Transdisciplinary AI Observatory -- Retrospective Analyses and Future-Oriented Contradistinctions

AI observatories need multiple perspectives: The paper argues that effective AI safety monitoring requires a "transdisciplinary" approach that integrates diverse viewpoints rather than relying on single disciplines, recognizing that AI risks have "socio-psycho-technological impacts" affecting society in complex ways.

Distinguishing intentional from unintentional AI risks matters: The research differentiates between risks that occur accidentally versus those deliberately caused, suggesting that safety strategies need to address these distinct categories differently—a distinction often overlooked in general AI safety discussions.

Learning from past AI incidents is crucial: The paper employs "retrospective descriptive analysis" and "counterfactual risk analysis" of real AI cases, emphasizing that examining what actually happened and what could have happened provides practical lessons for preventing future problems.

Short-term AI safety consensus exists across different viewpoints: Despite disagreements about long-term AI development directions, the paper identifies that different AI safety paradigms ("artificial stupidity" and "eternal creativity") share common near-term safety guidelines, suggesting there is actionable agreement on immediate protective measures.

Long-term AI safety visions fundamentally diverge: The two major safety paradigms discussed differ "fundamentally in the nature of multiple envisaged long-term solution patterns," indicating that the field lacks consensus on how to ensure AI safety as the technology becomes more advanced.