邁向與價值一致的體系的步驟（Computers and Society）

• 2020 年 2 月 18 日
• 筆記

算法(包括AI/ML)決策工件是我們決策生態系統中已建立和正在發展的一部分。他們現在是不可或缺的工具，幫助我們管理洪水般的信息，我們試圖在一個複雜的世界作出有效的決定。當前的文獻中充滿了關於單個工件如何違反社會規範和期望的例子(例如，違反公平、隱私或安全規範)。在這種背景下，本文的討論強調了一個未被重視的觀點，即研究的重點是評估人工智能裝備的社會技術系統中的價值失調。到目前為止，對價值偏差的研究主要集中在單個技術工件的行為上。本討論主張採用更結構化的系統級方法來評估社會技術系統中的價值一致性。我們主要依靠對公平的研究來使我們的論點更加具體。我們利用這個機會來強調採用系統視角如何提高我們更好地解釋和處理價值偏差的能力。我們的討論以對優先級問題的探索結束，如果我們要確保整個系統的價值對齊，而不僅僅是單個工件，就需要關注這些問題。

原文題目：Steps Towards Value-Aligned Systems

原文：Algorithmic (including AI/ML) decision-making artifacts are an established and growing part of our decision-making ecosystem. They are now indispensable tools that help us manage the flood of information we use to try to make effective decisions in a complex world. The current literature is full of examples of how individual artifacts violate societal norms and expectations (e.g. violations of fairness, privacy, or safety norms). Against this backdrop, this discussion highlights an under-emphasized perspective in the body of research focused on assessing value misalignment in AI-equipped sociotechnical systems. The research on value misalignment so far has a strong focus on the behavior of individual tech artifacts. This discussion argues for a more structured systems-level approach for assessing value-alignment in sociotechnical systems. We rely primarily on the research on fairness to make our arguments more concrete. And we use the opportunity to highlight how adopting a system perspective improves our ability to explain and address value misalignments better. Our discussion ends with an exploration of priority questions that demand attention if we are to assure the value alignment of whole systems, not just individual artifacts.

原文作者：Osonde A. Osoba, Benjamin Boudreaux, Douglas Yeung

原文鏈接：https://arxiv.org/abs/2002.05672