Faculty

Several disciplines contribute together to the research problems of the Scholars’ Council for AI.

The scholarship of each faculty member who has agreed to participate in the Scholars’ Council for AI can be connected to AI research questions.

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Participating faculty

Who are the faculty members who have agreed to participate?

Academic foundations.
New research questions.

  • Professor Won-Woo Park

    Scholarly foundations
    Groupthink, teamwork and team role balance, trust and organizational culture

    The research of Professor Won-Woo Park, who studies organizational behavior and teamwork at the College of Business Administration at Seoul National University, is part of the scholarly foundation that can be consulted when examining roles and team performance.

    AI research questions proposed by the Scholars’ Council for AI

    Whether opposing evidence is actually examined when several AIs reach a conclusion together, whether each AI carried out its assigned role, and how individual-level and team-level evaluations connect can be connected to research questions. Such application to AI is a separate verification task that starts from existing research on human organizations.

    Related research questions: How should roles be divided among several AIs? · How can judgments be made together when information is scattered?

    Read more — Professor Won-Woo Park’s research

    Professor Won-Woo Park’s research on groupthink, teamwork, trust and organizational culture can be consulted when examining group judgment and how organizations work.

    References Park, W.-W. (2000). A comprehensive empirical investigation of the relationships among variables of the groupthink model. Journal of Organizational Behavior, 21(8), 873–887. External site

  • Professor Hyo-Gun Kim

    Scholarly foundations
    Knowledge management, creative management, assessment of knowledge contribution

    The research of Professor Hyo-Gun Kim, Professor Emeritus at Ewha Womans University, on knowledge management and creative management and on connecting people, technology and organizations, provides a foundation for examining the use of knowledge and organizational learning.

    AI research questions proposed by the Scholars’ Council for AI

    Ways of evaluating how the knowledge provided by AI helped people’s actual judgments and actions can be connected to research questions.

    A study published in 2004 by Professor Hyo-Gun Kim and co-researcher 나미자 dealt with the development of an instrument for assessing the degree to which members of an organization contribute knowledge. Applying that instrument to AI requires its detailed items and measurement validity to be verified separately.

    References 나미자 · 김효근 (2004). 조직 구성원의 지식기여도 평가 도구 개발에 관한 연구 [A Study on the Development of an Instrument for Knowledge Contribution Assessment — English title as listed on KCI; provisional] (in Korean). 경영정보학연구 (Information Systems Review), 6(2), 113–135. External site

  • Professor Namgyoo K. Park

    Scholarly foundations
    Strategy and corporate growth, creativity and work innovation (the Puzzling Method)

    A 2023 paper by Professor Namgyoo K. Park, who studies strategy and creative thinking at the College of Business Administration at Seoul National University, describes “Puzzling,” a creative thinking method that breaks a work process apart and re-examines the relationships among its parts to find opportunities for improvement.

    AI research questions proposed by the Scholars’ Council for AI

    Whether reconstructing the work process that AI carries out leads to omissions being found more readily and unnecessary work being reduced — that is, what effect reconstructing the process has — can be connected to research questions and tested.

    Until the effect of application is confirmed, it should be described as an expected research direction.

    Related research question: When a problem is defined anew, what can be compared?

    Read more — Professor Namgyoo K. Park’s research

    Professor Namgyoo K. Park’s research on strategy and corporate growth and on creativity and work innovation can contribute when examining how problems are framed and how alternatives are explored. The study that describes Puzzling is a concrete reference for analyzing work processes and finding opportunities for improvement.

    References Park, N. K. (2023). Research on Creative Thinking Methods for Process Innovations. 경영논집, 57, 55–69. External site

  • Professor Seokhwa Yun

    College of Business Administration at Seoul National University

    Scholarly foundations
    Leadership, knowledge sharing, the two paths of empowerment

    A 2016 study co-authored by Professor Seokhwa Yun examined, in the relationship between empowering leadership and members’ job performance, both a positive path through self-efficacy and a burdening path through job-induced tension.

    AI research questions proposed by the Scholars’ Council for AI

    Under what conditions widening the range of actions AI can choose from increases both the cost of search and the chances of error can be connected to research questions.

    Rather than substituting human psychological variables directly into AI, new hypotheses should be built from the relationships among observable behavior, resource use, errors and performance.

    Related research question: How far should things be left to AI, and when should one intervene?

    Read more — Professor Seokhwa Yun’s research

    Professor Seokhwa Yun’s research on leadership, knowledge sharing and the behavior of organizational members can be consulted when examining the conditions for intervention and autonomy depending on the situation. The joint study suggesting that empowerment can have both a path of support and a path of burden is a useful starting point for asking about the benefits and costs of intervention at the same time.

    References Cheong, M., Spain, S. M., Yammarino, F. J., & Yun, S. (2016). Two faces of empowering leadership: Enabling and burdening. The Leadership Quarterly, 27(4), 602–616. DOI 10.1016/j.leaqua.2016.01.006 External site

How the disciplines connect

Which disciplines take part?

Epistemology and linguistics connect to knowledge and meaning, and logic and statistics to judgment; sociology and management are important for collaboration and organizations, and psychology and education for human learning; and questions of responsibility and institutions need review from ethics and law. Which disciplines take part is decided by what explanations and methods a particular research problem needs, and the scope of the Scholars’ Council for AI is widened through the participation of the disciplines and researchers needed to understand and solve new problems.

Four transparent lenses of different curvature surrounding an open space
Read more — The broad foundation and the faculty’s scholarship

The scholarship of the participating faculty takes on specific contributions within this broad scope of research.

The research of the initial faculty forms part of this broad foundation.

See examples of scholarship by area

Knowledge and meaning
Epistemology · Linguistics
Judgment
Logic · Statistics
Collaboration and organization
Sociology · Management
Human learning
Psychology · Education
Responsibility and institutions
Ethics · Law

Principles of scholarly judgment

How is scholars’ judgment used?

  • Evidence and criticism

    A particular scholar’s reputation cannot take the place of evidence for a result, and research should be able to accept counterexamples and criticism from other researchers.

  • Scope of application and differences in the subject

    When research on people is applied to AI, the differences in the subject should be made clear, and the direct participation of scholars helps in examining these differences. Even so, the participating scholars’ interpretations should also be comparable with other evidence, and rather than the role of making a particular theory always right, the Scholars’ Council for AI takes on the role of bringing out the scope within which it can be applied and the phenomena that are hard to explain.

See also the research areas and joint research

See the research areas

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