TY - GEN
T1 - Exploring the Privacy Paradox in AI Adoption
T2 - 6th International Conference on Artificial Intelligence, Robotics, and Control, AIRC 2025
AU - Olatunde, Samuel
AU - Shalan, Atef Mohamed
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025/5/7
Y1 - 2025/5/7
N2 - Artificial intelligence (AI) has revolutionized various industries by enhancing efficiency and user experiences. However, as AI systems process vast amounts of personal data, concerns about privacy, security, and potential misuse have intensified. This study examines the relationship between AI adoption and data privacy concerns, analyzing behavioral patterns from a dataset of 656 participants using Orange Data Mining for descriptive statistical analysis, comparative analysis, clustering, and correlation techniques. The research investigates how AI trust influences Chatbot and virtual assistant usage, payment preferences, and demographic trends. The findings reveal a privacy paradox, where many users who distrust AI privacy still engage with AI-powered tools, highlighting the need for greater transparency and user awareness. This paper advocates stronger AI privacy policies, ethical data practices, and regulatory frameworks to ensure that AI development remains both innovative and privacy-conscious.
AB - Artificial intelligence (AI) has revolutionized various industries by enhancing efficiency and user experiences. However, as AI systems process vast amounts of personal data, concerns about privacy, security, and potential misuse have intensified. This study examines the relationship between AI adoption and data privacy concerns, analyzing behavioral patterns from a dataset of 656 participants using Orange Data Mining for descriptive statistical analysis, comparative analysis, clustering, and correlation techniques. The research investigates how AI trust influences Chatbot and virtual assistant usage, payment preferences, and demographic trends. The findings reveal a privacy paradox, where many users who distrust AI privacy still engage with AI-powered tools, highlighting the need for greater transparency and user awareness. This paper advocates stronger AI privacy policies, ethical data practices, and regulatory frameworks to ensure that AI development remains both innovative and privacy-conscious.
KW - AI
KW - Data Exploitation
KW - Data Privacy
KW - Data Protection
KW - Ethics
KW - Privacy Regulations
KW - Security
UR - https://www.scopus.com/pages/publications/105012179770
U2 - 10.1109/AIRC64931.2025.11077547
DO - 10.1109/AIRC64931.2025.11077547
M3 - Conference article
AN - SCOPUS:105012179770
SN - 9798331543488
T3 - 2025 6th International Conference on Artificial Intelligence, Robotics and Control (AIRC)
SP - 424
EP - 429
BT - 2025 6th International Conference on Artificial Intelligence, Robotics, and Control, AIRC 2025
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 7 May 2025 through 9 May 2025
ER -