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The grand humanist project of technological advancements has culminated in fascinating intelligent technologies and AI-based automated decision-making systems (ADMS) that replace human decision-makers in complex social processes. Widespread use of ADMS, underpinned by humanist values and ethics, it is claimed, not only contributes to more effective and efficient, but also to more objective, non-biased, fair, responsible, and ethical decision-making. Growing literature however shows paradoxical outcomes: ADMS use often discriminates against certain individuals and groups and produces detrimental and harmful social consequences. What is at stake is the reconstruction of reality in the image of ADMS, that threatens our existence and sociality. This presents a compelling motivation for this article which examines a) on what bases are ADMS claimed to be ethical, b) how do ADMS, designed and implemented with the explicit aim to act ethically, produce individually and socially harmful consequences, and c) can ADMS, or more broadly, automated algorithmic decision-making be ethical. This article contributes a critique of dominant humanist ethical theories underpinning the development and use of ADMS and demonstrates why such ethical theories are inadequate in understanding and responding to ADMS' harmful consequences and emerging ethical demands. To respond to such ethical demands, the article contributes a posthumanist relational ethics (that extends Barad's agential realist ethics with Zigon's relational ethics) that enables novel understanding of how ADMS performs harmful effects and why ethical demands of subjects of decision-making cannot be met. The article also explains why ADMS are not and cannot be ethical and why the very concept of automated decision-making in complex social processes is flowed and dangerous, threatening our sociality and humanity.
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Stored only when both papers are in the corpus — 16 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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