User-Centric Adoption of Democratized Generative AI: Focus on Human-Machine Interaction and Overcoming Challenges
User-Centric Adoption of Democratized Generative AI: Focus on Human-Machine Interaction and Overcoming Challenges |
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| © 2024 by IJETT Journal | ||
| Volume-72 Issue-9 |
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| Year of Publication : 2024 | ||
| Author : Abdinor Abukar Ahmed, Mohamed Khalif Ali |
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| DOI : 10.14445/22315381/IJETT-V72I9P107 | ||
How to Cite?
Abdinor Abukar Ahmed, Mohamed Khalif Ali, "User-Centric Adoption of Democratized Generative AI: Focus on Human-Machine Interaction and Overcoming Challenges," International Journal of Engineering Trends and Technology, vol. 72, no. 9, pp. 78-95, 2024. Crossref, https://doi.org/10.14445/22315381/IJETT-V72I9P107
Abstract
The rise of Generative Artificial Intelligence (GenAI) has triggered significant progress across multiple fields, presenting unparalleled abilities in fostering creativity, addressing problems, and simulating human-like interactions. Despite their potential, Generative AI tools present challenges in user understanding and engagement across various industries. Professionals in diverse roles encounter difficulties integrating these advanced tools into daily operations, hindering seamless adoption. The diverse reliability and accuracy of AI-generated content require stringent validation and quality assurance. Democratized Generative AI emerges as a novel strategy for expanding the reach of AI technology to a diverse user base, intending to distribute its advantages equitably and contribute to the collective well-being of society, even fostering the expansion of access to non-technical. The user-centric adoption of democratized GenAI positions at the forefront, emphasizing a crucial shift towards inclusive and interactive human-machine collaboration. The arrangement of the work enables us to not only determine the positioning of the research but also visualize the existing challenges, like ethical use, privacy, security concerns, and use cases within the domain. Finally, the researchers explore future directions in democratizing GenAI, encompassing improvements in digital prototyping, enhanced encryption methods, and the promotion of interdisciplinary insights for societal impact.
Keywords
Democratized GenAI, Deepfake technology, Explainability, Hyper-personalization, JCAS, Predictive maintenance, Privacy, SORA.
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