The Challenges and Opportunities of Artificial Intelligence in Implementing Trustworthy Robotics and Autonomous Systems
The Challenges and Opportunities of Artificial Intelligence in Implementing Trustworthy Robotics and Autonomous Systems
This review paper analyzes the challenges and opportunities of artificial intelligence in implementing trustworthy robots and autonomous systems (RAS). It identifies four key properties required for trustworthiness—robustness for health issues, safety in surrounding environments, cyber security, and trusted human-machine interaction—while examining how AI techniques can help address these challenges. The study emphasizes the emerging concept of human-centred AI as core to building fully trustworthy autonomous systems.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
Researchers, developers, and engineers working on artificial intelligence, robotics, and autonomous systems seeking an overview of trustworthiness requirements and technical challenges.
What the document contains
The document covers the fundamental requirements, technical challenges, and AI-driven solutions for establishing trustworthiness in robots and autonomous systems. It specifically examines cyber security vulnerabilities, safety hazards, health maintenance and fault diagnosis, and human-machine interaction.
The document does not provide binding legal regulations, formal compliance certification schemes, or specific enforcement mechanisms.
- Effective robots and autonomous systems (RAS) must be trustworthy, adhering to the principle that 'No trust, no use'.
- Trustworthiness in RAS depends on four key properties: health robustness, environmental safety, cyber security, and trusted human-machine interaction.
- While AI offers powerful capabilities for automation, threat detection, and fault diagnosis, it also introduces potential risks such as adversarial vulnerabilities and biased decision-making.
- Human-centred AI (HAI) serves as a vital core framework to ensure that next-generation intelligent systems reflect human intelligence and enhance rather than replace human capabilities.
· I. Introduction · II. Key factors that affect RAS' trustworthiness · III. The challenges in implementing trustworthy RAS · IV. The opportunities of AI technology · V. Conclusions
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
0/5Clear responsibility for AI outcomes
screening score · 2026-10-23
Fairness
2/5Non-discrimination and equitable treatment
Machine learning-based AI systems trained with incomplete or distorted data (i.e. their “worldview”) can lead to biased “thinking,” which may in turn magnify prejudice and inequality
V. Conclusions
screening score · 2026-10-23
Human Dignity
3/5Respect for the inherent worth of persons
The new concept of human-centred AI will be the core in implementing the trustworthy RAS.
Abstract
screening score · 2026-10-23
Human Oversight
4/5Humans remain in control of consequential decisions
No matter which level a system’s autonomy is at, human should be able to interrupt the system, even if the execution of autonomous systems does not need to have the intervention of human
II. Key Factors That Affect RAS’ Trustworthiness
screening score · 2026-10-23
Privacy
3/5Protection of personal data and private life
The privacy of RAS is a branch of security, which focuses on the data protection, especially, personal information protection, and regulation compliance (e.g. GDPR).
II. Key Factors That Affect RAS’ Trustworthiness
screening score · 2026-10-23
Transparency
2/5Openness about how AI systems work and are used
Through the intuitive and efficient visualization of sensed quantities, estimated statistics, and the automatic identification of trends over time, both users and the system could be better informed on their conditions
II. Key Factors That Affect RAS’ Trustworthiness
screening score · 2026-10-23
Enforcement
0/5Consequences and compliance mechanisms with real force
screening score · 2026-10-23
Impact Assessment
2/5Required assessment of an AI system's risks/impacts before or during use
While we put our eyes on the benefits that AI brings to human, we should realise the potential risks that could be caused by AI.
Abstract
screening score · 2026-10-23