Dr. Taylor opened with a discussion of AI’s impact on advertising creativity, emphasizing the importance of the “human touch.” Drawing on early research into AI-generated advertising and music, he noted that combining AI with human creative input can produce better results than AI alone. However, he cautioned that such benefits are not universal and highlighted opportunities for further research into how human involvement shapes creativity, advertising effectiveness, and consumer responses. He also identified future research opportunities involving AI-driven personalization, consumer privacy, and the ethical implications of emerging advertising technologies.
Dr. Kim explored the practical applications and ethical challenges of AI-assisted research, demonstrating how AI tools can support literature discovery, research development, and the creation of interactive experimental settings. “AI can be our assistant, but it cannot be an author,” she emphasized, reminding researchers to follow institutional and journal guidelines, protect confidential information, and retain responsibility for theoretical development, research design, and the accuracy of AI-generated outputs.
The lecture sparked a lively exchange on AI-assisted content analysis, peer review, and academic writing. Responding to doctoral student Hung-Yen Hsu (許弘諺), Dr. Kim distinguished between evaluating AI’s coding capabilities and using AI coding to answer substantive research questions. She also stressed that peer review should focus on theoretical arguments and scholarly contributions rather than language-level corrections. “We are trying to create new knowledge, and that is where AI still struggles,” Dr. Taylor added.
College alumna Yi-Ying Lin (林怡瑩) and doctoral student Yang Lee (李羏) raised questions about AI-assisted interpretation, editing, and translation. Dr. Kim explained how she uses AI to critique her initial interpretations and identify potential oversights. Dr. Taylor noted that AI-assisted copy editing is generally accepted, but cautioned that translation can alter subtle distinctions in survey measures.
Drawing on her experience supervising research in local contexts, Dr. Lin highlighted the importance of maintaining conceptual accuracy across languages, particularly in theoretical arguments and research instruments. “As you receive more help from AI, you also need to strengthen your own expertise to verify the content and concepts,” she told students.
By bringing international journal editors into the doctoral classroom, the session offered students firsthand perspectives on how AI is reshaping academic research and scholarly publishing. The exchange reinforced the value of cultivating independent research judgment and engaging with emerging methodological and ethical challenges early in doctoral training.
(Text and Images by Che-Wei Hsu, Ph.D. Student)
