International Workshop: AI-Biz2023

One day during June 4-6, 2023:
Venue: Kumamoto-Jo Hall, Kumamoto, Japan (onsite/online/hybrid styles are all available):

Aims and Scope

The objective of this workshop is to foster the concepts and techniques of“Business Intelligence (BI).” in Artificial Intelligence. BI should include such cutting-edge techniques as data science, agent-based modelling, complex adaptive systems, and IoT. The application areas include but not limited to business management, finance engineering, service sciences, manufacturing engineering, and so on.

The basic idea of BI would enhance the capabilities of conventional techniques in business domain, however, so far, we have not discussed BI concepts deeply in artificial intelligence literature. We would like to focus on BI topics to the issues of firms and organizations for getting more benefits on interactions with human- and computer- mixed systems.

The main purpose of this workshop is to provide a forum to discuss important research questions and practical challenges in Business Intelligence, Business Informatics, Data Analysis and Agent-based Modelling to exchange latest results, to join efforts in solving the common challenges. It is also to establish an effective communication between researchers and developers involved in the both areas. The workshop will provide opportunities for the participants to exchange new ideas and experiences to establish research or business network and to find global partners for future collaboration.


June 4, 2023

13:00 - 13:10
Opening session
Prof. Takao Terano, Chiba University of Commerce

13:10 - 14:30
1st Session: Chair Hiroshi Takahashi, Keio University

A Study on the Requirements of Japanese High School Teachers from the Parents based on the Regional Characteristics
Kenji Kido and Masakazu Takahashi

Human-in-the-Loop Machine Learning When Labels Are Noisy
Takao Arai and Setsuya Kurahashi

Constructing a Macroeconomic Agent-based Simulator with Supplier-customer Relationships
Takahiro Obata, Jun Sakazaki, and Setsuya Kurahashi

Do young people in regional cities of Japan really shift away from owning automobiles? – From an empirical study and a semi-structured interview
Akiko Ueno, Yuko Okiyama, Nozomi Masuda, Ken-ichi Yamaga, Aino Yamagata, Kazuto Yoshioka, Arata Abe, Koichi Kitanishi, and Takashi Yamada

14:30 - 15:00

15:00 - 15:50
Invited Talk: Chair Setsuya Kurahashi, University of Tsukuba

Teaching Artificial Intelligence in K-12 Education: The Policy Landscape and Research Directions
Dr. Chathura Rajapakse, University of Kelaniya, Sri Lanka

16:00 - 17:20
2nd Session: Chair Masakazu Takahashi, Yamaguchi University

Study on Government-Initiated Bid-Rigging by Gaming Simulation and Agent-Based Simulation
Hideyuki Morofuji and Setsuya Kurahash

Exploring the Shift from Nature Protection to Nature-Based Solutions in Japanese Government’s Environmental White Papers: A Text Mining Case Study
Keiko Yoshikawa

Proactive behavior factor analysis using network analysis
Hidetoshi Miyaji and Setuya Kurahashi

BERTopic study on the acquisition of information on business activities through news analysis: a year-by-year analysis
Haruna Okazaki and Hiroshi Takahashi

17:20 - 17:30
Closing session

AI-Biz2023 Invited Talk

Dr. Chathura Rajapakse

Teaching Artificial Intelligence in K-12 Education: The Policy Landscape and Research Directions


Abstract: According to an analysis done by McKinsey in 2018, 70% of global firms are expected to adopt at least one type of artificial intelligence technology by 2030. This will potentially make a significant impact not only on the global workforce but also on the majority of the citizens around the world. The future citizens will have to live in a world where the man-machine as well as machine-machine interactions would be an essential component of their everyday life. Moreover, the future workforce will have to be comprising of such citizens who could effectively adopt artificial intelligence in the overall process of digital transformation in both public and private sectors. Hence, the artificial intelligence literacy of the future citizens is something that every government will have to think of and invest in. Under such circumstances, some governments have already taken initiative to include artificial intelligence to their K-12 curriculums with the intention of bringing up their future citizens with essential artificial intelligence skills to meet the sustainability goals of the next decade. However, the policy landscapes for effectively teaching artificial intelligence at schools are still being evolved with important questions such as 1) what to be taught at which level, 2) how to be taught 3) what techniques are best to be used to teach and 4) what challenges are to be overcome and how. This opens up significant research gaps for us to address focusing on the curriculums, pedagogy, teaching and learning tools, as well as the training of the teaching staff. This talk is expected to bring some existing policy frameworks and challenges of teaching artificial intelligence in K-12 education into discussion, with a special focus to some ongoing initiatives in Sri Lanka to teach artificial intelligence at the pre-tertiary level.

Dr. Chathura Rajapakse
Department of Industrial Management, Faculty of Science
University of Kelaniya, Sri Lanka

Important Dates

Submission Deadline: March 31, 2023
Notification: April 30, 2023
Camera-ready due: May 15, 2023
Deadline for Early registration : until May 21, 2023
Workshop: One day during June 4, 2023


Papers must be prepared according to the Springer LNCS/LNAI format. The page limit is 14 pages, including figures and bibliography. This conference uses a double-blind review.
Selected papers will be published as post-proceedings via Springer Verlag LNAI after the second round of a double-blind review after the workshop.
Please ensure that your paper fully complies with the LNAI format.
Guidelines for the LNAI format
LNCS/LNAI style files
Submission and review of papers for AI-Biz2023


Please register the workshop at registration page of JSAI International Symposia on AI 2023.


The topics include but not limited to:
  • Data Mining, Text Mining and Data Analysis
  • Empirical Analysis on Managerial Decision Making
  • Agent-Based Computational Economics & Finance
  • Agent-Based Game, Serious Game and Business Game
  • Agent Based Economics
  • Agent Based Policy Making
  • Gaming Simulation on Social and Business Problems
  • Issues and Case Studies on Business and Finance Problems
  • Knowledge Management
  • Information Security
  • Collective Intelligence and Human Computation on Social Problems
  • Participatory Design and Simulation on Social Problems
  • Simulators for Macroeconomic Policy
  • Valuation and Asset Pricing
  • Corporate Governance and Regulation
  • Discrete Choice Models in Economics and Management Sciences
  • Emergence and Dynamics of Norms and Conventions
  • Financial Market models and Auction
  • Dynamics of Complex, Social and Economic Networks
  • Complexity and Market Dynamics
  • Health and Infectious Diseases
  • Power Market and Consumer Market Analysis
  • Micro Service Orchestration
  • IoT, IoE for Business Process Innovation
  • Environmental Accounting
  • Multi Dimensional Accounting
  • Private Finance Initiative
  • Disaster Management
  • Real World Operating System


    Information of Workshop leader
  • Takao Terano (Chiba University of Commerce)
    Information of Workshop co-leader
  • Setsuya Kurahashi (University of Tsukuba)
  • Hiroshi Takahashi (Keio University)
    Steering Committee Members(Tentative)
  • Chang-Won Ahn (Vaiv Company Inc.)
  • Ernesto Carella (University of Oxford)
  • Reiko Hishiyama (Waseda University)
  • Manabu Ichikawa (Shibaura Institute of Technology)
  • Yoko Ishino (Yamaguchi University)
  • Hajime Kita (Kyoto University)
  • Hajime Mizuyama (Aoyama Gakuin University)
  • Chathura Rajapaksha (University of Kelaniya)
  • Masakazu Takahashi (Yamaguchi University)
  • Alfred Taudes (Vienna University)
  • Shingo Takahashi (Waseda University)
  • Takashi Yamada (Yamaguchi University)
  • Matthias Raddant (Kiel University)
  • Chao Yang (Hunan University)

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