Voice Against Bias: Exploring Voice Assistants as a Method of Countering Implicit Bias
| 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 | Tokyo Institute of Technology |
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Principal Investigator |
シーボーン ケイティー 東京工業大学, 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 |
Granted (Fiscal Year 2023)
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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 / computer voice / implicit bias / ageism / user experience / human-agent interaction / voice perceptions / older adults / voice assistant / 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 Annual Research Achievements |
Two new voices were created and evaluated. Results through perception studies and interviews with the voice actors indicated high technical and user experience quality. A new system combining an existing anti-misinformation metacognitive tool developed in the lab for Twitter/X (ELEMI) was created; later, a ChatGPT extension was added. A user study was conducted. However, due to poor user results and the instability of the platform, development on a new system began. Two journal papers were published to top-ranked, international, peer-reviewed venues in human-computer interaction: ACM CSUR and Wiley Human Behavior and Emerging Technologies. A spin-off project on kawaii vocalics was developed and accepted for Grants-in-Aid.
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| Current Status of Research Progress |
Current Status of Research Progress
3: Progress in research has been slightly delayed.
Reason
Due to COVID-19 and other intervening factors, we were granted a year extension. This has been invaluable for progress. We are on track to finish the final system, run the final user study, and conduct the field study. However, one student member is refusing to complete the promised work on the measurement part after graduation; the other team members will need to do it, causing serious delays. Still, we have completed all other tasks outlined in the grant proposal.
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| Strategy for Future Research Activity |
We aim to complete the main studies by September 2024. We will begin to transition work to the new, follow-up grant at that time.
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Report
(3 results)
Research Products
(10 results)
