The article is devoted to the urgent problem of training specialists in the field of digital identification of images created using artificial intelligence (AI). It considers modern approaches to teaching students the competencies of digital image examination, which is significant in the context of the widespread use of generative models and the need to protect the authenticity of digital content. The authors describe in detail five AI models for identifying generated images using specialized artificial intelligence models DIRE, De-Fake, Hive AI Detector, Optic and Illuminatry, focusing on the technological and applied features of these tools. The work emphasizes the importance of integrating these models into educational programs, including disciplines aimed at developing not only technical and analytical skills, but also creative and ethical competencies. The authors point out the need to combine traditional teaching methods with innovative courses focused on the development of an interdisciplinary approach, including computer vision, creativity and critical thinking. The purpose of this study is to determine the main directions of formation of competencies of modern specialists capable of competently and responsibly carrying out digital identification of images created using artificial intelligence, based on the analysis of the current state of this problem and the prospects for its further development. The research design includes the expert interview about effectiveness of AI learning and digital image expertise that was conducted among lecturers of computer technologies in leading universities of St Petersburg.

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Digital Image Expertise in the Age of Artificial Intelligence: Building Competencies for Art and Science

  • Olga Ignatjeva,
  • Konstantin Kondratenko,
  • Irina Tolstikova

摘要

The article is devoted to the urgent problem of training specialists in the field of digital identification of images created using artificial intelligence (AI). It considers modern approaches to teaching students the competencies of digital image examination, which is significant in the context of the widespread use of generative models and the need to protect the authenticity of digital content. The authors describe in detail five AI models for identifying generated images using specialized artificial intelligence models DIRE, De-Fake, Hive AI Detector, Optic and Illuminatry, focusing on the technological and applied features of these tools. The work emphasizes the importance of integrating these models into educational programs, including disciplines aimed at developing not only technical and analytical skills, but also creative and ethical competencies. The authors point out the need to combine traditional teaching methods with innovative courses focused on the development of an interdisciplinary approach, including computer vision, creativity and critical thinking. The purpose of this study is to determine the main directions of formation of competencies of modern specialists capable of competently and responsibly carrying out digital identification of images created using artificial intelligence, based on the analysis of the current state of this problem and the prospects for its further development. The research design includes the expert interview about effectiveness of AI learning and digital image expertise that was conducted among lecturers of computer technologies in leading universities of St Petersburg.