Consequences of an Analysis Using Biblical Analogies for Automated Vehicle Control Design

NÉMETH, Balázs · 2022 · Crossref

DOI: 10.24193/subbtref.67.2.02

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Summary

This paper addresses the ethical challenges inherent in designing automated vehicle control systems, specifically focusing on learning-based approaches. The author argues that while engineering research has increasingly examined the social and ethical implications of autonomous driving, there is a lack of practical solutions for control engineers to integrate ethical considerations into system design. The study is motivated by the difficulty of establishing ethical laws that are simultaneously acceptable to consumers and society, technically reliable, and mathematically formulable for control objectives. To bridge this gap, the paper employs a novel interdisciplinary method, creating analogies between selected biblical texts and the operational concepts of supervised, unsupervised, and reinforcement learning. The methodology involves a theological analysis of three primary machine learning paradigms. For supervised learning, the author draws parallels to strict rule-following, citing biblical critiques of the Pharisees who adhered to formal laws while neglecting higher principles like justice and love. This analogy highlights the limitation of static rules in complex scenarios, such as traffic jams caused by rigid adherence to safety distances. For unsupervised learning, the analysis focuses on the difficulty of defining metrics, using the biblical concept of "loving the Lord" as an abstract metric that distinguishes between life and death outcomes. For reinforcement learning, the paper analogizes the agent’s training episodes to the historical experiences of biblical figures, such as the prophets and the Apostle Paul, where feedback (reward) is derived from real-world consequences and suffering, guided by the ultimate guarantee of divine grace. The analysis yields three primary consequences for automated control design. First, it is extremely difficult to form appropriate control objectives for complex real-world scenarios because determining absolute "good" and "bad" is a theological issue beyond the scope of engineering, rooted in human limitations and original sin. Second, considering human objectives in control is problematic because human intentions are inherently flawed; thus, imitation learning has limited validity. Third, systems must be viewed in their entirety, acknowledging that no mathematical formulation can fully capture the complexity of ethical decision-making. The paper applies these findings to an illustrative route selection problem, proposing a multi-layer control concept that incorporates these theological insights to handle ethical challenges, suggesting that while simplified objectives can be formed, complex multi-vehicle scenarios require acknowledging the inherent limitations of algorithmic ethics.

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• automation surprise

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• Theoretical Contribution: computational model