (and a surprisingly difficult one to answer). Because the global climate is so complex, questions like "what makes a system complex?" also fall into this category. There are a number of existing definitions of `complexity,' and while all of them capture some aspects of what makes intuitively complex systems distinctive, none is entirely satisfactory. Most existing accounts of complexity have been developed to work with information-theoretic objects (signals, for instance) rather than the physical and social systems studied by scientists. -/- Dynamical complexity, a concept articulated in detail in the first third of the dissertation, is designed to bridge the gap between the mathematics of contemporary complexity theory (in particular the formalism of "effective complexity" developed by Gell-Mann and Lloyd [2003]) and a more general account of the structure of science generally. Dynamical complexity provides a physical interpretation of the formal tools of mathematical complexity theory, and thus can be used as a framework for thinking about general problems in the philosophy of science, including theories, explanation, and lawhood. -/- Methodological questions include questions about how climate science constructs its models, on what basis we trust those models, and how we might improve those models. In order to answer questions about climate modeling, it's important to understand what climate models look like and how they are constructed. Climate model families are significantly more diverse than are the model families of most other sciences (even sciences that study other complex systems). Existing climate models range from basic models that can be solved on paper to staggeringly complicated models that can only be analyzed using the most advanced supercomputers in the world. I introduce some of the central concepts in climatology by demonstrating how one of the most basic climate models might be constructed. I begin with the assumption that the Earth is a simple featureless blackbody which receives energy from the sun and releases it into space, and show how to model that assumption formally. I then gradually add other factors (e.g. albedo and the greenhouse effect) to the model, and show how each addition brings the model's prediction closer to agreement with observation. After constructing this basic model, I describe the so-called "complexity hierarchy" of the rest of climate models, and argue that the sense of "complexity" used in the climate modeling community is related to dynamical complexity. -/- With a clear understanding of the basics of climate modeling in hand, I then argue that foundational issues discussed early in the dissertation suggest that computation plays an irrevocably central role in climate modeling. "Science by simulation" is essential given the complexity of the global climate, but features of the climate system--the presence of non-linearities, feedback loops, and chaotic dynamics--put principled limits on the effectiveness of computational models. This tension is at the root of the staggering pluralism of the climate model hierarchy, and suggests that such pluralism is here to stay, rather than an artifact of our ignorance. Rather than attempting to converge on a single "best fit" climate model, we ought to embrace the diversity of climate models, and view each as a specialized tool designed to predict and explain a rather narrow range of phenomena. Understanding the climate system as a whole requires examining a number of different models, and correlating their outputs. This is the most significant methodological challenge of climatology. -/- Climatology's role contemporary political discourse raises an unusually high number of evaluative questions for a physical science. The two leading approaches to crafting policy surrounding climate change center on mitigation (i.e. stopping the changes from occurring) and adaptation (making post hoc changes to ameliorate the harm caused by those changes). Crafting an effective socio-political response to the threat of anthropogenic climate change, however, requires us to integrate multiple perspectives and values: the proper response will be just as diverse and pluralistic as the climate models themselves, and will incorporate aspects of both approaches. I conclude by offering some concrete recommendations about how to integrate this value pluralism into our socio-political decision making framework. (shrink)

This chapter qualitatively lays out some of the ways that climate change impacts are evaluated in integrated assessment models (IAMs). Putting aside the physical representations of these models, it first discusses some key social or structural assumptions, such as the damage functions and the way growth is modeled. Second, it turns to the moral assumptions, including parameters associated with intertemporal evaluation and interpersonal inequality aversion, but also assumptions in population ethics about how different-sized populations are compared and how we (...) think about distributing goods across or within times. The intention is to survey the morally important assumptions that go into estimates of the social cost of carbon, the marginal cost of an additional tonne of carbon dioxide to society. (shrink)

Numerous societal issues, from climate change to pandemics, require public engagement with scientific research. Such engagement reveals challenges that can arise when experts communicate with laypeople. One of the most common frameworks for framing these communicative interactions is the deficit model of science communication, which holds that laypeople lack scientific knowledge and/or positive attitudes towards science, and that imparting knowledge will fill knowledge gaps, lead to desirable attitude/behavior changes, and increase trust in science. §1 introduces the deficit model in (...) more detail and shows that adhering to this model often fails to achieve its aims, which motivates the main question of this chapter: how can Ludwik Fleck’s theory of thinking collectives address the persistent problem of deficit approaches in science communication? I suggest that it can do so by exposing the deficit model’s implicit assumption of an expert-lay divide. Accordingly, §2 lays out Fleck’s theory and §3 contrasts it with contemporary debates about science communication. Following this descriptive work, §4 draws on Fleck’s ideas to make four concrete suggestions for further questioning the expert-lay divide. (shrink)

For computer simulation models to usefully inform climate risk management, uncertainties in model projections must be explored and characterized. Because doing so requires running the model many ti...

The aim of this dissertation is to comprehensively study various robustness arguments proposed in the literature from Levins to Lloyd as well as the opposition offered to them and pose enquiry into the degree of epistemic virtue that they provide to the model prediction results with respect to climate science and modeling. Another critical issue that this dissertation strives to examine is that of the actual epistemic notion that is operational when scientists and philosophers appeal to robustness. In attempting (...) to explicate this idea, the discussion turns to arguments provided by Schupbach who completely rejects probabilistic independence in favour of explanatory reasoning, Stegenga and Menon who still see some value in probabilistic independence, and Winsberg who takes applies Schupbach’s to climate science, going beyond models to involve multi-modal evidence. After an exhaustive discussion on these arguments, this dissertation attempts to provide a thorough and updated notion of robustness in climate modeling and climate science. (shrink)

Game theorists tend to model climate negotiations as a so-called ‘tragedy of the commons’. This is rather worrisome, since the conditions under which such commons problems have historically been solved are almost entirely absent in the case of international greenhouse gas emissions. In this paper, I will argue that the predictive accuracy of the tragedy model might not stem from the model’s inherent match with reality but rather from the model’s ability to make self-fulfilling predictions. I then sketch some (...) possible ways to dispel the tragedy, including (1) recognizing some ways the assumptions of the model fail, (2) taking seriously recent work suggesting that increasing greenhouse gas emissions is not in most nations’ own self-interest, and (3) preferring alternative models like collective risk dilemmas, bargaining games, or cooperative models. (shrink)

The geosciences include a wide spectrum of disciplines ranging from paleontology to climate science, and involve studies of a vast range of spatial and temporal scales, from the deep-time history of microbial life to the future of a system no less immense and complex than the entire Earth. Modeling is thus a central and indispensable tool across the geosciences. Here, we review both the history and current state of model-based inquiry in the geosciences. Research in these fields makes use (...) of a wide variety of models, such as conceptual, physical, and numerical models, and more specifically cellular automata, artificial neural networks, agent-based models, coupled models, and hierarchical models. We note the increasing demands to incorporate biological and social systems into geoscience modeling, challenging the traditional boundaries of these fields. Understanding and articulating the many different sources of scientific uncertainty – and finding tools and methods to address them – has been at the forefront of most research in geoscience modeling. We discuss not only structuralmodel uncertainties, parameter uncertainties, and solution uncertainties, but also the diverse sources of uncertainty arising from the complex nature of geoscience systems themselves. Without an examination of the geosciences, our philosophies of science and our understanding of the nature of model-based science are incomplete. (shrink)

Can political sovereignty still be theoretically and practically useful in tackling climate change in a socially fair way? The global nature of climate change unequivocally demands a high degree of international coordination. Traditionally viewed as an impediment to effective climate action, sovereignty has been criticised for fostering nationalistic and isolationist tendencies that obstruct global environmental cooperation. This paper challenges the prevailing “sovereignty-as-enemy” thesis and argues for a nuanced reappraisal of sovereignty as a potentially valuable asset in addressing (...) the climate crisis. This paper posits that sovereignty can be a critical tool for promoting decisive and equitable climate policies by examining its historical and theoretical underpinnings and complex relationship with neoliberal globalisation. The argument is rooted in a multidisciplinary literature comprising critiques of the neoliberal economy and globalisation model, the erosion of states’ sovereign prerogatives, critiques of neoliberal environmentalism, the interaction between trade and climate regimes, and the intellectual history of sovereignty. The public-private dichotomy is identified as a significant feature of sovereignty in times of climate change. Keywords:sovereignty, climate politics, neoliberal globalisation, public-private divide. (shrink)

There has been a recent resurgence of what Betsy Hartmann dubbed “the greening of hate” (blaming immigrants for environmental issues in the US). When immigrants move to the U.S., the argument goes, their CO2 emissions increase, thereby making climate change worse. Using migration from the Lower 48 to Alaska as a model, I illustrate how this anti-immigration argument has more traction than it is generally given credit for, and might be more convincing in a different situation. Nonetheless, it is (...) not convincing given the current pattern of climate emissions and prevailing justice considerations. Climate matters; how we treat each other matters, too. (shrink)

Geoengineering; specifically Solar Radiation Management ; has been proposed to effect rapid influence over the Earth’s climate system in order to counteract Anthropogenic Global Warming. This poses near-term to long-term governance challenges; some of which are within the planning horizon of current political administrations. Previous discussions of governance of SRM have focused primarily on two scenarios: an isolated “Greenfinger” individual; or state; acting independently ; versus more consensual; internationalist approaches. I argue that these models represent a very limited sub-set (...) of plausible deployment scenarios. To generate a range of alternative models; I offer a short; relatively unstructured discussion of a range of different types of warfare – each with an analogous SRM deployment regime. (shrink)

We critically engage two traditional views of scientific data and outline a novel philosophical view that we call the pragmatic-representational view of data. On the PR view, data are representations that are the product of a process of inquiry, and they should be evaluated in terms of their adequacy or fitness for particular purposes. Some important implications of the PR view for data assessment, related to misrepresentation, context-sensitivity, and complementary use, are highlighted. The PR view provides insight into the common (...) but little-discussed practices of iteratively reusing and repurposing data, which result in many datasets’ having a phylogeny—an origin and complex evolutionary history—that is relevant to their evaluation and future use. We relate these insights to the open-data and data-rescue movements, and highlight several future avenues of research that build on the PR view of data. (shrink)

Can investing in women’s agriculture increase productivity? This paper argues that it can. We assess climate and gender bias impacts on women’s production in the global South and North and challenge the male model of agricultural development to argue further that women’s farming approaches can be more sustainable. Level-based analysis (global, regional, local) draws on a literature review, including the authors’ published longitudinal field research in Ghana and the United States. Women farmers are shown to be undervalued and to (...) work harder, with fewer resources, for less compensation; gender bias challenges are shared globally while economic disparities differentiate; breaches of distributive, gender, and intergenerational justices as well as compromise of food sovereignty affect women everywhere. We conclude that investing in women’s agriculture needs more than standard approaches of capital and technology investment. Effective ‘investment’ would include systemic interventions into agricultural policy, governance, education, and industry; be directed at men as well as women; and use gender metrics, for example, quotas, budgets, vulnerability and impacts assessments, to generate assessment reports and track gender parity in agriculture. Increasing women’s access, capacity, and productivity cannot succeed without men’s awareness and proactivity. Systemic change can increase productivity and sustainability. (shrink)

The climate change mitigation effort is being translated into several actions and discourses that make collateral benefits and their rationale increasingly relevant for sustainability, in such a way that they are now a constant part of the political agenda. Taking a broader and consensual perspective, co-benefits are considered here to be emerging advantages of implementing measures to lower greenhouse gases. Starting with the analysis of policy documents referring to two European urban transportation strategies, the emergent co-benefits are problematized and (...) discussed to better understand their moral aspect. Further ethical reflection is conducted after an analysis of some unintended consequences of the co-benefits rationale arising from the examples. The discussion focuses primarily on the challenges of an integrative moral justification for co-benefits and also for their role in the climate change mitigation effort. We also discuss the limitations of the current normative models that frame a co-benefits rationale, both from a moral viewpoint and in relation to the overall climate change mitigation strategy. In this article, we propose the concepts of well-being and freedom, as portrayed by the Capability Approach, as possible guiding notions for the moral and social evaluation of goodness of these emergent benefits as well as their rationale. Additionally, some preliminary conclusions are drawn regarding the potential of the presented concepts to support climate change mitigation action. Finally, we outline a scenario where the Capability Approach is the moral guideline for a co-benefits rationale and illustrates its potential in terms of enhancing climate change mitigation strategy. (shrink)

Global structural injustices are harms caused by structural processes, involving multiple individuals, acting across more than one state. Young (2011) developed the concept of ‘political responsibility,’ to allocate responsibility for structural injustice. In this paper, I am going to argue that when considering the climate crisis Young’s model needs to be adapted— to have agency as a basis for allocating political responsibility instead of contribution. This is a more intuitive way to allocate responsibility for the climate crisis given (...) its nature as a threshold problem, and the subtle structural positions occupied by the individuals involved. (shrink)

In this article, we describe a project in which philosophy, in combination with methods drawn from mental modeling, was used to structure dialogue among stakeholders in a region-scale climate adaptation process. The case study we discuss synthesizes the Toolbox dialogue method, a philosophically grounded approach to enhancing communication and collaboration in complex research and practice, with a mental modeling approach rooted in risk analysis, assessment, and communication to structure conversations among non-academic stakeholders who have a common interest in planning (...) for a sustainable future. We begin by describing the background of this project, including details about climate resiliency efforts in West Michigan and the Toolbox dialogue method, which was extended in this project from academic research into community organization involving the West Michigan Climate Resiliency Framework Initiative. This extension involved application of several methods, which are the focus of the Methods section. We then present and discuss preliminary results that suggest the potential for philosophical dialogue to enhance mutual understanding in complex community initiatives that focus on sustainable responses to climate change. Overall, the article supplies a detailed, instructive example of how philosophy can support policy-relevant decision-making processes at the community level. (shrink)

This article argues that common intuitions regarding (a) the specialness of ‘use-novel’ data for confirmation and (b) that this specialness implies the ‘no-double-counting rule’, which says that data used in ‘constructing’ (calibrating) a model cannot also play a role in confirming the model’s predictions, are too crude. The intuitions in question are pertinent in all the sciences, but we appeal to a climate science case study to illustrate what is at stake. Our strategy is to analyse the intuitive claims (...) in light of prominent accounts of confirmation of model predictions. We show that on the Bayesian account of confirmation, and also on the standard classical hypothesis-testing account, claims (a) and (b) are not generally true; but for some select cases, it is possible to distinguish data used for calibration from use-novel data, where only the latter confirm. The more specialized classical model-selection methods, on the other hand, uphold a nuanced version of claim (a), but this comes apart from (b), which must be rejected in favour of a more refined account of the relationship between calibration and confirmation. Thus, depending on the framework of confirmation, either the scope or the simplicity of the intuitive position must be revised. (shrink)

Development plans at different levels – from local to global – aspire to eliminate poverty, famine, to make health care accessible, to create better access to education, to improve transportation, employment, and the quality of life, all within next decades. Yet, these plans collide with the reality of climate change, more precisely the Anthropocene, which already creates high-dimensional conflicts. These will only intensify within decades because climate change and other consequences of the environment global devastation lead to a (...) real decrease of resources. These resources enable not only development but also an elementary reproduction of the essential preconditions of life. The current model of development has substantially contributed to the intensification of unequal accessibility to resources and existing conflicts have thus heightened and new ones have emerged. Water as an essential resource will cause new conflicts. Growing population, expansion of deserts and a sea level rise then increase conflicts for the land. Heat waves occur more often which strengthens conflicts for land suitable for human life, meaning that inhabitable areas are spreading. Therefore there is a need to re-evaluate the character and hierarchy of resources and their accessibility, and also concepts of development. The existing development of humankind has been done at the expense of others in many cases and mainly at the expense of the environment. The current situation raises a question of climate justice from both historical and systematic viewpoints. It opens a need to reformulate the concept of human rights from the perspective of their essential environmental preconditions and to define the status of environmental migrants. (shrink)

This paper sketches an emotion-aware model of environmental ethics education. The proposal draws on insights from feminists scholars, moral sentimentalism, as well as work in the pedagogy of discomfort traditions. It identifies and defends four core elements of climate change ethic, noting how they shed new light on the aims and challenges of environmental ethics education.

Do forest owners’ levels of education or value profiles explain their responses to climate change? The cultural cognition thesis has cast serious doubt on the familiar and often criticized "knowledge deficit" model, which says that laypeople are less concerned about climate change because they lack scientific knowledge. Advocates of CCT maintain that citizens with the highest degrees of scientific literacy and numeracy are not the most concerned about climate change. Rather, this is the group in which cultural (...) polarization is greatest, and thus individuals with more limited scientific literacy and numeracy are more concerned about climate change under certain circumstances than those with higher scientific literacy and numeracy. The CCT predicts that cultural and other values will trump the positive effects of education on some forest owners' attitudes to climate change. Here, using survey data collected in 2010 from 766 private forest owners in Sweden and Germany, we provide the first evidence that perceptions of climate change risk are uncorrelated with, or sometimes positively correlated with, education level and can be explained without reference to cultural or other values. We conclude that the recent claim that advanced scientific literacy and numeracy polarizes perceptions of climate change risk is unsupported by the forest owner data. In neither of the two countries was university education found to reduce the perception of risk from climate change. Indeed in most cases university education increased the perception of risk. Even more importantly, the effect of university education was not dependent on the individuals' value profile. (shrink)

Since the release of OpenAI's ChatGPT, the world has entered a race to develop more capable and powerful AI, including artificial general intelligence (AGI). The development is constrained by the dependency of AI on the model, quality, and quantity of training data, making the AI training process highly costly in terms of resources and environmental consequences. Thus, improving the effectiveness and efficiency of the AI training process is essential, especially when the Earth is approaching the climate tipping points and (...) planetary boundaries. It is evident that AI can function better when trained to mimic certain human mental processes. Based on insights from quantum mechanics and the informational entropy-based notion of value, we suggest AI developers can enhance the AI training processes' effectiveness and efficiency by creating and implementing parameter systems that are capable of effectively assigning probabilities to informational quanta. Such systems can help reduce entropy within the system, which lowers the energy required for data storage and processing while decreasing the likelihood of information loss during training. Successfully applying the concept of information entropy-based value in AI development will be crucial for advancing generative AI and achieving AGI in a sustainable manner. (shrink)

Climate negotiations under the United Nations Framework Convention on Climate Change have so far failed to achieve a robust international agreement to reduce greenhouse gas emissions. Game theory has been used to investigate possible climate negotiation solutions and strategies for accomplishing them. Negotiations have been primarily modelled as public goods games such as the Prisoner’s Dilemma, though coordination games or games of conflict have also been used. Many of these models have solutions, in the form of equilibria, (...) corresponding to possible positive outcomes—that is, agreements with the requisite emissions reduction commitments. Other work on large-scale social dilemmas suggests that it should be possible to resolve the climate problem. It therefore seems that equilibrium selection may be a barrier to successful negotiations. Here we use an N-player bargaining game in an agent-based model with learning dynamics to examine the past failures of and future prospects for a robust international climate agreement. The model suggests reasons why the desirable solutions identified in previous game-theoretic models have not yet been accomplished in practice and what mechanisms might be used to achieve these solutions. (shrink)

This paper aims to clarify the relationship between extraversion and employees’ innovative and disclose the moderating effect of organizational innovative climate on that relationship. To this end, 300 employees were selected from various enterprises in three Chinese cities, and subjected to a questionnaire survey based on the five factor model (FFM) and 5-point Likert scale. Through statistical regressions, the author explored the effects of extraversion and organizational innovative climate have on employees’ innovative behavior. Then, the organizational innovative (...) class='Hi'>climate was divided into five dimensions, and the feature activation theory was implemented to reveal the moderating effect of each dimension on relationship between extraversion and employees’ innovation. Through the above analysis, it is concluded that extraversion has a positive effect on employees’ innovative behavior; the five dimensions of organizational innovative climate all exert a positive effect on employees’ innovative behavior; the resource support in organizational innovative climate has a moderating effect on the relationship between extraversion and employees’ innovation. The research findings shed new light on the improvement of organizational innovative and the construction of an innovative country. (shrink)

Moral circles help define the boundaries of one’s moral consideration. One’s moral circle may provide insight into how one perceives or treats other entities. A data-driven model exploration was conducted to explore predictors and prediction models. Candidate predictors were built upon past research using moral foundations and political orientation. Moreover, we also employed additional moral psychological indicators, i.e., moral reasoning, moral identity, and empathy, based on prior research in moral development and education. We used model exploration methods, i.e., Bayesian model (...) exploration, Bayesian model averaging, and elastic-net regression. The study successfully replicated past research supporting the relationship between moral foundations, political orientation, and the moral circle. Additional moral psychological constructs, such as post-conventional moral reasoning and moral identity, significantly predicted the moral circle width. The identified components of the moral circle were conceptually related to phronesis, i.e., practical wisdom. We discussed the educational implications of the findings, particularly those related to moral education focusing on phronesis cultivation, multiculturalism and global citizenship, and climate justice. (shrink)

This book provides a critical reflection on automated science and addresses the question whether the computational tools we developed in last decades are changing the way we humans do science. More concretely: Can machines replace scientists in crucial aspects of scientific practice? The contributors to this book rethink and refine some of the main concepts by which science is understood, drawing a fascinating picture of the developments we expect over the next decades of human-machine co-evolution. The volume covers examples from (...) various fields and areas, such as molecular biology, climate modeling, clinical medicine, and artificial intelligence. The explosion of technological tools and drivers for scientific research calls for a renewed understanding of the human character of science. This book aims precisely to contribute to such a renewed understanding of science. (shrink)

The EU proposal for the Artificial Intelligence Act (AIA) defines four risk categories: unacceptable, high, limited, and minimal. However, as these categories statically depend on broad fields of application of AI, the risk magnitude may be wrongly estimated, and the AIA may not be enforced effectively. This problem is particularly challenging when it comes to regulating general-purpose AI (GPAI), which has versatile and often unpredictable applications. Recent amendments to the compromise text, though introducing context-specific assessments, remain insufficient. To address this, (...) we propose applying the risk categories to specific AI scenarios, rather than solely to fields of application, using a risk assessment model that integrates the AIA with the risk approach arising from the Intergovernmental Panel on Climate Change (IPCC) and related literature. This model enables the estimation of the magnitude of AI risk by considering the interaction between (a) risk determinants, (b) individual drivers of determinants, and (c) multiple risk types. We use large language models (LLMs) as an example. (shrink)

This paper discusses ethical issues surrounding Integrated Assessment Models (IAMs) of the economic effects of climate change, and how climate economists acting as policy advisors ought to represent the uncertain possibility of catastrophe. Some climate economists, especially Martin Weitzman, have argued for a precautionary approach where avoiding catastrophe should structure climate economists’ welfare analysis. This paper details ethical arguments that justify this approach, showing how Weitzman’s “fat tail” probabilities of climate catastrophe pose ethical problems for (...) widely used IAMs. The main claim is that economists who ignore or downplay catastrophic risks in their representations of uncertainty likely fall afoul of ethical constraints on scientists acting as policy advisors. Such scientists have duties to honestly articulate uncertainties and manage (some) inductive risks, or the risks of being wrong in different ways. (shrink)

In this research, an agent-based model was developed to study the propagation of physical climate shocks through supply chain networks. By combining supply chain and financial models, the study examines the effects of climate shocks on firms’ production capacities and their subsequent impacts on firm default risk. A comprehensive mathematical framework is presented for the simulation of physical risks, their subsequent up- and downstream impacts along the supply chain, and the translation of physical impacts into an increased level (...) of default risk. The results highlight the importance of supply chains as a transmission channel for physical climate risks and emphasize the effectiveness of implementing adaptation measures. Practical examples demonstrate the model’s behavior under different hypothetical climate scenarios and identify the sectors most vulnerable to increases in the frequency and intensity of climate events. Overall, this study provides insights into the transmission dynamics of climate shocks and emphasizes the need for resilience against climate events in supply chain networks. (shrink)

I address questions about values in model-making in engineering, specifically: Might the role of values be attributable solely to interests involved in specifying and using the model? Selected examples illustrate the surprisingly wide variety of things one must take into account in the model-making itself. The notions of system, and physically similar systems are important and powerful in determining what is relevant to an engineering model. Another example illustrates how an idea to completely re-characterize, or reframe, an engineering problem arose (...) during model-making. I employ a qualitative analogue of the notion of physically similar systems. Historical cases can thus be drawn upon; I illustrate with a comparison between a geoengineering proposal to inject, or spray, sulfate aerosols, and two different historical cases involving the spraying of DDT. The current geoengineering proposal is seen to be like the disastrous and counterproductive case, and unlike the successful case, of the spraying of DDT. I conclude by explaining my view that model-making in science is analogous to moral perception in action, drawing on a view in moral theory that has come to be called moral particularism. (shrink)

The Latin America and the Caribbean (LAC) region is a distinct geographic, economic and cultural area with a place in the climate change landscape. LAC has suffered the impacts of climate change at a level disproportionate to the amount of emissions it produces. Awareness of this experience, in addition to factors such as the region’s large young population, increasing middle class, vast natural resources and considerable economic growth potential provide reasons to hope LAC can implement significant climate (...) change policies to meet its Paris commitments. Springing from its cultural and historical affinities, the region has borne a flurry of polycentric initiatives promoting exchange, integration and coordinated approaches to common problems. Climate policy implementation to meet Paris commitments is still incipient, with some of its countries serving as models, some as laggards and the rest positioned somewhere in between. For this reason, partnerships with regions which have advanced more in this area can prove useful. The EU-CELAC summits and the Euroclima program are two examples. Due to its high levels of inequality and social unrest, the key challenge to implementing climate policies in LAC will be the strengthening of a political atmosphere where human rights, the rule of law and democratic values prevail. (shrink)