I really like Wikipedia, though, and I think over time we will get around to fixing it up.
In addition, the answer to the question is already available so I want any question asker to put in a little bit of effort and if they’re not going to do that then I’m not really interested in talking to them since I prefer peer interactions to tutorials.
As soon as there is a plausible agenda for selecting a narrative the way Wikipedia works we should be sceptical.
For recent examples, everything to do with Biden and family, and Gamergate. These pages are still full of discussion; and what's written is more ideological than factual. You can follow these pages to see how an in-group selects a narrative.
And these topics are not nearly as controversial as race, feminism, or transgender topics.
Brian hit Jim can be a fact. But if you emit "Jim murdered Brians whole family", its a disortation of truth
> Gamergate or GamerGate (GG) was a loosely organized misogynistic online harassment campaign motivated by a right-wing backlash against feminism, diversity, and progressivism in video game culture. It was conducted using the hashtag "#Gamergate" primarily in 2014 and 2015. Gamergate targeted women in the video game industry, most notably feminist media critic Anita Sarkeesian and video game developers Zoë Quinn and Brianna Wu.
Grokipedia's:
> Gamergate was a grassroots online movement that emerged in August 2014, primarily focused on exposing conflicts of interest and lack of transparency in video game journalism, initiated by a blog post detailing the romantic involvement of indie developer Zoë Quinn with journalists who covered her work without disclosure. The controversy began when Eron Gjoni, Quinn's ex-boyfriend, published "The Zoe Post," accusing her of infidelity with multiple individuals, including Kotaku journalist Nathan Grayson, whose article on Quinn's game Depression Quest omitted any mention of their prior personal contact. This revelation highlighted broader patterns of undisclosed relationships and coordinated industry practices, such as private mailing lists among journalists, fueling demands for ethical reforms like mandatory disclosure policies.
I don't care about "Gamergate" and never use Grokipedia, but Wiki definitely has a stronger slant: it's as if an article about Black Lives Matter started with a statement that it was a campaign meant to scam people to pay for mansions for leadership.
... it does sound like an online harassment campaign.
An article doesn't avoid bias by avoiding unpleasant facts.
You can write an equivalent article starting with "Gamergate was a movement reacting to the improper collusion between game developers and journalists" and find just as many sources, but the current article wants to promote the idea that it was a harrassment campaign first.
Reframed, the study seemed to find (a) black kids are adopted less readily and (b) the longer a kid spends in the foster system, the lower their IQ at 17. (There is also limited controlling for epigenetic factors because we didn’t understand those well in the 1970s and 80s.)
Based on how new human cognition is, and genetically similar human races are, it would be somewhat groundbreaking to find an emergent complex trait like IQ to map to social constructs like race, particularly ones as broad as American white and black. (There is more genetic diversity in single African tribes than in some small European countries. And American whites and blacks are all complex hybridized social categories.)
[1] https://en.wikipedia.org/wiki/Minnesota_Transracial_Adoption...
We can easily identify the geographic locations of people's ancestors by looking at them. That means that we evolved quite a few exterior physical traits that are easily grouped and identifiable. Do you really think our brain, which is our most important survival trait, was immune to evolution? That people that moved to specific regions didn't have had selective pressures of some kind on the way we think?
Where this can go awry are the people that learn about this and then think that it's reason to discriminate against individuals or groups - of course it isn't. As you said, genetic diversity within groups is large. And even something like IQ certainly doesn't sum up the worth of someone, or even their brain.
The whole point of what I posted though was just to point out the fact that Wikipedia is, in fact, biased in what's put on there. It wasn't that long ago that it was perfectly OK as an academic to study the racial differences in IQ. Now? Good luck. Wikipedia reflects that.
And: it remains perfectly OK to study racial differences in IQ. It's an actively studied topic. In fact, it's studied by at least three major scientific fields (quantitative psychology, behavioral genetics, and molecular genetics). The idea that you can't is a cringe online racist canard borne out of the fact that the studies aren't coming out the way they want them to.
James Flynn (of the Flynn effect) has also publicly stated that grants for research clarifying genetic vs. environmental causes of IQ gaps weren't approved because of university fears of public furor.
Noah Carl has a sociology doctorate. He doesn't work in the fields that study this; he just tries to launder his way into them.
Flynn is, famously, a race/IQ skeptic.
https://www.theguardian.com/education/2019/may/01/cambridge-...
> for merely arguing that race-IQ research should not be off-limits.
Help me connect the dots here.
Which is what we all mean by race, anyways.
The latter is more genetically diverse than any other human population by an incredible margin. Making generalized statements about them is impossible (including this one). As for African American populations, ancestry estimates of how closely related they are to African populations vary massively for each individual. Many people are much closer to "white" populations than any African population, due to the history of African Americans in North America. If you really mean race as a geographic proxy, the "black" label is simply confusing what you actually mean.
For what it's worth, I'm mixed as hell. European, Asian, Jewish, north african, and native american. I look white, though - and I am, in fact, majority European ancestry. Therefore in most studies (of anything race related), I would presumably be lumped in with white people. It's not a perfect "measure," but it's still the easiest proxy for geographic location of our ancestors that we have and on a population level it works just fine for studies.
Though I will say it's beyond argument that geographic ancestry has an effect on IQ on a statistical group level (the reasons for this are what's debated), and that IQ is the best measurement of G that we have.
It "is biased" to document human knowledge as accurately as possible. Is there something wrong with that?
Regardless, one can see this claim of inaccuracy repeated in these comments with no provided example of such. The saying goes "what is presented without evidence can be dismissed without evidence". It is therefore reasonable for a reader to conclude that the claim of inaccuracy can be dismissed as "bullshit", in the sense that the person making it cares not for its veracity.
- this tends to approximate consensus.
- Wikipedia does care, and has a policy on this: https://en.wikipedia.org/wiki/Wikipedia:Scientific_consensus
Look at the top of that page.
>This is an essay. It contains the advice or opinions of one or more Wikipedia contributors. This page is not an encyclopedia article or a Wikipedia policy, as it has not been reviewed by the community.
The document outlines normative / prescriptive approaches that are followed in practice.
"Anonymous surveys of intelligence experts reveal division: a 2016 survey found that about 49% attributed 50% or more of the Black-White gap to genetics, while over 80% attributed at least 20%; an earlier 1980s survey showed similar splits. These views are more common in private or anonymous contexts, contrasting with public statements from bodies like the APA that find no support for genetic explanations."
Hm, sure seems like Wikipedia should probably have a more balanced, nuanced discussion considering the experts are split at least 50/50.
Bringing up an opinion poll as a counterpoint makes it read like you're arguing that Wikipedia should focus less on fact and more on opinion. Of course, you're free to think what you wish, but I suspect that's where most disagree.
Genetics certainly don't explain all the differences in IQ. They very well might not explain the majority of the the difference. However, considering we know that intelligence is quite heritable along with various adoption and twin studies that have happened throughout the decades (along with simple freaking logic), we have a pretty good idea that it explains at least some of the difference. That "opinion poll," while not super-great because only some elected to reply, was a poll of experts in the fields that study this stuff, not random people.
A real unbiased article would mention that (and perhaps whatever counterarguments there are), not straight up do the encyclopedia equivalent of sticking their fingers in their ears and going "nah uh I can't hear you."
Did I miss where you presented evidence that wikipedia is wrong? You seem to be taking an assumption you carry (race is related to IQ) and assuming everyone believes it's true as well, thus wikipedia is lying.
Rushton, J. P., & Jensen, A. R. (2005). Thirty years of research on race differences in cognitive ability. Psychology, Public Policy, and Law, 11(2), 235–294.
Neisser, U., et al. (1996). Intelligence: Knowns and unknowns. (APA Task Force report). American Psychologist, 51(2), 77–101.
https://www.tandfonline.com/doi/epdf/10.1080/25785648.2023.2...
Quote from the conclusion:
> This essay has shown that in the last decade, a handful of editors have been steering Wikipedia’s narrative on Holocaust history away from sound, evidence-driven research, toward a skewed version of events touted by right-wing Polish groups. Wikipedia’s articles on Jewish topics, especially on Polish–Jewish history before, during, and after World War II, contain and bolster harmful stereotypes and fallacies. Our study provides numerous examples, but many more exist. We have shown how the distortionist editors add false content and use unreliable sources or misrepresent legitimate ones.
For a more recent paper, "Disinformation as a tool for digital political activism: Croatian Wikipedia and the case for critical information literacy" by Car et al. says that:
> The Hr.WP [Croatian Wikipedia] case exemplifies disinformation not only as content manipulation, but also as process manipulation weaponising neutrality and verifiability policies to suppress dissent and enforce a single ideological position.
Vs.
What Elon is doing...
Then we're not even comparing fruits to fruits.
Really? Have you used AI to write documentation for software? Or used AI to generate deep research reports by scouring the internet?
Because, while both can have some issues (but so do humans), AI already does extremely well at both those tasks (multiple models do, look at the various labs' Deep Research products, or look at NotebookLM).
Grokipedia is roughly the same concept of "take these 10,000 topics, and for each topic make a deep research report, verify stuff, etc, and make minimal changes to the existing deep research report on it. preserve citations"
So it's not like it's automatically some anti-woke can't-be-trusted thing. In fact, if you trust the idea of an AI doing deep research reports, this is a generalizable and automated form of that.
We can judge an idea by its merits, politics aside. I think it's a fascinating idea in general (like the idea of writing software documentation or doing deep research reports), whether it needs tweaks to remove political bias aside.
Hi. I have edited AI-generated first drafts of documentation -- in the last few months, so we are not talking about old and moldy models -- and describing the performance as "extremely well" is exceedingly generous. Large language models write documentation the same way they do all tasks, i.e., through statistical computation of the most likely output. So, in no particular order:
- AI-authored documentation is not aware of your house style guide. (No, giving it your style guide will not help.)
- AI-authored documentation will not match your house voice. (No, saying "please write this in the voice of the other documentation in this repo" will not help.)
- The generated documentation will tend to be extremely generic and repetitive, often effectively duplicating other work in your documentation repo.
- Internal links to other pages will often be incorrect.
- Summaries will often be superfluous.
- It will love "here is a common problem and here is how to fix it" sections, whether or not that's appropriate for the kind of document it's writing. (It won't distinguish reliably between tutorial documentation, reference documentation, and cookbook articles.)
- The common problems it tells you how to fix are sometimes imagined and frequently not actually problems worth documenting.
- It's subject to unnecessary digression, e.g., while writing a high-level overview of how to accomplish a task, it will mention that using version control is a good idea, then detour for a hundred lines giving you a quick introduction to Git.
As for using AI "to generate deep research reports by scouring the internet", that sounds like an incredibly fraught idea. LLMs are not doing searches, they are doing statistical computation of likely results. In practice the results of that computation and a web search frequently line up, but "frequently" is not good enough for "deep research": the fewer points of reference for a complex query there are in an LLM's training corpus, the more likely it is to generate a bullshit answer delivered with a veneer of absolute confidence. Perhaps you can make the case that that's still a good place to start, but it is absolutely not something to rely on.
This was true of ChatGPT in 2022, but any modern platform that advertises a "deep research" feature provides its LLMs with tools to actually do a web search, pull the results it finds into context and cite them in the generated text.
I'm sure there are many variables across our experiences. But I know I'm not imagining what I'm seeing, so I'm bullish on the idea of an AI-curated encyclopedia, whether Elon Musk is involved or not.
edit: I am not very excited by AI-generated documentations either. I think that LLMs are very useful tools, but I see a potential problem when the sources of information that their usefulness is largely based on is also LLM-generated. I am afraid that this will inevitably result in drop in quality that will also affect the LLMs themselves downstream. I think we underestimate the importance that intentionality in human-written text plays in being in the training sets/context windows of LLMs for them to give relevant/useful output.
So you can understand someone not liking something, but you cannot understand that person liking the idea of an alternative? What is the idea for you if not just an alternative to the established service with the undesired part changed?
Which one is the "undesirable part changed" here? Wikipedia is written by humans, it has a not-for-profit governance model, it encompasses a large, international community of authors/editors that attempt to operate democratically, it has an investment/commitment in being an openly available and public source of information. Grokipedia, on the other hand, is AI-generated, and operated by a for-profit AI company. Even if "grokipedia" managed somehow to get traction and "overthrow" wikipedia, there is no reason on earth why a company would operate it for free and not try to make profit out of it, or use it for their ends in ways much more direct than what may or may not be happening to wikipedia. Having a billionaire basically control something that may be considered "ground truth" of information seems a bad idea, and having AI generate that an even worse one.
I can understand somebody not liking something in how wikipedia is governed or operating, after all whatever has to do with getting humans work together in such a scale is bound to be challenging. I can understand somebody ideologically disagreeing with some of the stances that such a project has to take eventually (even if one tries to be neutral as much as possible, it is inevitable to avoid some clash somewhere about where this neutrality exactly lies). But grokipedia much more than "wikipedia but different ideologically".
edit: just to be clear, I see a critique of the "idea of grokipedia" as eg the critique of it being a billionaire controlled, AI generated project to substitute wikipedia; a critique of the implementation would be finding flaws to actual articles in grokipedia (overall). I think the idea of it is already flawed enough.
Wikipedia is fine for uncontroversial facts. The obscure ones can have individual mistakes but it's generally correct.
For controversial topics, it's an eternal battle between factions of "volunteers" trying to present their view of a conflict. The articles reflect which side has the best organized influencer operations. Factual truth may or may not shine through, but as a side effect, not a result of the governing process.
Grokipedia operates by Grok writing what it considers the true and interesting facts. That doesn't mean it's always right, but it's a model far less influenced by influencer operations.
I wildly disagree with the critique based on the wealth of the top executive. I care about the truth and quality of the articles.
If Grok is trained on a corpus of information written by humans trying to influence other humans, and it has no ability to perform its own original investigation in the real world, then how can it be anything but the product of influence?
In reality, Grok is trained on pretty much the same giant web crawl/text corpus as other contemporary AIs.