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Using statutory guidance and codes of practice to build on whistleblowing legislation : the Irish experience
Abstract
In our opinion, the use of Guidance regarding whistleblower protection represents best international practice with regard to protected disclosures. It is devised on the premise that a one-size-fits-all approach is not appropriate given the different nature and scope of public sector bodies. In the authors’ opinion, the Irish experience demonstrates how statutory guidance and Codes of Practice can be valuable methods of explaining how the law is intended to operate as well as encouraging best practice which goes beyond the minimum statutory floor of rights.
... Additionally, employees may be apprehensive about potential job losses due to unmet KPIs, prompting them to release products without adhering to internal protocols requiring approval from authorized personnel or to manipulate records when granted access to the database. Notably, in systems involving manual data transfer to the company database using hybrid computerized systems, transcription errors may occur, resulting in inaccurate data records (18,19). ...
data integrity as the maintenance of accuracy, consistency, and completeness of data over time.Recently, “artificial intelligence” has become prevalent across industries, education, culture,and technology, denoting systems that mimic human intelligence and critical thinking using computers and related technologies. Objective: This article examines the construction of a robust artificial intelligence (AI) system and the incorporation of ALCOA+ principles for data validation, with a specific focus on enhancing data certainty and security. Methods: This study was carried out through a comprehensive review of various Scopus-indexed literature over the past decade. Results and Discussion: AI has been widely applied in Manufacturing System Optimization, involving organizing production systems, including machines, robots, conveyors, and related operations like maintenance and material handling. Moreover, it’s used for Process Monitoring, Diagnostics, and Prognostics in medicine, as well as supervision and regulation in industries. Yet, it’s not immune to shortcomings, which could result in system biases and jeopardize data security. Conclusion: This article explores the creation of a robust AI system, implementing ALCOA+ for data validation in AI-Driven Digital Transformation to improve data certainty and security in industries. It involves systematically recording AI system activities, ensuring database validity, sustaining data recording practices, regularly updating records, ensuring authenticity and completeness, and facilitating data accessibility for review and audits. As AI integration in education advances, there’s a crucial need for oversight to maintain data integrity in these systems.
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