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Telecom workers call for restrictions over use of artificial intelligence
The alliance says AI is monitoring workers, masking offshore accents and could worsen automation-driven job losses across the sector.
- On April 30, The Canadian Telecommunications Workers Alliance appeared before the House of Commons Standing Committee on Industry and Technology in Ottawa, demanding restrictions on artificial intelligence use in the sector.
- Unifor telecommunications sector director Roch Leblanc cited the loss of roughly 20,000 jobs over 15 years due to automation and offshoring, warning that AI-based monitoring intensifies worker stress and psychological strain.
- The alliance highlighted that companies use AI to mask accents of offshore agents, a practice they claim could "mislead Canadians" into believing jobs remain in the country rather than being offshored.
- Artificial Intelligence Minister Evan Solomon said on Monday the government's promised national AI strategy will consider labor market impacts, responding to the alliance's calls for stronger worker protections.
- Research advisor Nathalie Blais of the Canadian Union of Public Employees advocated for a permanent federal working group to ensure AI implementation serves "the common good" rather than eliminating jobs or misleading workers.
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Telecom workers say AI being used to monitor employees, disguise accents of offshore agents
Telecommunications workers are calling for government restrictions on the use of artificial intelligence in the sector, suggesting the technology is being used to monitor workers and disguise the accents of overseas call centre workers.
·Canada
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The Toronto Star+18 Reposted by 18 other sources
Telecom workers call for restrictions over use of artificial intelligence
MONTREAL - Telecommunications workers are calling for government restrictions on the use of artificial intelligence in the sector, suggesting the technology is being used to monitor workers and disguise the
·Toronto, Canada
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Total News Sources20
Leaning Left18Leaning Right0Center2Last UpdatedBias Distribution90% Left
Bias Distribution
- 90% of the sources lean Left
90% Left
L 90%
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