AI-Assisted Simulations to Explore Responsibility and Escape from Responsibility
- 1 Management and Economics, Open University of Israel, Raanana, Israel
Abstract
Based on the concepts and findings presented in a recent paper ( Bar-Haim, 2025 ), I propose using AI-assisted simulations and analyses to examine broader contexts of responsibility behavior and the mechanisms by which responsibility may be escaped. The idea of simulating data, questionnaires, and demographic conditions arises from theoretical, methodological, and practical considerations. In research papers, it is common to identify shortcomings, potential improvements, and directions for further inquiry, as I do in my own work. However, actual “further research” is seldom pursued due to limited time and resources. Simulating plausible scenarios for subsequent studies in this field can support the preparation and planning of future research projects. Three simulated scenarios are designed: 1) Replicating studies on perceived responsibility using an enhanced facet theory-based questionnaire and a simulated dataset; 2) Replicating a dataset on escape from responsibility, incorporating additional behavioral indices from multiple global statistical databases; 3) Developing a facet theory-based questionnaire on escape from responsibility with AI and generating a simulated dataset based on it.
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