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All Journal Majority Science Journal Technologia Journal
aghata, frhendy
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Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Law, Crime, Criminology & Criminal Justice

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Integrating Technology With Human Insight: The Era of Digital Collaboration Dwiyanto, Dwiyanto; Aghata, Frhendy
Technologia Journal Vol. 2 No. 1 (2025): Technologia Journal - February
Publisher : Pt. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/sztfq724

Abstract

This study aims to identify an integrative approach between technology and human insight in digital collaboration. The method used is the Systematic Literature Review (SLR), which allows a systematic review of related literature to understand the concepts, models, benefits, and challenges in this integration. This study focuses on three main questions: (1) how technology and human insight are combined in digital collaboration practices, (2) what technologies are commonly used, and (3) what are the benefits and obstacles in this integration. The results of the study show three main patterns of human-technology collaboration: interactive, adaptive, and limited autonomy. In the interactive pattern, humans become decision makers with the support of data-based technology. The adaptive pattern utilizes AI and machine learning that learn from human interactions, but still requires ethical supervision. Meanwhile, the limited autonomy pattern gives decision-making authority to technology in a certain scope with human control. This study emphasizes the importance of the role of human values—such as intuition, empathy, and ethics—in maintaining the effectiveness of digital collaboration. The success of this integration is also influenced by organizational culture and leadership that are adaptive to innovation and a human-centered approach
ETHICAL AND DATA SECURITY ANALYSIS IN THE IMPLEMENTATION OF GENERATIVE AI IN HIGHER EDUCATION ENVIRONMENTS Haetami, Aceng; Aghata, Frhendy
MSJ : Majority Science Journal Vol. 3 No. 4 (2025): MSJ-November
Publisher : PT. Hafasy Dwi Nawasena

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61942/msj.v3i4.482

Abstract

The rapid adoption of generative artificial intelligence in higher education has introduced significant pedagogical opportunities while simultaneously raising critical concerns regarding academic ethics and data security. This study aims to analyze ethical risks and data vulnerabilities associated with the use of generative AI by university students and lecturers, as well as to assess institutional readiness in establishing responsible AI governance. Using an analytical literature study with a descriptive qualitative approach, this research synthesizes empirical and conceptual findings from reputable international publications between 2015 and 2024. The findings indicate that generative AI poses threats to academic integrity through machine-generated plagiarism, reduced critical thinking, and algorithmic bias in learning processes. From a data security perspective, major risks include opaque data-storage policies, potential model memorization of sensitive information, and weak cybersecurity infrastructures in universities. Institutional readiness remains limited, marked by the absence of AI ethics guidelines, low AI literacy among academic communities, and inadequate monitoring mechanisms. This study recommends the development of generative-AI ethical guidelines, enhancement of digital literacy, improvement of data protection standards, and the establishment of AI governance committees within universities.
Co-Authors Aceng Haetami, Aceng Dwiyanto .