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The challenges and opportunities of human-centred AI for trustworthy robots and autonomous systems

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journal contribution
posted on 2021-12-06, 10:01 authored by Hongmei He, John Gray, Angelo Cangelosi, Qinggang MengQinggang Meng, TM McGinnity, Jorn Mehnen

The trustworthiness of robots and autonomous systems (RAS) has taken a prominent position on the way towards full autonomy. This work is the first to systematically explore the key facets of human-centred AI for trustworthy RAS. We identified five key properties of a trustworthy RAS, i.e., RAS must be (i) safe in any uncertain and dynamic environment; (ii) secure, i.e., protect itself from cyber threats; (iii) healthy and fault-tolerant; (iv) trusted and easy to use to enable effective human-machine interaction (HMI); (v) compliant with the law and ethical expectations. While the applications of RAS have mainly focused on performance and productivity, not enough scientific attention has been paid to the risks posed by advanced AI in RAS. We analytically examine the challenges of implementing trustworthy RAS with respect to the five key properties and explore the role and roadmap of AI technologies in ensuring the trustworthiness of RAS in respect of safety, security, health, HMI, and ethics. A new acceptance model of RAS is provided as a framework for human-centric AI requirements and for implementing trustworthy RAS by design. This approach promotes human-level intelligence to augment human capabilities and focuses on contribution to humanity.

Funding

Air Force Office of Scientific Research, USAF under Award FA9550-19-1-7002

UKRI TAS Node on Trust

History

School

  • Science

Department

  • Computer Science

Published in

IEEE Transactions on Cognitive and Developmental Systems

Volume

14

Issue

4

Pages

1398 - 1412

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Version

  • AM (Accepted Manuscript)

Rights holder

© IEEE

Publisher statement

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Acceptance date

2021-11-24

Publication date

2021-12-02

Copyright date

2021

ISSN

2379-8920

eISSN

2379-8939

Language

  • en

Depositor

Prof Qinggang Meng . Deposit date: 4 December 2021

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