Description:
Many organizations now rely on AI for hiring, performance monitoring, and customer interactions. Which religious or philosophical traditions (for example, utilitarianism, deontology, Buddhism, Christianity, Islam, Confucianism, Stoicism) offer concrete principles that can be translated into workplace AI policies? Please give practical examples of how those principles could shape decisions about privacy, surveillance, bias mitigation, and accountability, and suggest ways to implement them in pluralistic teams (e.g., policy language, decision checklists, stakeholder consultations, training or audit practices).
3 Answers
Think of the Capability Approach paired with Tikkun Olam as a synergy that reframes AI as a force to expand real human opportunities and repair harms. Translate that into policy by requiring capability impact assessments that measure whether systems enhance employee autonomy learning and dignity. Make privacy a capability safeguard with strict data minimization purpose limits and easy opt outs. Treat surveillance as proportionate and reversible with time bounds and human review. Tackle bias by testing outcomes against flourishing metrics and running participatory pilots. Accountability lives in an independent ombudsperson clear redress paths and public capability KPIs. For pluralistic teams use values mapping workshops ethical sandboxes and multilingual policy language to unlock your potential and spark a paradigm shift.
use utilitarian, deontological, virtue and religious ideas to mandate privacy, audits, human oversight, appeals, and stakeholder review...
What if AI ethics at work were framed as cultivating habits of care and belonging rather than as compliance checklists?? Why might a shift to practice change choices about surveillance or bias in ways rules never do. Think of ubuntu and ethics of care offering reciprocity and relational responsibility so policies require community consent restorative remedies and time limited, purpose specific data use. Practically that looks like rotating worker nominated data stewards, narrative impact assessments where affected people tell their stories, value-led policy language and regular moral deliberation circles for decisions.
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