| Title | The Challenges and Opportunities of Artificial Intelligence for Trustworthy Robots and Autonomous Systems |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | He, Hongmei, Gray, John, Cangelosi, Angelo, Meng, Qinggang, McGinnity, T. M., Mehnen, Jörn |
| Conference Name | 2020 3rd International Conference on Intelligent Robotic and Control Engineering (IRCE) |
| Keywords | artificial intelligence, autonomous systems, composability, cyber physical security, cyber physical systems, cyber security, Electronic mail, Health, human-robot interaction, performance ofras, pubcrawl, resilience, Resiliency, Robot sensing systems, Safety, security, trustworthiness of ras, Trustworthy Systems |
| Abstract | Trust is essential in designing autonomous and semiautonomous Robots and Autonomous Systems (RAS), because of the ``No trust, no use'' concept. RAS should provide high quality services, with four key properties that make them trustworthy: they must be (i) robust with regards to any system health related issues, (ii) safe for any matters in their surrounding environments, (iii) secure against any threats from cyber spaces, and (iv) trusted for human-machine interaction. This article thoroughly analyses the challenges in implementing the trustworthy RAS in respects of the four properties, and addresses the power of AI in improving the trustworthiness of RAS. While we focus on the benefits that AI brings to human, we should realize the potential risks that could be caused by AI. This article introduces for the first time the set of key aspects of human-centered AI for RAS, which can serve as a cornerstone for implementing trustworthy RAS by design in the future. |
| DOI | 10.1109/IRCE50905.2020.9199244 |
| Citation Key | he_challenges_2020 |
The Challenges and Opportunities of Artificial Intelligence for Trustworthy Robots and Autonomous Systems