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Developing and Operating Artificial Intelligence Models in Trustworthy Autonomous Systems

Conference paper
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Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 415)

Abstract

Companies dealing with Artificial Intelligence (AI) models in Autonomous Systems (AS) face several problems, such as users’ lack of trust in adverse or unknown conditions, gaps between software engineering and AI model development, and operation in a continuously changing operational environment. This work-in-progress paper aims to close the gap between the development and operation of trustworthy AI-based AS by defining an approach that coordinates both activities. We synthesize the main challenges of AI-based AS in industrial settings. We reflect on the research efforts required to overcome these challenges and propose a novel, holistic DevOps approach to put it into practice. We elaborate on four research directions: (a) increased users’ trust by monitoring operational AI-based AS and identifying self-adaptation needs in critical situations; (b) integrated agile process for the development and evolution of AI models and AS; (c) continuous deployment of different context-specific instances of AI models in a distributed setting of AS; and (d) holistic DevOps-based lifecycle for AI-based AS.

Keywords

DevOps Autonomous Systems AI Trustworthiness 

Notes

Acknowledgment

This work has been partially supported by the Beatriz Galindo programme (BGP18/00075) and the Catalan Research Agency (AGAUR, contract 2017 SGR 1694).

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Copyright information

© Springer Nature Switzerland AG 2021

Authors and Affiliations

  1. 1.Universitat Politècnica de Catalunya - BarcelonaTechBarcelonaSpain
  2. 2.Fraunhofer IESEKaiserslauternGermany

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