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Nurses are essential in patient care, upholding the ethical principles of their profession and effectively navigating ethical dilemmas. Neglecting ethical issues can lead to inadequate patient care, compromised therapeutic relationships, and moral distress among healthcare workers.
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Landscape of Machine Implemented Ethics.

Vivek Nallur1

  • 1School of Computer Science, University College Dublin, Dublin, D04 V1W8, Republic of Ireland. vivek.nallur@ucd.ie.

Science and Engineering Ethics
|July 10, 2020
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Summary
This summary is machine-generated.

This survey explores machine ethics, focusing on implementing ethical behavior in AI systems. It highlights the lack of consensus on theories, techniques, and validation methods for artificial intelligence ethics.

Keywords:
Artificial intelligenceAutonomous systemsImplementation and designMachine ethicsRobotics

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Robotics
  • Philosophy

Background:

  • The field of machine ethics investigates the implementation of ethical principles in artificial systems.
  • Current research addresses ethical behavior in robots, autonomous vehicles, and software.

Purpose of the Study:

  • To survey the state-of-the-art in machine ethics.
  • To cover the breadth of ethical theories and implementation techniques.
  • To discuss the challenges in objectively validating ethical AI implementations.

Main Methods:

  • Literature review of current research in machine ethics.
  • Analysis of various ethical theories and their application in AI.
  • Examination of validation techniques, including ethical dilemmas ('whetstones').

Main Results:

  • No consensus exists on the optimal ethical theory or implementation technique for AI.
  • Objective validation of machine ethics remains an unresolved problem.
  • Ethical dilemmas are commonly used as validation benchmarks.

Conclusions:

  • Creating domain-specific ethics may be a precursor to general machine ethics.
  • Further research is needed to establish consensus on theories and validation.
  • The development of ethical AI requires interdisciplinary collaboration.