计算机与社会

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,"…

Open source software (OSS) is not homogeneous. A project's purpose, governance, and funding shape how its community forms, who contributes, and how the software is maintained, yet empirical research often samples OSS broadly and reports…

Human-annotated data remains foundational for machine learning and social media analysis. However, traditional data collection often relies on cumbersome pipelines that isolate content from its original source, compromising ecological…

Corporate sponsorship is increasingly prevalent at computer science conferences. However, a quantitative understanding of this phenomenon has yet to be established, let alone insights into the interplay between academic conferences and…

Agentic AI systems generate runtime records, logs, traces, and audit artefacts, but the existence or integrity of such records does not by itself establish that legally operative oversight findings can be recovered from them. This technical…

Advances in generative AI are rapidly increasing the quality and commercial value of generated music, and this progress depends on large catalogs of creators' recordings. This raises a central question for platform design: how should…

In the current era of great-power competition and the diffusion of emerging disruptive technologies on the battlefield, NATO's approach to coordinating the development, adoption, and standardization of new technologies is changing from its…

As computing education expands beyond traditional programming into operational domains such as systems administration and command-line environments, existing pedagogical frameworks struggle to capture a dimension that is critical in these…

Emotional bonds between humans and AI companions are growing, and the question of whether a person may marry an AI system will soon move from speculative fiction into law. This chapter examines whether the autonomy-centered logic that has…

Research on artificial intelligence (AI) in the public sector often treats "AI" as a single category, neglecting technical distinctions between different AI systems. But these distinctions affect how different systems impact core public…

Flaw reporting for deployed AI systems is fundamental to identifying system failures and improving AI safety. Yet the AI reporting ecosystem is fragmented: researchers who identify flaws often do not know what or where to report, and groups…

Since the introduction of the GDPR in 2018, cookie banners have become the primary mechanism for users to express preferences on online tracking and advertising. Consequently, their visual design and the options they present significantly…

Agentic artificial intelligence is increasingly deployed not as a single assistant but as a collective of planners, solvers, reviewers, memory managers, tool users, and orchestrators. These systems are entering organisational workflows…

Recent studies argue that LLMs can predict human stereotypical judgments. Yet whether LLMs emulate the cognitive processes underlying human stereotypes, or merely retrieve learned associations to solve prediction tasks, remains unclear.…

Student access to Large Language Models (LLMs) is reshaping learning behaviors; at the same time students are entering the workforce where effective LLM use is becoming an expected skill. In this Experience Report we share our DURA…

Community Notes, a bridging-based crowd-sourced fact-checking system, has emerged as a new mechanism for moderating misleading information on social media and has been adopted by major platforms including X, Facebook, Instagram, Threads,…

As large language models (LLMs) become common in computing courses, we need to understand how the social setting shapes how students use them. This paper reports findings from a semester-long study of 96 undergraduate students who completed…

Using 380 trillion tokens of realized AI consumption across more than four hundred large language models from the licensed proprietary OpenRouter dataset covering approximately 2 percent of current global monthly AI token consumption, we…

Prompt-based programming, a new modality enabled by large language models (LLMs), allows users to express computational goals through natural language rather than traditional code. While this approach lowers barriers to entry, especially…

Current large language models are extraordinary statistical engines. They compress vast amounts of text into useful patterns and can explain science, write code, imitate reasoning, and participate in philosophical conversation. Yet pattern…