Robots in the Danger Zone: Exploring Public Perception through Engagement. Robb, D., Ahmad, M., Tiseo, C., Aracri, S., McConnell, A., C., Page, V., Dondrup, C., Garcia, F., J., C., Nguyen, H., Pairet Artau, È., Ardon, P., Semwal, T., Taylor, H., Wilson, L., Lane, D., M., Hastie, H., & Lohan, K., S. In 15th Annual ACM/IEEE International Conference on Human Robot Interaction, 2020. ![Robots in the Danger Zone: Exploring Public Perception through Engagement [link]](https://bibbase.org/img/filetypes/link.svg "link")
Website doi abstract bibtex 1 download Public perceptions of Robotics and Artificial Intelligence (RAI) are important in the acceptance, uptake, government regulation and research funding of this technology. Recent research has shown that the public's understanding of RAI can be negative or inaccurate. We believe effective public engagement can help ensure that public opinion is better informed. In this paper, we describe our first iteration of a high throughput in-person public engagement activity. We describe the use of a light touch quiz-format survey instrument to integrate in-the-wild research participation into the engagement, allowing us to probe both the effectiveness of our engagement strategy, and public perceptions of the future roles of robots and humans working in dangerous settings, such as in the off-shore energy sector. We critique our methods and share interesting results into generational differences within the public's view of the future of Robotics and AI in hazardous environments. These findings include that older peoples' views about the future of robots in hazardous environments were not swayed by exposure to our exhibit, while the views of younger people were affected by our exhibit, leading us to consider carefully in future how to more effectively engage with and inform older people.
@inproceedings{
title = {Robots in the Danger Zone: Exploring Public Perception through Engagement},
type = {inproceedings},
year = {2020},
websites = {https://dl.acm.org/doi/abs/10.1145/3319502.3374789?casa_token=y1VbWQxbE-kAAAAA:FjcegWHe7SzN-Rg2YKqYXsXO3LZDG2rTlHRfDqtdI8nerenvSubfNkheTlfxFIC6DGfGBmCuZyKi8fk},
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created = {2022-01-11T12:53:58.700Z},
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notes = {15th Annual ACM/IEEE International Conference on Human-Robot Interaction 2020, HRI 2020 ; Conference date: 23-03-2020 Through 26-03-2020},
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abstract = {Public perceptions of Robotics and Artificial Intelligence (RAI) are important in the acceptance, uptake, government regulation and research funding of this technology. Recent research has shown that the public's understanding of RAI can be negative or inaccurate. We believe effective public engagement can help ensure that public opinion is better informed. In this paper, we describe our first iteration of a high throughput in-person public engagement activity. We describe the use of a light touch quiz-format survey instrument to integrate in-the-wild research participation into the engagement, allowing us to probe both the effectiveness of our engagement strategy, and public perceptions of the future roles of robots and humans working in dangerous settings, such as in the off-shore energy sector. We critique our methods and share interesting results into generational differences within the public's view of the future of Robotics and AI in hazardous environments. These findings include that older peoples' views about the future of robots in hazardous environments were not swayed by exposure to our exhibit, while the views of younger people were affected by our exhibit, leading us to consider carefully in future how to more effectively engage with and inform older people.},
bibtype = {inproceedings},
author = {Robb, David and Ahmad, Muneeb and Tiseo, Carlo and Aracri, Simona and McConnell, Alistair Campbell and Page, Vincent and Dondrup, Christian and Garcia, Francisco Javier Chiyah and Nguyen, Hai-Nguyen and Pairet Artau, Èric and Ardon, Paola and Semwal, Tushar and Taylor, Hazel and Wilson, Lindsay and Lane, David Michael and Hastie, Helen and Lohan, Katrin Solveig},
doi = {10.1145/3319502.3374789},
booktitle = {15th Annual ACM/IEEE International Conference on Human Robot Interaction}
}
Downloads: 1
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