Keywords
public administration
transparency
accountability
artificial intelligence
How to Cite
Abstract
The increasing reliance on decision-making algorithms in public administration raises significant legal and ethical challenges. This article examines the key issues associated with algorithmic governance, including transparency, accountability, and potential biases in automated decision-making processes. Using a legal-analytical method, I evaluate whether machine-learning algorithms can comply with existing legal principles while enhancing efficiency in governance. My findings suggest that while algorithms can improve decision-making speed and accuracy, their nature complicates compliance with legal transparency and due process requirements. I argue that algorithmic accountability mechanisms, including explainability frameworks and regulatory oversight, are essential in order to ensure fairness and legality in automated administrative decisions.
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Copyright (c) 2025 Jakub Sawicki
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