Social design for excess punishment and risk reduction under the zero information cost society

2022 Fiscal Year Final Research Report

• Project/Area Number: 19H02376
• Research Category: Grant-in-Aid for Scientific Research (B)
• Allocation Type: Single-year Grants
• Section: 一般
• Review Section: Basic Section 25010:Social systems engineering-related
• Research Institution: The University of Tokyo
• Principal Investigator: Toriumi Fujio 東京大学, 大学院工学系研究科(工学部), 教授 (30377775)
• Co-Investigator(Kenkyū-buntansha): 秋山 英三 筑波大学, システム情報系, 教授 (40317300) ; 岡田 勇 創価大学, 経営学部, 准教授 (60323888) ; 山本 仁志 立正大学, 経営学部, 教授 (70328574)
• Project Period (FY): 2019-04-01 – 2023-03-31
• Keywords: 過剰懲罰 / 公共財ゲーム / 囚人のジレンマ / エージェントシミュレーション / 多元的無知

Outline of Final Research Achievements

We analyzed excessive punishment from the perspectives of modeling, simulation, and experimentation.
First, we clarified the conditions under which cooperation can be achieved even without punishment. We conducted continuous panel surveys in the framework of social dilemmas regarding voluntary self-restraint during the COVID-19 pandemic to reveal the characteristics of people with punitive norms and the impact of media exposure.
Then, We demonstrated that punishment through participation refusal rules significantly improves the probability of cooperation. We showed that estimating the opinions of others may lead to group polarization or pluralistic ignorance.

Free Research Field

計算社会科学

Academic Significance and Societal Importance of the Research Achievements

本研究では，公共財ゲームを中心に，過剰懲罰の回避及び懲罰がなくとも協調的行動を実現できる条件を明らかにした．ネットワークの効果やインセンティブの与え方などによって懲罰を回避しつつ，社会集団の協力率を安定的に保つ可能性が示された．
また，過剰懲罰の遠因となりうる集団極性化・多元的無知などが生じる要因をシミュレーションにより推定する等，過剰懲罰社会に対して多角的に分析研究した意義は大きい．