Accountability as a service for robotics: Performance assessment of different accountability strategies for autonomous robots

Author:

Fernández-Becerra Laura1,Manuel Guerrero-Higueras Ángel2,Rodríguez-Lera Francisco Javier3,Matellán Vicente4

Affiliation:

1. Robotics Group , Universidad de León, Campus de Vegazana s/n, Léon, 24071, Spain, inflfb00@estudiantes.unileon.es

2. Robotics Group , Universidad de León, Campus de Vegazana s/n, Léon, 24071, Spain, am.guerrero@unileon.es

3. Robotics Group , Universidad de León, Campus de Vegazana s/n, Léon, 24071, Spain, fjrodl@unileon.es

4. SCAYLE (Supercomputación Castilla y León) , Campus de Vegazana s/n, Léon, 24007, Spain, vmato@unileon.es

Abstract

Abstract An essential requirement for increasing human confidence in computer systems is knowing an event’s origin. Therefore, it is necessary to have an efficient method to record such information. It is especially challenging in robotics, where unexpected behaviours can have unpredictable consequences, endangering the interests of people or even their safety. Furthermore, to analyse an incident’s cause or anticipate future behaviours, we must identify the events that cause a specific action. Although it is common to use logging systems for such purposes, issues such as partial recording of events, unhelpful data or the impact on robot performance suggest conceiving new accountability solutions that assist when determining the responsible entities or the provenance of specific information. This paper presents a general-purpose approach to developing an accountability system for autonomous robots. It consists of four main components: a system event logger, a message producer, a distributed event streaming platform and a database. Our proposal is completely decoupled from the monitored system and allows real-time analysis, improving flexibility, besides system protection and transparency. Finally, the need to reduce the impact of the audit process and logging tasks on robot performance has promoted the development of different assessment scenarios to determine the best strategy for providing accounting services.

Publisher

Oxford University Press (OUP)

Reference45 articles.

1. Lsof–list open files;Abell,2022

2. Explainable agents and robots: results from a systematic literature review;Anjomshoae,2019

3. Kafka clients;Apache,2022

4. Robustness based on accountability in multiagent organizations;Baldoni,2021

5. Apache kafka with confluent;Confluent,2022

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