Engadget42%

Microsoft's AI Drive Saw Its Carbon Emissions Grow By 25 Percent In 2025 4%

By Mariella Moon44%

7/10/2026, 3:44:27 AM

BS Summary: This article contains 23 faulty reasoning types, including Self-Serving Bias, Optimism Bias, and Ambiguity (Equivocation), with Negativity Bias as the most egregious example at 26.2% saturation with 108 hits. Analysis detected 847 faulty-reasoning hits from 412 analyzed words, generating a BS Score of 17.8% and a BS Rank of 4% (21,079 of 21,887 articles). This article is better (less manipulative) than 96.30% of the article peer group.

Microsoft's AI drive saw its carbon emissions grow by 25 percent in 2025 
The company said it wanted to be carbon negative by 2030. 
July 10, 2026 6:44 am EST 
Microsoft's carbon emissions grew 25 percent year over year in 2025, the company has revealed in its 2026 environmental sustainability report . 
The report covers the company's 2025 fiscal year and measures its progress against its 2020 baseline. 
Microsoft says this growth in emissions is mostly caused by the expansion of its investments in AI data center infrastructure. 
As GeekWire notes, Microsoft seems to be moving in the opposite direction of where it wants to go in order to achieve its goal. 
The company announced in 2020 that it plans to be carbon negative , or to remove more carbon from the atmosphere than it creates, by 2030. 
It only has four more years to get there. 
"While AI infrastructure is driving demand for energy, water, land, and materials, sustainability solutions are not scaling fast enough to meet demand," it admits. 
The company knows it has to refine its "strategies as conditions change, data improves, and tradeoffs become clearer." 
Microsoft says that it's not lowering its ambitions because AI demands are outpacing sustainability solutions. 
In which case, the company has a lot of work ahead of it. 
"We continue to really be focused around carbon negativity by 2030," Melanie Nakagawa, chief sustainability officer, told GeekWire . 
In addition to AI infrastructure buildouts, another reason why Microsoft reported a 25 percent yoy growth in carbon emissions, is because it stopped buying unbundled renewable energy certificates. 
One certificate signifies that an entity owns one megawatt-hour of zero-carbon electricity generated by a renewable source and delivered to the grid. 
Microsoft says its decision increased its reported emissions in the near term, but it enables the company to focus on adding all forms of carbon-free electricity to the grids where it operates rather than just on relying on certificates. 
"We believe this change will create more long-term sustainability benefits," it wrote. 
While it admits to emitting more carbon in its report, Microsoft also highlights its successes for the fiscal year of 2025. 
It says it matched 100 percent of its annual global electricity consumption with renewal energy. 
The company also replenished more water than it withdrew globally, which pushes the company closer towards achieving its goal to become water positive by 2030 . 
Article reasoning-pattern comparisonThis article: 6.8%Mariella Moon: 4.1%Engadget: 3.1%Confirmation Bias6.8%This article: 0.0%Mariella Moon: 1.2%Engadget: 1.4%Anchoring Bias0.0%This article: 5.8%Mariella Moon: 1.8%Engadget: 3.1%Availability Heuristic5.8%This article: 0.0%Mariella Moon: 0.9%Engadget: 1.1%Representativeness Heuristic0.0%This article: 0.0%Mariella Moon: 0.4%Engadget: 0.6%Hindsight Bias0.0%This article: 3.2%Mariella Moon: 3.1%Engadget: 2.6%Overconfidence Bias3.2%This article: 10.0%Mariella Moon: 7.7%Engadget: 6.0%Framing Effect10.0%This article: 0.0%Mariella Moon: 1.4%Engadget: 1.0%Loss Aversion0.0%This article: 0.0%Mariella Moon: 1.3%Engadget: 0.8%Status Quo Bias0.0%This article: 0.0%Mariella Moon: 0.0%Engadget: 0.2%Sunk Cost Effect0.0%This article: 15.5%Mariella Moon: 5.2%Engadget: 4.6%Optimism Bias15.5%This article: 8.0%Mariella Moon: 1.4%Engadget: 2.2%Pessimism Bias8.0%This article: 26.2%Mariella Moon: 4.8%Engadget: 7.0%Negativity Bias26.2%This article: 18.9%Mariella Moon: 2.3%Engadget: 1.6%Self-Serving Bias18.9%This article: 0.0%Mariella Moon: 0.4%Engadget: 0.4%Fundamental Attribution Error0.0%This article: 0.0%Mariella Moon: 0.0%Engadget: 0.2%Actor-Observer Bias0.0%This article: 0.0%Mariella Moon: 0.2%Engadget: 0.2%In-Group Bias0.0%This article: 0.0%Mariella Moon: 0.3%Engadget: 0.1%Out-Group Homogeneity Bias0.0%This article: 10.0%Mariella Moon: 2.0%Engadget: 1.9%Halo Effect10.0%This article: 0.0%Mariella Moon: 0.3%Engadget: 0.2%Horn Effect0.0%This article: 0.0%Mariella Moon: 0.0%Engadget: 0.0%Dunning-Kruger Effect0.0%This article: 2.2%Mariella Moon: 0.4%Engadget: 1.8%Recency Bias2.2%This article: 0.0%Mariella Moon: 0.0%Engadget: 0.4%Primacy Effect0.0%This article: 0.0%Mariella Moon: 0.0%Engadget: 0.1%Blind-Spot Bias0.0%This article: 0.0%Mariella Moon: 0.0%Engadget: 0.2%Ad Hominem0.0%This article: 5.8%Mariella Moon: 0.0%Engadget: 0.3%Straw Man5.8%This article: 4.6%Mariella Moon: 7.2%Engadget: 4.9%Appeal to Authority4.6%This article: 3.6%Mariella Moon: 0.9%Engadget: 1.2%False Dilemma3.6%This article: 0.0%Mariella Moon: 0.6%Engadget: 1.0%Slippery Slope0.0%This article: 0.0%Mariella Moon: 0.2%Engadget: 0.1%Circular Reasoning0.0%This article: 5.8%Mariella Moon: 3.2%Engadget: 5.3%Hasty Generalization5.8%This article: 0.0%Mariella Moon: 0.2%Engadget: 0.3%Red Herring0.0%This article: 0.0%Mariella Moon: 0.3%Engadget: 0.9%Bandwagon0.0%This article: 3.2%Mariella Moon: 2.1%Engadget: 3.2%Appeal to Emotion3.2%This article: 7.8%Mariella Moon: 2.0%Engadget: 1.0%Begging the Question7.8%This article: 12.6%Mariella Moon: 2.2%Engadget: 2.7%Post Hoc (False Cause)12.6%This article: 0.0%Mariella Moon: 0.6%Engadget: 0.1%Tu Quoque0.0%This article: 5.8%Mariella Moon: 0.4%Engadget: 0.6%Burden of Proof5.8%This article: 0.0%Mariella Moon: 0.1%Engadget: 0.1%Appeal to Nature0.0%This article: 6.3%Mariella Moon: 0.0%Engadget: 0.2%Composition/Division6.3%This article: 0.0%Mariella Moon: 1.4%Engadget: 2.3%Anecdotal0.0%This article: 0.0%Mariella Moon: 0.0%Engadget: 0.0%No True Scotsman0.0%This article: 15.3%Mariella Moon: 2.9%Engadget: 2.4%Ambiguity (Equivocation)15.3%This article: 0.0%Mariella Moon: 0.0%Engadget: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Mariella Moon: 0.0%Engadget: 0.2%Middle Ground0.0%This article: 0.0%Mariella Moon: 0.0%Engadget: 0.1%Personal Incredulity0.0%This article: 9.5%Mariella Moon: 0.3%Engadget: 0.2%Special Pleading9.5%This article: 0.0%Mariella Moon: 0.5%Engadget: 0.1%Genetic Fallacy0.0%This article: 14.1%Mariella Moon: 3.8%Engadget: 2.9%Unattributed Quote14.1%This article: 4.6%Mariella Moon: 1.7%Engadget: 1.2%Quote-first Misdirection4.6%This article: 0.0%Mariella Moon: 1.9%Engadget: 7.5%Biased Writer Voice0.0%This article: 0.0%Mariella Moon: 0.6%Engadget: 1.0%Indoctrination0.0%This article: 0.0%Mariella Moon: 0.0%Engadget: 0.1%Politically Left Leaning Bias0.0%This article: 0.0%Mariella Moon: 0.0%Engadget: 0.0%Politically Right Leaning Bias0.0%This article: 0.0%Mariella Moon: 9.6%Engadget: 4.0%Attempt to Sell a Product or S…0.0%

412 words analyzed.

Speakers

3speakers70%attributed speech125writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 13 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageMicrosoft • 11 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageMicrosoft • 22 words • 100.0% coverageMicrosoft • 16 words • 0.0% coverageMicrosoft • 20 words • 0.0% coverageGeekWire • 24 words • 0.0% coverageMicrosoft • 26 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageMicrosoft • 24 words • 100.0% coverageMicrosoft • 18 words • 0.0% coverageMicrosoft • 15 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageMelanie Nakagawa • 19 words • 100.0% coverageWriter's voice • 28 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageMicrosoft • 39 words • 0.0% coverageMicrosoft • 12 words • 100.0% coverageWriter's voice • 21 words • 0.0% coverageMicrosoft • 15 words • 0.0% coverageMicrosoft • 26 words • 0.0% coverage
Selected voice

GeekWire

100%flagged-word coverage
24 attributed words8.4% of attributed speech78% writer coverage

No manipulation-pattern hits were found in this speaker's attributed words or the writer's voice.

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.