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Understanding Automated Decision-Making in the Public Sector: A Classification of Automated, Administrative Decision-Making

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Service Automation in the Public Sector

Part of the book series: Progress in IS ((PROIS))

Abstract

Service automation in the public sector is applied to a range of different activities that include policy development, administrative decision-making and public service delivery. This chapter focusses on the use of automated, administrative decision-making and conceptualises a classification of six ideal types ranging from Minimal automation to Autonomous decisions. Each type describes a configuration of decision authority between civil servants and algorithmic systems which illustrates how the use of advanced technology does not exist independent of its users and contextual factors. The classification allows new empirical sensitivities to be applied to applications of automated administrative decision-making that go beyond basic differentiations of semi- and fully automated decisions. It emphasises the need to understand empirical instances of automated decisions-making usage as ambiguous and often consisting of several ideal types of use. The chapter provides a basis for the understanding of consequences of automated administrative decision-making in the public sector. The classification furthermore supports informed choices among practitioners of appropriate IT-system design and test as well as choices of appropriate professional and management practices in relation to automated administrative decision-making.

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Notes

  1. 1.

    “ADM” is a common abbreviation for automated decision-making; “AADM” is used in this chapter to emphasise the focus on automated administrative decision-making as a particular type of automated decision-making.

  2. 2.

    “Civil servant” is used as a term for case workers, case managers, adjudicators and other officials who are responsible for administrative decisions. In addition and for sake of ease, the singular “civil servant” is used although often it is empirically more correct to speak of civil servants in plural.

  3. 3.

    Although frameworks of administrative law vary across legal traditions, the concept of administrative decisions is generic and known under headings such as “acte administratif individual” (Francophone tradition); “Verwaltungsakte” (German tradition); and “förvaltningsbeslut”/”-afgørelse”/”-vedtak” (Scandinavian tradition).

  4. 4.

    Originating in relation to autonomous weapon systems, industrial production, etc., and occasionally mentioned as a theoretical possibility in discussions of automated decision-making in the public sector, it is also possible for the human operator to be ‘on’ the loop. This implies the operator is supervising the fully automated decision-making with the ability to stop it within a given timeframe (Hauptman, 2013). Empirical instances of the “on”-type in relation to administrative decision-making seem to be very few or non-existent.

  5. 5.

    Parasuraman et al. (2000) suggest a two-dimensional model of function and level of automation. For sake of clarity and adaptability to administrative decision-making this has been combined to one dimension in Table 1

  6. 6.

    A short caveat is appropriate in relation to the illustration of the classification (Figure 1): the illustration is downward sloping towards Autonomous decisions (Type F) thereby risking indicating a negative understanding of this type of automated decision-making (i.e. towards a “digital nightmare”). Bearing the descriptive nature of the classification in mind, this is not the intention, but the sloping character has been chosen—as a matter of the lesser of two evils—to avoid the risk of indicating a positive understanding of a “digital nirvana” through an upward slope.

  7. 7.

    This basically describes a continuous process of “training” decision models based on previous patterns of use and/or data: it is thus also possible to envision a situation where an increased number of decisions are processed automatically (Type E) over time rather than processed manually (Type C or D) based on an explicit assessment of previous patterns of use by civil servants.

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Conflict of Interest

The research described in this paper has been carried out as part of a PhD Project partly financed by the Danish public sector company, KOMBIT Ltd. After the author’s best consideration there are no conflicts of interests.

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Correspondence to Ulrik B. U. Roehl .

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Appendix: Empirical Examples of Ideal Types of Use of AADM

Appendix: Empirical Examples of Ideal Types of Use of AADM

See Table 4.

Table 4 Selected, approximate empirical examples of ideal types of AADM usage. “X” indicates that the example bears resemblance to the type; and “(X)” indicates the example might bear resemblance to the type. Please note empirical examples are not based on thorough review and are simplified in descriptions. “*” indicates technology appears to no longer be in use as described

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Roehl, U.B.U. (2022). Understanding Automated Decision-Making in the Public Sector: A Classification of Automated, Administrative Decision-Making. In: Juell-Skielse, G., Lindgren, I., Åkesson, M. (eds) Service Automation in the Public Sector. Progress in IS. Springer, Cham. https://doi.org/10.1007/978-3-030-92644-1_3

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