Pluralistic Alignment Over Time
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866916485371265024 |
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| author | Klassen, Toryn Q. Alamdari, Parand A. McIlraith, Sheila A. |
| author_facet | Klassen, Toryn Q. Alamdari, Parand A. McIlraith, Sheila A. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_10654 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Pluralistic Alignment Over Time Klassen, Toryn Q. Alamdari, Parand A. McIlraith, Sheila A. Artificial Intelligence Computers and Society Machine Learning 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. |
| title | Pluralistic Alignment Over Time |
| topic | Artificial Intelligence Computers and Society Machine Learning |
| url | https://arxiv.org/abs/2411.10654 |