Self-Driving Cars and Engineering Ethics: The Need for a System Level Analysis

Area of Science:

• Computer Science
• Ethics
• Sociology

Background:

• Current research on self-driving car ethics primarily focuses on individual vehicle dilemmas.
• This narrow focus is insufficient for understanding the broader societal impact of autonomous technology.
• A system-level perspective is needed to analyze vehicle interactions and integration into socio-technical systems.

Purpose of the Study:

• To shift the discourse on autonomous vehicle ethics from individual to system-level considerations.
• To identify and analyze complexities arising from the interactions of self-driving cars within traffic and societal systems.
• To propose frameworks for addressing these system-level ethical challenges.

Main Methods:

• Analysis of two distinct traffic scenarios to illustrate system-level ethical issues.
• Description of three potential approaches for managing these complexities.
• Application of the "Moral Responsibility for Computing Artifacts: The Rules" framework.

Main Results:

• Traffic scenarios reveal emergent ethical challenges not apparent at the individual vehicle level.
• Identified shortcomings in proposed approaches highlight the need for robust ethical frameworks.
• The "Moral Responsibility for Computing Artifacts: The Rules" offers a structured method for ethical analysis.

Conclusions:

• A system-level ethical analysis is essential for the responsible development of self-driving cars.
• Understanding vehicle-to-vehicle and vehicle-to-system interactions is critical.
• Ethical frameworks like "Moral Responsibility for Computing Artifacts: The Rules" are vital for navigating autonomous technology's societal integration.