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Artificial intelligence (AI) has transformed various sectors and institutions, including education and healthcare. Although AI offers immense potential for innovation and problem solving, its integration also raises significant ethical…

Computers and Society · Computer Science 2024-12-05 William Franz Lamberti

Trustworthy artificial intelligence (AI) technology has revolutionized daily life and greatly benefited human society. Among various AI technologies, Federated Learning (FL) stands out as a promising solution for diverse real-world…

Machine Learning · Computer Science 2023-02-22 Yifei Zhang , Dun Zeng , Jinglong Luo , Zenglin Xu , Irwin King

Artificial Intelligence (AI) poses both significant risks and valuable opportunities for democratic governance. This paper introduces a dual taxonomy to evaluate AI's complex relationship with democracy: the AI Risks to Democracy (AIRD)…

Privacy concerns and fears of unauthorized access in smart home devices often stem from misunderstandings about how data is collected, used, and protected. This study explores how AI-powered tools can offer innovative privacy protections…

Human-Computer Interaction · Computer Science 2025-09-18 Wael Albayaydh , Ivan Flechais , Rui Zhao , Jood Albayaydh

The scarcity of accessible, compliant, and ethically sourced data presents a considerable challenge to the adoption of artificial intelligence (AI) in sensitive fields like healthcare, finance, and biomedical research. Furthermore, access…

Machine Learning · Computer Science 2025-04-02 Kumar Kshitij Patel , Weitong Zhang , Lingxiao Wang

As large-scale theft of data from corporate servers is becoming increasingly common, it becomes interesting to examine alternatives to the paradigm of centralizing sensitive data into large databases. Instead, one could use cryptography and…

Artificial Intelligence · Computer Science 2014-07-15 Thomas Leaute , Boi Faltings

This article examines the ethical and legal implications of artificial intelligence (AI) driven data collection, focusing on developments from 2023 to 2024. It analyzes recent advancements in AI technologies and their impact on data…

Computers and Society · Computer Science 2025-03-20 Shahmar Mirishli

As the paradigm of Human-Centered AI (HCAI) gains prominence, its benefits to society are accompanied by significant ethical concerns, one of which is the protection of individual privacy. This chapter provides a comprehensive overview of…

Human-Computer Interaction · Computer Science 2026-02-05 Luyi Sun , Wei Xu , Zaifeng Gao

Complex decision-making by autonomous machines and algorithms could underpin the foundations of future society. Generative AI is emerging as a powerful engine for such transitions. However, we show that Generative AI-driven developments…

Robotics · Computer Science 2026-01-15 Le Liu , Bangguo Yu , Nynke Vellinga , Ming Cao

As the demand grows for scalable and privacy-aware AI systems, Federated Learning (FL) has emerged as a promising solution, allowing decentralized model training without moving raw data. At the same time, the combination of high-performance…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-11-26 Sangam Ghimire , Paribartan Timalsina , Nirjal Bhurtel , Bishal Neupane , Bigyan Byanju Shrestha , Subarna Bhattarai , Prajwal Gaire , Jessica Thapa , Sudan Jha

The rapid growth of artificial intelligence (AI) technologies has raised major privacy and ethical concerns. However, existing AI incident taxonomies and guidelines lack grounding in real-world cases, limiting their effectiveness for…

Computers and Society · Computer Science 2025-09-22 Hilda Hadan , Reza Hadi Mogavi , Leah Zhang-Kennedy , Lennart E. Nacke

In the growing world of artificial intelligence, federated learning is a distributed learning framework enhanced to preserve the privacy of individuals' data. Federated learning lays the groundwork for collaborative research in areas where…

Machine Learning · Computer Science 2023-11-21 Elaheh Jafarigol , Theodore Trafalis , Talayeh Razzaghi , Mona Zamankhani

In recent years, privacy and security concerns in machine learning have promoted trusted federated learning to the forefront of research. Differential privacy has emerged as the de facto standard for privacy protection in federated learning…

Cryptography and Security · Computer Science 2025-10-03 Jie Fu , Yuan Hong , Xinpeng Ling , Leixia Wang , Xun Ran , Zhiyu Sun , Wendy Hui Wang , Zhili Chen , Yang Cao

Artificial Intelligence (AI) is rapidly integrating into various aspects of our daily lives, influencing decision-making processes in areas such as targeted advertising and matchmaking algorithms. As AI systems become increasingly…

Artificial Intelligence · Computer Science 2025-03-11 Md. Tanzib Hosain , Mehedi Hasan Anik , Sadman Rafi , Rana Tabassum , Khaleque Insia , Md. Mehrab Siddiky

The rapid proliferation of artificial intelligence (AI) technologies has led to a dynamic regulatory landscape, where legislative frameworks strive to keep pace with technical advancements. As AI paradigms shift towards greater autonomy,…

Cryptography and Security · Computer Science 2026-03-20 Shiliang Zhang , Sabita Maharjan

The growing use of Machine Learning and Artificial Intelligence (AI), particularly Large Language Models (LLMs) like OpenAI's GPT series, leads to disruptive changes across organizations. At the same time, there is a growing concern about…

This paper details the privacy and security landscape in today's cloud ecosystem and identifies that there is a gap in addressing the risks introduced by machine learning models. As machine learning algorithms continue to evolve and find…

Cryptography and Security · Computer Science 2024-02-05 Alka Luqman , Riya Mahesh , Anupam Chattopadhyay

Despite Artificial Intelligence (AI) transformative potential for public sector services, decision-making, and administrative efficiency, adoption remains uneven due to complex technical, organizational, and institutional challenges.…

The AI landscape demands a broad set of legal, ethical, and societal considerations to be accounted for in order to develop ethical AI (eAI) solutions which sustain human values and rights. Currently, a variety of guidelines and a handful…

Computers and Society · Computer Science 2021-12-03 Anna Felländer , Jonathan Rebane , Stefan Larsson , Mattias Wiggberg , Fredrik Heintz

Federated Learning (FL) offers a promising approach for training clinical AI models without centralizing sensitive patient data. However, its real-world adoption is hindered by challenges related to privacy, resource constraints, and…