Blazsek, V. orcid.org/0000-0002-0663-9548 (2025) Written Evidence by Dr Virág Blazsek (AIFS0014) to the UK Parliament Treasury Committee AI in financial services: Chief proposal - The UK should hold a referendum on the fundamental questions of AI. Report. UK Parliament
Abstract
The risks related to artificial intelligence (AI), and in particular Generative AI (GenAI) should be taken extremely seriously. A major issue is that very fundamental (philosophical) questions of AI and GenAI remain open. And how can we develop a regulatory framework that would be capable of mitigating the related risks without first addressing those fundamental questions? The scope of this issue goes beyond financial regulation. Different answers to those fundamental questions lead to fundamentally different regulatory approaches and solutions. Therefore, in line with the principle of democratic authorisation, it would be logical, and in multiple ways beneficial for the United Kingdom (UK), to hold a referendum on questions of this magnitude, capable of reshaping our economy and society, having a most fundamental impact on people’s lives and livelihoods.
Metadata
Item Type: | Monograph |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © UK Parliament 2025. This is an open access article under the terms of the Open Parliament Licence v3.0, which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Education, Social Sciences and Law (Leeds) > School of Law (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 23 Jun 2025 14:23 |
Last Modified: | 23 Jun 2025 14:23 |
Published Version: | https://committees.parliament.uk/work/8901/ai-in-f... |
Status: | Published |
Publisher: | UK Parliament |
Identification Number: | https://committees.parliament.uk/work/8901/ai-in-financial-services/publications/written-evidence/?page=1 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:227982 |
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Licence: Open Government Licence (v3)