Pluralistic Alignment Over Time

TL;DR

This paper discusses the importance of evaluating AI alignment over time, considering changing stakeholder preferences and satisfaction, and proposes applying fairness evaluation methods to achieve temporal pluralism in AI systems.

Contribution

It introduces the concept of temporal pluralism, advocating for AI systems to adapt to stakeholders' evolving values and preferences over time.

Findings

Proposes applying fairness over time to pluralistic alignment

Highlights the need to consider changing stakeholder satisfaction

Suggests a framework for temporal adaptation in AI alignment

Abstract

If an AI system makes decisions over time, how should we evaluate how aligned it is with a group of stakeholders (who may have conflicting values and preferences)? In this position paper, we advocate for consideration of temporal aspects including stakeholders' changing levels of satisfaction and their possibly temporally extended preferences. We suggest how a recent approach to evaluating fairness over time could be applied to a new form of pluralistic alignment: temporal pluralism, where the AI system reflects different stakeholders' values at different times.