Algorithmic transparency and bureaucratic discretion: The case of SALER early warning system

Abstract

The governance of public sector organizations has been challenged by the growing adoption and use of Artificial Intelligence (AI) systems and algorithms. Algorithmic transparency, conceptualized here using the dimensions of accessibility and explainability, fosters the appraisal of algorithms’ footprint in decisions of public agencies, and should include impacts on civil servants’ work. However, although discretion will not disappear, AI innovations might have a negative impact on how public employees support their decisions. This article is intended to answer the following research questions: RQ1. To what extent algorithms affect discretionary power of civil servants to make decisions?RQ2. How algorithmic transparency can impact discretionary power of civil servants? To do so, we analyze SALER, a case based on a set of algorithms focused on the prevention of irregularities in the Valencian regional administration (GVA), Spain, using a qualitative methodology supported on semi-structured interviews and documentary analysis. Among the results of the study, our empirical work suggests the existence of a series of factors that might be linked to the positive impacts of algorithms on the work and discretionary power of civil servants. Also, we identify different pathways for achieving algorithmic transparency, such as the involvement of civil servants in active development, or auditing processes being recognized by law, among others.

Can artificial intelligence’s limitations drive innovative work behaviour?

“…Workers, therefore, can reskill and upskill themselves because of the introduction of AI in the workplace (Jaiswal et al 2021). When upskilling and reskilling combine data with human intuition to make the most of AI technological advances, algorithms can positively impact workers' work and discretionary power (Criadoa et al 2020;Jaiswal et al 2021). However, not only practical and technical knowledge and skills are necessary for that purpose, but also creativity-focused skills such as managing uncertainty, critical thinking, problem-solving, exploring possibilities, tolerating ambiguity, exhibiting self-efficacy, teamwork, and effective communication (Cropley 2020;Rampersad 2020).…”

“…Therefore, though workplace AI requires upskilling and reskilling (Braganza et al 2020), workplace AI places high demands on workers' cognitive processing (Van Acker et al 2021). Gamification and simulations help workers understand the feasibility of ideas by collaborating in cross-functional teams and being involved in the active development and auditing processes of AI applications (Anjali and Priyanka 2020;Criadoa et al 2020). Consequently, human-AI collaboration is needed to overcome AI limitations in the workplace.…”

“…Hence, although organisations are increasingly using AI systems and algorithms, the accessibility and interpretability of algorithms (algorithmic transparency) have drawn attention to the organisation's algorithmic footprint (Criadoa et al 2020). As a result, innovative behaviour in the workplace entails addressing the ethical, social, economic, and legal aspects of AI applications (Di Vaio et al 2020).…”

Inteligencia Artificial (y Administración Pública)

“…Los gobiernos y administraciones públicas desarrollan sus actividades gracias a dispositivos y tecnologías que les permiten gestionar y controlar los datos, sobre todo, que emanan de la ciudadanía. En consecuencia, los algoritmos incorporan características que son diferenciales y suponen la necesidad de conocer su potencial, así como las dimensiones en las que tendrán un impacto directo en la sociedad y la gobernanza de lo púbico (Criado et al, 2020). Las reglas incrustadas en los algoritmos tienen una directa consecuencia en aspectos como los procesos de adopción de decisiones del personal directivo, sobre qué empleados contratar, la elegibilidad para recibir ayudas públicas, la denegación de un permiso carcelario, la decisión de proporcionar un tratamiento médico, la elección de las rutas de patrullaje en una ciudad, etc.…”

Human Control and Discretion in AI-driven Decision-making in Government

“…This might have negative consequences for administrative decision making. Criado et al (2020) analyze the implications in decision-making processes supported by the use of an AI-based system and the effects in the discretionary power of public employees involved in its implementation. They found a positive impact of algorithms on the work and discretionary power of civil servants, as AI was viewed as a decision support system instead of a decision-making system.…”