Video stats
Public counts from the last refresh.
- Views
- 95,166
- Likes
- 12,066
- Comments
- 261
- Shares
- 1,142
- Saves
- 2,315
- Engagement
- 14.15%
- Duration
- 150s
- Posted
- Jul 29, 2026
Video insights
@distilledscience's TikTok video "AI Water use is weirdly polarizing: The people who hate AI like to talk about how it's destroying the environment, often quoting the one bottle per prompt statistic, and the AI supporters tend to write the whole thing off as nothing compared to real water sucks, like beef or corn. Or golf. But, as per usual, the issue NEEDS NUANCE! A normal text prompt can have a tiny direct cooling footprint while billions of requests, expanding infrastructure and electricity generation create a much larger aggregate footprint. National totals can also look small while one facility creates serious pressure on a particular town, aquifer or water system. The numbers change depending on whether we count withdrawal or consumption; direct cooling or electricity; blue water or rain; averages or peaks; measurements or projections. It’s what lets each side with apparently contradictory claims each sound credible. Pay attention: Google's use of median vs. mean is tricky. Two precision notes for this video: The 0.04% national comparison is derived by dividing LBNL’s modeled 2023 data-center consumption by an older national blue-water-footprint estimate Microsoft’s paper says 31–52% less blue water in its abstract, while its main results table reports 31–48% under grid electricity. The table is the safer figure. Morgan Stanley’s 1.068-trillion-liter number is a 2028 base-case projection for global AI-data-center cooling and electricity—not a measurement, withdrawal estimate or all-data-center total. The point isn’t that AI is harmless or uniquely catastrophic. It’s that we need comparable, facility-level disclosure with honest boundaries. Peer-reviewed sources and DOIs: Li et al.: DOI 10.1145/3724499 Mekonnen & Hoekstra: DOI 10.5194/hess-15-1577-2011 Rushforth & Ruddell: DOI 10.5194/hess-22-3007-2018 Lei et al.: DOI 10.1016/j.resconrec.2025.108310 Alissa et al.: DOI 10.1038/s41586-025-08832-3 Additional sources: LBNL-2001637; arXiv:2607.02531; Google’s 2025 Gemini environmental analysis; DOE FEMP; USDA EIB-99; Morgan Stanley projection reported by *The Economic Times*. #AI #Water #DataCenters #Sustainability" has 95,166 views, 12,066 likes, 261 comments, 1,142 shares in the public metrics captured by this index. That is an engagement rate of 14.15% (likes, comments and shares over views). It was posted 3 months ago and runs 2 minutes 30 seconds. It has been saved 2,315 times.
Data as of Oct 20, 2026 (UTC), from the last public refresh captured by this index.
Avisha |🧬Scientist Mythbuster
@distilledscience
🧬Your Skeptical Scientist: Distilling Truth from Trends🤦♂️ #Optimalist 💪 - NYC Business: 📧 [email protected]
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Frequently asked questions
- How many views does this TikTok video have?
- The capture indexed here reports 95,166 views, 12,066 likes and 261 comments.
- Who posted this TikTok video?
- It was posted by @distilledscience, who is linked from this page.
- What is this TikTok video's engagement rate?
- Across the captured metrics the engagement rate is 14.15% (likes + comments + shares over views).
- When was this TikTok video posted?
- It was posted on 2026-07-29, 3 months ago.
- What hashtags are used in this video?
- The capture links 2 hashtags, starting with #ai.
- How long is this TikTok video?
- The captured clip runs 2 minutes 30 seconds.