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Exploring the Transition from “Contextual AI” to “Generative AI” in Management: Cases of ChatGPT and DALL-E 2

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Advances in Intelligent Manufacturing and Service System Informatics (IMSS 2023)

Part of the book series: Lecture Notes in Mechanical Engineering ((LNME))

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Abstract

The transition towards Generative Artificial Intelligence (GAI) is rapidly transforming the digital realm and providing new avenues for creativity for all humanity. In the past two years, several generative models have disrupted worldwide, including ChatGPT and DALL-E 2, developed by OpenAI, which are currently receiving significant media attention. These models can generate new content, respond to prompts, and automatically create new images and videos. Nevertheless, despite this progress of GAI, research into its application in business and industry is still in its infancy. Generative AI is bringing ground-breaking innovations that go beyond the limitations of conventional Contextual AI. This new type of AI can generate novel patterns in human-like creativity, encompassing various forms of content such as text, images, and media. It transforms how people communicate, create, and share content, taking organizations by surprise. Unfortunately, these organizations were not fully prepared as they were focused on the advancements and impacts of Contextual AI. Given the significant organizational-societal opportunities and challenges posed by generative models, it is crucial to comprehend their ramifications. However, the excessive hype surrounding GAI currently makes it difficult to determine how organizations can effectively utilize and regulate these powerful algorithms. In research, the primary question is how organizations can manage the intersection of human creativity and machine creativity, and how can they leverage this intersection to their advantage? To address this question and mitigate concerns related to it, a comprehensive understanding of GAI is essential. Therefore, this paper aims to provide technical insights into this paradigm and analyze its potential, opportunities, and constraints for business and industrial research.

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Authors and Affiliations

  1. HuManis Laboratory of EM Strasbourg Business School, Strasbourg, France

    Samia Chehbi Gamoura

  2. Industrial Engineering Department, Süleyman Demirel University, Isparta, Turkey

    Halil İbrahim Koruca & Kemal Burak Urgancı

Authors
  1. Samia Chehbi Gamoura
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  2. Halil İbrahim Koruca
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  3. Kemal Burak Urgancı
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Corresponding author

Correspondence to Samia Chehbi Gamoura .

Editor information

Editors and Affiliations

  1. Istanbul Medipol University, Istanbul, Türkiye

    Zekâi Şen

  2. Department of Industrial Engineering, Sakarya University, Serdivan, Sakarya, Türkiye

    Özer Uygun

  3. Faculty of Applied Sciences, Sakarya University of Applied Sciences, Kaynarca, Sakarya, Türkiye

    Caner Erden

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Gamoura, S.C., Koruca, H.İ., Urgancı, K.B. (2024). Exploring the Transition from “Contextual AI” to “Generative AI” in Management: Cases of ChatGPT and DALL-E 2. In: Şen, Z., Uygun, Ö., Erden, C. (eds) Advances in Intelligent Manufacturing and Service System Informatics. IMSS 2023. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-99-6062-0_34

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  • DOI: https://doi.org/10.1007/978-981-99-6062-0_34

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