OPERATIONALISING ARTIFICIAL INTELIGENCE ETHICAL PRINCIPLES IN BUSINESS – A CONCEPTUAL FRAMEWORK
OPERATIONALISING ARTIFICIAL INTELIGENCE ETHICAL PRINCIPLES IN BUSINESS – A CONCEPTUAL FRAMEWORK

Author(s): Alexandru Constatin Ciobanu, Gabriela Mesnita
Subject(s): Economy, ICT Information and Communications Technologies
Published by: Editura Universităţii »Alexandru Ioan Cuza« din Iaşi
Keywords: artificial intelligence; ethics, framework; practice; business;
Summary/Abstract: Historically, technology was always a key differentiator and an enabler for business or societal developments. With the rapid advancements in technology, businesses have been able to increase their efficiency, productivity, or profitability through automation and digitization. The European Union elaborated clear strategies that aims overall economic development trough digital transformation, one of the core technology components being Artificial Intelligence (AI). While the added value of AI technologies, in terms of optimization, efficiency, automation is clear and undeniable, there are different challenges related to the ethical aspect of AI use. Hence the AI ethics discussions are currently very present in the public space. A collection of different AI ethical frameworks was redacted either by the researchers or by governments or by the tech industry, but developing consistent AI ethical system is still a grey area. Some of the main challenges revealed by different researchers are related to the practical implementation of ethical principles in AI technologies during its lifecycle.This paper proposes a conceptual framework for operationalizing AI ethical principles in business contexts. The framework is based on a comprehensive literature review of existing AI ethical frameworks, which highlights the current gaps in their implementation. The proposed framework addresses these gaps by providing a step-by-step approach that can be easily integrated into existing business processes. It covers various stages of AI development, including problem formulation, data collection and preprocessing, model training, model evaluation, and deployment. The practical validation of the framework will be conducted in future work. The results suggest that the proposed framework can provide a systematic approach to operationalizing AI ethical principles in business contexts, thereby contributing to the development of responsible AI systems.

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