Missed opportunities in AI regulation: lessons from Canada’s AI and data act

We interrogate efforts to legislate artificial intelligence (AI) through Canada’s Artificial Intelligence and Data Act (AIDA) and argue it represents a series of missed opportunities that so delayed the Act that it died. We note how much of this bill was explicitly tied to economic development and i...

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Main Authors: Ana Brandusescu, Renée E. Sieber
Format: Article
Language:English
Published: Cambridge University Press 2025-01-01
Series:Data & Policy
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Online Access:https://www.cambridge.org/core/product/identifier/S2632324925000173/type/journal_article
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author Ana Brandusescu
Renée E. Sieber
author_facet Ana Brandusescu
Renée E. Sieber
author_sort Ana Brandusescu
collection DOAJ
description We interrogate efforts to legislate artificial intelligence (AI) through Canada’s Artificial Intelligence and Data Act (AIDA) and argue it represents a series of missed opportunities that so delayed the Act that it died. We note how much of this bill was explicitly tied to economic development and implicitly tied to a narrow jurisdictional form of shared prosperity. Instead, we contend that the benefits of AI are not shared but disproportionately favour specific groups, in this case, the AI industry. This trend appears typical of many countries’ AI and data regulations, which tend to privilege the few, despite promises to favour the many. We discuss the origins of AIDA, drafted by Canada’s federal Department for Innovation Science and Economic Development (ISED). We then consider four problems: (1) AIDA relied on public trust in a digital and data economy; (2) ISED tried to both regulate and promote AI and data; (3) Public consultation was insufficient for AIDA; and (4) Workers’ rights in Canada and worldwide were excluded in AIDA. Without strong checks and balances built into regulation like AIDA, innovation will fail to deliver on its claims. We recommend the Canadian government and, by extension, other governments invest in an AI act that prioritises: (1) Accountability mechanisms and tools for the public and private sectors; (2) Robust workers’ rights in terms of data handling; and (3) Meaningful public participation in all stages of legislation. These policies are essential to countering wealth concentration in the industry, which would stifle progress and widespread economic growth.
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spelling doaj-art-7a95561ee6bc478a83d6eeb80c50d25a2025-08-20T03:49:37ZengCambridge University PressData & Policy2632-32492025-01-01710.1017/dap.2025.17Missed opportunities in AI regulation: lessons from Canada’s AI and data actAna Brandusescu0https://orcid.org/0000-0003-1672-5244Renée E. Sieber1Department of Geography, Faculty of Science, McGill University, Montreal, CanadaDepartment of Geography, Faculty of Science, McGill University, Montreal, CanadaWe interrogate efforts to legislate artificial intelligence (AI) through Canada’s Artificial Intelligence and Data Act (AIDA) and argue it represents a series of missed opportunities that so delayed the Act that it died. We note how much of this bill was explicitly tied to economic development and implicitly tied to a narrow jurisdictional form of shared prosperity. Instead, we contend that the benefits of AI are not shared but disproportionately favour specific groups, in this case, the AI industry. This trend appears typical of many countries’ AI and data regulations, which tend to privilege the few, despite promises to favour the many. We discuss the origins of AIDA, drafted by Canada’s federal Department for Innovation Science and Economic Development (ISED). We then consider four problems: (1) AIDA relied on public trust in a digital and data economy; (2) ISED tried to both regulate and promote AI and data; (3) Public consultation was insufficient for AIDA; and (4) Workers’ rights in Canada and worldwide were excluded in AIDA. Without strong checks and balances built into regulation like AIDA, innovation will fail to deliver on its claims. We recommend the Canadian government and, by extension, other governments invest in an AI act that prioritises: (1) Accountability mechanisms and tools for the public and private sectors; (2) Robust workers’ rights in terms of data handling; and (3) Meaningful public participation in all stages of legislation. These policies are essential to countering wealth concentration in the industry, which would stifle progress and widespread economic growth.https://www.cambridge.org/core/product/identifier/S2632324925000173/type/journal_articleartificial intelligenceintellectual propertyshared prosperitygovernmentlabour
spellingShingle Ana Brandusescu
Renée E. Sieber
Missed opportunities in AI regulation: lessons from Canada’s AI and data act
Data & Policy
artificial intelligence
intellectual property
shared prosperity
government
labour
title Missed opportunities in AI regulation: lessons from Canada’s AI and data act
title_full Missed opportunities in AI regulation: lessons from Canada’s AI and data act
title_fullStr Missed opportunities in AI regulation: lessons from Canada’s AI and data act
title_full_unstemmed Missed opportunities in AI regulation: lessons from Canada’s AI and data act
title_short Missed opportunities in AI regulation: lessons from Canada’s AI and data act
title_sort missed opportunities in ai regulation lessons from canada s ai and data act
topic artificial intelligence
intellectual property
shared prosperity
government
labour
url https://www.cambridge.org/core/product/identifier/S2632324925000173/type/journal_article
work_keys_str_mv AT anabrandusescu missedopportunitiesinairegulationlessonsfromcanadasaianddataact
AT reneeesieber missedopportunitiesinairegulationlessonsfromcanadasaianddataact