Ensuring Trustworthiness of Hybrid AI-Based Robotics Systems

Alexander Eguia*, Nuria Quintano, Irina Marsh, Michel Barreteau, Jakub Główka, Agnieszka Sprońska

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Hybrid Artificial Intelligence (HAI) algorithms are well adapted to the industrial environment since they require significantly less data than data-driven Artificial Intelligence (AI) algorithms, matching the industry constraints. However, HAI does not fully address the issue of trust (validity, transparency, explainability, and ethics) which must be tackled to achieve world-class HAI beneficial to humans individually, organisationally, and societally. This paper focuses on describing the methods used to collect and elicit trustworthiness requirements in the European ULTIMATE project. It includes requirements register and a trustworthiness glossary of terms.

Original languageEnglish
Title of host publicationEuropean Robotics Forum 2024 - 15th ERF
EditorsCristian Secchi, Lorenzo Marconi
PublisherSpringer Nature
Pages142-146
Number of pages5
ISBN (Print)9783031764271
DOIs
Publication statusPublished - 2024
Event15th European Robotics Forum, ERF 2024 - Rimini, Italy
Duration: 13 Mar 202415 Mar 2024

Publication series

NameSpringer Proceedings in Advanced Robotics
Volume33 SPAR
ISSN (Print)2511-1256
ISSN (Electronic)2511-1264

Conference

Conference15th European Robotics Forum, ERF 2024
Country/TerritoryItaly
CityRimini
Period13/03/2415/03/24

Keywords

  • ethics
  • hybrid AI
  • robotics
  • trustworthiness

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