Bonilla, George J.J. and Dietlmeier, Simon Frederic and Urmetzer, Florian (2023): Multi-Stakeholder Ecosystem for Standardization of AI in Industry.
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Abstract
The increasing governmental interest in fostering the Artificial Intelligence sector in Britain has rapidly increased; the United Kingdom has recognised AI’s significance and incorporated it into its policy frameworks.
The UK’s Industrial Strategy framework of 2017 emphasises the need for investment, research, and collaboration in this field, and these effortsraise a significant question: How do Regional AI SMEs have access to framework, networks and resources?
In line with this research endeavour, the research focuses on how three AI SMEs located in different regions of Britain are influenced by the introduction of those policy frameworks in their business operations.
By examining these aspects, this research provides insights into the impact of the domestic AI policy framework on Britain’s AI SMEs. It focuses on how policies can shape the development and adoption of such frameworks in SMEs and how these frameworks influences might differ from one SME to another, by utilising two frameworks:
1. The Stakeholder Assessment Criterion, defines three models: ‘Statist-model’, ‘Laissez-Faire model’ and ‘Academia Model’.
2. The Governance Matrix.
These two frameworks aided this research to in comprehending the current British AI ecosystem policy developments influencing the three AI SMEs. This research was propelled by an inductive reasoning process and qualitative data collection methodology.
Three case studies were conducted: one in a company based in London, England’s capital; another in Reading, located in Berkshire; and a third in Sheffield, situated in the South Yorkshire County of northern England. These observations took place between June 12 and July 14. Several interviews with stakeholders from these companies were conducted, providing the opportunity to scrutinise and cross-reference the recent AI policy framework developments implemented by the British Parliament. Furthermore, the study engaged regional and domestic policymakers in interviews to comprehend the external factors influencing these companies
Item Type: | MPRA Paper |
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Original Title: | Multi-Stakeholder Ecosystem for Standardization of AI in Industry |
Language: | English |
Keywords: | Standardization; Multi-Stakeholder; Forum; Artificial Intelligence; Policy |
Subjects: | A - General Economics and Teaching > A1 - General Economics B - History of Economic Thought, Methodology, and Heterodox Approaches > B2 - History of Economic Thought since 1925 C - Mathematical and Quantitative Methods > C8 - Data Collection and Data Estimation Methodology ; Computer Programs F - International Economics > F5 - International Relations, National Security, and International Political Economy Y - Miscellaneous Categories > Y4 - Dissertations (unclassified) |
Item ID: | 120619 |
Depositing User: | Mr Simon Frederic Dietlmeier |
Date Deposited: | 12 Apr 2024 14:17 |
Last Modified: | 12 Apr 2024 14:17 |
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URI: | https://mpra.ub.uni-muenchen.de/id/eprint/120619 |