HI-TAM, a hybrid intelligence framework for training and adoption of generative design assistants
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 cogn...
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Frontiers Media S.A.
2024-11-01
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| Series: | Frontiers in Computer Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fcomp.2024.1460381/full |
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| author | Yaoli Mao Janet Rafner Janet Rafner Yi Wang Jacob Sherson |
| author_facet | Yaoli Mao Janet Rafner Janet Rafner Yi Wang Jacob Sherson |
| author_sort | Yaoli Mao |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-5869e884fa514b28a0f50e0b1baf2194 |
| institution | OA Journals |
| issn | 2624-9898 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Computer Science |
| spelling | doaj-art-5869e884fa514b28a0f50e0b1baf21942025-08-20T02:07:02ZengFrontiers Media S.A.Frontiers in Computer Science2624-98982024-11-01610.3389/fcomp.2024.14603811460381HI-TAM, a hybrid intelligence framework for training and adoption of generative design assistantsYaoli Mao0Janet Rafner1Janet Rafner2Yi Wang3Jacob Sherson4Autodesk Inc., San Francisco, CA, United StatesCenter for Hybrid Intelligence, Department of Management, School of Business and Social Science, Aarhus University, Aarhus, DenmarkAarhus Institute for Advanced Studies, Aarhus University, Aarhus, DenmarkAutodesk Research, San Francisco, CA, United StatesCenter for Hybrid Intelligence, Department of Management, School of Business and Social Science, Aarhus University, Aarhus, DenmarkThe 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.https://www.frontiersin.org/articles/10.3389/fcomp.2024.1460381/fullgenerative designco-creativityhybrid intelligencehuman-centered AIarchitecture |
| spellingShingle | Yaoli Mao Janet Rafner Janet Rafner Yi Wang Jacob Sherson HI-TAM, a hybrid intelligence framework for training and adoption of generative design assistants Frontiers in Computer Science generative design co-creativity hybrid intelligence human-centered AI architecture |
| title | HI-TAM, a hybrid intelligence framework for training and adoption of generative design assistants |
| title_full | HI-TAM, a hybrid intelligence framework for training and adoption of generative design assistants |
| title_fullStr | HI-TAM, a hybrid intelligence framework for training and adoption of generative design assistants |
| title_full_unstemmed | HI-TAM, a hybrid intelligence framework for training and adoption of generative design assistants |
| title_short | HI-TAM, a hybrid intelligence framework for training and adoption of generative design assistants |
| title_sort | hi tam a hybrid intelligence framework for training and adoption of generative design assistants |
| topic | generative design co-creativity hybrid intelligence human-centered AI architecture |
| url | https://www.frontiersin.org/articles/10.3389/fcomp.2024.1460381/full |
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