Trustworthiness and Well-Being: The Ethical, Legal, and Social Challenge of Robotic Assistance
This academic book chapter examines the ethical, legal, and social implications of robotic assistance in daily life and care settings, drawing on findings from the Bremen AI Delphi study. It explores public attitudes, trust dimensions, and perceived well-being in human-robot interaction, revealing high overall interest in AI accompanied by deep skepticism regarding human-centric applications such as domestic care and conversation robots. The analysis highlights that perceived technological trustworthiness and imagined well-being heavily influence the public's willingness to adopt robotic assistance.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
Researchers and policymakers studying public trust, social acceptance, and ethical challenges in human-robot interaction and care robotics.
What the document contains
The text covers public survey findings on the acceptance and trust of AI and robots, analyzing specific use cases including household chores, caregiving, job applicant preselection, legal advice, algorithms, and self-driving cars. It assesses how personal self-image, beliefs, and imagined well-being shape the willingness to adopt robotic technologies.
The document does not provide binding regulatory standards, legal frameworks, or direct enforcement mechanisms, focusing instead on empirical social science survey analysis and conceptual discussions.
- While populations show a generally positive image of AI and robots, they exhibit significant skepticism concerning safety, reliability, and trustworthiness.
- Acceptance of robots drops sharply the closer the technology gets to human-centric domains, such as care, education, and private everyday life.
- The willingness to use robotic assistance in care is strongly tied to whether individuals can imagine engaging in comfortable communication with robots.
- Open-mindedness toward technical innovations strongly correlates with positive feelings toward imagined human-robot interactions and willingness to adopt AI.
- Perceived technological capabilities and the perceived integrity of the application represent independent assessment dimensions.
· 1.1 Introduction · 1.2 Acceptance · 1.3 Trust in Robotic Assistance and Autonomous AI · 1.4 Accepting Robotic Assistance and Talking with Robots · 1.5 Technical Innovation, Religion, and Human Values and the Tried and Tested as Elements of the Individual Self-Image · 1.6 Feeling at Ease with Imagined Situations of Human–Robot Interaction · 1.7 Trustworthiness and Well-Being in the Context of Robotic Assistance
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
ensure diversity, non-discrimination, fairness, and accountability
Trustworthiness
screening score · 2026-10-24
Fairness
3/5Non-discrimination and equitable treatment
Ideas of fairness, justice, and transparency are no less relevant for the people than for interest groups.
Trustworthiness
screening score · 2026-10-24
Human Dignity
3/5Respect for the inherent worth of persons
AI systems should support human autonomy and decision-making
Trustworthiness
screening score · 2026-10-24
Human Oversight
0/5Humans remain in control of consequential decisions
1.1 Introduction
screening score · 2026-10-24
Privacy
3/5Protection of personal data and private life
ensure prevention of harm to privacy, and be transparent
Trustworthiness
screening score · 2026-10-24
Transparency
3/5Openness about how AI systems work and are used
relying on maximum of transparency in all relevant respects regarding the further development of robotic assistance appear very useful
1.7 Trustworthiness and Well-Being in the Context of Robotic Assistance
screening score · 2026-10-24
Enforcement
0/5Consequences and compliance mechanisms with real force
1.1 Introduction
screening score · 2026-10-24
Impact Assessment
0/5Required assessment of an AI system's risks/impacts before or during use
1.1 Introduction
screening score · 2026-10-24