Navigasi Etis Dan Yuridis Dalam Governansi Digital
Tinjauan Literatur Sistematis Terhadap Integrasi Artificial Intelligence 2020-2025
DOI:
https://doi.org/10.61104/alz.v4i3.5967Keywords:
Artificial Intelligence, Digital Governance, Ethics, Law, AccountabilityAbstract
Integrasi kecerdasan buatan (AI) yang cepat ke dalam governansi digital sering kali mengabaikan perlindungan etis dan hukum yang esensial, sehingga menimbulkan risiko signifikan terhadap akuntabilitas demokratis. Penelitian ini bertujuan untuk mengidentifikasi tantangan etis dan yuridis utama dalam implementasi AI serta mengusulkan kerangka kerja navigasi untuk tata kelola digital yang berkeadilan. Tinjauan literatur sistematis (SLR) dilakukan terhadap 25 artikel jurnal bereputasi yang diterbitkan antara tahun 2020 hingga 2025 dengan mengikuti standar PRISMA untuk seleksi yang ketat. Analisis mengungkapkan bahwa kekhawatiran etis, terutama bias algoritma dan fenomena "kotak hitam", mendominasi diskursus akademik kontemporer. Temuan menunjukkan bahwa kerangka hukum saat ini sebagian besar masih bersifat antroposentris, sehingga menciptakan celah akuntabilitas yang krusial saat sistem otomatis menggunakan diskresi administratif. Hasil penelitian lebih lanjut menekankan bahwa memastikan explainability algoritma sangat vital untuk menjaga kepercayaan publik terhadap layanan otomatis. Selain itu, kesiapan institusi yang bervariasi secara signifikan menuntut pergeseran paradigma dari efisiensi teknosentris menuju tata kelola yang berpusat pada manusia. Pada akhirnya, sinkronisasi regulasi perlindungan data dengan hukum administrasi negara sangat penting bagi masa depan digital yang berkepastian hukum. Penelitian ini menyimpulkan bahwa integrasi mekanisme "human-in-the-loop" merupakan prasyarat mutlak untuk memastikan bahwa transformasi digital tetap selaras dengan keadilan sosial dan supremasi hukum
References
Busuioc, M. (2021). Accountable artificial intelligence: Holding algorithms to account in public administration. European Journal of Risk Regulation, 12(4), 825–846. https://doi.org/10.1017/err.2021.51
Coppola, M. (2021). The AI Act and the public sector: A legal analysis. Journal of Digital Governance, 1(1), 1–15. https://doi.org/10.3233/DG-210001
Dwivedi, Y. K., et al. (2021). Setting the future of digital and social media marketing research: Perspectives and theoretical insights. International Journal of Information Management, 59, 102168. https://doi.org/10.1016/j.ijinfomgt.2020.102168
Janssen, M., et al. (2020). Data governance: Organizing data for trustworthy Artificial Intelligence. Government Information Quarterly, 37(3), 101493. https://doi.org/10.1016/j.giq.2020.101493
Jobin, A., Ienca, M., & Vayena, E. (2020). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), 389–399. https://doi.org/10.1038/s42256-019-0088-2
Larsson, S. (2021). On the ethics of AI in government. Frontiers in Big Data, 4, 635032. https://doi.org/10.3389/fdata.2021.635032
Madan, R., & Ashok, M. (2023). AI adoption and diffusion in public administration: A systematic literature review and future research agenda. Government Information Quarterly, 40(1), 101774. https://doi.org/10.1016/j.giq.2022.101774
Page, M. J., et al. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. Systematic Reviews, 10(1), 1–11. https://doi.org/10.1186/s13643-021-01626-4
Shin, D. (2020). The boundaries of algorithmic justice: What it means to be explainable and accountable of algorithms. Journal of Information, Communication and Ethics in Society, 18(2), 145–158. https://doi.org/10.1108/JICES-12-2019-0134
Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–339. https://doi.org/10.1016/j.jbusres.2019.07.039
Sun, T. Q., & Medaglia, R. (2020). Mapping the challenges of Artificial Intelligence in the public sector: Evidence from public healthcare. Government Information Quarterly, 36(2), 368–383. https://doi.org/10.1016/j.giq.2018.11.008
Taeihagh, A. (2021). Governance of artificial intelligence. Policy and Society, 40(2), 137–157. https://doi.org/10.1080/14494035.2021.1928361
Tallberg, J., et al. (2023). Global governance of artificial intelligence: Next steps for empirical and normative research. International Studies Review, 25(3), viad027. https://doi.org/10.1093/isr/viad027
Wirtz, B. W., Weyerer, J. C., & Geyer, C. (2019). Artificial intelligence and the public sector: applications and challenges. International Journal of Public Administration, 42(7), 596–615. https://doi.org/10.1080/01900692.2018.1498103
Xiao, Y., & Watson, M. (2019). Guidance on conducting a systematic literature review. Journal of Planning Education and Research, 39(1), 93–112. https://doi.org/10.1177/0739456X17723392
Zuiderwijk, A., et al. (2021). Implications of the use of artificial intelligence in public governance: A systematic literature review and a research agenda. Government Information Quarterly, 38(3), 101577. https://doi.org/10.1016/j.giq.2021.101577
Neuendorf, K. A. (2017). The content analysis guidebook (2nd ed.). Thousand Oaks, CA: Sage.
Stahl, B. C. (2021). Artificial Intelligence for a Better Future: An Ecosystem Perspective on the Ethics of AI and Emerging Digital Technologies. Springer Nature. https://doi.org/10.1007/978-3-030-69978-9
Wischmeyer, T., & Rademacher, C. (2020). Regulating Artificial Intelligence. Springer. https://doi.org/10.1007/978-3-030-32361-5
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