| Project/Area Number |
21K18005
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 90010:Design-related
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| Research Institution | Institute of Science Tokyo |
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Principal Investigator |
Seaborn Katie 東京科学大学, 工学院, 准教授 (70831262)
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| Project Period (FY) |
2021-04-01 – 2025-03-31
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| Project Status |
Completed (Fiscal Year 2024)
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| Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2023: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2022: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2021: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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| Keywords | HCI / voice assistant / implicit ageism / voice UX / computer voice / ageism / artificial intelligence / older adults / implicit bias / user experience / human-agent interaction / voice perceptions / voice ux / usability / intergenerational / Computer voice / Voice asssistants / Inclusive design / Implicit bias / Older adults |
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| Outline of Research at the Start |
"Older adult" voice assistants will be explored as a novel method of reducing the cognitive bias of implicit ageism. To this end, three longitudinal experimental studies will be conducted on: (1) voice assistants that use "aged" voices with older adults; (2) voice assistants that use the older adult participant's own voice; and (3) voice assistants with "aged" voices used by younger age groups. Outcomes will include empirical evidence of attitude change and debiasing, a psychosocial model of impact, and design knowledge on "aged" machine voices for intergenerational populations.
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| Outline of Final Research Achievements |
MAKOTO, a voice assistant designed with an older adult persona, was developed through a multi-phase process involving custom voice recordings, advanced TTS generation using the Tsubame Supercomputer, and extensive user research. The system, housed in the MAKOTO-Dreamsmithy platform, was created to offer brief, positive daily interactions. The project involved several user studies, literature reviews, and the development of new evaluation tools like VOXI and a translated PMQ. A longitudinal field study showed that repeated interaction with MAKOTO led to reduced implicit ageism in people with initially strong implicit ageism. Older adults rated MAKOTO’s voice and persona more positively than younger users, and most participants found the system engaging and easy to use. The project provides one of the first empirical demonstrations that a voice assistant with an older persona can help reduce unconscious ageism, offering insights for designing more socially responsible AI systems.
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| Academic Significance and Societal Importance of the Research Achievements |
The main scientific achievement is demonstration that repeated exposure to an "older adult" voice assistant can reduce implicit ageism in the most biased. This could lead to social innovation on bias reduction through design and highlights the social value of inclusive, age-friendly AI technologies.
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