The perils and pitfalls of explainable AI: Strategies for explaining algorithmic decision-making

Governments look at explainable artificial intelligence's (XAI) potential to tackle the criticisms of the opaqueness of algorithmic decision-making with AI. Although XAI is appealing as a solution for automated decisions, the wicked nature of the challenges governments face complicates the use of XAI. Wickedness means that the facts that define...

On humans, algorithms and data

Purpose: The purpose of this paper is to introduce the papers in this special issue on humans, algorithms and data. The authors first set themselves the task of identifying the main challenges arising from the adoption and use of algorithms and data analytics in management, accounting and organisations in general, many of which have been...

The governance of platform development processes: A metaphor and a simulation model

Platform market competition has been extensively researched, but the governance of the platform development process prior to market launch has received little attention. We develop a system dynamics simulation model using the avalanche game as a metaphor for platform development. We describe a typical platform development process, and show...

Big data in the public sector: Uncertainties and readiness

Big data is being implemented with success in the private sector and science. Yet the public sector seems to be falling behind, despite the potential value of big data for government. Government organizations do recognize the opportunities of big data but seem uncertain about whether they are ready for the introduction of big data, and if...