msteffen

Ok, I did more reading. I was actually super wrong about this, but it took me a while to get there. Oops! But very interesting!

Basically, people and firms are little black holes of unmet demand for all sorts of things. When the productivity shock happens, demand for stuff in the now-high-productivity sector(s) is now (mostly) met, freeing up money (that people and firms in the high-productivity sectors have more money to meet their own latent demand is also true, but somewhat incidental). That money goes to meeting other latent demand, some of which is for stuff in low-productivity sectors (housing, childcare, education, healthcare, construction), and that’s what drives up prices until/as people eventually move into those sectors. Even if housing specifically isn’t constrained, it still happens.

And I guess…as wages go up, some forms of automation also become economically sensible, which is what changes the balance of low/high productivity sectors. Latent demand for rope-holding is met with cones, latent demand for maids is (mostly) met with washing machines and dishwashers, latent demand for secretaries is (mostly) met with personal computers, etc.

So with AI, it sounds like people will move out of software into construction, healthcare, etc (only specialized work where the automation isn’t “good enough” stays). All the “teaching kids to code” that schools are doing now, eventually turns into people dealing with their own AI output as adults, where previously they would’ve hired a developer (like how managers who used to have a secretary now get a computer and type for themselves). Wages go up, education, healthcare, and housing get more expensive.

TIL! I’m entirely inexpert in the topic and posted as a curious layperson.

That said, some of what’s in the article only makes sense to me in the context of a system that’s at least somewhat like what I tried to describe. Maybe you can enlighten me?

> This effect is an example of cross elasticity of demand.

Is the cross-elasticity of demand here not referring specifically to the cross-elasticity of different forms of labor, which exists due to the many common inputs of different forms of labor? Eg land, healthcare, unskilled labor (as an input, in the case of skilled labor as the output—doctors and engineers in my comment)?

In the case of a quartet, if musicians charged what they did in 1700, they would quickly become homeless, and then quickly get other jobs.

So people are either leaving the profession or raising their prices, and either firms pay, high-wage-earners pay, or they get no customers and again get other jobs (like the rope-holders). Is that not the effect?

I think this is what Baumol’s cost disease is about (productivity growth on one sector drives up labor costs and ultimately prices in other sectors, such as healthcare, construction). Basically, when software or AI is super lucrative,

1. students go into new lucrative thing

2. supply of doctors goes down

3. doctor wages go up

4. hospital margins go down

5. Hospitals raise their prices to stay in business

6. Wealthy engineers are able to afford higher prices

7. Services that are transitively consumed by the high-productivity sector stabilize at a higher price. Services not transitively consumed by the high-productivity sector go out of business.

- I remember visiting a developing country about 15 years ago and seeing people getting paid to stand there and hold a rope, because I guess their time was cheaper than cones, which I think is the inverse of this.

- I also think that, in the limit, society consists of a handful of economically viable occupations and infinite cheap stuff. Nothing else is worth the prices that a seller would have to charge to afford employees.

- I also think that we’re entering a stabilization phase.

Yeah, I forget the wording but there’s a notification like “so-and-so’s AirTag is near you and they can see where you are.” My spouse put AirTags in our baby stuff and I get them whenever I’m using it.

> At this point, it seems more a discussion of morals and social values rather than a scientific "how to lose fat".

He uses language like that in the book (and I was speculating about “what he would say”).

I think the reason is that when people hear the theory “UPFs caused the obesity epidemic,” their brain sometimes goes to “well what is in UPFs that causes obesity?” His answer is “nothing.” He’s trying to emphasize that the issue isn’t some toxic ingredient, but that UPFs are a technology that are being used in a way that leads to this outcome.

(though the research in TFA might actually challenge the “nothing,” by showing that there is some kind of toxicity)

> That's the point at which it becomes highly speculative.

The “…in order to sell more product” part is scientifically speculative, I agree—the book makes the claim, but the scientific research it references does not, IIRC. The book’s author imputes it from interviews and the like.

The “overwhelm…feedback mechanisms” part is mainly substantiated by a 2019 study by Kevin Hall where, similar to TFA, they had people essentially live inside a calorimeter and eat calorie- and nutrient-matched meals that were UPF or not. They found that when given UPF, the same people ate more and faster, and gained weight at a pace that surprised the study authors (who were initially skeptical of the theory and had constructed the study to try and disprove it. The study author is interviewed and explains why he found it compelling).

Whether you find the evidence compelling is, of course, up to you :-), but I felt the book did a good job interviewing members of the obesity research community and tracing the history of the theory.

The book discusses this a bit, actually. It basically credits the UPF theory to one Brazilian researcher, Carlos Monteiro, and discusses how he developed the theory by applying epidemiological techniques to the obesity epidemic in Brazil. It gives the specific example that, in Monteiro's research, if a family bought sugar at the grocery store, it actually reduced the likelihood that they were obese because, even though sugar is not healthy, it meant they were still cooking at home.

My understanding is that he would probably make similar predictions about your examples: people who eat fried chicken and chocolate as part of a mostly home-cooked diet are less likely to be obese than people who drink diet coke as part of a diet that mostly comes out of wrappers. He would probably also say that there's nothing inherently bad about diet coke, but there is something bad about getting all your food from people trying to make money instead of from people who love you.

For anyone who hasn’t read it, I highly recommend the book “Ultraprocessed People.” It's a scientifically literate and yet quite readable overview of research into ultraprocessed foods.

FWIW there are four categories:

1 is whole foods (eg fruits, nuts)

2 is stuff that is processed but still basically an ingredient (eg flour, maple syrup)

3 is combinations of 1 and 2 (most restaurants are here)

4 is ultraprocessed food (UPF): things that were not food that have been turned into food (e.g. modified starches, artificial flavors). Also, anything containing UPFs is a UPF, so e.g. most breakfast cereal (food coloring, flavors)

The basic thesis (which this research challenges, interestingly) is that UPFs aren’t inherently bad, but food scientists are shockingly good at creating highly specific and desirable flavors and textures (the book gives the example of a food company creating "ice cream" out of various modified starches and flavors so that it doesn't melt during shipping), and foods that come out of this process have generally been engineered to overwhelm our natural feedback mechanisms against overeating in order to sell more product.

As social commentary, I think a lot of people in this thread are expressing interest in and engaging with this level of math who might not have pre-AI.

I bet, for people who don't understand these problems or their solutions but are close and are now interested, AI makes then considerably more accessible than they would've been previously, and behind this big visible wave of results there actually will be (or already is) a wave of improved comprehension by a lot of curious people.

I'm not at all at this level at all, but I did learn quite a bit about polynomials over fields yesterday.

My understanding was that they take issue with the word "attributable". They don't attempt to propose a mechanism by which living near Costco causes cancer (the most strongly associated of the landmarks they measured). Rather, the implication is that it doesn't. Like I think it's a lot of words arguing that "correlation doesn't prove causation" could be restated "association doesn't prove attribution."

I liked this a lot. I have also struggled with this, and I feel compelled to suggest my own angle: this is often caused by issues that are not (just) professional skill gaps, though closing those gaps can help resolve it.

Avoiding status updates, needing to “prove yourself,” things like these, were all products of a deeper lack of trust for me. TFA alludes to this with “imposter syndrome”. I was so used to this that it took a long time to figure out. What helped me (and I wouldn’t say I’m better, but better than I was) was a few ideas:

1. Trust is equal parts competence and communication. Trust is lost when you expected X and didn’t get it, which means half the problem is not getting it and the other half is expecting it in the first place.

2. So trust requires clear communication, and clear communication requires trust in the other direction. At a totally dysfunctional company, all of engineering doesn’t trust leadership, so they're not honest with leadership, and soon enough leadership doesn't trust engineering, if that hasn’t happened already. So lack of trust in one direction breaks down trust in the other direction.

3. If you don't feel comfortable saying something that's true (anything! “I got nothing done yesterday because I still don’t really understand the problem I’m solving,” or whatever kind of thing you’re afraid to say), it means you don't trust whoever you're talking to. This is a problem—see #2. In the context of TFA, this is the problem that leads to you skipping status updates or going off and building without prior discussion.

The solution is building your own trust, which can actually be hard to do and requires some self-knowledge (e.g. did you have a bad experience at a prior job? Are you dispositionally a nervous person? Did your boss/leadership break your trust in some way already—large or small?).

This is IMO what TFA is really about, and the strategy it suggests is a great one if a bit of positive feedback and encouragement is what helps you extend trust (which is fine! It's worth knowing that about yourself) and grunt work earns you that feedback (which it might, though you can't control what other people do—it may also help to communicate that you're looking for that, e.g. "I want to see what kind of contributions are celebrated here, and I thought these might be." A small trust exercise in the context of the larger one.)

It might be something else. Off the top of my head: will work respect my needs if a life event temporarily interferes with my work? If I'm missing context on a project, will I be given help or hostility? Am I being given a clear explanation of the expectations for the role?

(Finally, I think it's worth mentioning the version of this where your boss or leadership isn't building trust in you, and IMO it looks like you stuck in a marginal role and not given a path to larger ones, even though you're clear that you want them. Sometimes you can convince them to trust you, but you can't control what other people do. In particular, if you're building something without prior discussion, consider that a lack of trust from the company to you is now creating a lack of trust from you to the company. Maybe it'll be fixed, but no guarantees.)