In the last years, artificial intelligence (AI) safety gained international recognition in the light of heterogeneous safety-critical and ethical issues that risk overshadowing the broad beneficial impacts of AI. In this context, the implementation of AI observatory endeavors represents one key research direction. This paper motivates the need for an inherently transdisciplinary AI observatory approach integrating diverse retrospective and counterfactual views. We delineate aims and limitations while providing hands-on-advice utilizing concrete practical examples. Distinguishing between unintentionally and intentionally triggered AI risks with diverse socio-psycho-technological impacts, we exemplify a retrospective descriptive analysis followed by a retrospective counterfactual risk analysis. Building on these AI observatory tools, we present near-term transdisciplinary guidelines for AI safety. As further contribution, we discuss differentiated and tailored long-term directions through the lens of two disparate modern AI safety paradigms. For simplicity, we refer to these two different paradigms with the terms artificial stupidity (AS) and eternal creativity (EC) respectively. While both AS and EC acknowledge the need for a hybrid cognitive-affective approach to AI safety and overlap with regard to many short-term considerations, they differ fundamentally in the nature of multiple envisaged long-term solution patterns. By compiling relevant underlying contradistinctions, we aim to provide future-oriented incentives for constructive dialectics in practical and theoretical AI safety research.

中文翻译：

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跨学科AI天文台-回顾性分析和面向未来的矛盾

在过去的几年中，鉴于各种各样的安全关键和道德问题有可能掩盖AI的广泛有益影响，人工智能（AI）安全获得了国际认可。在这种情况下，实施AI天文台工作代表了一个关键的研究方向。本文激发了一种固有的跨学科AI观测方法的需求，该方法整合了各种回顾性和反事实性观点。我们在描述目标和局限性的同时，利用具体的实际示例提供动手建议。区分具有多种社会心理技术影响的无意和有意触发的AI风险，我们举例说明了回顾性描述性分析，然后进行了分析。回顾性事实风险分析。在这些AI观测工具的基础上，我们介绍了AI安全的近期跨学科指南。作为进一步的贡献，我们通过两种截然不同的现代AI安全范例讨论了差异化和量身定制的长期方向。为了简单起见，我们分别用术语“人工愚蠢”（AS）和“永恒创造力”（EC）来指代这两种不同的范例。尽管AS和EC都承认需要采用混合认知-情感方法来实现AI安全，并且在许多短期考虑方面存在重叠，但它们在多种设想的长期解决方案模式的本质上存在根本差异。通过汇编相关的基本矛盾，我们旨在在实践和理论上的AI安全性研究中为建设性辩证法提供面向未来的激励措施。