The MADE framework Best practices for creating effective experimental stimuli using generative AI
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| Publication date | 2024 |
| Journal | Journal of Advertising |
| Volume | Issue number | 53 | 5 |
| Pages (from-to) | 732–753 |
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| Abstract |
This paper introduces the MADE (Mapping, Assembling, Demonstrating, Executing) framework, a comprehensive set of best practices for the ethical and effective use of generative artificial intelligence (AI) in creating experimental stimuli for advertising research. The framework was developed through an extensive exploration of various emergent generative AI tools used in common experimental manipulations. We apply the MADE framework to demonstrate the creation of high-quality, realistic experimental ads using leading generative AI tools. Our empirical testing shows that AI-generated stimuli are valid, with consumers rating them equally high in quality, appropriateness, and realism compared with professionally created ads. This finding underscores the viability of AI-generated ads in advertising research. Additionally, we discuss the importance of adhering to ethical standards and ensuring transparency in AI use. By combining technological innovation with methodological rigor, this paper aims to guide researchers in leveraging the potential of generative AI while addressing its ethical implications, thereby enhancing the realism and validity of experimental advertising research.
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| Document type | Article |
| Language | English |
| Published at | https://doi.org/10.1080/00913367.2024.2397777 |
| Other links | https://www.tandfonline.com/doi/full/10.1080/00913367.2024.2397777 |
| Downloads |
The MADE framework
(Final published version)
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