Beyond RoboDebt

2020 ◽  
Vol 11 (2) ◽  
pp. 1-24
Author(s):  
Michael D'Rosario ◽  
Carlene D'Rosario

Automated decision support systems with high stake decision processes are frequently controversial. The Online Compliance Intervention (herewith “OCI” or “RoboDebt”) is a system of compliance implemented with the intention to facilitate automatic issuance of statutory debt notices to individuals, taking a receipt of welfare payments and exceeding their entitlement. The system appears to employ rudimentary data scraping and expert systems to determine whether notices should be validly issued. However, many individuals that take receipt of debt notices assert that they were issued in error. The commentary on the system has resulted in a lot of conflation of the system with other system types and caused many to question the role of decision of support systems in public administration given the potentially deleterious impacts of such systems for the most vulnerable. The authors employ a taxonomy of Robotic Process Automation (RPA) issues, to review the OCI and RPA more generally. This paper identifies potential problems of bias, inconsistency, procedural fairness, and overall systematic error. This research also considers a series of RoboDebt specific issues regarding contractor arrangements and the potential impact of the system for Australia's Indigenous population. The authors offer a set of recommendations based on the observed challenges, emphasizing the importance of moderation, independent algorithmic audits, and ongoing reviews. Most notably, this paper emphasizes the need for greater transparency and a broadening of criteria to determine vulnerability that encompasses, temporal, geographic, and technological considerations.

2022 ◽  
pp. 236-262
Author(s):  
Michael D'Rosario ◽  
Carlene D'Rosario

Automated decision support systems with high stake decision processes are frequently controversial. The Online Compliance Intervention (herewith “OCI” or “RoboDebt”) is a system of compliance implemented with the intention to facilitate automatic issuance of statutory debt notices to individuals, taking a receipt of welfare payments and exceeding their entitlement. The system appears to employ rudimentary data scraping and expert systems to determine whether notices should be validly issued. However, many individuals that take receipt of debt notices assert that they were issued in error. The commentary on the system has resulted in a lot of conflation of the system with other system types and caused many to question the role of decision of support systems in public administration given the potentially deleterious impacts of such systems for the most vulnerable. The authors employ a taxonomy of Robotic Process Automation (RPA) issues, to review the OCI and RPA more generally. This paper identifies potential problems of bias, inconsistency, procedural fairness, and overall systematic error. This research also considers a series of RoboDebt specific issues regarding contractor arrangements and the potential impact of the system for Australia's Indigenous population. The authors offer a set of recommendations based on the observed challenges, emphasizing the importance of moderation, independent algorithmic audits, and ongoing reviews. Most notably, this paper emphasizes the need for greater transparency and a broadening of criteria to determine vulnerability that encompasses, temporal, geographic, and technological considerations.


Author(s):  
Michael D'Rosario ◽  
Carlene D'Rosario

Automated decision support systems with high stake decision processes are frequently controversial. The Online Compliance Intervention (herewith “OCI” or “RoboDebt”) is a system of compliance implemented with the intention to facilitate automatic issuance of statutory debt notices to individuals, taking a receipt of welfare payments and exceeding their entitlement. The system appears to employ rudimentary data scraping and expert systems to determine whether notices should be validly issued. However, many individuals that take receipt of debt notices assert that they were issued in error. The commentary on the system has resulted in a lot of conflation of the system with other system types and caused many to question the role of decision of support systems in public administration given the potentially deleterious impacts of such systems for the most vulnerable. The authors employ a taxonomy of Robotic Process Automation (RPA) issues, to review the OCI and RPA more generally. This paper identifies potential problems of bias, inconsistency, procedural fairness, and overall systematic error. This research also considers a series of RoboDebt specific issues regarding contractor arrangements and the potential impact of the system for Australia's Indigenous population. The authors offer a set of recommendations based on the observed challenges, emphasizing the importance of moderation, independent algorithmic audits, and ongoing reviews. Most notably, this paper emphasizes the need for greater transparency and a broadening of criteria to determine vulnerability that encompasses, temporal, geographic, and technological considerations.


2014 ◽  
pp. 241-259 ◽  
Author(s):  
Aleix Serrat-Capdevila ◽  
Juan B. Valdés ◽  
Hoshin V. Gupta ◽  
Graciela Schneier-Madanes

The domain of construction is a very knowledge-intensive domain with so many factors involved. This implies undertaking any action requires an understanding of the different factors and how best to combine them to achieve a favourable and optimal outcome. Thus decision-making has been extensively used in the domain of construction. The aim of this chapter is to undertake a review of various decision support systems and to provide insights into their applications in the domain of construction. Specifically, the principle of cost index, sub-work chaining diagram method, linear regression and cost over-runs in time-overrun context (CCOTOV) model and Markov decision processes (MDP), ontology and rule-based systems have been reviewed. Based on the review the Markov decision processes (MDP), ontology and rule-based systems were chosen as the more suitable for the cost control case considered in this study.


2009 ◽  
pp. 82-89
Author(s):  
John Wang ◽  
James Yao

Group decision support systems (GDSSs) which aim at increasing some of the benefits of collaboration and reducing the inherent losses are interactive information technology-based environments that support concerted and coordinated group efforts toward completion of joint tasks (Dennis, George, Jessup, Nunamaker, & Vogel, 1998). The term group support systems (GSSs) was coined at the start of the 1990’s to replace the term GDSS. The reason for this is that the role of collaborative computing was expanded to more than just supporting decision making (Patrick & Garrick, 2006). For the avoidance of any ambiguities, the latter term shall be used in the discussion throughout this paper


Author(s):  
Miroslaw Staron ◽  
Wilhelm Meding ◽  
Kent Niesel ◽  
Ola Söder

Measurement data can be used for decision support in multiple ways – from one-time, manual data collection/presentation (reporting) through flexible business intelligence solutions to online, automated measurement systems. In centralized organizations, the measurement data is often collected through reporting, but the trends in modern organizations with empowered teams, globalized development, and needs to monitor continuously longer supply chains requires shift in the design and use of measurement systems. In this chapter, we present a study of evolving measurement systems at three companies with global businesses – Ericsson, Volvo Cars, and Axis Communications. The results of the study include the identification of the timeline of the evolution, distinct generations of measurement systems and information needs in the different phases of the evolution. The experiences show how to evolve centralized decision support systems to support global and distributed decision support.


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