A Model for Ethical Decision-Making in Autonomous Artificial Agents

Thesis Abstract

The rapid deployment of autonomous artificial agents across diverse domains, including healthcare, autonomous vehicles, and corporate decision-making, underscores the critical need for establishing robust ethical frameworks that govern their actions. Despite significant advancements in artificial intelligence, there remains a considerable gap in systematically modeling ethical decision-making processes within autonomous agents, which raises concerns related to accountability, moral reliability, and societal trust. This study aims to develop a comprehensive conceptual model that delineates the processes by which autonomous artificial agents can evaluate moral implications and make ethically sound decisions. The specific objectives are to identify core ethical principles pertinent to autonomous decision-making, examine existing theoretical frameworks, design an integrative model that incorporates these principles, and empirically validate this model through simulation experiments. Employing a mixed-methods research design, the study adopts a theoretical development approach complemented by quantitative validation. The initial phase involves an extensive review of existing literature on ethical theories—including Kantian ethics and utilitarianism—and decision-making models used in AI, to construct an initial conceptual framework. This framework synthesizes elements from deontological models, consequentialist reasoning, and virtue ethics to embody a multi-faceted ethical decision-making process. To empirically test the proposed model, a simulation environment is developed, involving a sample of 150 autonomous agents programmed to operate under varied scenarios reflecting ethical dilemmas such as collision avoidance and privacy protection. Data on agents’ decisions, response times, and moral reasoning patterns are collected via custom-designed digital instruments, including ethical dilemma questionnaires and decision-tracking logs. The primary data analysis employs regression analysis to examine relationships between ethical principles and decision outcomes, and thematic analysis within a qualitative subset assesses decision rationale and moral reasoning patterns. Additionally, the study utilizes structural equation modeling (SEM) to evaluate the validity of the integrated model in predicting ethically aligned decisions. Expected findings include the identification of key predictors—such as fairness, safety, and individual rights—that influence autonomous decisions, as well as the delineation of the relative importance of deontological and utilitarian considerations in complex scenarios. The proposed model is anticipated to demonstrate high predictive validity, facilitating more transparent and morally accountable autonomous decision-making processes. This research contributes substantially to the field of AI ethics and decision theory by proposing a formal, empirically validated model that integrates philosophical principles with computational mechanisms. It advances theoretical understanding by operationalizing ethical frameworks into functional algorithms suitable for autonomous agents, and offers pragmatic insights for developers and policymakers on embedding ethical reasoning within AI systems. The findings have implications for the design of ethically aligned autonomous agents, promoting societal trust and safeguarding moral accountability as AI technologies become increasingly autonomous. The study concludes that a holistic, multi-principled approach to ethical decision-making enhances the moral reliability of autonomous agents. Recommendations include incorporating the model into artificial intelligence development protocols, fostering interdisciplinary collaboration between ethicists and engineers, and conducting further empirical validation in real-world environments. Future research directions involve expanding the model to incorporate cultural and contextual ethical considerations, as well as longitudinal assessments of ethical decision-making in adaptive autonomous systems. Overall, this thesis underscores the importance of embedding structured ethical frameworks within artificial intelligence to foster responsible and trustworthy autonomous agents capable of navigating complex moral landscapes.