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Minding the gap between theory and implementation of ethical AI
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School of Business |
Master's thesis
Electronic archive copy is available via Aalto Thesis Database.
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en
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95
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Abstract
Artificial intelligence (AI) has evolved from a fictional concept from the 1950s to an actual technology that is an integral part of daily life in current modern day society. Despite the growing presence of AI across industries, concerns such as privacy violations, algorithmic bias, and societal impacts have accompanied its rapid advancement. Ethical AI frameworks, including the OECD AI Principles, NIST AI Framework, IEEE guidelines, and the EU AI Act, offer important guidance. However, the practical implementation of these principles remains difficult.
This research examines how ethical AI is translated into practice and the challenges faced in bridging the gap between theoretical guidelines and real-world application. Using a qualitative multi-level approach, combining a review of frameworks and expert interviews, this study analyses barriers at the macro-, meso-, and micro-levels.
Findings highlight the need for clearer accountability structures, stronger industry-specific regulations, and enhanced AI ethics education. Ethical AI implementation requires a balanced approach integrating regulation, education, organizational culture, and individual responsibility to bridge the gap between theory and practice.