ScholarWorks@숙명여자대학교

초록

As interactions between Big Data and AI increasingly raise concerns about bias and ethical errors in decision-making, establishing trust within the big data ecosystem has become essential. As data types diversify and the volume of information grows exponentially, environments where real-time information processing is crucial, such as autonomous driving and IoT, require fair and reliable system management. This study introduces a trust-centric big data ecosystem designed to address challenges through an ethical framework for autonomous driving. The core of the big data ecosystem is a trust management layer that ensures data integrity and transparency, and integrated with advanced algorithms for real-time bias detection and mitigation. The proposed framework incorporates a cultural context module that enables ethically sound and culturally appropriate decision-making, along with bias detection, self-inspection, and risk assessment. By embedding trust and ethics into every layer of data processing and decision-making, this system ensures fairness and transparency in big data processing, thus contributing to the advancement of the big data ecosystem.

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