A Comparative Study of Privacy-Preserving Techniques in Federated Learning: A Performance and Security Analysis by Eman Shalabi, Walid Khedr, Ehab Rushdy, Ahmad Salah

“…Federated learning (FL) is a machine learning technique where clients exchange only local model updates with a central server that combines them to create a global model after local training. While FL offers privacy benefits through local training, privacy-preserving strategies are needed since model updates can leak training data information due to various attacks. …”
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Exploring assessment methods used by Grade Four English First Additional Language Teachers by Kofi Nkonkonya Mpuangnan, Gladys Phumzile Mngomezulu, Samantha Govender

“…The researchers opted for a thematic analysis approach, allowing for a thorough examination of the data while respecting the privacy and confidentiality of the participants. …”
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Artificial intelligence methods used in various aquaculture applications: A systematic literature review by Thurein Aung, Rafiza Abdul Razak, Adibi Rahiman Bin Md Nor

“…However, the review also uncovered substantial challenges that will continue limiting widespread adoption, including restricted access to representative data, prohibitive expenses, technical complexities, lack of social acceptance, and data privacy and security concerns. …”
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The Use of Artificial Intelligence in Medical Diagnostics: Opportunities, Prospects and Risks by Nataliia Sheliemina

“…The AI integration in healthcare can revolutionise the industry by improving patient outcomes, optimising resource allocation, and reducing operational costs. However, the AI use in medicine carries certain risks related to ethics and data privacy, shortcomings in the quality of data for training algorithms, and importance of protecting against cyberthreats. …”
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Ethical aspects of the use of social networks during the employment process by Branislav Sančanin

“…Employers violate the privacy of potential candidates by obtaining data in this manner without making prior notification and receiving consent, which opens up a whole range of complex ethical and legal issues, especially in the light of the large number of fake profiles and pages on social networks. …”
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Differential Private POI Queries via Johnson-Lindenstrauss Transform by Mengmeng Yang, Tianqing Zhu, Bo Liu, Yang Xiang, Wanlei Zhou

“…In addition, the proposed perturbation method based on the Johnson Lindenstrauss transform satisfies the differential privacy. Two popular point of interest queries, <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-NN and Range, are used to evaluate the method on two real-world data sets. …”
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Multifaceted Assessment of Responsible Use and Bias in Language Models for Education by Ishrat Ahmed, Wenxing Liu, Rod D. Roscoe, Elizabeth Reilley, Danielle S. McNamara

“…This study proposes a framework for the automatic detection of biases and violations of responsible use using a synthetic question-based dataset mimicking student–chatbot interactions. …”
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An Evaluation on the Potential of Large Language Models for Use in Trauma Triage by Kelvin Le, Jiahang Chen, Deon Mai, Khang Duy Ricky Le

“…Overall, the literature highlights multifaceted applications of LLMs, especially in emergency trauma settings, albeit with clear limitations and ethical considerations, such as artificial hallucinations, biased outputs and data privacy issues. There remains room for more rigorous research into refining the consistency and capabilities of LLMs, ensuring their effective integration in real-world trauma triaging to improve patient outcomes and resource utilisation.…”
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COVID-19 detection using federated machine learning. by Mustafa Abdul Salam, Sanaa Taha, Mohamed Ramadan

“…AI plays an essential role in COVID-19 case classification as we can apply machine learning models on COVID-19 case data to predict infectious cases and recovery rates using chest x-ray. …”
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Using Federated Learning for Collaborative Intrusion Detection Systems by Matteo Rizzato, Youssef Laarouchi, Christophe Geissler

“…Traditional implementations provide fast and accurate predictions, but require centralised storage of labelled historical data for training. This solution is not always suitable for real-world applications, where regulatory constraints and privacy concerns hamper the collection of sensitive data into a single server. …”
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Characterizing user mobility using mobile sensing systems by Sébastien Faye, Walter Bronzi, Ibrahim Tahirou, Thomas Engel

“…Furthermore, we detail the need to use methods that respect the privacy of users and investigate the possibilities offered by network traces, including Wi-Fi and Bluetooth communication technologies. …”
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Ethical Considerations for Using Artificial Intelligence in Digital Technologies by William Jorgensen, Matt Bjornsen, Rikke Carlsen

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THE POSSIBILITY OF USING ELECTRONIC MEDICAL RECORDS FOR CLINICAL OBSERVATION by R. D. Kurbanov, R. Kh. Trigulova

“…Of course, there are problems and obstacles to expanding the use of EMC, and one of the solutions to these obstacles is to address issues of semantic compatibility, privacy, and security. …”
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Behavioural Economics and Consumer Decision-Making in the Age of Artificial Intelligence (AI), Data Science, Business Analytics, and Internet of Things (IoT) by Yuki Haruto Yamamoto

“…However, while AI and IoT facilitate more efficient and engaging consumer experiences, they introduce complex ethical and practical concerns, particularly around data privacy, algorithmic fairness, and maintenance of consumer trust. …”
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Legal Challenges of Marine Insurance Laws in the Use of Unmanned Ships by Mahsa Bahadoran- Baghbaderani, Masoud Shirani, Reza Soltani

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FFM: Flood Forecasting Model Using Federated Learning by Muhammad Shoaib Farooq, Rabia Tehseen, Junaid Nasir Qureshi, Uzma Omer, Rimsha Yaqoob, Hafiz Abdullah Tanweer, Zabihullah Atal

“…Federated Learning is the most advanced technique of machine learning (ML) that guarantees data privacy, ensures data availability, promises data security, and handles network latency trials inherent in prediction of floods by prohibiting data to be transferred over the network for model training. …”
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#BeSeen: understanding young people’s views of the motivation and impacts of sharing self-harm imagery online and use of their social media data for research—a UK participatory art... by Ann John, Ashrafunnesa Khanom, Todd Smith, Amanda Marchant, Dana Dekel, Harley Morgan, Sarah Tombs, Karen Ingham

“…Participants from the RAS group were more inclined to agree to their data being used and had higher levels of trust in government.Conclusion Young people care about their privacy and use of their data even when it is publicly available. …”
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Testing scenarios for using telepresence robots in healthcare settings by Janika Leoste, Kadri Strömberg-Järvis, Tarmo Robal, Kristel Marmor, Katrin Kangur, Anne-Mari Rebane

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Barriers to contraceptive access and use among youths (15–24 Years) living in informal urban settlements of Kigali, Rwanda: a qualitative study by Emmanuel Okiror Okello, Alexandre Edgard Murinzi, Colyse Nduwimana, Rashidah Nambaziira

“…Abstract Background Contraceptive use among youths below 19 years in Rwanda is still very low, as low as 3.7%, yet their level of sexual activity is high. …”
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Comments on &#x201C;Exploring Secure V2X Communication Networks for Human-Centric Security and Privacy in Smart Cities&#x201D;&#x2014;Privacy-Preserving Certificate in V2X Communic... by Abel C. H. Chen

“…The proposed framework validates vehicle legitimacy using individual certificates and subsequently transmits data collected and integrated by intermediate entities to the blockchain, thereby avoiding direct exposure of vehicle privacy. …”
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