How the Global South Can Chart a New Path for AI
- Bias Rating
- Reliability
10% ReliableLimited
- Policy Leaning
-56% Medium Left
- 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
18% Positive
- Liberal
| Sentence | Sentiment | Bias |
|---|---|---|
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
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Contributing sentiments towards policy:
58% : An AI managing a nation's electricity grid could optimize purely for cost, or it could be targeted to balance equitable access, renewable energy integration, and climate resilience simultaneously.57% : A humanitarian practitioner who spent over 20 years at the United Nations, Walther currently works with the UN in Morocco and Sunway University's Center for Planetary Health in Malaysia on developing national blueprints for prosocial AI that are designed, delivered, and deployed to serve people and planet.
56% : Does this loan algorithm perpetuate discrimination?
55% : What Is the Problem? Three dominant AI paradigms have emerged: the United States' market-driven model, China's state-coordinated approach, and the European Union's regulatory framework.
55% : In regions where strong communal ties form the primary social safety net, this algorithmic isolation carries existential consequences.
*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.