transparentare

Transparentare is a term used to describe a framework of practices and principles aimed at embedding transparency into information processing systems, particularly in governance, data management, and automated decision making. It emphasizes making data sources and quality visible, exposing the criteria and logic behind decisions, and providing clear outcomes so that systems can be verified, audited, and held accountable.

Origin and usage: The term has appeared in academic and industry discussions about responsible AI and public administration in the 2010s and 2020s. It is not a formal standard, but a conceptual target that organizations may adopt to guide transparency-oriented design and governance.

Core components: Data provenance and lineage; documentation of decision criteria and model logic; explanations or rationale appropriate to different audiences; user-facing transparency controls and disclosures; tamper-evident audit trails; governance processes governing data collection, model updates, and access.

Applications: AI decision systems, public-sector services and procurement, data-sharing platforms, and corporate governance aimed at assessing algorithmic impact, bias, and privacy. Practices may accompany explainability, auditability, and data minimization.

Benefits and challenges: Potential to improve accountability, trust, and compliance with privacy and data-protection laws. Challenges include balancing openness with confidentiality and security, preventing information overload or misinterpretation, and achieving scalable, standardized implementation.