The ugly truth behind ChatGPT: AI is guzzling resources at planet-eating rates | Mariana Mazzucato
- Bias Rating
Center
- Reliability
55% ReliableFair
- Policy Leaning
N/A
- Politician Portrayal
N/A
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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
7% Positive
- Liberal
- Conservative
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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:
63% : Google's global datacentre and Meta's ambitious plans for a new AI Research SuperCluster (RSC) further underscore the industry's energy-intensive nature, raising concerns that these facilities could significantly increase energy consumption.56% : It is hardly news that the tech bubble's self-glorification has obscured the uglier sides of this industry, from its proclivity for tax avoidance to its invasion of privacy and exploitation of our attention span.
56% : Making disclosure of environmental practices and impacts a condition for government support could ensure greater transparency and accountability.
52% : Trying to achieve one climate goal of limiting our dependence on fossil fuels can compromise another goal, of ensuring everyone has a safe and accessible water supply.
51% : Moreover, when significant energy resources are allocated to tech-related endeavours, it can lead to energy shortages for essential needs such as residential power supply.
44% : Additionally, as these companies aim to reduce their reliance on fossil fuels, they may opt to base their datacentres in regions with cheaper electricity, such as the southern US, potentially exacerbating water consumption issues in drier parts of the world.
39% : This will only get worse as households move away from using fossil fuels and rely more on electricity, putting even more pressure on the National Grid.
*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.