计算机与社会
Street-level bureaucrats, such as caseworkers and border guards routinely face the dilemma of whether to follow rigid policy or exercise discretion based on professional judgement. However, frequent overrides threaten consistency and…
Generative AI tools are increasingly used for legal tasks, including legal research, drafting documents, and even for legal decision-making. As for other purposes, the use of GenAI in the legal domain comes with various risks and benefits…
The integration of Artificial Intelligence (AI) into Higher Education Institutions (HEIs) in Ecuador is not a technological option but a strategic imperative to prevent institutional obsolescence and academic irrelevance in Latin America.…
The growing adoption of AI-driven smart home devices has introduced new privacy risks for domestic workers (DWs), who are frequently monitored in employers' homes while also using smart devices in their own households. We conducted…
The accelerating militarization of artificial intelligence has transformed the ethics, politics, and governance of warfare. This article interrogates how AI-driven targeting systems function as epistemic infrastructures that classify,…
Recent reports claim that Large Language Models (LLMs) have achieved the ability to derive new science and exhibit human-level general intelligence. We argue that such claims are not rigorous scientific claims, as they do not satisfy…
Privacy is a human right that sustains patient-provider trust. Clinical notes capture a patient's private vulnerability and individuality, which are used for care coordination and research. Under HIPAA Safe Harbor, these notes are…
The rapid expansion of artificial intelligence in public governance has generated strong optimism about faster processes, smarter decisions, and more modern administrative systems. Yet despite this enthusiasm, we still know surprisingly…
The widespread use of foundation models has introduced a new risk factor of copyright issue. This issue is leading to an active, lively and on-going debate amongst the data-science community as well as amongst legal scholars. Where claims…
This workshop paper examines challenges in designing agentic AI systems from a citizen-centric perspective. Drawing on three participatory workshops conducted in 2025 with members of the general public and cross-sector stakeholders, we…
Ethnography attends to relations among people, practices, and the technologies that mediate them. Central to this method is the duality of roles ethnographers navigate as researchers and participants and as outsiders and insiders. However,…
The field of AI alignment is increasingly concerned with the questions of how values are integrated into the design of generative AI systems and how their integration shapes the social consequences of AI. However, existing transparency…
After almost four decades of participating in competitive research funding -- as applicant, coordinator, evaluator, and panel member -- I have come to see a structural paradox: many participants recognize that the current system is…
Integration of AI into environmental regulation represents a significant advancement in data management. It offers promising results in both data protection plus algorithmic fairness. This research addresses the critical need for…
Tokenization constitutes a fundamental stage in Large Language Model (LLM) processing; however, subword-based tokenization methods optimized on English-dominant corpora may produce token fragmentation misaligned with the linguistic…
The purpose of this study is to introduce a new model of teaching Chinese as a foreign language from the perspective of integrating wisdom. Its characteristics are as follows: focusing on the butterfly model of interpretation before…
AI systems are increasingly used in high-stakes domains such as credit rating, where fairness concerns are critical. Existing fairness assessments are typically conducted by AI experts or regulators using predefined protected attributes and…
This work examines how leading generative artificial intelligence companies construct and communicate the concept of "safety" through public-facing documents. Drawing on critical discourse analysis, we analyze a corpus of corporate…
AI safety benchmarks are pivotal for safety in advanced AI systems; however, they have significant technical, epistemic, and sociotechnical shortcomings. We present a review of 210 safety benchmarks that maps out common challenges in safety…
We outline a vision for frontier AI auditing, which we define as rigorous third-party verification of frontier AI developers' safety and security claims, and evaluation of their systems and practices against relevant standards, based on…