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Who Should Decide How Machines Make Morally Laden Decisions?

Dominic Martin1,2

  • 1John Molson School of Business, Concordia University, Montréal, Canada. dominic.martin@concordia.ca.

Science and Engineering Ethics
|December 2, 2016
PubMed
Summary
This summary is machine-generated.

Determining who decides on machine morality is crucial. This paper explores four approaches—makers, users, collective, or machine-based decisions—and argues for context-dependent solutions.

Keywords:
Artificial intelligenceCollective decision-makingEconomic efficiencyEthicsMarket freedomMoral agencyPublic policiesRegulationSelf-driving car

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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.