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The ethical apparatus: The material-discursive shaping of ethics, autonomy, and the driverless car
(2023)
This research argues that the emergent driverless car, as a kind of autonomous vehicle, is a Foucault-ian "ethical apparatus", working as an epistemic device to materially embody and enable discursive power by generating notions of "autonomy" and "ethical decision-making". The ethical implications of AI, algorithmic, and autonomous technologies are topics of current regulatory and academic concern. This concern relates to the lack of meaningful oversight of black boxes inside AI systems, liabilities for manufacturers, and inadequate frameworks to hold AI-based socio-technical systems to account. One recent artefact, the driverless car, has taken on these concerns quite literally in the shaping of a niche discourse of the "ethics of autonomous driving". Ambitions to produce a fully autonomous vehicle based on AI technologies are constrained by speculative concerns that its decision-making in unexpected accident situations cannot be assumed to protect humans. "The ethics of autonomous driving" evaluates proposals to build "ethical machines" by examining the relationship between structures of human values and moral decision-making, and how they comport to computational architectures for decision-making. This is the first case this work takes up, chiefly organised around an analysis of a thought experiment, the Trolley Problem, and the online game, Moral Machine, that crowdsourced values to suggest approaches to an "ethics of autonomous driving". Rather than evaluate the feasibility or appropriateness of these two approaches, this work attends to the more critical issue that ethics is being proposed in terms of technologies turning on the logics of risk, speculation, and probabilistic correlations that are fundamental to how machine learning makes decisions. The concern in this work is less a normative framework or approach for a better or more appropriate ethics of autonomous driving. Rather, this work argues that what we understand as "the ethical" is being transformed when architected by, through, and for Artificial Intelligence / autonomous technologies to become their own regulators. Hence the production of autonomous driving necessitates computational infrastructures that are creating a world legible to and for the navigation of a driverless car. The author argues that this is fostering computational governance that has implications for human bodies and social relations, chiefly that conventional approaches to regulation and accountability attend to human values and decision-making rather than computational ones. A second case that this research examines is that of driverless car crashes, to examine how "autonomous" driving requires substantial embodied human knowledge and micro-work. Taken together, these two cases make an argument for how myriad practices of knowledge-production are translating the human world into something legible to the navigational needs of the car, producing changes in the human world through the actions of the car on that basis, and advancing notions of "autonomy". This work concludes with arguments for a critical reconceptualisation of ethics and ethical decision-making in AI / autonomous systems.
Companies are invited to contribute to the United Nations' 17 Sustainable Development Goals (SDGs) and sustainability management accounting (SMA) has an important role to play in achieving them. However, if companies are to address the SDGs and linkages beyond organizational boundaries, SMA needs a broader scope than is conventionally assumed. Therefore, the author advances a multi-level framework that addresses context, action-formation, and transformative contributions (CAT) in the following directions: first, an innovative systematic method that allows screening company-related SDGs and assessing corporate contributions to selected SDGs is introduced; second, management control systems are integrated to support managers in guiding employee behavior to make contributions to the SDGs; and, third, self-reinforcing mechanisms of the path-dependence theory are incorporated to serve as a guide to identifying barriers to individuals and groups becoming involved in SMA. This advanced CAT framework contributes to corporate practice and research by providing a multilevel framework that offers concrete management guidance for SMA to address the SDGs. It also facilitates analysis of both enabling and inhibiting factors at the organizational level. The advanced CAT framework has several implications for SMA: it promotes backcasting from the SDGs for benchmarking purposes, integrates different social, environmental, and economic issues, facilitates future-oriented action and transformation planning, addresses different layers such as the company as well as individuals and groups within it and enables to identify barriers hindering individuals and groups from becoming involved in SMA.
This dissertation deals with the increasingly recognized role of incumbent firms in advancing sustainability-oriented industry transitions. Incumbent firms are understood as firms-in-industries, which are embedded in established market structures and thereby contrast new entrant firms. The purpose of this research is twofold. First, to provide empirical evidence of barriers to and success factors of incumbent-driven industry transitions. Second, to unify hitherto dispersed descriptions of transition-related firm behaviour in a new understanding of incumbent firms in industry transitions. To this end, theoretical concepts are discussed and extended on the basis of different empirical studies in the German meat industry. The meat industry serves as suitable research setting due to its diverse sustainability challenges, ranging from climate change and pollution to animal welfare and public health, as well as its current developments towards sustainable protein alternatives. The meat context also offers opportunities to delve into individual-level processes influencing transition-related behaviour. The main contribution of this dissertation is a Multi Embeddedness Framework (MEF) that details processes and outcomes of integrated incumbent firm behaviour, including passive, reactive and proactive behaviors. The framework acknowledges the diversity in incumbent firm behaviors within industries and firms and provides new insights into transition-related behaviors at firm and individual level. With regard to the latter, the potential of learning about and from innovative start-up firms as well as shared sensemaking processes are discussed. The contents of this dissertation provide valuable contributions to the transition literature as well as important management implications with regard to the stimulation and promotion of proactive behaviors
The Sustainable Development Goals (SDGs) recognize the importance of the inextricable link between social and ecological systems and human quality of life (QoL) and biodiversity. Therefore, understanding the feedback and interactions between biodiversity, nature’s contributions to people (NCP), and QoL plays a central role in advancing toward sustainability. In this context, the social-ecological systems (SES) approach has advanced on the subject, particularly in recent decades; however, much remains to be done to comprehensively understand these relationships and interactions, especially at local decision-making scales. In this thesis, through the lenses of the SES approach, the researcher investigates connections between biodiversity, NCP, and QoL in a tropical dry forest (TDF) on the Western coast of Mexico. This place is one of the best-known Neotropical TDF and has been the focus of SES research in the past 20 years, making it an excellent case study for exploring these connections. First, to approach the need for dialogue among different global and local scales and between global and local frameworks, the thesis identifies five key components of the SES dynamics-(1) ecological supply, (2) co-production of NCP, (3) management, (4) demand, and (5) benefits - and three local decision-making scales of analysis: individual plot, smallholder, and land tenure or governance units. A literature review was performed on the social-ecological indicators for the last 11 years in the Chamela-Cuixmala region to operationalize this framework. Second, this thesis uses social-ecological information to identify social-ecological systems units (SESU) spatially explicitly. A methodology was provided to spatially identify the components of social-ecological systems that environmental conditions and management practices have shaped at three previously stated relevant decision-making scales: plots owned by individuals, plot owners, and governance units. To do so, the research group identified and characterized: (1) ecological clusters (EC), (2) social-management clusters (SC), and (3) SESU in a TDF in western Mexico. The findings suggested that decision-makers (ejidatarios, i.e., type of ownership (related to agrarian reform), that in most cases the land allocated is small-smallholders) are bounded by the topographical characteristics and the public policies that determine communal (or private) governance and the number of resources available to them. Finally, the thesis examines the self-perceived QoL across the different SESU, finding 48 QoL items, which were grouped into six categories: 1) social capital, 2) economic capital, 3) agency, 4) nature, 5) peasant non-work activities, and 6) government and services; and two additional dimensions referred to obstacles and enablers of QoL. The researchers found that the more land cover transformation, the more enablers, and obstacles of QoL are identified; emphasis was put on economic capital to achieve QoL. As management is intensified and governance fosters individualism across SES, the higher the Current Welfare Index, and the lower the self-perceived material and non-material satisfaction.
Environmental governance beyond borders: Governing telecoupled systems towards sustainability
(2023)
This doctoral dissertation analyses the environmental governance of long-distance social-ecological interactions in telecoupled systems in two issue domains: global commodity chains and infrastructure projects as part of China’s Belt and Road Initiative (BRI). Although both domains involve different governance actors, institutions and processes, they both concern the question of how the involved actors develop governance structures and institutional responses to telecoupling. This dissertation aims to contribute to a deeper understanding of how to govern environmental problems that are associated with global flows. Since many multilateral environmental governance initiatives have not yet produced the desired solutions to global problems, particular attention is directed at unilateral state-led governance approaches. This dissertation addresses the questions of (1) how to achieve a spatial fit between the scale of telecoupled systems and the scale of governance institutions, (2) how governance actors exercise agency in governing telecoupled systems, and (3) how state actors can govern the domestic and foreign environmental effects of telecoupled flows. The results show that creating a spatial fit in the governance of global commodity flows is challenging because boundary and resolution mismatches can emerge. Boundary mismatches denote situations where social-ecological problems transcend established jurisdictional boundaries, whereas resolution mismatches refer to governance institutions that have too coarse a spatial resolution to allow them to address the specific aspects of social-ecological problems effectively. No single governance institution is likely to avoid all mismatches, which highlights the need to align multiple governance approaches to effectively govern telecoupled systems.
This dissertation evaluated the efficacy of three different internet-based interventions that can be regarded as indirect interventions to reduce depression since they primarily targeted risk factors for depression. For this purpose three registered randomized controlled trials were conducted. In addition to assessing the efficacy of the interventions regarding the primary outcomes, the efficacy to reduce depression and further secondary outcomes was studied. In Study I (N=200) the efficacy of an internet-based stress management intervention (iSMI), which was adapted and tailored to career starting teachers, was compared to a waitlist control group (WLG). The participants of the intervention group (IG) reported significant reductions on the primary outcome perceived stress at post-intervention (T2) and three month follow-up (3-MFU). Furthermore, it was shown that the intervention indirectly also reduced depression at T2 and 3-MFU. The effects were sustained at an extended 6-MFU. Besides efficacy, the feasibility to complement the iSMI with a newly developed internet-based classroom management training was shown. Moreover, mediation analyses corroborated the role of problem- and emotion-focused coping skills in the intervention's effect on stress and the indirect effect of the intervention on depression through stress. Study II (N=262) demonstrated the efficacy of an internet- and app-based gratitude intervention on the reduction of primary assessed repetitive negative thoughts at T2 and 3-MFU, as compared to a WLG. The participants of the IG also reported significantly reduced depressive symptoms at T2, and 3-MFU, with significant clinically meaningful effects. The effects were sustained at an extended 6-MFU. Besides efficacy, mediation analyses showed that repetitive negative thinking mediated the gratitude intervention's effect on depression. Finally, Study III N(=351) showed that an internet-based intervention, tackling worries at the beginning of the COVID-19 pandemic, was effective as compared to an active mental health advice group. At T2, two weeks after randomization, the IG reported significantly reduced levels on the primary outcome worry as compared to controls. Participants of the IG also reported significantly reduced levels of depression at T2, with significant clinically meaningful reductions. The extended follow-ups in the IG indicated that the improvements from baseline were sustained until the 2-MFU and the 6-MFU. In a mediation analysis, worry was shown to mediate the intervention's effect on depression. Across all three studies a reliable deterioration of depression was occasionally observed. In summary, the studies in this dissertation demonstrated the efficacy of various indirect interventions focusing on rather common psychological problems to indirectly reduce depressive symptoms. The extent to which depression severity could be reduced is comparable to reductions found within participants with comparable baseline depression severity, in internet-based interventions directly addressing depressive symptoms. Indirect interventions are suggested to increase the uptake of interventions that reduce depressive symptoms, since they might be perceived as less stigmatizing and might broaden the range of interventions to choose from.
The research described in this dissertation focuses on developing a process to remove oligomers and suppress their formation by intercepting the aging procedure's precursors using adsorbents when biodiesel and its blends are used as fuel. So far, there has been no attempt to cause the stabilization of biodiesel and its blends using adsorbents from open literature. This investigation is one of the first studies on the use of adsorbents to mitigate biodiesel and diesel fuel's stability behavior–biodiesel blends and the removal of oligomers or suppressing the formation of high molecular mass species in aging oil. This study's primary aim has been achieved by several experimental measurements that provided results on adsorbents' effecton fuel oxidative stability, especially ester-based fuel like biodiesel and its blends. The chemical composition and some critical rheological analyses of the samples have been measured to understand their role in the oxidation of the sample by comparing the presence and absence of the adsorbents during the aging process. Furthermore, it aims to use adsorbents to suppress oligomers' formation and remove them in aging oil due to the influence of biodiesel and its blends. The research project also seeks to stabilize fuel, especially ester-based fuel like biodiesel, and its blends using the adsorbents. The adsorbents' application will enhance biodiesel's oxidative stability and its blends during long-term storage or application, focusing on its use in plug-in hybrid vehicles, emergency power plants,and generators. The combustion engine only starts in plug-in hybrid vehicles if the battery cannot supply energy on longer journeys. As a result, the fuel remains longer in plug-in hybrid vehicles. Fuels that are exposed to heat and oxygen over anextendedperiod can form aging products. These aging products lead to the formation of deposits, especially in the case of diesel fuels mixed with biodiesel content,and can, therefore, endanger the operational safety of the vehicle in critical components such as injectors or filter units.
In past digital health interventions, an issue has been that participants drop out over time which is referred to as the "law of attrition" (Eysenbach, 2005). Based on this, the study proposes that though initially, participants respond to the intervention, there is a hypothesized second diminishing effect of an intervention. However, the study suggests that on top, there is a third effect. Independent of the individual notification or nudge, people could build the knowledge, skills and practice needed to independently engage in the behavior themselves (schraefel and Hekler, 2020). Using behavioral theory and inspired by prior animal computational models of behavior, the thesis proposes a dynamical computational model to allow for a separation of intervention and internalization. It is targeted towards the specific case of the HeartSteps intervention that could not explain a diminishing immediate effect of the intervention, second hypothesized effect, while a person’s overall steps remained constant, third effect (Klasnja et al., 2019). The study incorporates a habituation mechanism from learning theory that can account for the immediate diminishing effect. At the same time, a reinforcement mechanism allows participants to internalize the message and engage in behavior independently. The simulation shows the importance of a participant’s responsiveness to the intervention and a sufficient recovery period after each notification. To estimate the model, the study uses data from the HeartSteps intervention (Klasnja et al., 2019; Liao et al., 2020), a just-in-time adaptive intervention that sent two to five walking suggestions per day. The study runs a Bayesian estimation with Stan in R. Additional validation tests are needed to estimate the accuracy of the model for different individuals. It could however serve as a template for future just-intime adaptive interventions due to its generic structure. In addition, this model is of high practical relevance as its derived dynamics can be used to improve future walking suggestions and ultimately optimize notification-based digital health interventions.
This thesis aims to contribute to a better understanding of the actual implementation of transdisciplinary research in sustainability science. Following three aims, this work likes to (1) contribute to the measurability of transdisciplinary research processes as well as their societal and academic outputs and impacts, to (2) demarcate transdisciplinary research from other modes of research in sustainability science and to (3) identify and examine the determinants that shape the contribution of transdisciplinary research to societal action for sustainable development and to scientific knowledge production. To serve these aims a mixed methods approach is applied that combines strong quantitative elements with in-depth qualitative analyses that integrate the perspectives of practitioners. This thesis provides a broad set of indicators to describe and assess transdisciplinary research that translate theoretical concepts form transdisciplinarity theory into observable variables. The indicators offer a holistic perspective on transdisciplinary research by representing research mode characteristics, societal as well as scientific outcomes of research projects and their specific context. To theoretically demarcate transdisciplinary research from other forms of research, a narrative literature review first elaborates the differences between "normal science", political use of scientific knowledge and transdisciplinarity in their underlying logics of problem definition, knowledge production and research utilization. Subsequently, these concepts were compared with perspectives and expectations of practitioners in the forest sector on integrative research settings. Moreover, a cluster analysis of data from 59 research projects identified five research modes that empirically demarcate ideal-typical transdisciplinary research from other research modes within sustainability science: (1) purely academic research, (2) practice consultation, (3) selective practitioner involvement, (4) ideal-typical transdisciplinary research and (5) practice-oriented research. Based on this finding, transdisciplinary research can be characterized as an intensive, but balanced involvement of practitioners. It incorporates not only the needs and goals of the practitioners but also their norms and values. Ideal-typical transdisciplinary research goes beyond mere consultatory research approaches and must be distinguished from what is conceptualized as applied research. Regression analysis of 81 research projects and statistical group comparisons of the five research mode clusters show that societal and academic outputs and impacts vary with specific project characteristics and combinations of project characteristics defined as research modes. The findings indicate that more interactive research modes reach more societal impacts. In particular, the involvement of practitioners in early project phases and the targeted dissemination of the research results positively affect societal impacts. This finding also aligns with practitioner expectations on integrative research and research utilization, provided by qualitative analysis. Moreover, the quantitative results show that scientific outputs and impacts decrease with the intensity of interactions, indicating a trade-off between societal and scientific outcomes and impacts. Overall, the empirical results of this thesis support the claimed effectiveness of transdisciplinary research in providing societally relevant, applicable knowledge and encourage further funding of transdisciplinary research by funding agencies.
The computational analysis and the optimization of transport and mixing processes in fluid flows are of ongoing scientific interest. Transfer operator methods are powerful tools for the study of these processes in dynamical systems. The focus in this context has been mostly on closed dynamical systems and the main applications have been geophysical flows. In this thesis, the authors consider transport and mixing in closed flow systems and in open flow systems that mimic technical mixing devices. Via transfer operator methods, They study the coherent behavior in closed example systems including a turbulent Rayleigh-Bénard convection flow and consider the finite-time mixing of two fluids. They extend the transfer operator framework to specific open flows. In particular, they study time-periodic open flow systems with constant inflow and outflow of fluid particles and consider several example systems. In this case, the transfer operator is represented by a transition matrix of a time-homogeneous absorbing Markov chain restricted to finite transient states. The chaotic saddle and its stable and unstable manifolds organize the transport processes in open systems. The authors extract these structures directly from leading eigenvectors of the transition matrix. For a constant source of two fluids in different colors, the mass distribution in the mixer and its outlet region converges to an invariant mixing pattern. In parameter studies, they quantify the degree of mixing of the resulting patterns by several mixing measures. More recently, network-based methods that construct graphs on trajectories of fluid particles have been developed to study coherent behavior in fluid flow. They use a method based on diffusion maps to extract organizing structures in open example systems directly from trajectories of fluid particles and extend this method to describe the mixing of two types of fluids.