AIT Academy introduces a tripartite curriculum for AI agents across natural science, humanities, and social science domains, with reported gains of 15.9 points in security and 7 points in social reasoning under specific scheduling.
AI and Ethics1(3), 283–296 (Aug 2021)
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A privacy-by-design pipeline using static Drebin features fed to an SVM with dual-reject thresholds defers 6.7% of samples to sandboxed dynamic analysis and reaches F1 0.87 on 2024-2025 data without accessing user information.
Twelve semistructured interviews yield twelve knowledge-based design requirements for tutoring generative social robots, grouped into self-knowledge, user-knowledge, and context-knowledge categories.
A local pipeline integrating diarization, ASR, SER and adversarial LLM reasoning for privacy-preserving conversational analysis, reporting 48.8% SER accuracy on RAVDESS four-class subset with honest cross-corpus limitations.
Topic modeling of 6520 AI papers reveals divergent and sometimes contradictory conceptions of bias within the research community.
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AIT Academy: Cultivating the Complete Agent with a Confucian Three-Domain Curriculum
AIT Academy introduces a tripartite curriculum for AI agents across natural science, humanities, and social science domains, with reported gains of 15.9 points in security and 7 points in social reasoning under specific scheduling.
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Don't Trust Us: A privacy-by-design android malware detection pipeline
A privacy-by-design pipeline using static Drebin features fed to an SVM with dual-reject thresholds defers 6.7% of samples to sandboxed dynamic analysis and reaches F1 0.87 on 2024-2025 data without accessing user information.
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Knowledge-Based Design Requirements for Generative Social Robots in Higher Education
Twelve semistructured interviews yield twelve knowledge-based design requirements for tutoring generative social robots, grouped into self-knowledge, user-knowledge, and context-knowledge categories.
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EmotionAI: A Privacy-Preserving Computational Intelligence Pipeline for Speech-Emotion-Grounded Conversational Analysis
A local pipeline integrating diarization, ASR, SER and adversarial LLM reasoning for privacy-preserving conversational analysis, reporting 48.8% SER accuracy on RAVDESS four-class subset with honest cross-corpus limitations.
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Navigating the muddy waters of bias in artificial intelligence research: Understanding divergent meanings and conceptions
Topic modeling of 6520 AI papers reveals divergent and sometimes contradictory conceptions of bias within the research community.