From Ballpark to Society: Understanding Stakeholders’ Adaptation to Automated Judgment via ABS in Baseball

Paper Title

From Ballpark to Society: Understanding Stakeholders’ Adaptation to Automated Judgment via ABS in Baseball

Publication Info

• Topic area: Stakeholder adaptation to AI-driven judgment systems in sports.
• Keywords: Automated Ball-Strike System, judgment automation, stakeholder adaptation, consistency, fairness, transparency, governance, role reconfiguration, professional baseball, AI adjudication.

Background and Problem

• Problem / challenge: Existing research on AI judgment systems lacks empirical accounts of sustained, ecosystem-wide adaptation across multiple stakeholder groups, especially in high-frequency, high-stakes domains.
• Significance: Understanding adaptation dynamics is critical for designing systems that balance fairness, legitimacy, and stakeholder needs, particularly as AI replaces human judgment in professional and public contexts.
• Motivation and related work: Prior studies focus on limited-scope pilots or isolated deployments, often emphasizing technical accuracy without exploring social implications. The Korea Baseball Organization’s league-wide adoption of ABS provides a unique opportunity to study sustained adaptation in a public, high-frequency judgment domain.

Solution

• Proposed approach: Empirical investigation of stakeholder adaptation to the Automated Ball-Strike System (ABS) in South Korea’s professional baseball ecosystem.
• Novelty:
  1. First ecosystem-level empirical account of sustained adaptation to large-scale judgment automation.
  2. Identification of consistency and verifiability as primary drivers of acceptance, over accuracy.
  3. Development of a conceptual framework for impact redistribution and role reconfiguration in judgment automation.
  4. Proposal of governance principles emphasizing transparency, feedback mechanisms, and adaptive role reconfiguration.
• Procedure and key techniques:
  • Conducted semi-structured interviews with 38 stakeholders (umpires, players, coaches, fans) during ABS’s second season.
  • Thematic analysis of interview data using sensitizing concepts: trust, role reconfiguration, and contextual fit.
  • Derived insights into pre-adoption expectations, post-adoption impacts, and broader governance implications.

Results

• Concrete findings:
  • ABS acceptance was driven by consistency and verifiability rather than accuracy.
  • Redistribution of adaptive burdens: players faced strategic recalibration, umpires experienced reduced authority, and fans encountered calmer viewing experiences.
  • Legitimacy hinged on procedural transparency and visible feedback mechanisms.
• Advantage over baselines:
  • Reduced emotional conflict and disputes compared to human umpiring.
  • Enhanced fairness perception due to uniform application of strike-zone rules.
• Experiments / evaluation:
  • Interviews with 38 stakeholders: 8 umpires, 10 players, 5 coaches, 15 fans.
  • Analysis of adaptation dynamics across roles and perspectives.
• Limitations and future work:
  • Limited representation of top-tier KBO umpires and system developers.
  • Findings are qualitative and situated; future studies should explore longitudinal and cross-domain applications.
  • Need for expanded focus on design, governance, and public discourse.

Summary

This study investigates the Korea Baseball Organization’s adoption of the Automated Ball-Strike System (ABS), offering the first ecosystem-level account of adaptation to judgment automation. Stakeholders valued consistency and verifiability over accuracy, with players bearing the greatest adaptive burden, umpires experiencing reduced authority, and fans appreciating calmer viewing experiences. Findings emphasize the importance of transparent governance, feedback mechanisms, and adaptive role reconfiguration for sustainable AI adoption. These insights inform broader applications of judgment automation in sports, law, and medicine, highlighting the need for participatory and responsive systems.