Alternative federal budget 2026: Artificial intelligence | CCPA
- Bias Rating
- Reliability
35% ReliableAverage
- Policy Leaning
-8% Center
- Politician Portrayal
N/A
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Bias Score Analysis
The A.I. bias rating includes policy and politician portrayal leanings based on the author’s tone found in the article using machine learning. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral.
Sentiments
51% Positive
- Liberal
- Conservative
| Sentence | Sentiment | Bias |
|---|---|---|
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
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-100%
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100%
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Contributing sentiments towards policy:
60% : The new federal government has made several additional promises in this area, including a $100-million-per-year tax credit for businesses that adopt AI systems and a promise to expedite approvals for new data centres.55% : Precisely how their jobs are changed remains to be seen, and will be shaped by various factors, including regulation, collective agreements and cultural expectations.
54% : Montreal AI Ethics Institute, January 17, 2025, https://montrealethics.ai/the-death-of-canadas-artificial-intelligence-and-data-act-what-happened-and-whats-next-for-ai-regulation-in-canada.
50% : In part, that is due to the pervasive trend of successful Canadian tech companies being bought up or otherwise relocating south of the border -- a trend that is unlikely to change with the government's current tax credit approach to industrial strategy.
48% : Yet there are currently no rules or regulations governing young peoples' use of these tools, let alone support for teachers grappling with the implications.
37% : The Artificial Intelligence and Data Act was tabled in 2022 but was widely criticized as being inadequate and never passed into law.Blair Attard-Frost, "The Death of Canada's Artificial Intelligence and Data Act: What Happened, and What's Next for AI Regulation in Canada?"
*Our bias meter rating uses data science including sentiment analysis, machine learning and our proprietary algorithm for determining biases in news articles. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral. The rating is an independent analysis and is not affiliated nor sponsored by the news source or any other organization.
