APA paper proposes a pipeline to keep AI alignment updated as values change

sebkrier · x · 2026-07-26

• The paper proposes Adaptive Pluralistic Alignment (APA), a modular pipeline for updating AI systems as societal values change over time.
• APA has three stages: compact personalized reward models, a jury that selects outputs via social-choice style voting, and continual adaptation of jury weights as annotator preferences shift.
• The authors argue this avoids value lock-in and reduces the need to retrain from scratch or repeatedly collect large new preference datasets.
• A proof-of-concept using the PRISM multi-user alignment dataset suggests that jury composition and voting rule can materially affect outcomes, especially when preferences are heterogeneous.
• The code and resulting preference datasets are published on GitHub.

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