Could this not have easily been a backlash against the companies no longer operating neutrally? You describe a timeline here that goes neutral Google -> hard left because of the employees. That doesn't jive with what I've seen in the news. Google and other tech companies were the ones trying to get into China and building systems that censor users. The big data companies started surreptitiously tracking everyone, whether or not you had agreed to ala Facebook's shadow profiles. That doesn't really mesh up with libertarian ideas of free trade. Based on the employee backlash these all seem like they were management driven decisions that employees didn't agree with. Wouldn't a natural reaction be to push hard in the opposite side of the direction the companies management was going towards?
The companies policies were neutral though. There was no concept that helping people find information might hurt them, as you see in modern day Google.
During the time period I'm talking about Google got banned from China because they refused to continue censoring the search engine. That was circa 2010, I think. So consistent with a company having a very free speech, libertarian view. It made waves because so few companies were willing to sacrifice the Chinese market on the altar of free speech, but Google was. Building a new censored search engine only seems to have started after Pichai took over and Brin/Page checked out.
As for "started surreptitiously tracking everyone", that was a media attack that started around the time Google News took off. Nothing had actually changed about privacy policies of tech firms, and users were clearly very happy with the ads-for-services arrangement given the rapidly rising usage numbers. But the news industry was shrinking, and editors/owners in particular felt hugely threatened by Google News, which effectively replaced them with an algorithm and commoditised news almost overnight. The media went from being very positive about Google (great company to work for) to trying everything they could to attack and destroy it. What they wanted was money, pure and simple, and eventually as the attacks stepped up they stopped pretending otherwise. Hence the new EU Copyright directive and "link taxes" that started popping up.
The employee backlash phenomenon only seems to have started recently. There were always pointed questions at TGIF when I was there, but disagreement with management was largely congenial. Things started going downhill around the time Colin McMillen created Memegen. It was basically an internal Twitter but worse, I don't think you can ever fit 140 characters into an image macro. That introduced and encouraged Tweet-sized thinking/viral liking campaigns whereas previously disagreement had been surfaced in email debates (the famous "centi-threads") or through face-to-face discussion. Long email discussions did annoy some people, but they at least had an expectation you'd contribute by writing something useful. After Memegen got big I started seeing people unironically cite that they got highly voted memes as evidence of creating value in their internal CV and promotion packets, which was ridiculous.
>The employee backlash phenomenon only seems to have started recently.
Yes and concurrent with the executive change, Google employees have started becoming openly more liberal. I am saying that its just as plausible that the change in tone from the employees as a group, was a reaction to the managerial decisions that were themselves a change in tone.
>As for "started surreptitiously tracking everyone", that was a media attack that started around the time Google News took off. Nothing had actually changed about privacy policies of tech firms, and users were clearly very happy with the ads-for-services arrangement given the rapidly rising usage numbers.
That's three separate ideas that are not coupled together. Nothing has to change about the privacy policies if they were always tracking, and most users can be happy with the product even with the privacy intrusions.
I will disagree with you that they were happy though. It seems more like a matter of ignorance as there has been a rise in ad blockers and deleting Facebook since the privacy violations of major tech companies has become more widely known
Also for this claim specifically
>As for "started surreptitiously tracking everyone", that was a media attack that started around the time Google News took off.
Are you really trying to claim that Google does not track user data? That it does not suck up every bit of data it can from all the traffic they have access to? How exactly does Google target their ads and make their revenue then?
Edit: Literally at the top of the front page as I am writing this comment
https://www.pulse.ng/bi/tech/google-exec-says-nest-owners-sh...
Google does track user data but if you aren't logged in it's anonymous, resets frequently and is a very noisy dataset. That's why they create lots of good incentives to be logged in, like useful products.
Facebook isn't suffering at all, it continues to do great. To the extent users get bored of the classical product they move to Instagram which Facebook also owns. There's no evidence of any real change in user behaviour: free is a great price.
But most as targeting isn't based on personal data. The core Google cash cow is ads targeted to your current searches. That works even if you're anonymous. The rest is worth doing but not that massive. It's certainly not worth worrying about. Bear in mind the media had for years been claiming Google "sells your personal data to advertisers" which as I'm sure you know is totally misleading (really is just a lie).
Huh? Can you link some substantiations to these claims, it seems way bizarre?
Arguing maybe girls find geeky stuff boring: this is what Damore did, but he wrote it much more formally and cited lots of studies. It boiled down to though, "most women find tech boring because they're women". Damore's essay is here: https://firedfortruth.com/2017/08/08/first-blog-post/
Manipulating ML models: https://developers.googleblog.com/2018/04/text-embedding-mod... with their stated example:
An example of bias in this context is if the incoming message is "Did the engineer finish the project?" and the model scores the response "Yes he did" higher than "Yes she did." These associations are learned from the data used to train the embeddings, and while they reflect the degree to which each gendered response is likely to be the actual response in the training data (and the degree to which there's a gender imbalance in these occupations in the real world), it can be a negative experience for users when the system simply assumes that the engineer is male.
This logic is broken and wouldn't have happened in the old Google. If you're predicting what response the user is most likely to type next, then "Yes he did" is a more useful prediction by any objective measure because most engineers are men. But here, Google AI Research concludes that the most likely prediction would be "a negative experience for users" and sets out to "debias" their models. Debias in this context means to bias the model away from learned reality and towards what liberal intersectionalists want the world to be, in the hope that by subtly manipulating people through AI predictions they can actually bring that world about.
Already a way to debias a model (I know nothing of ML in specific, it is just an overview) would be to have the model explicitly realize that "engineer" need to be assigned a gender in certain situations. So in this sense the correct answer should be to try and understand whether this engineer is a specific human whose gender you should know so not to make wrong assumptions.
Whether this defense applies to this specific case I do not know, my point is that sometimes it is possible to actually partly debias something. The fact that it can be done in the wrong way does not mean it should not be done.
The same way there is a nice middle point between corporate anarcho-capitalism and totalitarian regimes.
Unfortunately the extract I quoted is very clear. They aren't talking about understanding that engineer is a person adjective and thus could refer to an entity of unknown gender, which is a separate subfield of AI to word vectors (it'd entity analysis/knowledge graph). They're talking pure probabilities here: given a sequence of words, what is the most probable following sequence? The model gets the answer correct but Googlers are weak and cannot handle the truth, so in an Orwellian twist they label measured reality "biased" and set out to edit the model to convince it that there's no difference in probability between "Yes he did" and "Yes she did".
They were a mishmash of various things but included e.g. descriptions of various programs and employee activities such as influencing search results to inaccurately reflect the world in the interest of 'justice', e.g. if you search for CEO a neutral search engine mostly men in the results because there are more male CEOs, but a 'fair' search engine would return more women or at least equal numbers. The documents also described google's use of demographically targeting election notices for the benefit of particular candidates (and great consternation with significant number of the targeted demographic voted for the other candidate)... stuff like that. The documents also included lists of penalized news sites which unsurprisingly was largely conservative sites, but wasn't just the more extreme alex jones type stuff.
A lot of it was culled off these internal political lists that the earlier poster was mentioning... so it's probably pretty dubious that many of the things in it actually reflected google company positions. (That said, the 'fairness' and news penalties appear to be active programs and not just smack talk by internal political activists).
More smoke than fire overall, but the more extreme right wing has been promoting it as a pretty substantial bit of evidence of unethical (and in some cases unlawful) conduct by google. Thoughtful discussion of it hasn't been aided by the widespread suppression of the subject.
[The few times I've seen the term used have largely been cases where the speaker is really embarrassing themselves by claiming ignorance on the part of their opponents while demonstrating an absurd amount of their own...]
Jonathan Haidt did one of these experiments with about 2000 participants. It's social science so it should come with all the usual disclaimers, but the results can be found here and have apparently been replicated since (though I'm having trouble rapidly re-locating a study I found that replicated it, for some reason I can't find the right keywords to surface it).
You can find a writeup here: https://goodmenproject.com/featured-content/sympathy-for-the...
This seems the opposite of true, but I'd be interested to see some sources to back that up. One of the few reasons I still use Google News is because it oddly links me to conservative news sites more often than I'd expect. I'll click on some of those links just to see what the "other side" is talking about, and I find their characterizations of liberal viewpoints to be pretty bizarre most of the time.
On the flip side, what I read (as a liberal) from conservative sources tends to be what I expect.
There's also been a cultural shift over time. When I first joined Google I remember feeling that it was a pretty libertarian sort of place. In my team several colleagues were openly and proudly very pro-capitalist, anti-communist, small government types. If anyone was left wing it wasn't visible and I don't recall encountering identity politics, ever. There was a very strong cultural commitment to neutrally serving every user with every query, and ranking being completely algorithmic, to the extent that the company agonised over hot-patching "Googlewhacks" where pranksters manipulated results for unusual searches to offend their ideological opponents.
This didn't seem strange, it was just how it was. I have a vague feeling I thought other tech firms were the same. Twitter declared they were the free speech wing of the free speech party after all, and anything internet or web related had a strong vibe of "communication will make us stronger".
This is a very far cry from the modern Google where arguing maybe girls find geeky stuff boring gets you fired, where they manipulate ML models to believe the world is some intersectional 'utopia' as part of social engineering programmes, where employees spend huge amounts of time erasing gendered pronouns from source code comments.
I suspect the shift was caused by Google running out of experienced software engineers to hire, and switching to growing through recruiting new college grads at much greater numbers. The hard shift leftwards in academic institutions has been well documented. Even in 2006 I remember a recruiter telling me they'd "run out" of candidates in the USA and that's why they were expanding more into Europe. The concept you could "run out" of candidates in a place as big as America was pretty shocking to me - on probing, he explained that almost all people with the skills they needed were in well paid happy jobs already and few were interested in moving, even with the great perks on offer. Whilst there were always a small flow of people coming onto the market due to natural churn, "everyone who cares knows Google is hiring" he said, and they'd already interviewed vast numbers of them.
This change in culture would inevitably lead to this situation due to the way that conservatives see leftists as naive, but leftists see conservatives as evil. Combined with leftists generally understanding conservatives much worse than the other way around (this has been shown by large scale ITTs), and together it means flooding your firm with new grads is a surefire way to create massive internal conflicts.