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  1. AI ageism: a critical roadmap for studying age discrimination and exclusion in digitalized societies.Justyna Stypinska - 2023 - AI and Society 38 (2):665-677.
    In the last few years, we have witnessed a surge in scholarly interest and scientific evidence of how algorithms can produce discriminatory outcomes, especially with regard to gender and race. However, the analysis of fairness and bias in AI, important for the debate of AI for social good, has paid insufficient attention to the category of age and older people. Ageing populations have been largely neglected during the turn to digitality and AI. In this article, the concept of AI ageism (...)
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  • The AI doctor will see you now: assessing the framing of AI in news coverage.Mercedes Bunz & Marco Braghieri - 2022 - AI and Society 37 (1):9-22.
    One of the sectors for which Artificial Intelligence applications have been considered as exceptionally promising is the healthcare sector. As a public-facing sector, the introduction of AI applications has been subject to extended news coverage. This article conducts a quantitative and qualitative data analysis of English news media articles covering AI systems that allow the automation of tasks that so far needed to be done by a medical expert such as a doctor or a nurse thereby redistributing their agency. We (...)
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  • Distinguishing regeneration from degradation in coral ecosystems: the role of value.Elis Jones - 2021 - Synthese 199 (1-2):5225-5253.
    In this paper I argue that the value attributed to coral reefs drives the characterisation of evidence for their regeneration or degradation. I observe that regeneration and degradation depend on an understanding of what an ecosystem looks like when undegraded (a baseline), and that many mutually exclusive baselines can be given for any single case. Consequently, facts about ecological processes are insufficient to usefully and non-arbitrarily characterise changes to ecosystems. By examining how baselines and the value of reefs interact in (...)
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