The Rise of GenAI: What it Means for Research, Teaching, and Practice Beyond ChatGPT
by Jorge Luis Alonso with ChatGPT
Have you heard about ChatGPT? It’s OpenAI’s free chatbot that has been generating text at an impressive rate. In just two months, it has attracted over 100 million users! However, a recent study showed that only 68% of the generated abstracts and 14% of the original abstracts could be correctly identified as being generated by the chatbot. This highlights the importance of properly citing any results obtained from ChatGPT or other Generative Artificial Intelligence (GenAI) tools. The International Journal of Research in Marketing (IJRM) has even put forward guidelines for handling AI-generated literature reviews, as their editorial policy doesn’t allow the use of AI as co-authors due to the lack of accountability.
An editorial in this journal aims to initiate a dialogue and promote research to maximize the potential of GenAI in marketing while addressing its challenges.
While GenAI tools have the potential to revolutionize research methods and evaluation, their limited accuracy and lack of references raise concerns about their reliability for literature reviews without human review. Therefore, it’s essential to maintain “human in the loop” when using ChatGPT for research purposes.
However, the implications of GenAI extend far beyond ChatGPT. We’re talking about tools that generate intelligent output in response to human input, such as text, code, simulations, images, 3D objects, and video! Some examples of such tools include Magic Write, Eleven Labs, DALL-E 2, Midjourney, Stable Diffusion, and Channel.
The potential for GenAI tools to identify high-impact research questions and hypotheses and speed up the reporting process is enormous. They could also benefit researchers with limited English proficiency or in disadvantaged institutions and help disseminate research to a wider audience. However, their reliability and validity must be continually monitored and explored, especially with regard to unintended biases.
In education, the emergence of ChatGPT and other forms of GenAI has led to discussions on how to incorporate them into training students to effectively use the latest technologies to solve real-world problems. Rather than focusing on detecting AI-generated text and ensuring academic integrity, a more progressive approach would be to teach students about prompt engineering, evaluate the output of GenAI, and understand its limitations.
In marketing, GenAI will transform the industry by reducing marketing costs, increasing productivity and job satisfaction, and democratizing marketing. This will benefit startups, small businesses, entrepreneurs, non-profits, and bottom-of-the-pyramid companies. It’ll also democratize creative activities by reducing barriers to entry for untrained novices, empowering crowdsourcing efforts, and challenging the role of expertise in bringing successful new products to market. However, experts need to be cautious of the downsides and new questions for the theory and practice of creativity and innovation management.
Lastly, the proliferation of GenAI tools raises intellectual property concerns, as AI is often trained on data that are not owned by the companies marketing the tools. Protecting the results of GenAI raises questions about copyright infringement and whether a human should get credit for creating art using GenAI. Differences between the use of GenAI and other forms of creation, as well as differences in the perceptions of creators and evaluators, also need to be considered. It’s important for experts to take note of these issues.
IJRM encourages research and empirical projects to explore the implications of GenAI for marketing research, teaching, and business. Manuscripts reporting related work are welcome to be submitted to the journal.
Source: Peres, R., Schreier, M., Schweidel, D., & Sorescu, A. (2023). On ChatGPT and Beyond: How Generative Artificial Intelligence May Affect Research, Teaching, and Practice. International Journal of Research in Marketing [ Journal pre-proofs ]
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