Research・研究内容

Research

Below are my research projects at Tokyo Tech. For my previous research, please see my personal website.

Kawaii Vocalics

Projects

Kawaii Computing

Kawaii computing explores the Japanese concept of cute in human-computer interaction contexts.We consider the socio-cultural features of kawaii in interactive experiences with computers.

カワイイ・コンピューティングは、ヒューマン・コンピュータ・インタラクションの文脈における日本の「カワイイ」の概念を探求している。我々は、コンピュータとのインタラクティブな体験における「カワイイ」の社会文化的特徴を考察する。

  • Lab Members:
    Katie Seaborn
    Yijia Wang
  • Publications:
  • Timeline: FY24~
Modelling Kawaii Vocalics

Little is known about kawaii as a sound phenomenon. What features of visual kawaii transfer? What unique properties does kawaii sound have? We ask.

音の現象としてのカワイイについてはほとんど知られていない。視覚的なカワイイにはどのような特徴があるのか？カワイイ音声にはどんなユニークな特性があるのか？我々は問う。

  • Lab Members:
    Katie Seaborn
    Tatsuya Itagaki
    Miu Kojima
    Yuto Mandai
    Julia Keckeis
    Yijia Wang
  • Publications:
  • Funding:[pending]
  • Timeline: FY22~
Kawaii Game Voice UX

Kawaii game voice user experiences (voice UX) are characterized by visual and sound phenomena associated with characters and other diegetic agents.

カワイイゲーム音声UX（ボイスUX）は、キャラクターや他のダイスジェティックエージェントに関連する視覚的・音響的現象が特徴です。

  • Lab Members:
    Katie Seaborn
    Miu Kojima
    Yijia Wang
  • Publications:
  • Funding:[pending]
  • Timeline: FY23~

Interactions in the Negaverse

Projects

ELEMI: Exoskeleton for the Mind

Exploring whether and how a metacognitive agent can help us grapple with misinformation on social media.

メタ認知エージェントがSNS上の誤報に対処するのに役立つかどうか、またどのように対処するかを探ります。

Trust in AI

What factors affect trust and reliance in AI-based agents, systems, and environments? Exploring layperson and expert perspectives.

AIを活用したエージェント、システム、環境に対する信頼や信用に影響を与える要因とは？一般人や専門家の視点を探ります。

Dark Patterns and Deceptive Design

Exploring dark patterns, deceptive interactions, and persuasive interfaces in Japan and elsewhere.

日本と海外のダークパターン、欺瞞的なインターアクション、説得力のあるインターフェイスを探ります。

  • Lab Members:
    Katie Seaborn
    Shun Hidaka
    Sota Kobuki
    Tatsuya Itagaki
    Mizuki Watanabe
    Jo Yukami
    Weichen Joe Chang
  • Publications:
  • Timeline: FY21~

AI and Intersectional Design

Projects

Gender Neutrality in Robots

We’re exploring whether and how robots can be perceived as gender-neutral.

ロボットがジェンダーニュートラルと認識されるかどうか、またどのように認識されるかを探っています。

  • Lab Members:
    Katie Seaborn
  • Publications:
  • Funding:Engineering Academy Young Scientist Encouragement Award
  • Timeline: FY22~
Social Identity in Robots

We're exploring how social identity affects human-robot interactions.

社会的アイデンティティが人間とロボットの相互作用にどのような影響を与えるかを探っています。

  • Lab Members:
    Katie Seaborn
    Haruki Kotani
    Takao Fujii
  • Publications:
  • Timeline: FY22~
Biases and Intersectionality

We're approaching biases within and around us from an intersectional lens.

私たちの中や周りのバイアス・偏見に、交差点的なレンズからアプローチしています。

  • Lab Members:
    Katie Seaborn
    Yeongdae Kim
    Shruti Chandra
  • Publications:
  • Funding:Engineering Academy Young Scientist Encouragement Award
  • Timeline: FY22~

Voice UX

Projects

Voice Against Bias

Can voice influence attitudes towards age? We aim to find out with MAKOTO, our “older adult” voice assistant.

音声は年齢に対する意識に影響を与えることができるのか？お年寄りぽい音声アシスタント「MAKOTO」を使って、それを明らかにすることを目指します。

Evaluating Voice UX

We're exploring ways to measure and evaluate interactions with voice-based agents, interfaces, and environments.

音声エージェント、インターフェース、環境とのインタラクションを測定・評価する方法を模索しています。

Morphologies in Voice and Body

What kinds of bodies should voice-based agents have, if any? We explore a range of modalities and morphologies.

音声ベースのエージェントは、どのような身体を持つべきなのでしょうか。私たちは、さまざまなモダリティとモルフォロジーを探求しています。

Li, G. “Rikaku,” & Seaborn, K. (2024). No joke: An embodied conversational agent greeting older adults with humour or a smile unrelated to initial acceptance. Extended Abstracts of the 2024 CHI Conference on Human Factors in Computing Systems, accepted. https://doi.org/10.1145/3613905.3650918 Cite
Wang, Y., & Seaborn, K. (2024). Kawaii computing: Scoping out the Japanese notion of cute in user experiences with interactive systems. Extended Abstracts of the 2024 CHI Conference on Human Factors in Computing Systems, accepted. Cite
Seaborn, K., Rogers, K., Nam, S., & Kojima, M. (2023). Kawaii game vocalics: A preliminary model. Companion Proceedings of the Annual Symposium on Computer-Human Interaction in Play, 202–208. https://doi.org/10.1145/3573382.3616099 Cite
Hidaka, S., Kobuki, S., Watanabe, M., & Seaborn, K. (2023). Linguistic dead-ends and alphabet soup: Finding dark patterns in Japanese apps. Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 1–13. https://doi.org/10.1145/3544548.3580942 Cite
Seaborn, K., Nam, S., Keckeis, J., & Itagaki, T. (2023). Can voice assistants sound cute? Towards a model of kawaii vocalics. Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, 1–7. https://doi.org/10.1145/3544549.3585656 Cite
Seaborn, K., Chandra, S., & Fabre, T. (2023). Transcending the “male code”: Implicit masculine biases in NLP contexts. Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 1–19. https://doi.org/10.1145/3544548.3581017 Cite
Seaborn, K. (2023). Interacting with masculinities: A scoping review. Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, 1–12. https://doi.org/10.1145/3544549.3585770 Cite
Seaborn, K., & Kim, Y. (2023). “I’m” lost in translation: Pronoun missteps in crowdsourced data sets. Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, 1–6. https://doi.org/10.1145/3544549.3585667 Cite
Ku, B., Itagaki, T., & Seaborn, K. (2023). Dis/immersion in mindfulness meditation with a wandering voice assistant. Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, 1–6. https://doi.org/10.1145/3544549.3585627 Cite
Ueno, T., Kim, Y., Oura, H., & Seaborn, K. (2023). Trust and reliance in consensus-based explanations from an anti-misinformation agent. Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, 1–7. https://doi.org/10.1145/3544549.3585713 Cite
Seaborn, K., Barbareschi, G., & Chandra, S. (2023). Not only WEIRD but “uncanny”? A systematic review of diversity in human-robot interaction research. International Journal of Social Robotics. https://doi.org/10.1007/s12369-023-00968-4 Cite
Kim, Y., Ueno, T., Seaborn, K., Oura, H., Urakami, J., & Sawa, Y. (2023). Exoskeleton for the mind: Exploring strategies against misinformation with a metacognitive agent. Proceedings of the 2023 ACM International Conference on Augmented Humans (AHs). AHs ’23, Glasgow, Scotland, UK. https://doi.org/10.1145/3582700.3582725 Cite
Seaborn, K., Miyake, N. P., Pennefather, P., & Otake-Matsuura, M. (2022). Voice in human–agent interaction: A survey. ACM Computing Surveys, 54(4), 1–43. https://doi.org/10.1145/3386867 Cite
Sawa, Y., & Seaborn, K. (2022). Localizing the Ambivalent Ageism Scale for Japan. The 8th Asian Conference on Aging & Gerontology 2022: Official Conference Proceedings, 33–36. https://doi.org/10.22492/issn.2432-4183.2022.4 Cite
Seaborn, K., & Pennefather, P. (2022). Neither “hear” nor “their”: Interrogating gender neutrality in robots. Proceedings of the 2022 ACM/IEEE International Conference on Human-Robot Interaction, 1030–1034. https://doi.org/10.5555/3523760.3523929 Cite
Seaborn, K., & Pennefather, P. (2022). Gender neutrality in robots: An open living review framework. Proceedings of the 2022 ACM/IEEE International Conference on Human-Robot Interaction, 634–638. https://doi.org/10.5555/3523760.3523845 Cite
Seaborn, K., & Frank, A. (2022). What pronouns for Pepper? A critical review of gender/ing in research. Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, 1–15. https://doi.org/10.1145/3491102.3501996 Cite
Seaborn, K., Pennefather, P., & Kotani, H. (2022). Exploring gender-expansive categorization options for robots. Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems, 1–6. https://doi.org/10.1145/3491101.3519646 Cite
Seaborn, K. (2022). From identified to self-identifying: Social Identity Theory for socially embodied artificial agents. Proceedings of the HRI 2022 Workshop on Robo-Identity 2. HRI Workshop on Robo-Identity ’22, Sapporo, Hokkaido, Japan. https://sites.google.com/view/robo-identity2 Cite
Ueno, T., Sawa, Y., Kim, Y., Urakami, J., Oura, H., & Seaborn, K. (2022). Trust in human-AI interaction: Scoping out models, measures, and methods. Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems, 1–7. https://doi.org/10.1145/3491101.3519772 Cite
Kobuki, S., Seaborn, K., Tokunaga, S., Fukumori, K., Hidaka, S., Tamura, K., Inoue, K., Kawahara, T., & Otake-Matsuura, M. (2022). Robots using “aizuchi” in online group conversation. Proceedings of the 40th Meeting of the Robotics Society of Japan (RSJ 2022). RJS 2022, Tokyo, Japan. https://ac.rsj-web.org/2022/ Cite
Urakami, J., Kim, Y., Oura, H., & Seaborn, K. (2022). Finding Strategies against Misinformation in Social Media: A Qualitative Study. Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems, 1–7. https://doi.org/10.1145/3491101.3519661 Cite
Seaborn, K., Urakami, J., & Oura, H. (2021, August 8). Bots Against Bias (BoAB): A seminar on designing robots that enhance human metacognition [Workshop]. 2021 IEEE International Conference on Robot and Human Interactive Communication (RO-MAN 2021), Vancouver, BC, Canada. https://aspirelab.io/boab2021/ Cite
Seaborn, K., & Urakami, J. (2021). Measuring voice UX quantitatively: A rapid review. Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems, 1–8. https://doi.org/10.1145/3411763.3451712 Cite
Seaborn, K., Pennefather, P., Miyake, N., & Otake-Matsuura, M. (2021). Crossing the Tepper line: An emerging ontology for describing the dynamic sociality of embodied AI. Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems, 1–6. https://doi.org/10.1145/3411763.3451783 Cite
Seaborn, K. (2021). Removing gamification: A research agenda. Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems, 1–7. https://doi.org/10.1145/3411763.3451695 Cite
Kawaii Vocalics

Collaboration

Kawaii Vocalics

This project will focus on the novel concept of kawaii vocalics. The two research trajectories are: (i) what is the nature of kawaii vocalics compared to kawaii visuals, which comprises almost all work on kawaii science so far (theoretical extension); and (ii) what emotions and behaviour do kawaii voices elicit compared to kawaii visuals (methodological extension).

このプロジェクトでは、「カワイイ・ヴォーカリクス」という新しい概念に焦点を当てる。研究の軌跡は以下の2つである： (i)これまでのカワイイ科学に関する研究のほとんどを占めるカワイイビジュアルと比較して、カワイイ・ヴォーカリックスの本質とは何か（理論的拡張）、(ii)カワイイビジュアルと比較して、カワイイ・ヴォイスはどのような感情や行動を引き起こすのか（方法論的拡張）。

April 2024 to March 2028

Prof. Katie Seaborn (Tokyo Tech)
Prof. Mayu Koike (Tokyo Tech)
Dr. Jun Kato (AIST)

Funding: [pending]

Collaboration

Aromanoidics

We will explore people's mental models of robot scent. To this end, we will conduct exploratory human subjects research on scent-to-robot matching and controlled experiments of different scents for different robots. This work is sure to spark research on robot aroma and olfactory interaction. The results may be used in the design of robots that work closely with people, such as in the workplace, in the home, as (aroma)therapeutic robots, and in customer service settings, especially at storefronts.

ロボットの香りに関する人々のメンタルモデルを探る。そのために、香りとロボットのマッチングに関する探索的な人体実験と、さまざまなロボットにさまざまな香りを適用する対照実験を行う。この研究は、ロボットの香りと嗅覚インタラクションの研究に火をつけるに違いない。この成果は、職場や家庭、（香り）治療ロボット、接客（特に店頭）など、人と密接に働くロボットの設計に活用されるかもしれない。

June 2023 to June 2024

Prof. Katie Seaborn (Tokyo Tech)
Prof. Gentiane Venture (The University of Tokyo)

Funding: 16th Shiseido Female Researcher Science Grant

Aromanoidics
Voice Against Bias

Independent

Voice Against Bias

We will explore the use of "elder" voice assistants as a novel method of reducing negative cognitive biases like implicit ageism. Cognitive biases are natural functions of the human mind that are influenced by the external world in positive and negative ways. Through co-design methodologies, intergenerational user studies, and long-term "in the wild" evaluations, we will examine whether voice assistants with older adult voices can shift biases in prosocial directions.

暗黙のエイジズムのような否定的な認知バイアスを軽減するための新しい方法として、「年長者」の音声アシスタントの使用の研究。認知バイアスとは、人間の心が持つ自然な機能であり、外界の影響を受けてポジティブにもネガティブにも変化するもの。共同デザイン手法、世代間のユーザー研究、および長期的な「イン・ザ・ワイルド」評価を通じて、高齢者の声を持つ音声アシスタントが偏見を向社会的な方向にシフトできるかどうかを検証する。

April 2021 to March 2025

Prof. Katie Seaborn

Funding: JSPS KAKENHI Wakate

Collaboration

Project Elemi

Our goal is to create and study Elemi, an “exoskeleton for the mind.” Elemi will be an AI-based intelligent support system designed to augment metacognition in everyday situations. Built with and for the public, it aims to help people with a range of everyday challenges in the information age.

本プロジェクトの目標は，心の外骨格「エレミ」を開発し研究することである。エレミは，日常的な状況におけるメタ認知を増強するためのAIベースの知的支援システムである。情報社会における日常の課題について人々を支援することがねらいである。

September 2020 to March 2022

Prof. Jacqueline Urakami (Tokyo Tech)
Prof. Hiroki Oura (Tokyo Tech / Tokyo University of Science)
Dr. Yeongdae Kim (Project Researcher)

Funding: DLab Challenge Grant

Project Elemi