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Affectosphere Group Kansai University, Keito Inoshita Laboratory
JP

Affectosphere Group

Creating space in the age of AI through emotion.

Measuring emotion and returning it to society. Toward a time when everyone can breathe a little easier.

About Affectosphere Research

Vision

About Affectosphere

Emotion envelops society like an atmosphere, quietly shaping our judgments, our relationships, and the very texture of our inner life. We read this ubiquitous affective sphere with AI, attune AI itself toward the shape that best serves people, and pursue research that connects this work to a society where, even in the age of AI, everyone can keep a margin in the heart.

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Keito Inoshita

Principal Investigator

Keito Inoshita

Affiliated with the Graduate School of Business Administration at Kansai University, the Data Science and AI Innovation Research Center at Shiga University, and the Japan Safety Society Research Center. In parallel, he pursues research and development at the intersection of AI and emotion through collaborations with a wide range of companies.

He founded the Affectosphere Group and works coherently across the generation, recognition, and understanding of human emotion with AI, on human-AI interaction, and on the ethics and philosophy of affective AI. The ultimate aim is to realize AI endowed with an EQ that surpasses humans.

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Research themes

Research domains of the lab.

Emotion and society, technology and ethics. Ten domains explored by Affectosphere Group.

Ethics and Philosophy of Affective AI

We keep asking who emotion-measuring technologies are for, and how they should be used. We reexamine, in the language of philosophy, the norms that lie between technology and the human.

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Understanding Human Emotion

How do humans actually experience and express emotion in the first place? We re-read the accumulated insights of psychology, cognitive science, and neuroscience as the foundation for AI research.

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Augmenting Emotional Data

We explore methods that augment and complete ambiguous, polysemous emotion labels while preserving their uncertainty — enabling faithful learning even from sparse annotation.

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Understanding the Inside of Affective AI

We unravel what models actually base their emotion judgments on and make the underlying behavior visible.

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Emotion Recognition by AI

Foundational recognition research that estimates emotion distributions from text, speech, and physiological signals — aiming for designs that handle uncertainty rather than point estimates.

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Affective AI and Human Interaction

How should we design the place where people and models face each other? Self-reflection, dialogue, and the problem of co-presence.

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Affective AI and Business

We re-frame the meeting point of uncertainty, acceptance, and ethics in industrial deployment as practitioner knowledge.

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Affective AI and Art

Art as the place where emotion and expression meet — a domain in which AI moves among three positions: 'making,' 'reading,' and 'inspiring.'

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Development Based on Affective AI

Development research that implements emotion-reading AI as applied systems and delivers them to society.

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Other AI Research

Themes of AI research that are not directly part of affective AI but that our lab pursues.

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AI for Science

Applying AI to scientific fields beyond emotion. This is where we bundle cross-disciplinary collaborations in biology, educational safety, and related domains.

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Looking for collaborators

We are recruiting collaborators in affective AI

We welcome students, collaborators, and industry partners interested in building and applying affective AI, across a broad range of backgrounds.

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Recent publications

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Latest News

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