Revisiting big data optimism: risks of data-driven black box algorithms for society [0.03%]
重新审视大数据的乐观主义：数据驱动的“黑箱”算法对社会的风险分析
Sachit Mahajan,Dirk Helbing
Sachit Mahajan
This paper critically examines the growing use of big data algorithms and AI in science, society, and public policy. While these tools are often introduced with the goal of increasing efficiency, the results do not always lead to greater em...
Personalised care, youth mental health, and digital technology: A value sensitive design perspective and framework [0.03%]
个性化护理、青年心理健康和数字技术：价值敏感设计视角与框架
Adam Poulsen,Ian B Hickie,Min K Chong et al.
Adam Poulsen et al.
Digital health is typically driven, in part, by the principle of personalised care. However, the underlying values and associated ethical design considerations at the intersection of personalised care, youth mental health, and digital techn...
Atay Kozlovski
Atay Kozlovski
The rapid proliferation of AI systems has raised many concerns about safety and responsibility in their design and use. The philosophical framework of Meaningful Human Control (MHC) was developed in response to these concerns, and tries to ...
The fundamental rights risks of countering cognitive warfare with artificial intelligence [0.03%]
利用人工智能对抗认知战的基本权利风险
Henning Lahmann,Bart Custers,Benjamyn I Scott
Henning Lahmann
This article analyses ideas to use AI-supported systems to counter 'cognitive warfare' and critically examines the implications of such systems for fundamental rights and values. After explicating the notion of 'cognitive warfare' as used i...
Establishing human responsibility and accountability at early stages of the lifecycle for AI-based defence systems [0.03%]
在基于人工智能的国防系统生命周期早期阶段建立人的责任和问责制
Ariel Conn,Ingvild Bode
Ariel Conn
The use of AI technologies in weapons systems has triggered a decade-long international debate, especially with regard to human control, responsibility, and accountability around autonomous and intelligent systems (AIS) in defence. However,...
Florian van Daalen,Marine Jacquemin,Johan van Soest et al.
Florian van Daalen et al.
Access to large datasets, the rise of the Internet of Things (IoT) and the ease of collecting personal data, have led to significant breakthroughs in machine learning. However, they have also raised new concerns about privacy data protectio...
Helpful, harmless, honest? Sociotechnical limits of AI alignment and safety through Reinforcement Learning from Human Feedback [0.03%]
乐于助人，无害且诚实？通过人类反馈强化学习实现AI对齐和安全的社会技术限制
Adam Dahlgren Lindström,Leila Methnani,Lea Krause et al.
Adam Dahlgren Lindström et al.
This paper critically evaluates the attempts to align Artificial Intelligence (AI) systems, especially Large Language Models (LLMs), with human values and intentions through Reinforcement Learning from Feedback methods, involving either hum...
Urban Digital Twins and metaverses towards city multiplicities: uniting or dividing urban experiences? [0.03%]
通向城市的多重宇宙：城市数字孪生和元宇宙使城市体验统一还是分裂？
Javier Argota Sánchez-Vaquerizo
Javier Argota Sánchez-Vaquerizo
Urban Digital Twins (UDTs) have become the new buzzword for researchers, planners, policymakers, and industry experts when it comes to designing, planning, and managing sustainable and efficient cities. It encapsulates the last iteration of...
Sarah A Fisher
Sarah A Fisher
Newly powerful large language models have burst onto the scene, with applications across a wide range of functions. We can now expect to encounter their outputs at rapidly increasing volumes and frequencies. Some commentators claim that lar...
Elisabeth Stockinger,Jonne Maas,Christofer Talvitie et al.
Elisabeth Stockinger et al.
Voting Advice Applications (VAAs) are interactive tools used to assist in one's choice of a party or candidate to vote for in an upcoming election. They have the potential to increase citizens' trust and participation in democratic structur...