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| Generative AI in Sensory Science: Data Crunching to Consumer Understanding |
| Michelle Murphy Niedziela Nerdoscientist LLC, , , |
The integration of generative AI technologies into sensory research holds promise for advancing our understanding of consumer responses to taste and smell. Generative AI tools, such as large language models, have demonstrated potential in automating the analysis of qualitative data, expediting thematic coding, and identifying patterns within consumer narratives. Moving beyond these established applications, this talk will explore the capacity of generative AI to enhance experimental design, simulate real-world sensory environments, and facilitate cross-modal insights. Using AI-driven virtual and augmented reality environments enables the recreation of ecologically valid contexts-such as noisy restaurants or serene outdoor settings-that are crucial for assessing sensory experiences in realistic conditions. AI's ability to model complex environmental variables, including ambient noise, lighting, and temperature, contributes to a more comprehensive understanding of how context influences sensory perception and satisfaction. Adaptive AI environments and chatbots can dynamically adjust to participant responses, offering novel approaches for studying the fluid and context-dependent nature of sensory experiences. The integration of behavioral science frameworks, such as decision-making models and theories of multisensory integration, enhances the interpretive value of AI-generated data, ensuring that insights, remain consumer-centric and actionable. Ethical considerations and the challenges of balancing technological advancements with consumer-focused research will also be discussed. The potential of generative AI to transform sensory research offers new methodologies that align with behavioral science principles and provides opportunities for more efficient, robust, and ecologically valid studies. |