cs.CY · 2026-09-11 · No. 112

Computers and Society, 2026-09-11.

3 new papers in cs.CY. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

3 entries
  1. 01

    Buyer Artificial Intelligence-Enabled Environmental Governance and Supplier Environmental Controversies: An Organizational Information Processing and Signaling

    Yongchao Martin Ma, Xinya Guan

    cs.CY · cs.AI · stat.AP

    Environmental controversies in global supply chains pose significant risks for global buyers. This study examines whether overseas suppliers' exposure to buyers' artificial intelligence (AI)-enabled environmental governance reduces supplier environmental controversies. Drawing on organizational information processing theory and signaling theory, we investigate how suppliers' exposure to AI-enabled governance influences their environmental...

    arxiv.org/abs/2609.11391 · PDF

  2. 02

    Characterizing Bluesky Content Moderation Service: From Automation of Service to Landscape of Harms

    Pushpdeep Singh, Sayeh Jarollahi, Ayan Majumdar, Vabuk Pahari, Abhijnan Chakraborty, Krishna P. Gummadi, Ingmar...

    cs.CY · cs.AI

    Empirical research on content moderation is fundamentally constrained by the opaque deployment of moderation systems on major social media platforms. To this end, the recent emergence of decentralized platforms with transparent, public moderation logs presents an unprecedented opportunity for independent audits. In this work, we leverage this architectural transparency to conduct the first large-scale audit of the default moderation system on...

    arxiv.org/abs/2609.11373 · PDF

  3. 03

    (Whose defaults?) Is artificial intelligence reorienting archaeological methods?

    Lorenzo Cardarelli, Roberto Ragno

    cs.CY · cs.AI · cs.CL · cs.HC

    Generative AI and the practice of "vibe coding" are changing how archaeologists carry out computational research, but their effects on the discipline's range of methods is still understudied. In this paper, we evaluate whether large language models (LLMs) are narrowing the variety of methods archaeologists use. We first analysed approximately 119,000 archaeology abstracts from Scopus, covering publications from 2010 to 2025. Using a locally...

    arxiv.org/abs/2609.11198 · PDF

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