> in part because Google fired two of the authors, Timnit Gebru
I remember being angry about this situation when I first saw it on social media, until I read the details: This person submitted a list of demands to her employer and said that if they weren’t met, she quit. Google wasn’t going to meet her demands so they considered it acceptance of her resignation. There has been a movement trying to debate whether it was a firing or resignation ever since.
The original paper they published gets recirculated every year or two as some landmark history of AI safety, but as other commenters have noted it wasn’t really a great paper nor was it groundbreaking at the time. If not for the controversy surrounding the resignation/firing (depending on your POV), I don’t think it would have been notable.
I think part of it is she had excellent PR skills and a dedicated fan base. I was at Google when she quit, working in ML, and hadn't heard of her until the story broke. I remember there were a large number of Memegen posts about it, but no one I spoke with knew about her, so I assumed it was brigading.
I think she's since since lost a lot of her allure, especially when she didn't change her mind when the facts about the AI water usage changed 1000x
What exactly are the facts about AI water usage? I have trouble separating hysteria from reality but most of what I see still claims water usage is enormous
The hysteria around water usage rests on people not knowing the scale of industrial civilization. First thing to do is compare any estimate of data center water usage with the water usage of almond farming. Or, if you want to focus on individual consumer choices, the water footprint of eating a hamburger.
> Or, if you want to focus on individual consumer choices, the water footprint of eating a hamburger.
To drive this point home: if every American ate exactly one less hamburger per year, it would entirely offset the annual water consumption of all US datacenters (including, therefore, the water footprint of AI).
> if every American ate exactly one less hamburger per year
I fear that you have unwittingly led us further into the inevitable Environmental Hamburger-Cost Continuum.
Wherein we will use EHCC units to inform the hamburger voters about a) the nobility of even the smallest hamburgerian sacrifice, and b) the gentle, loving hand of industrialisation.
I would expect within the same order of magnitude. Worst-case, skipping a burger once a month instead of once a year is hardly some insurmountable sacrifice (and I say that as a fatass who loves himself a good burger).
I prefer to use the hospital analogy. Locally, the water concerns are a big deal but a lot of people in my community are riled up about the potential need for diesel backup generators because of the noise pollution. They are not wrong and it's good to consider, but they are at this point grasping for reasons that would not (and have not) been concerns for other large footprint projects like hospitals with similar infrastructure needs.
Here in Reno the anti-datacenter crowd has been extending that tolerance to the local casinos and golf courses (of both of which there are many more than we arguably need). If the choice is between running servers to keep the Internet going v. letting poor schmucks get swindled out of their money on the slots, I'm picking the servers over the slots any day.
Breaking it down this way is a great way to minimize the numbers so that it appears reasonable.
See? Middle-Eastern investors are growing alfalfa in the western desert using legal allotments of water! That is so much worse than what we’re doing! Go after them!
They can both be using an egregious amount of water for silly purposes.
The other part of the water debate is also the pollution different systems create. Many data centres went in with the promise of closed-loop systems but changed half-way through construction and couldn’t be stopped.
I think it’s more complicated than, “they’re wrong, it’s just hype.”
Putting things into perspective is not minimising the problem. We literally have to do this to prioritise where our efforts can be useful.
Your argument makes sense if ai datacenters were using something close to like alfafa farming but the difference between them is soo massive it does not make sense.
Reducing pollution is a much better problem to fight for
I am guessing (not asserting) that there is a sort of cap on water used for agriculture. It's possible we've already reached it. (?)
So, on the matter of scale: there likely isn't a cap on water use of these datacenters. Both the heat emission and usage levels for these systems will likely go up unless there is a fundamental technical breakthrough.
On the matter of utility: As a sibling of GP mentioned, the utility of food is clear.
On the matter of polution: I am not remotely read on waste water and contamination due to industrial agriculture. Is this also something where the judgmental scale is tipped in favor of food production vs cooling systems?
what is the utility of alfaalfa? Because as it stands it's essentially just a way to export enormous amounts of water from a place where there's little (California) to a place where there's none (the Arabian peninsula).
Your alfalfa is a red herring. Agriculture encompasses more than a specific crop that we can always legislate against production for export. The data centers will not go away and the utility of the "AI" they are to enable is as of today dubious.
> This is bullshit to be charitable.
What is bullshit is sockpuppets shilling for the very few who have bet the 'farm' on this and want return on their investment, the wellbeing of society be damned.
Everything we do has side effects. Some have more than others; in the case of water, even heavy users of AI have a relatively small AI water footprint compared other things they do.
There are ideological perspectives--another comment in this chain declares that anything that an LLM does has zero value, purely by virtue of being from an LLM. There's not much to discuss there: maybe I find alfalfa useless and LLMs provide a lot of value, maybe you do the opposite. Short of violence, either immediate or delegated, the best way to resolve this conflict is to incorporate costs for resources like water appropriately (accounting for externalities), and let market participants bid to determine who gets access to it.
Datacenter owners are highly likely to find this a reasonable process, because they believe that what they are investing in and operating will provide a great deal of value on the market. And other industries (like your alfalfa) are far more likely to throw a fit at this process.
Or if you think alfalfa farms have fundamental, deep-seated water rights that don't extend to data centers, then data center operators can just purchase water from alfalfa farmers, and everyone involved will eagerly make that trade.
Well the other thing is that agricultural uses are generally on a different scale and use different sources. And at least you can eat almonds and alfalfa. Probably more useful than asking an LLM to autocomplete your homework. Depending on your needs.
Even amongst municipal water usage, it seems hard to figure out how much DC usage factors in to other uses because often they’re not required, and therefore don’t, disclose their usage.
All I’m saying is that it’s not a closed case and not everyone complaining about DC water usage is a Russian propaganda bot.
Nice false dichotomy you got there there, might as well calculate the entire water usage for a a single GPU in the supply chain too. Something tells me one is extremely worse than the other when you account for all the water that's used in a single supply chain for high end electronics, but if you want to plop the measuring stick where ever along the whole pony show that makes you look better people will notice.
Also to compare growing food with the totally optional, not useful in the slightest, LLMs that somehow demand local populaces bend to their will for reasons that never seem to benefit them is just bonkers level of self-blinding when it comes to populations absolutely despising big tech, big tech leadership, and big tech practices.
This mania might finally cause the software industry to become a highly regulated with licenses similar to that of other engineering disciplines due to amount of optional destruction they have decided to unleash upon on the planet in such a short time frame.
let's compare ai water usage with something even more useless, water leaking out of pipes. the United States currently loses about 2 trillion gallons of water annually to leaking pipes. this is in comparison to around 230 billion gallons used by data centers.
we're literally dumping several times the amount of water used by data centers onto the ground for no benefit at all. oddly enough I haven't seen any protests about this despite how concerned everyone is about water usage.
How do you know this doesn't suffer from Gell-Mann Amnesia? The first version had so many glaring errors that have been "corrected" (removed), and I don't have the energy to comb through this one.
I am highly skeptical of layperson debunking like this.
The thing that is off putting about how he uses rhetoric is that it feels like and-you deflection (tu quoque).
> Claim that a data center is using 1000x as much water as a city of 88,000 people, where it’s actually using about 0.22x as much water as the city, and only 3% of the municipal water system the city relies on. She’s off by a factor of 4500. This is the single largest error in any popular book that I’ve found on my own, and to my knowledge I’m the first person to notice it.
Yeah, she might be wrong. But a data center also using 1/5th of the water consumption of an 88k person city should still be what are debating. We also have a base rate fallacy, we don't know know how well or how poorly they are using water. Nearly all criticisms of AI data center criticisms boil (no pun intended) down to yeah, but what about almonds or rice or xyz. That isn't a healthy way to adjust how we talk about data center water consumption.
It is a classic debate tactic. Someone makes an argument, then buttresses that argument with a number. You attack the number, pretending that you didn't just correct the number, but also invalidate the original argument. We shouldn't be using these tactics to talk about the tragedy of the commons.
I worked for a hyperscaler, I poked around a bit about water usage both internally and externally and it wasn't good. There was little to no thought other than, "we can pay X to have water delivered, doesn't matter if it sourced responsibly." (to glibly paraphrase, company policy is to never write the honest part down)
Look at how hard Google fought to not have water data released in The Dalles Oregon for their DC there. Many DCs are supplied by water that is meant for humans, sourced from aquifers that took hundreds of thousands of years to fill, that are being depleted faster than they are filled, already.
I think AI is powerful tool, but we still can't give DC expansion a pass.
I'd love to see DCs scaled with renewables, they would throttle down and run slower at night. The abstraction that power is available at whatever rate you want it is an expensive myth at scale.
I defer plugging in my electric car until 10am so I know that my neighbors solar arrays are charging my car.
In Seattle, every watt saved is water saved since we are blessed with hydro.
> But a data center also using 1/5th of the water consumption of an 88k person city should still be what are debating.
Why, when that's such a minuscule amount of water in the grand scheme of things? Why focus our energy there? Why not spend that energy on the myriad many-orders-of-magnitude-worse offenders?
So I'm not sure if it's the first version of this doc, but I ran the first version of it that's on Wayback Machine[1] with the current version to see what the differences are.
Most of the changes seem to be because Masley found one counter-example (Newton County, Georgia) where AI datacenters do seem to be increasing water costs; the only deletions AFAICS is toning down language where Masley used to say "there are no examples" to "there is one counter-example". I don't see any other major corrections that have been removed.
What is interesting about it for me is: why would someone working on AI ethics choose to work for Google at all?
Did she really think Google cares about ethics? Such positions seem purely performative, we all know that ethics go out the window first to make room for more profits.
I missed that thread when it came out, it's really a wild read. The difference between how people describe her vs how she's normally portrayed in the media is really startling
People generally get fed the stories they already believe to be true
So that's why "Brave minority woman unfairly fired by evil AI corporation" sells better than "Self-entitled minority woman is terrible bully to colleagues"
True but also... she wasn't a software engineer putting code in production nor a researcher working no the fundamentals of machine learning negotiating a raise.
She was part of the "Ethical Artificial Intelligence Team" of what was then, and still is now, one of the corporations World wide spending the largest amount of resources precisely on using AI commercially.
I'm saying the paper itself wasn't a bombshell or even that noteworthy. The reason it got PR and continues to come up was because the authors manufactured this self-inflicted drama around it, not because it was leaking secret revelations that harmed the company.
Her demands included wanting to know the identities of anyone who wanted to comment on her paper, after she had a history of going after people publicly. That's enough right there, nobody should tolerate toxic behavior regardless of whether you agree with the politics.
Meanwhile, the paper has 2 points of criticism towards AI. 1 is a bunch of carbon consumption complaints assuming NVIDIA cards with coal-fired power, while a lot of effort at contemporary Google went towards getting TPUs running on green power. I suspect this was what people wanted to object to, a lot of effort went into those green power projects and she was just denying it. The complaint seems prophetic now but it was not true about Google then.
The other criticism was about which language the LLMs use, they average the input data of normal humans instead of talking the way the paper author thinks they should talk. The phrase "women doctors" is called out as problematic. I'm less inclined to think people objected strongly to this given the zeitgeist at the time, it was probably people who worked on the green energy projects and were pissed off that their contributions were ignored, but still, nobody elected her Queen of English, she can have her opinions but she's not a victim for not having them adopted by everyone.
One of the key points of that paper is that the body of written works is biased and those biases will be amplified by compressing that body into LLMs, with outlier data, with low coincidence rate, being suppressed as unreliable - data that is structurally dissimilar to the bulk is noise. Similarly to how PageRank suppressed nodes with low number of edges, probably contributing significantly to the homogenous corporate mall-internet we enjoy today.
I think this is completely misleading. If your employer asks to redact your paper because it ignores relevant research, naturally you want to know what research they are talking about and on what grounds, and also which researches reviewed the paper (probably assuming there was none, review process was used as an excuse to silence criticism, G has done it many times).
(BTW, quite bold to say input data from Reddit and 4Chan is how “normal” people speak. There is a lot of language in the training data of any model you really do not wish your application to use ever.)
Ugh. Ok if you're going to push one-sided propaganda I'll push the other side.
Google forced its researchers to retract an already submitted paper because it undermined its strategic and commercial story around large language models. The "we just accepted her resignation" is just a lie. Google made harsh demands with opaque reviewers that made vague objections, and then Jeff Dean moved very quickly to get rid of Gebru. Other Google researchers reported that they usually got to work through objections, Gebru got no such opportunity. Google showed that AI labs will not tolerate internal research that seriously criticizes technology central to its business.
Dean pulled a sweet Dungeon Master move in "accepting her resignation." She should have made them fire her, esp for ostensibly doing the job she was hired to do.
I think a better summary is that google gave someone the responsibility to ensure AI was developed and used ethically, and didn't give them the power to execute that responsibility.
Apparently google did not even give them the freedom to come to their own conclusions.
I just skimmed through the paper again and what it says seems to hold up well.
The paper is heritical in that it suggests slowing down, using carefully chosen less biased data, and understanding how it all works.
Basically challenging the AI bitter lesson.
I can see how that would meet with a lot of resistance from people who have gone all in on the bitter lesson.
I'm surprised that people still take Gebru seriously. She is a disgrace to the community because she always, I mean literally always, attacks her critics by motives. You think bias is a data problem? You're a bigot (See her dispute with LeCun). You disagree with my assessment on an ML model? You are white male oppressor (her attacking a Google's SVP). Oh, did I mention that she even said that some loss functions are more racists than others on X?
Gebru is not a researcher. She is a modern-age Trofim Lysenko, who politicizes everything and wields political correctness as a weapon to purge any dissent.
This is not why she was fired and wouldn't have been a plausible reason in 2020 when it happened.
>Timnit responded with an email requiring that a number of conditions be met in order for her to continue working at Google, including revealing the identities of every person who Megan and I had spoken to and consulted as part of the review of the paper and the exact feedback. Timnit wrote that if we didn’t meet these demands, she would leave Google and work on an end date. We accept and respect her decision to resign from Google.
This is Google's side of it; I think the following is a fair piece of primary-source journalism if you want to go deeper:
I remember being angry about this situation when I first saw it on social media, until I read the details: This person submitted a list of demands to her employer and said that if they weren’t met, she quit. Google wasn’t going to meet her demands so they considered it acceptance of her resignation. There has been a movement trying to debate whether it was a firing or resignation ever since.
The original paper they published gets recirculated every year or two as some landmark history of AI safety, but as other commenters have noted it wasn’t really a great paper nor was it groundbreaking at the time. If not for the controversy surrounding the resignation/firing (depending on your POV), I don’t think it would have been notable.