What ethical AI and robots could mean: a conceptual and ethical reflection
This opinion piece argues that AI ethics and robotics must move beyond the humanization narrative, which falsely attributes human moral agency, empathy, and consciousness to artificial systems. Instead, the author advocates for a relational and sociotechnical framework that situates human-AI interaction within specific practices, values, and domain norms. The paper outlines how interdisciplinary collaboration, integrating technical, ethical, domain-specific, and public perspectives, can address the conceptual and methodological challenges of evaluating AI systems.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
Researchers, developers, ethicists, and practitioners seeking a conceptual and ethical critique of human-centered narratives in AI and robotics.
What the document contains
The document addresses the conceptual and ethical challenges of anthropomorphism in artificial intelligence and robotics, analyzing the risks of the humanization narrative. It proposes a relational and sociotechnical framework for evaluating human-AI and human-robot interactions within specific institutional and social contexts, emphasizing interdisciplinary collaboration.
The text does not provide specific legal regulations, technical compliance standards, enforcement mechanisms, or formal policy definitions.
- The prevalent humanization narrative in AI and robotics creates a normative gap by confusing simulated conversational patterns with actual moral and experiential capabilities.
- Evaluating artificial intelligence through human-centered benchmarks introduces methodological problems and ignores that AI systems operate on statistics, prediction, and classification architectures.
- An alternative relational and sociotechnical account evaluates AI based on how well human-AI interactions support domain-specific norms and values rather than mimicking human traits.
- Embodied robots introduce distinct ethical considerations, such as physical presence and heightened expectations of agency, that differentiate them from non-embodied AI systems.
- Effective interdisciplinary collaboration requires integrating technical, ethical, domain-specific, and public perspectives while constructively utilizing disciplinary disagreements.
· 1 Introduction · 2 The need to move beyond the humanization narrative · 3 Ethical human-AI and human-robot interaction and collaboration: relational and sociotechnical account · 4 Discussion
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
3/5Clear responsibility for AI outcomes
Recognizing the importance of the distinction between AI systems and humans helps avoid both over-attribution of responsibility to AI systems and under-recognition of human responsibility in design, deployment, and governance.
2 The need to move beyond the humanization narrative
screening score · 2026-10-24
Fairness
1/5Non-discrimination and equitable treatment
Technical research may treat concepts such as fairness, transparency, or trust as measurable properties of systems, while ethical analysis emphasizes that these concepts are embedded in social practices and normative expectations.
4 Discussion
screening score · 2026-10-24
Human Dignity
1/5Respect for the inherent worth of persons
Ethical design must therefore attend not only to functionality but to how embodiment shapes relational dynamics and how it might expand vulnerability
3 Ethical human-AI and human-robot interaction and collaboration: relational and sociotechnical account
screening score · 2026-10-24
Human Oversight
1/5Humans remain in control of consequential decisions
What is at stake, then, is not whether AI or robots possess moral or conscious capacities or other human abilities, but whether the forms of interaction and collaboration they enable lead to harm or support beneficial and meaningful collaborations
3 Ethical human-AI and human-robot interaction and collaboration: relational and sociotechnical account
screening score · 2026-10-24
Privacy
0/5Protection of personal data and private life
N/A
screening score · 2026-10-24
Transparency
2/5Openness about how AI systems work and are used
A second source of disagreement concerns the scope of evaluation. Technical approaches may focus on optimizing specific system features, whereas ethical analysis may highlight broader sociotechnical contexts
4 Discussion
screening score · 2026-10-24
Enforcement
0/5Consequences and compliance mechanisms with real force
N/A
screening score · 2026-10-24
Impact Assessment
2/5Required assessment of an AI system's risks/impacts before or during use
Ethical evaluation should not be conducted at the level of AI or robots in general, but must consider particular systems, domains, and forms of interaction.
4 Discussion
screening score · 2026-10-24