OUP accepted manuscript

TL;DR: Zeng et al. as mentioned in this paper reviewed the rapid emergence of government applications of AI and provided a systematic review of proposed AI governance models and outlined their common components for the purpose of building a coherent, yet adaptable, AI Governance Framework and proposed a research agenda for policy and administration researchers.

TL;DR: This study explores the metaverse's suitability for digital public services, identifying 50 functional and 16 non-functional requirements, and assessing the suitability of 21 services for the EU's metaverse platform, highlighting unique government requirements and service suitability.

Abstract: Digital twin technology has great potential to transform urban planning. However, the governance aspects of city-scale digital twins (CDTs)— a virtual representation of urban environments —are understudied. This study bridges this knowledge gap by adopting a framework that scrutinizes the maturity stages of technology. We introduce the CITYSTEPS Maturity Model, a pioneering maturity framework tailored for CDTs, to assess all development stages of CDTs, including those utilizing artificial intelligence, and analyze the technology’s role in urban governance. We highlight the promise of CDTs in enhancing public participation in urban planning and addressing key smart city concerns, such as accountability and transparency. However, significant challenges remain, including public participation, public trust in privacy protection, and technical impediments like inadequate data integration, systems integration, and interoperability. There's also the pressing issue of social inclusion: the potential exclusion of marginalized groups, including those often overlooked in data collection, like the hidden homeless and informal sector workers. We propose CDTs should be designed with a human-centric approach, transparent and unbiased data collection and algorithms development, and be led by an adaptive regulatory framework. The CITYSTEPS Maturity Model lays out a framework to assess CDTs’ present state, forecast their future, and understand their governance implications, promoting more inclusive technology adoption.

TL;DR: It is argued that public service leaders must be attentive to ethical questions that converge around adopting “data-driven” techniques, including algorithmic decision-making, which will have implications for teaching public service ethics.

TL;DR: It is suggested that the choice of convenient, seemingly effective proxies for ground truth can be an important source of algorithmic bias in many contexts.

TL;DR: In the absence of a demonstrable intent to discriminate, the best doctrinal hope for data mining's victims would seem to lie in disparate impact doctrine as discussed by the authors, which holds that a practice can be justified as a business necessity when its outcomes are predictive of future employment outcomes, and data mining is specifically designed to find such statistical correlations.

TL;DR: The authors found that heavy Internet use is associated with increased participation in voluntary organizations and politics, and that people's interaction online supplements their face-to-face and telephone communication without increasing or decreasing it.

TL;DR: A characterisation of the Digital Twin is provided, identification of gaps in knowledge, and required areas of future research are identified: Perceived Benefits; Digital Twin across the Product Life-Cycle; Use-Cases; Technical Implementations; Levels of Fidelity; Data Ownership; and Integration between Virtual Entities; each of which are required to realise the Digital twin.