From diagnosis to patient scheduling, AI is increasingly being considered across different clinical applications. Despite increasingly powerful clinical AI, uptake into actual clinical workflows remains limited. One of the major challenges is developing appropriate trust with clinicians. In this paper, we investigate trust in clinical AI in a wider perspective beyond user interactions with the AI. We offer several points in the clinical AI development, usage, and monitoring process that can have a significant impact on trust. We argue that the calibration of trust in AI should go beyond explainable AI and focus on the entire process of clinical AI deployment. We illustrate our argument with case studies from practitioners implementing clinical AI in practice to show how trust can be affected by different stages in the deployment cycle.
This paper reveals how the automatising of protocols ignited a public conflict between Dutch banks and their Small and Medium-sized Enterprise (SME) clients in the years after the Global Financial Crisis. The bank’s “infirmary departments” for Financial Restructuring and Recovery (FR&R) were accused of (mal)treating SMEs. The conflict resulted in no formal regulatory or legal change despite public support. Instead, the banks created self-regulation to improve communication with SMEs, leading to shifts in governing FR&R for SMEs. This way, the banks mitigated significant negative symptoms of automation and solved the conflict with the SMEs while keeping FR&R and ongoing automation intact. The research uses an interdisciplinary analytical framework to understand national financial conflicts in a digitalised (business) world. It contributes to the theory of institutionalising values in discursive contests between action fields. The paper highlights the material and causes of normative conflicts of interest among critical actors in established public-private networks through discourse analysis and process tracing.
Over the past decade, a growing number of artists and critical practitioners have become engaged with algorithms. This artistic engagement has resulted in algorithmic theatre, bot art, and algorithmic media and performance art of various kinds that thematise the dissemination and deployment of algorithms in everyday life. Especially striking is the high volume of artistic engagements with facial recognition algorithms, trading algorithms and search engine algorithms over the past few years.The fact that these three types of algorithms have garnered more responses than other types of algorithms suggests that they form a popular subject of artistic critique. This critique addresses several significant, supra-individual anxieties of our decade: socio- political uncertainty and polarisation, the global economic crisis and cycles of recession, and the centralisation and corporatisation of access to online information. However, the constituents of these anxieties — which seem to be central to our experience of algorithmic culture — are rarely interrogated. They, therefore, merit closer attention.This book uses prominent artistic representations of facial recognition algorithms, trading algorithms, and search algorithms as the entry point into an exploration of the constituents of the anxieties braided around these algorithms. It proposes that the work of Søren Kierkegaard—one of the first theorists of anxiety—helps us to investigate and critically analyse the constituents of ‘algorithmic anxiety’.
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