LessWrong 2.0 Reader

I would say "the thing that contains the inheritance particles" rather than "the inheritance particle". "Particulate inheritance" is a technical term within genetics and it refers to how children don't end up precisely with the mean of their parents' traits (blending inheritance), but rather with some noise around that mean, which particulate inheritance asserts is due to the genetic influence being separated into discrete particles with the children receiving random subsets of their parent's genes. The significance of this is that under blending inheritance, the genetic variation between organisms within a species would be averaged away in a small number of generations, which would make evolution by natural selection ~impossible (as natural selection doesn't work without genetic variation).

I've been tempted to do this sometime, but I fear the prior is performing one very important role you are not making explicit: defining the universe of possible hypothesis you consider.

In turn, defining that universe of probabilities defines how bayesian updates look like. Here is a problem that arises when you ignore this: https://www.lesswrong.com/posts/R28ppqby8zftndDAM/a-bayesian-aggregation-paradox [LW · GW]

Isn't singular learning theory basically just another way of talking about the breadth of optima?

If some some pre-modern hominids ate high animal diets, and some populations of humans did, and that continued through history, I wouldn't call that relatively recent. I'm not the same person making the claim that there is overwhelming evidence that saturated fats can't possibly be bad for you. I'm making a much more restricted claim.

Previous LW discussion about the Inner Ring: [1 [LW · GW], 2 [LW · GW]].

Your hypothesis is ignoring environmental factors. I'd recommend reading over the following paper: https://journals.sagepub.com/doi/10.1177/2332858416673617

A few highlights:

Evidence from the nationally representative Early Childhood Longitudinal Study–Kindergarten Class of 1998-1999 (hereafter, ECLS-K:1999) indicated that U.S. boys and girls began kindergarten with similar math proficiency, but disparities in achievement and confidence developed by Grade 3 (Fryer & Levitt, 2010; Ganley & Lubienski, 2016; Husain & Millimet, 2009; Penner & Paret, 2008; Robinson & Lubienski, 2011). [...]

A recent analysis of ECLS-K:1999 data revealed that, in addition to being the largest predictor of later math achievement, early math achievement predicts changes in mathematics confidence and interest during elementary and middle grades (Ganley & Lubienski, 2016). Hence, math achievement in elementary school appears to influence girls’ emerging views of mathematics and their mathematical abilities. This is important because, as Eccles and Wang (2016) found, mathematics ability self-concept helps explain the gender gap in STEM career choices. Examining early gendered patterns in math can shed new light on differences in young girls’ and boys’ school experiences that may shape their later choices and outcomes. [...]

An ECLS-K:1999 study found that teachers rated the math skills of girls lower than those of similarly behaving and performing boys (Robinson-Cimpian et al., 2014b). These results indicated that teachers rated girls on par with similarly achieving boys only if they perceived those girls as working harder and behaving better than those boys. This pattern of differential teacher ratings did not occur in reading or with other underserved groups (e.g., Black and Hispanic students) in math. Therefore, this phenomenon appears to be unique to girls and math. In a follow-up instrumental-variable analysis, teachers’ differential ratings of boys and girls appeared to account for a substantial portion of the growth in gender gaps in math achievement during elementary school (Robinson-Cimpian et al., 2014b).

In a lot of ways the way you are looking at the topic perpetuates a rather unhealthy assumption of underlying biological differences in competency that avoids consideration of contributing environmental privileges and harms.

You can't just hand wave aside the inherent privilege of presenting male during early childhood education in evaluating later STEM performance. Rather than seeing the performance gap of trans women over women presenting that way from birth as a result of a hormonal advantage, it may be that what you are actually ending up measuring is the performance gap resulting from the disadvantage placed upon women due to early education experiences being treated differently from the many trans women who had been presenting as boys during those grades. i.e. Perhaps all women could have been doing quite a lot better in STEM fields if the world treated them the way it treated boys during Kindergarten through early grades and what we need socially isn't hormone prescriptions but serious adjustments to presumptions around gender and biologically driven competencies.

I think that people who work on AI alignment (including me) have generally not put enough thought into the question of whether a world where we build an aligned AI is better by their values than a world where we build an unaligned AI. I'd be interested in hearing people's answers to this question. Or, if you want more specific questions:

• By your values, do you think a misaligned AI creates a world that "rounds to zero", or still has substantial positive value?
• A common story for why aligned AI goes well goes something like: "If we (i.e. humanity) align AI, we can and will use it to figure out what we should use it for, and then we will use it in that way." To what extent is aligned AI going well contingent on something like this happening, and how likely do you think it is to happen? Why?
• To what extent is your belief that aligned AI would go well contingent on some sort of assumption like: my idealized values are the same as the idealized values of the people or coalition who will control the aligned AI?
• Do you care about AI welfare? Does your answer depend on whether the AI is aligned? If we built an aligned AI, how likely is it that we will create a world that treats AI welfare as important consideration? What if we build a misaligned AI?
• Do you think that, to a first approximation, most of the possible value of the future happens in worlds that are optimized for something that resembles your current or idealized values? How bad is it to mostly sacrifice each of these? (What if the future world's values are similar to yours, but is only kinda effectual at pursuing them? What if the world is optimized for something that's only slightly correlated with your values?) How likely are these various options under an aligned AI future vs. an unaligned AI future?

No I have not seen a detailed argument about this, just the claim that once centralization goes past a certain point there is no coming back. I would like to see such an argument/investigation as I think it is quite important. "Yuval Harari" does say something similar in "Sapiens" 

I don't have a strong opinion because I think there's huge uncertainty in what is healthy. But for instance, my intuition is that a plant-based meat that had very similar nutritional characteristics as animal meat would be about as healthy (or unhealthy) as the meat itself. The plant-based meat would be ultra-processed. But one could think of the animal meat as being ultra-processed plants, so I guess one could think that that is the reason that animal meat is unhealthy?

I always assumed that, since high IQ is correlated with high openness, the higher openness would be the cause of higher likelihood of becoming trans. 

(or, some more general situation where IQ is causing transness more than the other way around., e.g. high scores on IQ tests might be caused to some extent by earnestness/intensity etc., which could also cause more likelihood of becoming trans)