Artificial Intelligence (AI) Adoption in Canadian Local Governments: Opportunities, Challenges and Factors of Innovation
Notice bibliographique
Résumé
Artificial Intelligence (AI) has become increasingly prevalent in local governments worldwide, contributing to improved internal administrative processes and service delivery. Local governments serve as the frontline of citizen interactions and are vital to economic development and sustainability, whereas they face resource limitations and struggle to manage AI's high risks. Canada presents an interesting case study, as it is recognized as a leader in AI and invested heavily in AI firms, whereas Canadian governments are generally considered risk-averse. In this thesis, I empirically investigate AI adoption in Canadian local governments with the aim of understanding the aspects that play a crucial role in the successful adoption of AI.I begin by comparing and contrasting Information Technology (IT) and AI adoption in local governments, providing an opportunity to identify whether IT adoption can provide insights into AI adoption. I conclude that although AI presents unique issues, AI and IT adoption share similarities in their promises to local governments and pitfalls around their resource requirements and political influence. In Chapter 3, I present a survey of 28 representatives directly involved in AI projects in Canadian local governments. I highlight positive perceptions of the benefits of AI but also identify challenges related to resources, training, expertise, data and computing infrastructure. In Chapter 4, I examine the innovation factors that contribute to the success of AI adoption in the City of Edmonton, Alberta, Canada, a leader in AI among Canadian cities. I develop a framework that consists of internal and external factors specific to AI innovation in local governments then I apply these factors to Edmonton. The study highlights six internal factors, including AI-specific resources, internal needs, risk-taking culture, collaboration and knowledge sharing, upper management support, and AI process fit, and three external factors encompassing the innovation ecosystem, environmental drivers, and AI regulation and ethics.This thesis contributes to the research on and praxis of local government adoption of AI in several ways. First, it uncovers differences and similarities between traditional IT systems and AI systems in local governments, providing lessons for AI adoption. Second, the thesis offers the first empirical investigation on the current practice of AI in Canadian local government and identifies the challenges they face in adopting AI, providing insights for informed policy decisions and responsible AI implementation. Third, it introduces a framework for measuring AI innovation in the public sector, which aids future analysis of AI innovation and helps local governments understand the necessary conditions for AI innovation. Last, the thesis provides empirical evidence by analyzing AI practices in the City of Edmonton, showcasing how these innovation factors manifest in practice. These findings should guide future AI implementation in other local governments and contribute to research on AI adoption in the public sector
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».