Why should anyone listen to Timnit Gebru or Emily Blender after how consistently they've been wrong about everything? What insight or value do they bring to this?
Do you mean critical? They are expert in AI ethics, it’s pretty much their job to look for problems in the field. I’m not familiar with them but the posted article covers facts that are undeniable
Not straight factually wrong but they try to give the impression that the models performance in maths is not a big deal but have you looked at the kind of maths they are actually doing? It's way above your average human probably in the top 0.1% or 0.01%
check out the Frontier Math Tier 4 examples <a href="https://epoch.ai/frontiermath/tiers-1-4/benchmark-problems" rel="nofollow">https://epoch.ai/frontiermath/tiers-1-4/benchmark-problems which GPT 6.1 just got 100% at. Up from 5% for Claude 4.5 last year say. And probably 0% for me although I was quite good at maths at uni.
You’re absolutely right! In 2019, Timnit and Emily published a paper criticizing LLMs because of water usage / environmental impact, deception, and propagation of bias. They were completely wrong, and thankfully none of those criticisms apply to LLMs today!
You're right to push back! Honestly, calling someone with EA-adjacent ideas an effective altruist is an active lie! On the other hand, when AI companies claim that they have solved Millennium Prize problems, when really they plagiarized other academics' work, that's just an honest mistake.
You have a keen and insightful understanding of honesty!
Sigh. You're supposedly a PhD student. If you think LLMs are evil because of water usage, please, please do the least bit of due diligence and read a bit about it.
First, I never said LLMs were evil. Second, even though datacenters (and LLMs) consume relatively little water on an absolute scale, they can and often do overwhelm local water supplies, frequently in marginalized communities [1]. This is exactly what Timnit and Emily warned about [2]:
> When we perform risk/benefit analyses of language technology,
we must keep in mind how the risks and benefits are distributed,
because they do not accrue to the same people. On the one hand, it
is well documented in the literature on environmental racism that
the negative effects of climate change are reaching and impacting
the world’s most marginalized communities first.
Please, please do the least bit of due diligence and understand the discourse before condescending to other people.
Can you point to a single community or watershed where datacenter usage is even 10% of the agricultural usage in that same community? Or even just name a single community that's facing severe water shortages attributable to data centers?
OK - “often do” was wrong. There are cases where local communities’ water supplies was impacted by data center overconsumption, but they aren’t the norm [1].
A problem you’re not considering is that data centers, at least ones in current operation, consume mostly potable water, so you can’t compare agricultural use directly to data center usage. Doing some rough math:
Phoenix has about 150 data centers operational or planned. Let’s say 100 of those are operational. The average mid-sized data center uses 1.4 million liters / 0.37 million gallons of water per day for cooling servers. There is an additional 3x burden of water consumed to generate electricity. Let’s assume 70% of the data center water and 20% of the supplemental water consumed is potable [2]. We’re looking at 1.3 * 0.37 = 0.481 million gallons of potable water consumed per data center. So 100 * 365 * 0.481 = 17.5 billion gallons of potable water per year in the Phoenix region. That is a significant and growing fraction of the 110 billion gallons of potable water Phoenix produces per year.
These are using conservative estimates for potable water fraction.
[2] In 2023, 78% of Google data centers’ water consumption was potable. See “Alternative water sources”, <a href="https://www.gstatic.com/gumdrop/sustainability/google-2024-environmental-report.pdf" rel="nofollow">https://www.gstatic.com/gumdrop/sustainability/google-2024-e...
square_usual · · focus · HN ↗
dgellow · · focus · HN ↗
bitpush · · focus · HN ↗
Every technology has its negative parts, but breathlessly pointing out the negatives gets really old.
dgellow · · focus · HN ↗
tim333 · · focus · HN ↗
check out the Frontier Math Tier 4 examples <a href="https://epoch.ai/frontiermath/tiers-1-4/benchmark-problems" rel="nofollow">https://epoch.ai/frontiermath/tiers-1-4/benchmark-problems which GPT 6.1 just got 100% at. Up from 5% for Claude 4.5 last year say. And probably 0% for me although I was quite good at maths at uni.
tylerhou · · focus · HN ↗
E-Reverance · · focus · HN ↗
<a href="https://x.com/ByrneHobart/status/2105368471198380131" rel="nofollow">https://x.com/ByrneHobart/status/2105368471198380131
tylerhou · · focus · HN ↗
You have a keen and insightful understanding of honesty!
square_usual · · focus · HN ↗
Ok, clearly you don't know anything, moving on then.
tylerhou · · focus · HN ↗
<a href="https://www.reddit.com/r/mathematics/comments/1wauync/on_the_navierstokes_millennium_prize_problem/p8l7kmj/" rel="nofollow">https://www.reddit.com/r/mathematics/comments/1wauync/on_the...
scarmig · · focus · HN ↗
tylerhou · · focus · HN ↗
> When we perform risk/benefit analyses of language technology, we must keep in mind how the risks and benefits are distributed, because they do not accrue to the same people. On the one hand, it is well documented in the literature on environmental racism that the negative effects of climate change are reaching and impacting the world’s most marginalized communities first.
Please, please do the least bit of due diligence and understand the discourse before condescending to other people.
[1] <a href="https://cnr.ncsu.edu/news/2026/09/data-center-boom-water-resources/" rel="nofollow">https://cnr.ncsu.edu/news/2026/09/data-center-boom-water-res...
[2] <a href="https://dl.acm.org/doi/10.1145/3442188.3445922" rel="nofollow">https://dl.acm.org/doi/10.1145/3442188.3445922
scarmig · · focus · HN ↗
tylerhou · · focus · HN ↗
A problem you’re not considering is that data centers, at least ones in current operation, consume mostly potable water, so you can’t compare agricultural use directly to data center usage. Doing some rough math:
Phoenix has about 150 data centers operational or planned. Let’s say 100 of those are operational. The average mid-sized data center uses 1.4 million liters / 0.37 million gallons of water per day for cooling servers. There is an additional 3x burden of water consumed to generate electricity. Let’s assume 70% of the data center water and 20% of the supplemental water consumed is potable [2]. We’re looking at 1.3 * 0.37 = 0.481 million gallons of potable water consumed per data center. So 100 * 365 * 0.481 = 17.5 billion gallons of potable water per year in the Phoenix region. That is a significant and growing fraction of the 110 billion gallons of potable water Phoenix produces per year.
These are using conservative estimates for potable water fraction.
[1] <a href="https://www.reuters.com/sustainability/climate-energy/desert-storm-can-data-centres-slake-their-insatiable-thirst-water--ecmii-2025-12-17/" rel="nofollow">https://www.reuters.com/sustainability/climate-energy/desert...
[2] In 2023, 78% of Google data centers’ water consumption was potable. See “Alternative water sources”, <a href="https://www.gstatic.com/gumdrop/sustainability/google-2024-environmental-report.pdf" rel="nofollow">https://www.gstatic.com/gumdrop/sustainability/google-2024-e...
[3] <a href="https://www.politico.com/news/2026/05/08/georgia-data-centers-water-00909988" rel="nofollow">https://www.politico.com/news/2026/05/08/georgia-data-center...
peterdsharpe · · focus · HN ↗