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Record STMT-WA7949FAdvisory

Machine Ethics and Cognitive Robotics

Report ProfessionalGlobalin force

This review paper examines how to provide intelligent autonomous machines and cognitive robots with ethical reasoning capabilities. It evaluates previous research approaches such as case-based reasoning, neural networks, constraint satisfaction, category theory, and logic programming. The author argues that developing metric-based ethics and moral machine architectures may be necessary to ensure autonomous systems are trustworthy.

Summary and content fields are drawn from the document text and are pending editorial review.

Who issued it

SpringerIndustry
Publisher
Auckland University of TechnologyAcademic · NZ
Contributor
Legal forceAdvisory
Under whose authorityProfessional
Judged fromfull text

Who it governs

Researchers and academicsCompaniesAI developers and providers

Researchers and developers working on artificial intelligence, machine learning, and robotics who want to understand the challenges and approaches of machine ethics.

Sectors
Research and science · artificial intelligence and robotics researchTransport and mobility · intelligent autonomous vehicles

What the document contains

What's covered

The document reviews the history and state of intelligent autonomous vehicles and cognitive robotics, analyzes previous approaches to implementing ethical reasoning in machines, and discusses potential architectures for moral machines.

What's missing

The document does not provide binding legislation, enforceable regulatory standards, or concrete legal frameworks for deployment.

Key takeaways
  • Hardwiring robots with simple commands to avoid harm is inconsistent with genuine autonomy and flexibility.
  • Previous research approaches to machine ethics include case-based reasoning, neural networks, constraint satisfaction, category theory, and abductive or inductive logic.
  • Many existing ethical approaches in AI rely on closed-world assumptions or struggle to handle ethical dilemmas involving conflicting duties.
  • Embedding fuzzy logic or simulation-based training can help autonomous systems learn moral rules for unencountered situations.
  • Metric-based ethics may be necessary for machines because they operate fundamentally on numbers.
Principles it states
human rightswell-beingaccountabilitytransparencyawareness of misuse
Outline
· Introduction
· Intelligent Autonomous Vehicle (IAV) Development
· The Need for Improved AI in Autonomous Systems
· Moral Machines
· Moral Machine Architectures
· Conclusion
Issued26 January 2023
Length7,531 words · 9 pages
FormatNot recorded
Scopeglobal

How it scores

Pending review

Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.

Human Dignity

2/5

Respect for the inherent worth of persons

categorical imperative (we must act in accordance with human rational capacity and certain inviolable laws)

Moral Machine Architectures

screening score · 2026-10-24

Privacy

0/5

Protection of personal data and private life

N/A

screening score · 2026-10-24

Enforcement

0/5

Consequences and compliance mechanisms with real force

N/A

screening score · 2026-10-24

Impact Assessment

2/5

Required assessment of an AI system's risks/impacts before or during use

Recently reported fatalities involving driverless cars and reports of battlefield drones making autonomous decisions to fire on enemy targets have raised ethical concerns

Introduction

screening score · 2026-10-24

Topics

machine_ethics cognitive_robotics artificial_morality autonomous_vehicles ai_safety