Simon Hollnaicher

This chapter introduces the book's research question and explains its relevance. The book is concerned with the concept of feasibility and how scientific assessments in the climate context engage with it. Feasibility is a central concept in political philosophy and has been prominently featured in recent climate discourse. Integrated Assessment Models are scientific models that project various climate futures for given climate goals and thereby provide scenario evidence on the feasibility of climate goals and different mitigation strategies. The central philosophical problem of the book is introduced as the value problem in assessing feasibility. The question is how we can assess the seemingly empirical concept of feasibility with value-laden models, which inherently and deeply depend on a range of value assumptions. The book attempts to explain how the models can contribute to assessing feasibility, while at the same time critically discussing their normative basis and evaluating modeling practices in light of a principal solution to the value problem. This chapter outlines the content and argument the book makes and what it contributes to the existing literature.

This chapter argues that feasibility judgments are inherently value-laden and that recognizing this value dimension helps address two key conceptual challenges in the feasibility debate. It begins by introducing the widespread assumption that feasibility is a purely descriptive concept and that this notion helps separate scientific facts from values. The chapter then surveys conceptual contributions that challenge this separation and argues for a “thick” conception of feasibility, building on Wiens’ account. The proposed thick conception integrates value judgments in three ways: by excluding unacceptable means, rejecting measures with unacceptable side effects, and setting value-laden thresholds for acceptable levels of uncertainty. This value-laden understanding of feasibility addresses the first challenge of distinguishing feasibility from mere practical possibility. The chapter argues that the normative role of feasibility as ruling out proposals can be refined as demarcating options that are worthy of deliberation. This sense of ruling out is compatible with thick feasibility. Finally, it recovers the comparative sense of feasibility through related, value-laden concepts—such as options being “more challenging” or “more realistic”—thereby addressing the second challenge.

This chapter argues for understanding feasibility as a form of restricted possibility, drawing on Wiens’ (2015) account, and demonstrates its fittingness and relevance to understanding scientific feasibility assessments in the climate context. Feasibility concerns the question of how we can achieve a particular outcome. An outcome is feasible when there is a trajectory from here to the outcome in question that is compatible with the various limitations we face. The chapter begins with four illustrative anecdotes of feasibility judgments made by various actors in the climate policy debate. The chapter then reviews two prominent philosophical accounts of feasibility. The Conditional Probability Account defines feasibility as the probability of success given an agent’s efforts but is critiqued for being too narrow for assessing complex social goals. In contrast, Wiens’ conception of feasibility as restricted possibility – attainability constrained by available resources and processes – captures the pathway-oriented nature of feasibility assessments better in scientific and policy contexts. However, the chapter argues that Wiens’ account faces two unresolved challenges: distinguishing feasibility from mere practical possibility and explaining how we sometimes make meaningful comparative feasibility claims among policy options.

This chapter examines how the goal of objectivity in scientific policy assessments can be achieved despite the value-laden nature of Integrated Assessment Models (IAMs). It begins by outlining the legitimacy challenge faced by scientific assessments: if IAMs embed specific value judgments, they risk unduly influencing policy decisions and undermining their perceived neutrality. To address this, the chapter proposes three principles for ensuring legitimate and objective scientific assessments with IAMs. Value Transparency: Value judgments in IAMs must be made explicit and presented as separate premises of the results. Value Plurality: IAM scenarios should represent a diverse range of viable value outlooks, ensuring that different kinds of mitigation strategies are supported by scientific evidence. Democratic Endorsement: Deliberative venues should be established to involve the public in legitimizing the value judgments embedded in models and scenarios, fostering democratic endorsement. These principles offer a provisional solution to the problem of legitimacy, demonstrating how scientific assessments can remain credible and authoritative while acknowledging the normative dimensions of IAMs.

This chapter provides a detailed taxonomy of the value judgments embedded in Integrated Assessment Models (IAMs) and their outputs. It identifies eight aspects and areas of integrated modeling where value judgments influence scenario evidence, shaping how feasibility is assessed: (1) in choosing feasibility indicators and defining constraints, (2) in agenda-setting, (3) in the cost-effectiveness framework against other burden sharing principles, (4) in the conceptualization of well-being, (5) in representing global and social inequality, (6) in representing intergenerational inequality, especially in discounting future costs, (7) in defining the modeling domain, and (8) in the handling of uncertainty and inductive risk. For each aspect, the chapter explicates the embedded value judgments, contextualizes common modeling practices, and contrasts them with alternative value perspectives.

This chapter summarizes the findings of the book, offering a concise version of the answer the book gives to the “value problem in assessing feasibility”. It provides an overview of the book's argument, outlining how each chapter contributes to addressing this issue. The chapter also reflects on the book’s limitations, acknowledging the diversity within the field of integrated modeling and the normative standpoint adopted in the discussion. The chapter situates the book’s contribution within existing debates, emphasizing how it advances understanding of feasibility assessments in value-laden contexts. Finally, it cautions that despite their inherent value-dependence, Integrated Assessment Models convey a clear and robust call to action—the current trajectory of emissions must be decisively reversed to achieve sustainable futures.

The concluding chapter of the book critiques the current state of evidence produced by Integrated Assessment Models (IAMs), highlighting how biases in these models risk perpetuating existing injustices under the guise of seemingly neutral feasibility assessments. Three key biases are identified: a tendency to shift burdens to future generations, a deflection of responsibility from current major emitters, and a favoritism toward entrenched interests. These biases undermine the legitimacy of IAMs, as their pathways wield significant influence in shaping visions of the future. The chapter argues that IAMs obscure their normative dimension in two ways. First, value-laden assumptions made to render pathways “more realistic” often masquerade as neutral feasibility judgments. Second, presenting IAM outputs as feasibility assessments falsely conveys an image of objectivity, masking the models' normative dimensions. In response, the chapter emphasizes the need for ethically explicit scenarios incorporating justice considerations into scenario design. Ethicists must actively engage with IAMs to address these biases. Finally, revisiting the metaphor of modelers as mapmakers, the chapter proposes a type of value-explicit map design to be most fitting.

This chapter introduces Integrated Assessment Models (IAMs) and explains how the models increasingly engage with feasibility. Beginning with a brief history of IAMs, the chapter distinguishes between two primary classes of IAMs: Cost-Benefit IAMs (CB-IAMs) and Process-Based IAMs (PB-IAMs). While CB-IAMs focus on optimizing the balance between mitigation costs and climate impacts and have been extensively debated in philosophical circles, PB-IAMs remain relatively underexplored in climate philosophy and ethics despite their centrality to the science-policy interface. PB-IAMs differ from CB-IAMs by taking predefined climate goals – such as temperature targets – as fixed inputs and modeling the “mitigation pathways” required to achieve them. The chapter outlines the value PB-IAMs provide in understanding the complex interactions and dynamics at the heart of climate change mitigation. The chapter goes on to explain how IAMs use scenarios to explore possible futures and traces the recent evolution of PB-IAMs, particularly their increasing application in assessing the feasibility of climate goals and pathways. It is this recent history of assessing feasibility that should be of particular interest to climate philosophy.

This chapter explores how Integrated Assessment Models (IAMs) can contribute to feasibility assessments of climate goals, building on the conceptual groundwork established in earlier chapters. It argues that feasibility judgments require considering all relevant constraints simultaneously and accounting for complex, dynamic pathways of change – strengths inherent to IAMs. Solvable scenarios within IAMs can serve as evidence for the feasibility of specific climate goals, but such evidential claims depend on context-sensitive background assumptions. The chapter critically examines current methods of evaluating these assumptions, arguing that existing practices of model evaluation in IAMs fall short. Empirical testing approaches, including “appeals to the past,” fail to provide robust support due to high uncertainty and misaligned epistemic aims. The chapter critiques one recent empirical framework for assessing feasibility with IAMs (Brutschin et al., 2021) in more detail, arguing that it does not adequately address these issues. The chapter argues that feasibility assessment must pay closer attention to value judgments. Bringing in the perspective of values in science will provide a more solid and transparent ground for assessing feasibility with IAMs.

In this Open-Access-book, the author investigates the value dimension of Integrated Assessment Models and their application to questions of feasibility. Integrated models provide a quantified representation of the interaction between the socio-economic system with the climate and serve as a pivotal tool at the intersection of climate science, policymakers, and society. This book critically examines how IAMs approach the concept of feasibility. It unpacks the value assumptions embedded within integrated modeling, critiques the implicit normativity of these models, and proposes principles for responsibly managing value judgments in scientific advice. Arguing for a thick conception of feasibility—one that integrates key normative dimensions—it highlights the gap between conceptual discussions of feasibility and the scientific practices that inform feasibility assessments. Addressed to both philosophers and integrated modelers, this book sheds light on the implicit values shaping our collective visions for the future.

This paper analyzes the nonepistemic value judgments involved in modeling Carbon Dioxide Removal (CDR) techniques. The comparably high uncertainty of these techniques gives rise to epistemic risk when large-scale CDR is relied upon in most scenario evidence. Technological assumptions on CDR are thus entangled with nonepistemic value judgments. In particular, the reliance on large-scale CDR implies shifting risk to future generations and thereby gives a one-sided answer to questions of intergenerational justice. This bias in integrated assessment modeling is problematic given the policy-advising role of integrated modeling. Modeling climate mitigation should focus on transforming these implicit value positions into explicit scenario parameters and should aim to provide scenario evidence on the complete array of value-laden mitigation strategies.

According to a well-known problem in climate ethics, individual actions cannot be wrong due to their impact on climate change since the individual act does not make a difference. By referring to the practical interpretation of the categorical imperative, the author argues that certain actions lead to a contradiction in conception in light of the climate crisis. Universalizing these actions would cause foreseeable climate impacts, making it impossible to pursue the original maxim effectively. According to the practical interpretation, such actions are morally wrong. The wrongness of these actions does not depend on making a difference, rather these actions are wrong because they make it impossible for others to act accordingly. Thus, apart from imperfect duties, for which has been argued convincingly elsewhere, we also have perfect duties to refrain from certain actions in the face of the climate crisis.