cs.CY · 2026-07-06 · No. 45

Computers and Society, 2026-07-06.

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

01 — The papers

4 entries
  1. 01

    Human Capital, Not Model Benchmarks, Predicts Hybrid Intelligence in Forecasting

    Vivienne Ming

    cs.CY · cs.AI

    Whether pairing people with AI helps or hurts is usually reported as a single average effect. Using a real-money prediction market (Polymarket) as an objective, externally resolved benchmark, this pilot shows that the value of human-AI collaboration depends on a specific, measurable form of human capital. Analyzed at the level of the individual forecaster, hybrid performance is trimodal: most people either deferred to the model (matching it)...

    arxiv.org/abs/2607.02467 · PDF

  2. 02

    The Eticas AI Risk Taxonomy: Open Infrastructure for Operationalizing AI Audits

    Gemma Galdon Clavell, Pablo Accuosto, Usman Gohar

    cs.CY · cs.AI

    The rapid deployment of AI systems across high-stakes domains has created urgent demand for standardized evaluation, yet the field remains fragmented across competing risk taxonomies that catalog risks without showing how an audit is executed. At least 74 AI risk taxonomies exist, and almost all stop at the catalog. The hard part of auditing is not naming a risk but operationalizing it: turning it into a test run against a real system, a...

    arxiv.org/abs/2607.02201 · PDF

  3. 03

    Overview of Risk Assessment and Management for Intelligent Systems under the AI Act and Beyond

    Javier Irigoyen, Roberto Daza, Aythami Morales, Julian Fierrez, Ruben Tolosana, Ruben Vera-Rodriguez, Francisco...

    cs.CY · cs.AI · cs.CR

    The society and emerging risk-based regulatory frameworks for AI underscore the need for rigorous risk assessment to ensure safe and reliable AI systems. In response to this imperative, this paper presents an overview of AI risk assessment (identification and analysis) and management methodologies. It begins by reviewing the worldwide regulatory landscape that drives the need for systematic AI risk assessment. Then we characterize the...

    arxiv.org/abs/2607.02197 · PDF

  4. 04

    AI Virtue: What is "Good" Knowledge in the Age of Artificial Intelligence?

    Alan Liu

    cs.CY · cs.AI

    In the age of AI, what will be good knowledge? This article, which is accepted and forthcoming in a special issue of Modern Fiction Studies on "Cultural AI" in 2027, applies digital humanities methods to map epistemic virtues (like "true," "accurate," "creative") used in a corpus of 553 journal articles on AI published in 2024. "Creativity" comes in for special attention as an example. Exploring this discourse of value, the article considers...

    arxiv.org/abs/2607.01776 · PDF

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