Call for Paper (Paper submission deadline: May 15th)

Introduction

At ICONIP 2025, we are hosting a special session titled “Toward Safe Brain-Inspired AI” aimed at enhancing the safety, interpretability, and ethical aspects of AI inspired by the human brain. In this session, submitted papers will be published both as part of the Special Session. We warmly welcome innovative and cutting-edge research that bridges computational neuroscience and machine learning in the pursuit of interpretable, controllable, and safe AI solutions.

Special Session Overview <Toward Safe Brain-Inspired AI>

Modern deep learning systems have achieved remarkable successes but face critical challenges in interpretability, trustworthiness, and alignment with human values. Research at the interface of computational neuroscience and machine learning suggests that incorporating key principles from the human brain—such as sparse, modular network architectures—can enable the development of more interpretable and controllable AI models. At the same time, ensuring these systems are genuinely beneficial requires robust frameworks for AI alignment. These frameworks draw on ethics, policy, and advanced neurotechnology to detect latent internal states and guide system behavior toward socially acceptable outcomes.
This special session will highlight recent progress in brain-inspired mechanistic interpretability, ethical alignment strategies, and neurotechnology-driven cognitive understanding of AI. We will explore how biologically motivated network structures enable clearer insight into internal representations, how alignment mechanisms can be integrated without sacrificing performance, and how leveraging cognitive neuroscience tools can expand our understanding of human and artificial minds.
Through invited talks (spanning academic and industrial perspectives), contributed presentations, and an interdisciplinary panel discussion, attendees will gain a holistic overview of:

Brain-Inspired AI: Sparse and modular architectures, biologically plausible learning rules, and reverse-engineering neural computations.
AI Alignment: Balancing advanced capabilities with safety, ethical standards, and user trust.
Neurotechnology Applications: Using neuroimaging and cognitive modeling to interpret AI systems and refine human–machine interaction.

By uniting experts from neuroscience, AI, and ethics, this session aims to advance the development of human-centric, transparent, and responsible AI—and ultimately to foster new collaborations that propel the field forward.

Paper Submission Guidelines

We invite submissions of innovative and practically relevant research aligned with the themes of the special session. All submitted papers will undergo a rigorous peer review process and, upon acceptance, will be published as part of the Special Session while also being included in the Regular Paper section.

・Paper submission deadline: May 15th

・Submission Guidelines:
　https://iconip2025.apnns.org/call-for-papers/

The presentation time is planned to be around 20 minutes, including Q&A, similar to regular sessions, although this may be subject to slight adjustment. Additionally, the option to select the Special Session “Toward Safe Brain-Inspired AI” will soon be available.

Conference Dates & Venue

Conference Dates & Venue

Conference Dates: November 20-24
　This special session will be held on the afternoon of November 20th, the first day of the conference.
Venue: OIST Conference Center, Okinawa, Japan

Program(Tentative)

Introduction (15 minutes)
- Hiroshi Yamakawa
- A brief overview of the session’s scope and key objectives, emphasizing the importance of brain-inspired AI design, mechanistic interpretability, and ethical alignment.
Invited Talk(20 minutes)
- Hiro Taiyo Hamada (ARAYA)
- Title: Trait alignment for AI safety
- Humans are a model for AI safety, and multiple ideas are proposed to align human representation with AI by incorporating brain-inspired architectures like NeuroAI. Here, we will talk about a new proposal for AI alignment with AI trait/personality.
Contributed Short Talks (50 minutes total)
- Several presentations were selected from the submitted materials.
- Potential topics include theoretical advances, experimental results, or practical deployments related to brain-inspired AI, mechanistic interpretability, ethical AI alignment, or neurotechnology-informed methods.
Panel Discussion (25 minutes)
- A moderated session featuring the speakers and session organizers.
- Topics: Bridging neuroscience and AI; designing safe, transparent systems; ethical and societal implications of next-gen AI models.
Closing Remarks (5 minutes)
- Organizers summarize the main insights, propose next steps, and thank participants, speakers, and sponsors.

Organizers:

Hiroshi Yamakawa (The University of Tokyo / The Whole Brain Architecture Initiative):
- Hiroshi Yamakawa is the Chairperson of The Whole Brain Architecture Initiative (WBAI), a non-profit organization, a Visiting Professor of the University of Electro-Communications and a Visiting Professor of the Kindai University. He received an MS in physics and PhD in engineering from the University of Tokyo in 1989 and 1992 respectively. His research interest is brain-inspired artificial general intelligence and concept formation.
Akira Taniguchi (Ritsumeikan University):
- Dr. Akira Taniguchi is a Lecturer in the Department of Information Science and Engineering at Ritsumeikan University, specializing in symbol emergence in robotics, cognitive developmental robotics, and brain-inspired AI. He earned his Ph.D. in Engineering from Ritsumeikan University in 2018. He has been recognized with several awards, including the Research Encouragement Award from the Robotics Society of Japan and the Best Paper Award (Franklin V. Taylor Memorial Award) from the IEEE International Conference on Systems, Man, and Cybernetics (SMC). His research focuses on developing probabilistic generative models for spatial concept acquisition and the Brain Reference Architecture inspired by hippocampal formation.
Takeshi Nakashima (Ritsumeikan University)::
- Takeshi Nakashima is a doctoral student at the Graduate School of Information Science and Engineering, Ritsumeikan University. He received a MS in physics from Nagoya University in 2008. His research interest is the mechanism of adaptive behavior.

[CFP(May 15th)] Toward Safe Brain-Inspired AI @ICONIP2025