Societal and technological progress as sewing an ever-growing, ever-changing, patchy, and polychrome quilt
Joel Z. Leibo, Alexander Sasha Vezhnevets, William A. Cunningham,, S\'ebastien Krier, Manfred Diaz, Simon Osindero

TL;DR
This paper critiques the common assumption of moral convergence in AI alignment and proposes an appropriateness framework that emphasizes conflict management, cultural diversity, and adaptive governance for ethically complex AI systems.
Contribution
It introduces the appropriateness framework as an alternative to moral unification, grounded in conflict theory and designed for persistent moral disagreement in AI systems.
Findings
Proposes four principles: contextual grounding, community customization, continual adaptation, polycentric governance.
Argues shifting from moral unification to conflict management improves AI alignment.
Highlights urgency of adopting diverse, adaptive ethical frameworks in AI design.
Abstract
Artificial Intelligence (AI) systems are increasingly placed in positions where their decisions have real consequences, e.g., moderating online spaces, conducting research, and advising on policy. Ensuring they operate in a safe and ethically acceptable fashion is thus critical. However, most solutions have been a form of one-size-fits-all "alignment". We are worried that such systems, which overlook enduring moral diversity, will spark resistance, erode trust, and destabilize our institutions. This paper traces the underlying problem to an often-unstated Axiom of Rational Convergence: the idea that under ideal conditions, rational agents will converge in the limit of conversation on a single ethics. Treating that premise as both optional and doubtful, we propose what we call the appropriateness framework: an alternative approach grounded in conflict theory, cultural evolution,…
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Taxonomy
TopicsEthics and Social Impacts of AI · Innovation, Sustainability, Human-Machine Systems · Language and cultural evolution
