计算机与社会
In the age of generative AI and ubiquitous digital tools, human cognition faces a structural paradox: as external aids become more capable, internal memory systems risk atrophy. Drawing on neuroscience and cognitive psychology, this paper…
Urban digital twins are increasingly perceived as a way to pool the growing digital resources of cities for the purpose of a more sustainable and integrated urban planning. Models and simulations are central to this undertaking: They enable…
Language model agents are poised to mediate how people navigate and act online. If the companies that already dominate internet search, communication, and commerce -- or the firms trying to unseat them -- control these agents, the resulting…
In recent years, Artificial Intelligence (AI) models have grown in size and complexity, driving greater demand for computational power and natural resources. In parallel to this trend, transparency around the costs and impacts of these…
Ride-sharing platforms like Uber market themselves as enabling `flexibility' for their workforce, meaning that drivers are expected to anticipate when and where the algorithm will allocate them jobs, and how well remunerated those jobs will…
As Large Language Models (LLMs) increasingly appear in social science research (e.g., economics and marketing), it becomes crucial to assess how well these models replicate human behavior. In this work, using hypothesis testing, we present…
AI that can accelerate research could drive a century of technological progress over just a few years. During such a period, new technological or political developments will raise consequential and hard-to-reverse decisions, in rapid…
Traditionally, the introductory programming course for computer science students at Nuremberg Tech had been implemented as a combination of lectures and exercise sessions. Due to high failure rates in the winter semester 2023/24, an…
As AI systems continue to spread and become integrated into many aspects of society, the concept of "human-centered AI" has gained increasing prominence, raising the critical question of which humans are the AI systems to be centered…
Leadership in the field of AI is vital for our nation's economy and security. Maintaining this leadership requires investments by the federal government. The federal investment in foundation AI research is essential for U.S. leadership in…
Influencer marketing has become a crucial feature of digital marketing strategies. Despite its rapid growth and algorithmic relevance, the field of computational studies in influencer marketing remains fragmented, especially with limited…
Despite the rapid proliferation of generative AI in higher education, students in China face significant barriers in accessing global tools like ChatGPT due to regulations and constraints. Grounded in the Unified Theory of Acceptance and…
This paper presents a characterization of AI-generated images shared on 4chan, examining how this anonymous online community is (mis-)using generative image technologies. Through a methodical data collection process, we gathered 900 images…
The increasing availability and use of artificial intelligence (AI) tools in educational settings has raised concerns about students' overreliance on these technologies. Overreliance occurs when individuals accept incorrect AI-generated…
Synthetic data, which is artificially generated and intelligently mimicking or supplementing the real-world data, is increasingly used. The proliferation of AI agents and the adoption of synthetic data create a synthetic mirror that…
The proliferation of Large Language Models (LLMs) in high-stakes applications such as medical (self-)diagnosis and preliminary triage raises significant ethical and practical concerns about the effectiveness, appropriateness, and possible…
The rapid advancement of artificial intelligence has raised concerns about its potential to facilitate biological weapons development. We argue existing safety assessments of contemporary foundation AI models underestimate this risk,…
As machine learning systems become increasingly embedded in society, their impact on human and nonhuman life continues to escalate. Technical evaluations have addressed a variety of potential harms from large language models (LLMs) towards…
The shift towards pluralism in global data ethics acknowledges the importance of including perspectives from the Global Majority to develop responsible data science practices that mitigate systemic harms in the current data science…
Algorithmic discrimination is a critical concern as machine learning models are used in high-stakes decision-making in legally protected contexts. Although substantial research on algorithmic bias and discrimination has led to the…