Who Should Decide How Machines Make Morally Laden Decisions?

Area of Science:

• Artificial Intelligence Ethics
• Machine Decision-Making
• Autonomous Systems Morality

Background:

• Machines increasingly make autonomous, morally laden decisions in critical applications like driving and healthcare.
• Current societal preoccupation with machine moral decision-making is insufficient.
• The autonomy of advanced machines necessitates a framework for ethical governance.

Purpose of the Study:

• To explore and evaluate four distinct approaches to assigning moral decision-making authority in autonomous machines.
• To analyze the inherent limitations and shortcomings of each proposed decision-making framework.
• To propose a nuanced, context-dependent strategy for machine ethical governance.

Main Methods:

• Conceptual analysis of four proposed models for machine moral decision-making: maker-based, user-based, collective, and machine-based.
• Critical evaluation of the ethical and practical implications of each model.
• Argumentation for a differentiated approach based on machine type, situational context, and decision type.

Main Results:

• Each of the four explored approaches (maker, user, collective, machine-based) presents significant ethical and practical challenges.
• No single approach is universally suitable for all morally laden machine decisions.
• The effectiveness of each approach is contingent upon the specific application and context.

Conclusions:

• A one-size-fits-all solution for machine moral decision-making is inadequate.
• Future frameworks must consider the type of machine, the specific situation, and the nature of the moral decision.
• Emphasis should be placed on developing context-aware ethical guidelines for autonomous systems.