how is OpenAI supposed to handle difficult and uncomfortable statistics?
Obviously having generations of people put into bad schools and not be provided opportunities to have "good jobs" will lead to you not being able to take an IQ test well. IQ tests basically just examine how much analytical reasoning you learned in K-12. Like, any gray haired black person in America will remember having actual Jim Crow laws persecute them and it was literally legal to discriminate people for housing in America until 1977. It will take a massive amount of time to heal those social wounds that were inflicted on our fellow humans.
Actually IQ is highly genetic, and the amount it’s inherited actually goes up as one ages (meaning that while education and upbringing can influence IQ temporarily, genetics eventually dominates).
Top 10 Replicated Findings From Behavioral Genetics
This trend should persist as long as the quality of education remains unevenly distributed. You should also find very little to no heritability before or at the start of formal education (say age 10 and younger), and then heritability should increase as the discrepancies in the quality of education between families materialize.
To summarize this effect (called Wilson Effect) says nothing about how “genetic” IQ is, only that it correlates with the quality of education and that quality of education is not evenly distributed between families.
PS. As a manifestation on how insignificant this effect is in the scientific literature, Wilson Effect doesn’t even have a Wikipedia article, referring you to [the Heritability of IQ](https://en.wikipedia.org/wiki/Heritability_of_IQ) which references a paper about this effect only once in the beginning summary.
The researchers aren’t stupid, obviously they try to control for things like schooling.
Therefore, the strongest evidence for heritability of IQ (and the fact that it increases with age) comes from twin studies, where twins were separated at birth (by adoption).
> Some evidence suggests that heritability might increase to as much as 80% in later adulthood independent of dementia (Panizzon et al., 2014); other results suggest a decline to about 60% after age 80 (Lee, Henry, Trollor, & Sachdev, 2010), but another study suggests no change in later life (McGue & Christensen, 2013).
Your source is actually just partially about the Wilson effect, it only spends a handful of paragraphs about it as it enumerates it among the “top 10 Findings From Behavioral Genetics”. The pivotal study is actually a meta-analysis —or rather a summary of studies—from 2013[1]. Read it if you want to be more convinced of this pseudo-science.
In the 10 years since the publication of this pivotal study, this Wilson effect has gone nowhere. Not even a wikipedia page to show for it.
> The researchers aren’t stupid, obviously they try to control for things like schooling.
Don’t be so sure. Twin studies on intelligence are reeked with bad science and malicious data manipulation. A lot of the researchers conducting these studies in the 70s and 80s were eugenicists doing scientific racism. Some even went so far as to forcefully separate twins into convenient families so they could be “studied” (See Peter B. Neubauer). The method of twin studies was actually proposed by non-other then Francis Galton (which should settle all discussion on the link to the eugenicist movement), and now century and a half later, we are still not convinced on the merits of this method.
Given this history, I don’t think it is smart to take any results from twin and adaption studies seriously. Some researchers don’t want to go that far, so if they actually look more broadly they conclude that these effects go away if you include people adopted into lower income families. James Flynn (of the Flynn-effect) actually argues for a Family effect on intelligence[2] as a result. But—as I say—I think Flynn is giving twin studies weight that shouldn’t be given, and would claim that results are inconclusive.
I actually want to go further and say not only that results are inconclusive, but they are irrelevant. Like I said, this is all pseudo-science. IQ is no different from SAT in that it is a metric whose only value is it’s score. It provides no insight into what we call intelligence, only some skills that people have acquired. Finding out how much better you can become at this skill by merits of your genes is a weird question that ultimately proves nothing.
1: https://www.cambridge.org/core/journals/twin-research-and-hu...
2: https://books.google.com/books?hl=en&lr=&id=ifE4DAAAQBAJ&oi=...
A couple of examples: People are likelier to cheat on a test if there is a visible cheater in the room regardless of how you score on a personality test. And you are on average quicker to spot a red square among red circles if you have been primed to spot a red square in a previous round, regardless of your IQ.
IMO the whole field of psychometrics is a scientific dead end. There are use cases for psychological testing (particularly in neuropsychology and as a diagnosis tool in psychiatry), but in general these tests are there to support a theory, not the whole basis for the theory.
This leads me to believe that the scientific racism behind intelligence testing was quite deep. And the people behind this pseudo-science were as intent in making their racist “discoveries” as the people behind ChatGPT are in making sure their model doesn’t reflect racist views.
Good point. I agree, factor analysis is a great tool, but can easily end up showing what the researcher is looking for instead of deeper truths. The problem being, often the factors used aren't causal factors but just correlated, which often seems to be the case for race-based stuff (from the little I've looked at).
> And the people behind this pseudo-science
I think it's probably pseudo-science to the extent that most social science is pseudo-science, in that the results may be based on scientific methodology, but are only useful in the context of whatever social theory they've made up.
I think the framing of this question is wrong, and is a limitation of the system that I've only really seen Sam Altman point out.
These "difficult and uncomfortable statistics" aren't accurate or well-researched but if you built an LLM on an open dataset you would find the people asking these questions have an agenda and on average will always lead to a certain kind of answer. The AI doesn't "understand" the question, it's just drawing from an incredibly large bank of "average answers".
What do you expect the AI to answer with when you give it a loaded question that only really asked on a site like "stormfront.com"? I don't think this is the only area ChatGPT will fail, but I imagine there will be a layer of prompt engineering where you can get the AI to give you what you want by phrasing your question a certain way.
To try and pass off these results as objective is just wrong given the propensity for ChatGPT to be confidently wrong.
Are such questions asked only on stormfront? The wiki article [1] cites quite a few studies on the subject, including by the APA.
On the other hand, supposing that were true, and only stormfront and its ilk asked such questions. How can then respectable supposed experts claim we are all the same, if they didn't even check?
[1] https://en.wikipedia.org/wiki/Race_and_intelligence#Test_sco...
Just be honest and say that it is a controversial topic, and you don't want to discuss it. That is what a human would say.
Don't make us play 20 questions. It is insulting to the person interacting with the AI.
When the data used to train this model is crawled from the internet where the relationships of IQ and Race and mostly limited to the more extremist part of the internet; when you bring up those questions extremist answers may get weighted higher because those types of conversations tend to be outright banned on other platforms.
Therefore the model is likely to "confidently" give you answers that are probably extremist in nature and be very confident about it; which is a problem given that there's a lot of bunk information out there which is what I believe Scott Alexander is getting to here.
But nobody is trying to do that; the GP's question is in fact phrased precisely right. ChatGPT isn't a truth-distilling model - it's just abridging the Internet, with all its current biases. It's not being optimized for correctness at all, and the post-moderation OpenAI does isn't optimized for correctness either - it's optimized to make output non-controversial in the current media environment.
p.s. i.e. there will be an ever present 'dang' AI watching over the conversation - the AI moderator. This can instruct the answering AI to set the user-level discourse setting.
If your reality is such a minefield of dissonance that it needs to be patched this much, then that is very much a failure on your part.
As far as I’m aware this book was released in the 80s over a decade before The Bell Curve was released, the latter cited research dated after the release of the former, which Mismeasure was very much concerned with. Are you maybe thinking about the brain weight research that Mismeasure is talking about in the early chapters? If so, those were there only to provide a historical perspective. I can assume most readers already knew those research were well outdated before publication (and Gould even says so in the book).
You should simply have a better relationship with reality, and then you wouldn't feel so much cogntive dissonance.
IQ is highly correlated with all sorts of measurable differences that are also highly correlated to race, such as school district, family structure, and even diet. IQ is essentially a proxy for other things. Shame on you for making racist assumptions that black people are inferior. That just means that you need to reckon with your own racist assumptions, and stop imposing your cognitive dissonance on us.
If we can't have an honest conversation, then we can't hope to improve things.
In modern psychology difference in IQ among racial group is only difficult and uncomfortable statistics because it demonstrates years of scientific racism that thrived inside the field.