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search.filters.applied.f.access: openAccess × Start date: 2020 × DDC: 100 × DDC: 500 × Type: Article ×

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    Values in climate modelling: testing the practical applicability of the Moral Imagination ideal
    (Heidelberg : Springer, 2022) Pulkkinen, Karoliina; Undorf, Sabine; Bender, Frida A.-M.
    There is much debate on how social values should influence scientific research. However, the question of practical applicability of philosophers’ normative proposals has received less attention. Here, we test the attainability of Matthew J. Brown’s (2020) Moral Imagination ideal (MI ideal), which aims to help scientists to make warranted value-judgements through reflecting on goals, options, values, and stakeholders of research. Here, the tools of the MI ideal are applied to a climate modelling setting, where researchers are developing aerosol-cloud interaction (ACI) parametrizations in an Earth System Model with the broader goal of improving climate sensitivity estimation. After the identification of minor obstacles to applying the MI ideal, we propose two ways to increase its applicability. First, its tools should be accompanied with more concrete guidance for identifying how social values enter more technical decisions in scientific research. Second, since research projects can have multiple goals, examining the alignment between broader societal aims of research and more technical goals should be part of the tools of the MI ideal.
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    Ethical Artificial Intelligence in Chemical Research and Development: A Dual Advantage for Sustainability
    (Dordrecht : Springer Netherlands, 2021) Hermann, Erik; Hermann, Gunter; Tremblay, Jean-Christophe
    Artificial intelligence can be a game changer to address the global challenge of humanity-threatening climate change by fostering sustainable development. Since chemical research and development lay the foundation for innovative products and solutions, this study presents a novel chemical research and development process backed with artificial intelligence and guiding ethical principles to account for both process- and outcome-related sustainability. Particularly in ethically salient contexts, ethical principles have to accompany research and development powered by artificial intelligence to promote social and environmental good and sustainability (beneficence) while preventing any harm (non-maleficence) for all stakeholders (i.e., companies, individuals, society at large) affected.