HAIS 2020: Pre-ECIS 2020 Workshop on Hyper-automation and Information Systems The Congress Palace MOGADOR Marrakech, Morocco, June 14, 2020 |
Conference website | https://ecis2020.ma/workshops-and-ancillary-meetings/ |
Submission link | https://easychair.org/conferences/?conf=hais20200 |
Submission deadline | March 20, 2020 |
Hyper-automation and Information Systems
Information systems are developed to support operations, decision making, and management. While this is not new, more and more practitioners and researchers claim that tasks typically associated with humans are increasingly executed and even determined by information systems (Hirschheim & Klein, 2012). These arguments sketch a picture of “automation” taking over traditional operations, decision makings, and management tasks. Therefore, the concern becomes when, how, and what should be automated and what tasks should be done by humans.
Automation was introduced in the 19th century and it was traditionally defined as the execution by a machine agent of a function that was previously carried out by a human. Since then, automation has made lasting and imposing changes in the world of manual labor (Park, 2018). These changes, therefore, improved efficiency, quality, precision, and accuracy by replacing manual tasks with automated tasks executed by machine agents. For example, through ERP systems, process templates and integrated information were introduced as means to improve the utilization of enterprise resources. Recently, Robotic Process Automation (RPA) has emerged to automate structured and stable processes by executing repetitive, and high-volume routine tasks (van der Aalst, Bichler, & Heinzl, 2018). However, automation is not only about replacing manual labor with automated tasks. It goes beyond performing manual activities and moves towards performing more intellectual and cognitive tasks such as problem-solving using unstructured data, reasoning, decision making, and planning or combinations of multiple tasks (Fasth-Berglund and Stahre, 2013). Cognitive automation is an extension of RPA that utilizes approaches such as natural language processing, text analytics and machine learning, to bring intelligence to information rich work practices (Expert System, 2019).
The application of multiple techniques to advance work practices are sometimes called Hyper-automation. Hyper-automation refers to the combination of machine learning, packaged software and automation tools, including cognitive and robotic process automation to advance work practices (Gartner, 2019). For example, Wipro uses hyper-automation to leverage cognitive and robotic process automation to significantly change the IT delivery model (Obtv-admin, 2016). Hyper-automation also refers to all range of automation mechanisms and steps of automation itself such as discovering, analyzing, designing, automating, measuring, monitoring and reassessing (Gartner, 2019) and how combination of advance technologies and tools such as artificial intelligence (AI), Internet of things (IoT), big data, robotics, and machine learning (ML) can contribute to developing hyper-automation (Park, 2018).
Through rapid scaling, significant adaptations in capabilities have occurred as a result of the convergence of trends and technological developments. These changes have a large impact on the work practices, products, processes, and people (Donovan & Prabhu, 2017). Therefore, understanding the automation procedures, how they can be combined and coordinated becomes even more important. Furthermore, we are on the cusp of the next industrial revolution through technological developments such as augmented automation, digitizing and analyzing which will impact the connection between human and human, human and machines, and machine and machine, for instance when and how a machine should decide to hand in a task to a human and vice versa. Hyper-automation will also drive the need for different skills to understand, empathize, and collaborate. Automation through advanced technologies can augment human skills, but some of these skills cannot be replicated by a machine while ultimately humans should be accountable for decisions and outcomes (Berryhill, 2019).
By organizing this workshop, our aim is to increase the understanding of hyper-automation and its implications for information systems. Potential topics include, but are not limited to:
• Hyper-automation,
• Robotic Process Automation,
• Cognitive Automation, Artificial intelligence, Machine learning in relation to Hyper-automation
• Future workforce, autonomy, and responsibility
• Automated exception handling
• Human trust in automation technology
• Human and Machine: collaboration, understanding and decision transparency
• Implications of hyper-automation for management strategies
• Business capability implications of hyper-automation
• Examples of changes in routine capabilities through the use of hyper-automation
Submission Guidelines
We welcome researchers to participate in a full-day workshop. Interested researchers can participate in two ways in the workshop:
- Research paper (either research-in-progress or a full paper according the ECIS 2020 submission guideline). The submitted papers will be reviewed by the workshop committee and accepted papers will be discussed during the workshop.
- Experience paper. Experience papers present problems or challenges encountered in practice, relate success and failure stories, or report on industrial practice. The focus is on ‘what’ and on lessons learned, not on an in-depth analysis of ‘why’. The practice must be clearly described, and its context must be given. Readers should be able to draw conclusions for their own practice.
Organizing Committee
- Gustaf Juell-Skielse, Associate Professor,
Stockholm University, Sweden.
Email: gjs@dsv.su.se - Mohammad Jabbari, Dr.,
Queensland University of Technology, Australia.
Email: m.jabbarisabegh@qut.edu.au - Hajo A. Reijers, Professor,
Utrecht University, The Netherlands.
Email: h.a.reijers@uu.nl
Venue
The workshop will be held in the Congress Palace MOGADOR in Marrakech, Morocco.
Contact
All questions about submissions should be emailed to gjs@dsv.su.se.