HI-TAM, a hybrid intelligence framework for training and adoption of generative design assistants - Mao, Yaoli; Rafner, Janet; Wang, Yi; Sherson, Jacob (Frontiers in Computer Science, 2024)
The Hybrid Intelligence Technology Acceptance Model (HI-TAM) presented in this paper offers a novel framework for training and adopting generative design (GD) assistants, facilitating co-creation between human experts and AI systems. Despite the promising outcomes of GD, such as augmented human cognition and highly creative design products, challenges remain in the perception, adoption, and sustained collaboration with AI, especially in creative design industries where personalized and specialized assistance is crucial for individual style and expression. In this two-study paper, we present a holistic hybrid intelligence (HI) approach for individual experts to train and personalize their GD assistants on-the-fly. Culminating in the HI-TAM, our contribution to human-AI interaction is 4-fold including (i) domain-specific suitability of the HI approach for real-world application design, (ii) a programmable common language that facilitates the clear communication of expert design goals to the generative algorithm, (iii) a human-centered continual training loop that seamlessly integrates AI training into the expert's workflow, (iv) a hybrid intelligence narrative that encourages the psychological willingness to invest time and effort in training a virtual assistant. This approach facilitates individuals' direct communication of design objectives to AI and fosters a psychologically safe environment for adopting, training, and improving AI systems without the fear of job-replacement. To demonstrate the suitability of HI-TAM, in Study 1 we surveyed 41 architectural professionals to identify the most preferred workflow scenario for an HI approach. In Study 2, we used mixed methods to empirically evaluate this approach with 8 architectural professionals, who individually co-created floor plan layouts of office buildings with a GD assistant through the lens of HI-TAM. Our results suggest that the HI-TAM enables professionals, even non-technical ones, to adopt and trust AI-enhanced co-creative tools.