Ramdan Prawira Sutardjo, Irfan Dwiguna Sumitra

Artificial Intelligence Governance Audit for Public Information Disclosure (AI Government Audit)

Introduction

Artificial intelligence governance audit for public information disclosure (ai government audit). Improve transparency and accountability in public AI systems. This AI Government Audit Framework addresses ethical risks, bias, and ensures compliance through documentation and testing.

Abstract

Abstract— Background: The use of artificial intelligence (AI) in public services accelerates decision-making but also poses ethical risks, bias, and a loss of accountability. This article proposes an AI Government Audit Framework developed using a Design Science Research (DSR) approach. The methodology includes problem identification, artifact design and development, demonstration, and evaluation using conceptual case studies and cross-checking of policy documents. The results indicate that an audit framework combining documentation review, external (adversarial/black-box) testing, and policy compliance assessment can improve transparency and mitigate risks in public AI systems. Recommendations focus on strengthening internal/external audit capabilities, model documentation standards, and regulations for audit disclosure.

Full Text

Comments

You need to be logged in to post a comment.