> In the 1950s and early 1960s, Japanese households reveled in the chance to have washing machines, televisions, and refrigerators; in the following decade, it was cars, air conditioners, and color TVs. In the 2020s and 2030s, the next set of “sacred treasures” could be futuristic gadgets like electric cars, AI assistants, heat pumps, battery-powered appliances, or personal care robots. They could be simple things like bigger houses, cheaper elder care and child care, and more comfortable sofas. Or they could be something that hasn’t even been invented yet.
This next batch of "sacred treasures" really seems crappy in comparison to the previous batch.
I'm not sure I see how the "simple things" would come, since those have only gotten less accessible since the 50s even in countries like the US whose economy grew year over year and didn't stagnate.
So everything is really hindging on "not yet invented". I do think we're all hopeful for true AGI, full humanoid robots that can replace all home labor, fully self driving cars that are not constrained by terrain, weather, or location. And so on...
It depends, there were a lot of studies that showed prejudice and bias in the meritocratic process. You had examples of CVs with woman names removed getting more callbacks, and anonymous interviews having higher rates of hire and such.
Due to this, people considered affirmative actions to correct for this skew. That would actually make it a meritocratic motivated AA.
And then you have the idea of missed potential. Those who weren't given the opportunity to develop, it limits the pool of exceptional candidates. It's similar to when black athletes weren't allowed in sports. We thought we had a meritocratic process, but we were artificially limiting those with potential. The challenge is bigger here, so you need a bootstrapping process, because you're faced with a chicken and egg situation. You wouldn't know if it works or not unless you give it at least one if not two generations to take effect. I admit that this is the more controversial one, as it means temporarily favoring disadvantaged groups to bootstrap things. I just wanted to point out that there's a meritocratic angle to it as well.
Equity doesn't mean give those that suck a boost. It means give those that weren't given the environment to develop their full potential a chance at it, they may end up being even better than the alternative.
Yes, that's what I'm saying. These systems claimed to be meritocratic but empirically weren’t. AA was introduced as a corrective, not a rejection of merit. Was it successful at correcting it, did it introduce other defects, I don't know, but you can see that implementation of AA can result from wanting to be more meritocratic, not less.
> It depends, there were a lot of studies that showed prejudice and bias in the meritocratic process.
A meritocratic process by definition is not prejudiced or biased. There were studies that claimed to show processes to not actually be meritocratic. In my experience, these findings either haven't reproduced or don't appropriately account for confounders; and if they held up they would be pointing at things that are already illegal (and irrational).
> It's similar to when black athletes weren't allowed in sports. We thought we had a meritocratic process
What? How do you come to the conclusion that "we" thought any such thing? The term (https://en.wikipedia.org/wiki/Meritocracy) was coined in the 50s for socialist criticism invoking satire. The discourse had nothing to do with race and was about disputing how merit is measured, not about supposed prejudices (except perhaps class privilege). Nor did coaches, managers etc. imagine any inferiority on the part of black athletes in regards to physical prowess. Segregation was to keep the peace; see e.g. https://en.wikipedia.org/wiki/Baseball_color_line :
> Before the 1860s Civil War, black players participated in the highest levels of baseball.[2] During the war, baseball rose to prominence as a way to bring soldiers from various regions of the country together. In the aftermath of the war, baseball became a tool for national reconciliation; due to the racial issues involved in the war, baseball's unifying potential was mainly pursued among white Americans.[3]
Anyway,
> You wouldn't know if it works or not unless you give it at least one if not two generations to take effect.
This time lapse isn't required for a moral judgment, however.
> Equity doesn't mean give those that suck a boost. It means give those that weren't given the environment to develop their full potential a chance at it, they may end up being even better than the alternative.
An employer, or a college admissions officer, cannot provide what was missing from someone's "environment" during the formative years, and should not be expected to try; nor ought they shoulder the risk of anyone's "full potential" being absent. Everyone might as well hire randomly from the general population at that point.
Historically, institutions were widely believed to be selecting the best available candidates within the accepted social boundaries of the time. They did not call it meritocracy, but it was assumed.
AA advocacy exposed cracks in systems that claimed to be merit based and pushed reforms like anonymization and structured evaluation, which made selection more merit based, not less.
Merit is noisy and ties are unavoidable. When candidates are effectively equal, a tie breaker is required. The old default was incumbency and other status quo dynamics that favored the existing cohort. Random selection among equals would be defensible. Favoring candidates from groups historically denied opportunity is another possible tie breaker. You can disagree with that choice, but it is coherent to see it as pro merit rather than anti merit.
And that's just my point, some proponents of AA were arguing for better merit based systems, not all, but a lot did.
> within the accepted social boundaries of the time
Pulls a lot of weight there.
> AA advocacy exposed cracks in systems
No; it proposed a supposed justice for those former social boundaries.
> and pushed reforms like anonymization and structured evaluation
No, these are clearly not anything to do with AA programs as actually observed today. It's extremely disingenuous to attribute the "colourblindness" of the 90s to "AA" and then use that to justify the explicitly race-conscious policies of today.
> You can disagree with that choice, but it is coherent to see it as pro merit rather than anti merit.
No, it is not. It completely ignores what the word "merit" means.
It's an interesting case study, and I'm glad it worked for them. But I feel there would have been many other ways to solve the problem.
In fact, one thing I'm confused about, and that's not very clear to me, it sounds like prior to this new system, each food bank would just receive a random selection of foods of a given weight. But with the new system, they can choose exactly what foods they want to receive.
If so, this is a huge difference that has nothing to do with the bidding. A lot of the inefficiencies were probably due to this alone. You'd be getting things you don't need and not those you do and it created waste.
Now food banks could pick and choose what they needed.
This even justifies the introduction of bidding. Because once you have a proper catalogue and food banks can choose what they want, you have the problem of what if they all want the same limited quantity items?
You can make it first come first served. Now food banks would compete on being the quickest to enter their order. Or you can do other things, they went with bidding.
From that angle, bidding actually can look a lot fairer and "socialist" than "first come first served".
There's an interesting psychology at play here as well, if you are a programmer that chooses a "fast language" it's indicative of your priorities already, it's often not much the language, but that the programmer has decided to optimize for performance from the get go.
What I'm wondering is, why couldn't the AI generate this solution? And implement it all?
Why did they need to spend human time and effort to experiment, arrive at this solution and implement it?
I'm asking genuinely. I use GenAI a lot, every day, multiple times a day. It helps me write emails, documents, produce code, make configuration changes, create diagrams, research topics, etc.
Still, it's all assisted, I never use its output as is, the asks from me to the AI are small, so small, I wouldn't ever assign someone else a task this small. We're not talking 1 story point, we're talking 0.1 story point. And even with those, I have to review, re-prompt, dissect, and often manually fix up or complete the work.
Are there use-cases where this isn't true that I'm simply not tackling? Are there context engineering techniques that I simply fail to grasp? Are there agentic workflows that I don't have the patience to try?
How then, do models score so high on some of those tests, are the prompts to each question they solve hand crafted, rewritten multiple times until they find a prompt that one-shot the problem? Do they not consider all that human babysitting work as the model not truly solving the problem? Do they run the models with a GPU budget 100x that they sell us?
> What I'm wondering is, why couldn't the AI generate this solution? And implement it all?
My read of the blog post is that is exactly what happened, and the human time was mostly spent being confused why 40MB/s streams don't work well at a coffee shop.
I think you're asking a good question and it's not unreasonable at all.
The way I see it, the private sector is in a place to even potentially be able to fund research because of prior publicly funded research.
The capital expenditure needed to fund research in a way that leads to breakthroughs is massive. Private sector doesn't always have the cash needed. Definitely this was true for a long time, and is true for many countries still.
Then generally the private sector is pretty risk adverse, the majority of private sector funds are retirement and savings. People don't want to risk that, so it tends to invest in short term or more known ventures, which is rarely research.
Some private funding is research moonshots, but the pool of private money interested in that is a lot smaller.
That means, at least historically, private funding simply isn't incentivized to properly fund research, and may not always have the means to do so.
Now should the public still fund it? What kind of ROI does society gets?
Again, at least historically, the ROI has been massive. Let's just look at a short list:
- Internet
- GPS
- Semiconductor
- MRI/CT scans
- Vaccines
- Jet engine, aviation
- Lithium Ion batteries
- Touchscreens
- AI
- Fracking
- Mass agriculture
- Space exploration
You could also question investment in art and humanities. Private sector simply isn't interested. Do we want to learn about our history, preserve our arts, these don't have financial ROI, but depending on your opinion on the matter they could be societal ROI because you might want to live in a society with a rich culture and record of its heritage and a good understanding of its evolutionary roots and what not.
To be honest, it's hard to find a single private sector breakthrough that wasn't off the back of the public sector either through direct funding, prior discovery or indirect subsidy.
I feel the issue is that after the public funding achieves breakthrough, the private sector quickly capitalizes on the profits. At the same time, the private sector is really good at commercializing and finding efficiency and market fit. The ROI happens indirectly, society modernizes through access to new things, the private sector creates jobs, taxes are paid on private transactions and income generated from the discovery, etc.
At the end of the day, it's all opportunity cost. What else do we do with the money. You said paying down the dept, what's the societal ROI of that? Why not lay down the dept with some of the other tax money? Etc. It's a complex question.
As an aside, this is an example of why I always take history with a grain of salt. All historical knowledge is akin to LLM, most of it is hallucinated. The actual evidence is often meeger, contested, incomplete, hearsay, hard to understand the intent and meaning, and so on.
This next batch of "sacred treasures" really seems crappy in comparison to the previous batch.
I'm not sure I see how the "simple things" would come, since those have only gotten less accessible since the 50s even in countries like the US whose economy grew year over year and didn't stagnate.
So everything is really hindging on "not yet invented". I do think we're all hopeful for true AGI, full humanoid robots that can replace all home labor, fully self driving cars that are not constrained by terrain, weather, or location. And so on...
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