Affiliations: [a] School of Electromechanical Engineering, Lingnan Normal University, Zhanjiang, Guangdong, China | [b] Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, Macau, China | [c] Sichuan Digital Transportation Tech Co. Ltd., Chengdu, Sichuan, China
Correspondence:
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Corresponding author: Xinyuan Tian, Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, Macau 999078, China. E-mail: [email protected].
Abstract: In order to allow users to incorrectly identify images by manipulating them using deep neural networks, this paper analyses the shortcomings of deep learning for image classification. It also develops a game that uses this technique. In the game, players can select one of their preferred product categories, causing the model to classify other product categories incorrectly as the one they selected. The goal of this game is to demonstrate to players the limitations of AI. We evaluate these programs based on their overall effectiveness, user satisfaction, and achievement of their objectives. The results show that this program is a successful method for arousing curiosity and stimulating thought. They can learn to appreciate the limitations of AI and the need to prioritize AI security in their daily activities.
Keywords: Deep learning, adversarial attack, image classification, game
