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Writer's pictureLille My

Webinar summary: How Generative AI Changes Information Discovery

Updated: May 12

The webinar hosted by Wiley's training team was centered on the transformative impact of generative AI on information discovery, particularly in the context of scholarly research and publishing. Dr. Hong Zhu, the Director of Intelligence Service Group at Wiley Partner Solutions, was the featured speaker. The session was designed to clarify how AI technologies, especially generative AI, are reshaping the ways in which researchers interact with and leverage digital content.





The webinar commenced with a greeting and introduction by a member of Wiley's training team, who provided an overview of the session's logistics and resources available to the participants, including the recording availability post-session and downloadable slides for reference.


Dr. Zhu's presentation was structured into several parts, each addressing different aspects of AI's integration into the research and publishing landscape:


Dr. Zhu introduced the concept of digital transformation in scholarly research, emphasizing the integration of AI, big data, and cloud technologies. He outlined the role of AI in enhancing the discoverability and accessibility of research materials, thereby enabling researchers to derive more value from content.


A significant portion of the discussion focused on generative AI’s role in information discovery. Dr. Zhu explained how AI models like GPT and BERT are employed to generate research content and improve information retrieval processes. He highlighted several applications of AI in the research phase, from identifying research directions to aiding in the publication process.


Dr. Zhu shared examples of AI applications in real-world scenarios, such as entity mining in chemistry and the development of AI-driven knowledge graphs that helped identify potential treatments for COVID-19. Looking ahead, he speculated on the future of AI in research, suggesting a shift towards more integrated and intelligent systems that could potentially replace traditional search methodologies with more dynamic, AI-driven interactions.


Throughout the session, the audience was engaged through polls aimed at understanding their preferences and experiences with AI tools in scholarly work. The results indicated a strong preference for traditional search methods over conversational AI tools, highlighting an area for further development and user education.


Dr. Zhu concluded with thoughts on the ethical and practical implications of generative AI in research. The Q&A session that followed addressed specific concerns about AI's role in promoting or hindering novel research, with Dr. Zhu emphasizing AI as a tool to augment human work rather than replace it.


From an academic perspective, the webinar effectively highlighted the current capabilities and future potential of AI in scholarly research and publishing. It also underscored the necessity for ongoing education and adaptation among researchers to leverage AI technologies fully. The discussions pointed towards an increasing need to balance AI's benefits in automation and efficiency with critical considerations around ethics, bias, and data security.


In conclusion, the webinar provided comprehensive insights into the role of generative AI in transforming scholarly research and publishing. It offered a nuanced understanding of the challenges and opportunities presented by AI technologies, paving the way for further discussion and exploration in the academic community.


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