Artificial Intelligence (AI) and Big Election Data : Innovation in Transparency in Presenting Public Information
Kecerdasan Buatan (AI) dan Data Besar Pemilu: Inovasi Transparansi dalam Menyajikan Informasi Publik
DOI:
https://doi.org/10.36982/jpp.v11i4.7241Keywords:
Artificial Intelligence, Big Data, Election, Transparency, InformationAbstract
Purpose : To analyze the utilization of AI and Big Data in presenting public election information and the risks of procedural compliance governance (the illusion of transparency) on democratic electoral governance.
Design/methodology/approach : A qualitative approach using literature review and descriptive-analytical case study methods. Data sources include global literature, policy documents, and the institutional narratives of the Indonesian General Elections Commission (KPU RI) during the 2024 Election. Data analysis applies the interactive model of Miles, Huberman, and Saldaña by merging Smart Transparency and Publicness theoretical frameworks.
Findings : KPU's integration of AI and Big Data has the potential to realize smart transparency through real-time data. However, this practice risks falling into procedural compliance governance due to black-box algorithms, the absence of algorithmic audits, and weak data privacy regulations that trigger bias and digital exclusion.
Practical Implication : Provides a strategic reference for the KPU and policymakers to formulate AI governance regulations that prioritize algorithmic transparency, voter data protection, and digital literacy to strengthen democratic legitimacy rather than merely pursuing administrative efficiency.
Originality/value : The novelty of this research lies in the formulation of the Substantive Algorithmic Transparency Governance Model (MTAS). This model integrates four main pillars: Explainable Public AI (XPAI), Human-in-the-Loop (HITL) Mandate, Electoral Privacy by Design, and Universal Design for Digital Literacy to ensure election technology is auditable and publicly accountable.
Paper type : Review Paper
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