Vision and Motivation

Questions shape the evolution of science and technology. “Can machines think?” helped open the age of AI. What comes next in AI’s evolution? Hyper AI? Super AI? The next era of intelligence may begin with the questions we ask together.

Great questions can outlive their answers. Over a decade, Top10Qi and Top10Cs invited people worldwide to propose and vote on fundamental questions and challenges. Expert committees and the wider community produced remarkably similar top rankings. More than a decade later, questions such as “Can machines be creative?” still resonate today.

A new era calls for new questions. Since 2020, the IEEE Hyper-Intelligence Technical Committee (HITC) has opened a broader exploration of what intelligence may become. The Hyper/Super AI Questions Initiative (HAI-Q) now invites the global community to discover the fundamental questions that may shape the next era of intelligence.

HAI-Q Process

Stage 1: Ask — Question Collection. We invite people worldwide to submit one to three fundamental, forward-looking questions about Hyper/Super AI through the Google Form or Wenjuanxing by October 20, 2026. The goal is to gather diverse questions, perspectives, and concerns about what may come next in the evolution of AI.

Stage 2: Organize — AI-Assisted Question Analysis and Ranking. Submitted questions and related information will be analyzed using current tools and LLMs to identify semantic similarities, recurring themes, and emerging concerns. Questions with similar meanings but different wording may be grouped or consolidated, with human review to preserve their original intent. The resulting questions will then be analyzed and ranked to identify those that emerge most strongly from the collective input.

Stage 3: Explore — Question Discussion and Future Directions. The top-ranked questions, together with key patterns and insights revealed by the analysis, will be presented and explored during the HAI-Q panel discussion at GAI-HyperI 2026. The results may also be used in academic publications, conference presentations, and research reports. The goal is not simply to produce a ranking but to stimulate discussion, inspire new ideas, and open directions for future research on Hyper/Super AI.

Ethics Approval

This study was reviewed and approved by the Ethics Review Committee on Research with Human Subjects at Waseda University, Japan (Approval No. 2026-350).

Organizers

• Jianhua Ma, Hosei University, Japan

• Qun Jin, Waseda University, Japan

• Ao Guo, Nagoya University, Japan

• Yang Xiang, Swinburne University of Technology, Australia

• Chao Chen, RMIT University, Australia

Coordinators

• Ruichen Cong, Waseda University, Japan

• Binbin Zhou, Hangzhou City University, China

• Fuyi Wang, RMIT University, Australia

• Lifei Wang, Hosei University, Japan

Advisory Board

• Stephen S. Yau, Arizona State University, USA

• Hui-Huang Hsu, Tamkang University, Taiwan

• Qiangfu Zhao, Zhejiang Normal University, China

• Hong Zhu, Oxford Brookes University, United Kingdom

• Jerry Gao, San Jose State University, USA

• Oscar Lin, Athabasca University, Canada

• Qing Li, Hong Kong Polytechnic University, Hong Kong

• Toshiaki Miyazaki, AIST-UTokyo AI Chip Design Open Innovation Laboratory (AIDL), Japan

• Hironori Washizaki, Waseda University, Japan

• Flavia Delicato, Fluminense Federal University, Brazil

• Antonio Guerrieri, ICAR-CNR, Italy

• Yinsheng Li, Fudan University, China

• Klimis Ntalianis, University of West Attica, Greece

• Nicolas Tsapatsoulis, Cyprus University of Technology, Cyprus

• Yanchun Zhang, Zhejiang Normal University, China

• Naohiro Hayashibara, Kyoto Sangyo University, Japan

• Zhong Chen, Beijing Normal-Hong Kong Baptist University, China

• Md Zakirul Alam Bhuiyan, Fordham University, USA

• Liming Chen, Dalian University of Technology, China

• Claudio Miceli, Federal University of Rio de Janeiro, Brazil

• Takaki Nakamura, Tohoku University, Japan

• Zengwei Zheng, Hangzhou City University, China

• Sahraoui Dhelim, Dublin City University, Ireland

• Yan Wang, Macquarie University, Australia

• Jiannong Cao, Hong Kong Polytechnic University, Hong Kong

• Anna Kobusińska, Poznań University of Technology, Poland

• Anind K. Dey, University of Washington, USA

• Hui Yu, University of Glasgow, United Kingdom