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Record STMT-W2A0979Aspirational

Toward Ethical Natural Language Generation for Human-Robot Interaction

Position paper Institutional policyGlobaladopted

This academic paper explores the ethical implications of natural language generation algorithms in human-robot interaction. It argues that a robot simply asking for clarification may unintentionally communicate willingness to perform an unethical action, thereby negatively influencing human teammates. The work highlights potential gaps in how moral competence is communicated in conversational robotics.

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

Who issued it

Association for Computing MachineryOther
Publisher
Legal forceAspirational
Under whose authorityInstitutional policy
Judged fromfull text

Who it governs

Researchers and academicsAI developers and providers

Researchers and developers in human-robot interaction looking to understand the ethical communication challenges of conversational robots.

Sectors
Research and science · human-robot interaction research

What the document contains

What's covered

The ethical implications of natural language generation algorithms in human-robot interaction, specifically concerning how robots communicate intent and ethical programming through clarification requests.

What's missing

No specific regulatory enforcement mechanisms, policy standards, or legal definitions are provided.

Key takeaways
  • Natural language generation algorithms for human-robot interaction have often overlooked ethical implications.
  • A robot asking for clarification can unintentionally signal a willingness to perform unethical actions.
  • Miscommunicating a robot's ethical programming can negatively influence the morality of human teammates.
Issued1 March 2018
Length1,561 words
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.

Accountability

0/5

Clear responsibility for AI outcomes

Abstract

screening score · 2026-10-24

Fairness

0/5

Non-discrimination and equitable treatment

Abstract

screening score · 2026-10-24

Human Dignity

0/5

Respect for the inherent worth of persons

Abstract

screening score · 2026-10-24

Human Oversight

0/5

Humans remain in control of consequential decisions

Abstract

screening score · 2026-10-24

Privacy

0/5

Protection of personal data and private life

Abstract

screening score · 2026-10-24

Transparency

2/5

Openness about how AI systems work and are used

In doing so, the robot may not only miscommunicate its own ethical programming, but negatively influence the morality of its human teammates.

Abstract

screening score · 2026-10-24

Enforcement

0/5

Consequences and compliance mechanisms with real force

Abstract

screening score · 2026-10-24

Impact Assessment

2/5

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

In this work, we argue that simply by asking for clarification, a robot may unintentionally communicate that it would be willing to perform an unethical action

Abstract

screening score · 2026-10-24

Topics

robot_ethics natural_language_generation human_robot_interaction moral_competence conversational_ai