=Paper=
{{Paper
|id=Vol-3779/paper0
|storemode=property
|title=Balancing Autonomy and Trust to Enable Intelligent Robotic Process Automation
|pdfUrl=https://ceur-ws.org/Vol-3779/invited.pdf
|volume=Vol-3779
|authors=Andrea Marrella
|dblpUrl=https://dblp.org/rec/conf/pmai/Marrella24
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==Balancing Autonomy and Trust to Enable Intelligent Robotic Process Automation==
https://ceur-ws.org/Vol-3779/invited.pdf
Balancing Autonomy and Trust to Enable Intelligent
Robotic Process Automation
Andrea Marrella
Abstract
Robotic Process Automation (RPA) is a maturing technology that sits between the fields of Business
Process Management (BPM) and Artificial Intelligence (AI). RPA allows organizations to automate high-
volume and repetitive tasks performed by human operators. These tasks are enacted using a software
(SW) robot that works on the applications’ user interfaces (UIs) as the original human operators did.
The current generation of RPA tools is driven by predefined rules and manual configurations made
by expert users rather than intelligent solutions, making the current practice time-consuming and
error-prone. In this talk, we focus on a recent line of research devoted to leveraging the combined use of
process mining and reasoning about actions in AI to evolve RPA from a mere automated technology to a
(framed) autonomous solution capable of complex decision-making activities. In this journey, we also
conceptualize the notion of trust between humans and SW robots by discussing the research challenges
to pioneer new trust-aware solutions that work in partnership with the human workforce and strike the
right balance of autonomy and trust for achieving intelligent RPA.
Keywords
Intelligent Robotic Process Automation (RPA), Software (SW) Robot, Trust, Process Mining, Reasoning
about Actions in AI
Robotic Process Automation (RPA) is a maturing technology that sits between the fields of
Business Process Management (BPM) and Artificial Intelligence (AI). RPA allows organizations
to automate high-volume and repetitive tasks performed by human users without changing
the underlying IT systems [1]. These tasks are enacted using a software (SW) robot that works
on the applications’ user interfaces (UIs) as the original human operators did. Since RPA has
proven to work reliably [2], many organizations have recently adopted it [3].
The current generation of commercial RPA tools is driven by predefined rules and manual
configurations made by expert users rather than intelligent solutions, making the current
practice time-consuming and error-prone [4, 5]. To mitigate this issue, many researchers are
investigating how to leverage AI algorithms and intelligent techniques to improve the accuracy
and execution of SW robots to make them more autonomous and capable of complex decision-
making activities [6, 7]. The research literature shows that, among the others, techniques from
computer vision [8], machine learning [9], natural language processing [10], conversational AI
[11], automated planning [12] and process mining [13, 14] were proposed to inject intelligence
into current RPA technology.
In an era where RPA is pushing the automation of human tasks to the extreme, on the
other hand, recent research studies conducted on the effectiveness of RPA within organizations
3rd Int. Workshop on Process Management in the AI era, PMAI 2024, 19 October 2024, Santiago de Compostela, Spain
Envelope-Open marrella@diag.uniroma1.it (A. Marrella)
GLOBE https://www.diag.uniroma1.it/marrella/ (A. Marrella)
Orcid 0000-0002-1031-0374 (A. Marrella)
© 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
ceur-ws.org
Workshop ISSN 1613-0073
Proceedings
have found that implementation of SW robots does not always lead to the assumed effect, and
many SW robots are subsequently withdrawn. Consequently, the human workforce takes over
robotized tasks to perform them manually again and, in practice, replaces SW robots, leading
to a costly remanualization of the respective task [15]. One frequently cited barrier to wider
RPA adoption is the lack of trust between humans and SW robots [16, 17, 18]. Since human
employees are expected to share responsibilities with the SW robots, trust in their performance
is crucial for ensuring this technology’s adoption and proper use.
Although the literature on human-AI collaboration has extensively explored trust issues,
offering valuable lessons for RPA [19], the development of a framework striking a balance
between providing autonomy and trust for RPA requires considering the transactional, non-
anthropomorphic and abstract nature of SW robots, which is a specific nuance of this technology.
That is, the end-user perception of trust in RPA strongly depends on the outcomes the SW
robots deliver as the result of task execution.
In this talk, after discussing a recent line of research devoted to leveraging the combined
use of process mining and reasoning about actions in AI to evolve RPA from an automated
technology to a (framed) autonomous solution, we report on the key insights of a Dagstuhl
Seminar organized in July 2024, entitled Improving Trust between Humans and Software Robots in
Robotic Process Automation.1 The seminar was organized to pioneer new intelligent trust-aware
RPA solutions that work in partnership with the human workforce. Specifically, we present
the key factors contributing to creating or eroding trust in RPA and consolidate them in a
conceptual framework that indicates the dimensions and characteristics of trust. Then, we
specify the notion of trust in RPA as a measurable construct – Willingness to Give Up Control
(WGUC) – that allows assessing the level of trust between humans and SW robots. Finally, we
present the significant research challenges in the transition toward trustworthy and intelligent
RPA, and chart a roadmap for future RPA research.
Acknowledgments. This work has been supported by the Sapienza project FOND-AIBPM and
the PNRR MUR project PE0000013-FAIR. The author would like to thank all the people involved
in the Dagstuhl Seminar Improving Trust between Humans and Software Robots in Robotic Process
Automation for their ideas and lively discussions, which have contributed significantly to the
content of this talk, and in particular: Simone Agostinelli, Marco Angelini, Aleksandre Asatiani,
Bernhard Axmann, Piercosma Bisconti, Angelo Casciani, Christian Czarnecki, Adela del Río
Ortega, Andrea Delgado, José González Enríquez, Glenda Hannibal, Christian Janiesch, Andrés
Jiménez Ramírez, Faizan Ahmed Khan, Antonio Martínez Rojas, Artur Modlinski, Ralf Plattfaut,
Jana-Rebecca Rehse, Hajo A. Reijers, Manuel Resinas, Michael Rosemann, Flávia Santoro, Stefan
Sarkadi, Pnina Soffer, Barbara Weber, and Adriana Wilde.
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1
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