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The Challenges of Human Rights in the Era of Artificial Intelligence: Nehaluddin Ahmed et al
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Title: The Challenges of Human Rights in the Era of Artificial IntelligenceAuthors & Designations: Source: UUM Journal of Legal Studies, 16(1), 150–169 (January 2025)DOI: 10.32890/uumjls2025.16.1.9 (researchgate.net) APA Citation: Ahmad, N., Ali, A. W., & Yussof, M. H. B. (2025). The challenges of human rights in the era of artificial intelligence. UUM Journal of Legal…
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Revised Surgical CAse REport (SCARE) Guideline: An Update for the Age of Artificial Intelligence by Riaz A Agha et al
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Title: Revised Surgical CAse REport (SCARE) Guideline: An Update for the Age of Artificial Intelligence ABSTRACT Artificial intelligence (AI) is rapidly transforming healthcare and scientific publishing. Reporting guidelines need to be updated to consider this advance. The SCARE Guideline 2025 update introduces a new AI-focused domain to promote transparency, reproducibility, and ethical integrity in…
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Ethical and Bias Considerations in Artificial Intelligence/Machine Learning: Matthew G. Hanna et al
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ABSTRACT As artificial intelligence (AI) continues to play an increasingly prominent role in pathology and medical practice, critical attention must be paid to the ethical challenges and inherent biases associated with machine learning (ML) integration. While ML systems have demonstrated exceptional performance across a range of clinical tasks—including image analysis, natural language processing, and…
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Chain-of-Thought vs Direct Output: Which Improves Interpretability in LLMs?
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Chain-of-Thought (CoT) prompting is generally hypothesized to improve interpretability in LLMs compared to Direct Output generation, especially for complex, multi-step problem-solving tasks. CoT aims to enhance transparency, trust, and explainability by making the model’s reasoning process explicit through intermediate natural language steps. However, the actual improvement can depend on factors like task complexity, the…
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A comprehensive survey with critical analysis for deepfake speech detection: Lam Pham et al
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ABSTRACT Recent advancements in deep learning have significantly enhanced speech generation systems, enabling their integration into a wide range of real-world applications such as text-to-speech support for individuals with speech impairments, voice-enabled customer service chatbots, and cross-linguistic speech translation. Despite their beneficial uses, these technologies also introduce serious risks when exploited for malicious purposes,…
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Characterizing the MrDeepFakes Sexual Deepfake Marketplace: Catherine Han et al
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Title: Characterizing the MrDeepFakes Sexual Deepfake MarketplaceAuthors & Designations: Source: arXiv preprint arXiv:2410.11100 [cs.CY], originally submitted Oct 14 2024; revised Jan 30 2025 (arxiv.org, arxiv.org) APA Citation:Han, C., Li, A., Kumar, D., & Durumeric, Z. (2024). Characterizing the MrDeepFakes sexual deepfake marketplace. arXiv:2410.11100 [cs.CY]. 🔍 Background & Objectives Sexual deepfake content has surged online, driven by motives such…
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Regulating AI: A Study in the Comparison between South Asia and Other Countries
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AI legislation refers to any rule, law, or legal order enacted by the legitimate authority of a jurisdiction to govern, oversee, and regulate the attributes, evolution, and societal engagement of a digitally created artificial creature. This study offers a comparative examination of the regulatory framework for artificial intelligence in South Asian countries, juxtaposed with…