[HN Gopher] Anthropic Economic Index report: economic primitives
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Anthropic Economic Index report: economic primitives
Author : malshe
Score : 95 points
Date : 2026-01-22 21:54 UTC (1 days ago)
(HTM) web link (www.anthropic.com)
(TXT) w3m dump (www.anthropic.com)
| mips_avatar wrote:
| Every single AI economic analysis talks about travel planning but
| none of the AI labs have the primitives (transit routing,
| geocoding, etc.) in a semantic interface for the models to use.
| malshe wrote:
| Coincidentally, YouTube demos on vibe coding commonly make
| travel planning apps!
| doganugurlu wrote:
| Unfortunately, in this context travel planning means planning a
| vacation. And not the travel route of a traveling salesman.
| bix6 wrote:
| > These "primitives"--simple, foundational measures of how Claude
| is used, which we generate by asking Claude specific questions
| about anonymized Claude.ai and first-party (1P) API transcripts
|
| I just skimmed but is there any manual verification / human
| statistical analysis done on this or we just taking Claude's word
| for it?
| sdwr wrote:
| Looks like they are relying on Claude for it, which is
| interesting. I bet social scientists are going to love this
| approach
| adverbly wrote:
| This is very cool but it's not quite what I expected out of
| economic primitives.
|
| I expected to see measures of the economic productivity generated
| as a result of artificial intelligence use.
|
| Instead, what I'm seeing is measures of artificial intelligence
| use.
|
| I don't really see how this is measuring the most important
| economic primitives. Nothing related to productivity at all
| actually. Everything about how and where and who... This is just
| demographics and usage statistics...
| kurttheviking wrote:
| agree, was similarly hoping for something akin to a total
| factor productivity argument
| johnrob wrote:
| Until AI is used to generate new revenue streams (i.e. acquire
| new customers), I don't think the economic impact is going to
| impress. My two cents.
| p1necone wrote:
| > I expected to see measures of the economic productivity
| generated as a result of artificial intelligence use.
|
| >Instead, what I'm seeing is measures of artificial
| intelligence use.
|
| Fun fact: this is also how most large companies are measuring
| their productivity increases from AI usage ;), alongside asking
| employees to tell them how much faster AI is making them while
| simultaneously telling them they're expected to go faster with
| AI.
| hazyc wrote:
| productivity is such a nebulous concept in knowledge work -
| an amalgamation of mostly-qualitative measures that get baked
| into quantitative measures that are mostly just bad data
| reactordev wrote:
| You can thank agile for that
| janwirth wrote:
| You don't seem to like agile, whatever that word even
| means.
| reactordev wrote:
| On the contrary. I like agile for when you don't know
| exactly what you're building but you can react quickly to
| change and try to capture it.
|
| Moving fast and breaking things, agile.
|
| On the other hand. When you know what you want to build
| but it's a very large endeavor that takes careful
| planning and coordination across departments, traditional
| waterfall method still works best.
|
| You can break that down into an agile-fall process with
| SAFe and Scrum of Scrums and all that PM mumbo jumbo if
| you need to. Or just kanban it.
|
| In the end it's just a mode of working.
| PunchyHamster wrote:
| Knowing exactly what you want to build is pretty rare and
| is pretty much limited to "rewriting existing system" or
| some pretty narrow set of projects
|
| In general, delaying infrastructure decisions as much as
| possible in process usually yields better infrastructure
| because the farther you are the more knowledge you have
| about the problem.
|
| ...that being said I do dislike how agile gets used as
| excuse for not doing any planning where you really should
| and have enough information to at least pick direction.
| adverbly wrote:
| economic productivity is absolutely not nebulous. Its a
| measure of GDP per hour worked.
|
| https://ourworldindata.org/grapher/labor-productivity-per-
| ho...
| xkcd-sucks wrote:
| When your OKRs for the past year include "internal adoption
| of ai tools"
| salynchnew wrote:
| So.... motivated reasoning makes the world go 'round?
|
| https://en.wikipedia.org/wiki/Motivated_reasoning
| fuzzfactor wrote:
| >expected to see measures of the economic productivity
|
| I know what you mean.
|
| Imagine my disappointment when I was expecting their unique
| approach and brainpower to have arrived at a straightforward
| index of overall world macroeconomic conditions rather than an
| internal corporate outlook for AI alone.
| amelius wrote:
| I expected a simulation of the economy using economic
| primitives and AI.
| PunchyHamster wrote:
| I think we can surmise how bad that looked from the omission..
| sinnsro wrote:
| I wonder if it is even possible to get such measurements.
| With so many things affecting output, how can one establish a
| baseline or avoiding to compare apples to oranges?
| brap wrote:
| All of this performative bullshit coming out of Anthropic is
| slowly but surely making them my least favorite AI company.
|
| We get it guys the very scary future is here any minute now and
| you're the only ones taking it super seriously and responsibly
| and benevolently. That's great. Now please just build the damn
| thing
| ossa-ma wrote:
| These are economic studies on AI's impact on productivity,
| jobs, wages, global inequality. It's important to UNDERSTAND
| who benefits from technology and who gets left behind. Even
| putting the positive impacts of a study like this aside - this
| kinda due diligence is critical for them to understand
| developing markets and how to reach them.
| brap wrote:
| Ok Dario
| futuraperdita wrote:
| But the thing is that they really aren't rigorous economic
| studies. They're a sort of UX research-like sociological
| study with some statistics, but don't actually approach the
| topic with any sort of econometric modeling or give more than
| loose correlations to past economic data. So it does appear
| performative: it's "pop science" using a quantitative veneer
| to push a marketing message to _business leaders_ in a way
| that looks well-optimised mathematically.
|
| Note the papers cited are nearly all ones _about AI use_ ,
| and align more closely with management case studies vs.
| economics.
| mlsu wrote:
| > This also highlights the importance of model design and
| training. While Claude is able to respond in a highly
| sophisticated manner, it tends to do so only when users input
| sophisticated prompts.
|
| If the output of the model depends on the intelligence of the
| person picking outputs out of its training corpus, is the model
| intelligent?
|
| This is kind of what I don't quite understand when people talk
| about the models being intelligent. There's a huge blindspot,
| which is that the prompt entirely determines the output.
| thousand_nights wrote:
| i don't know, are we intelligent?
|
| you could argue that our input (senses) entirely define the
| output (thoughts, muscle movements, etc)
| HPsquared wrote:
| There's a bit of baked-in stuff as well. We are a full
| culture-mind-body[-spirit] system.
| fuzzfactor wrote:
| Fortunately we've got the full system because even under
| ideal conditions nobody's actually ever been intelligent
| _at all times_ and we need the momentum from that full
| system to resume in an intelligent direction after an upset
| when it 's not all at its best.
| bossyTeacher wrote:
| The whole point of humans is the way we process the input.
| Every life form out there receives sound vibrations and has
| photons hitting their body all the time, not everyone uses
| that information in the same way or at all. That plus natal
| reflexes and hardcoded assumptions
| wat10000 wrote:
| A smart person will tailor their answers to the perceived level
| of knowledge of the person asking, and the sophistication of
| the question is a big indicator of this.
| TrainedMonkey wrote:
| Humans also respond differently when prompted in different
| ways. For example, politeness often begets politeness. I would
| expect that to be reflected in training data.
| mlsu wrote:
| If I, a moron, hire a PhD to crack a tough problem for me, I
| don't need to go back and forth prompting him at a PhD level.
| I can set him loose on my problem and he'll come back to me
| with a solution.
| Herring wrote:
| Well if it ever gets to be a full replacement for phds,
| you'll know cause it will have already replaced you.
| nl wrote:
| > hire a PhD to crack a tough problem for me, I don't need
| to go back and forth prompting him at a PhD level. I can
| set him loose on my problem and he'll come back to me with
| a solution.
|
| In my experience with many PhDs they are just as prone to
| getting off track or using their pet techniques as LLMs!
| And many find it very hard to translate their work into
| everyday language too...
| HPsquared wrote:
| I think that's what is happening. It's simulating a
| conversation, after all. A bit like code switching.
| b00ty4breakfast wrote:
| that seems like something you wouldn't want from your tools.
| humans have that and that's fine, people are people and have
| emotions but I don't want my power-drill asking me why I only
| call when I need something.
| freejazz wrote:
| >Humans also respond differently when prompted in different
| ways.
|
| And?
| zozbot234 wrote:
| What is a "sophisticated prompt"? What if I just tack on
| "please think about this a lot and respond in a highly
| sophisticated manner" to my question/prompt? Anyone can do this
| once they're made aware of this potential issue. Sometimes the
| UX layer even adds this for you in the system prompt, you just
| have to tick the checkbox for "I want a long, highly
| sophisticated answer".
| mlsu wrote:
| They have a chart that shows it. The education level of the
| input determines the education level of the output.
|
| These things are supposed to have intelligence on tap. I'll
| imagine this in a very simple way. Let's say "intellignce" is
| like a fluid. It's a finite thing. Intelligence is very
| valuable, it's the substrate for real-world problem solving
| that makes these things ostensibly worth trillions of
| dollars. Intelligence comes from interaction with the world;
| someone's education and experience. You spend some effort and
| energy feeding someone, clothing them, sending them to
| college. And then you get something out, which is
| intelligence that can create value for society.
|
| When you are having a conversation with the AI, is the
| intelligence flowing out of the AI? Or is it flowing out of
| the human operator?
|
| The answer to this question is extremely important. If the AI
| can be intelligent "on its own" without a human operator,
| then it will be very valuable -- feed electricity into a
| datacenter and out comes business value. But if a model is
| only intelligent as someone using it, well, the utility seems
| to be very harshly capped. At best it saves a bit of time,
| but it will never do anything novel, it will never create
| value on its own, independently, it will never scale beyond a
| 1:1 "human picking outputs".
|
| If you must encode intelligence into the prompt to get
| intelligence out of the model, well, this doesn't quite look
| like AGI does it?
| mlsu wrote:
| ofc what I'm getting at is, you can't get something from
| nothing. There is no free lunch.
|
| You spend energy distilling the intelligence of the entire
| internet into a set of weights, but you still had to expend
| the energy to have humans create the internet first. And on
| top of this, in order to pick out what you want from the
| corpus, you have to put some energy in: first, the energy
| of inference, but second and far more importantly, the
| energy of prompting. The model is valuable because the
| dataset is valuable; the model output is valuable because
| the prompt is valuable.
|
| So wait then, where does this exponential increase in value
| come from again?
| felixgallo wrote:
| the same place an increase in power comes from when you
| use a lever.
| retsibsi wrote:
| > the same place an increase in power comes from when you
| use a lever.
|
| I don't understand the analogy. A lever doesn't give you
| an increase in power (which would be a free lunch); it
| gives you an increase in force, in exchange for a
| decrease in movement. What equivalent to this tradeoff
| are you pointing to?
| nl wrote:
| In general it will match the language style you use.
|
| If you ask a sophisticated question (lots of clauses, college
| reading level or above) it will respond in kind.
|
| You are basically moving where the generation happens in the
| latent space. By asking in a sophisticated way you are moving
| the latent space away from say children's books and towards
| say PhD dissertations.
| aisuxmorethanhn wrote:
| I don't find this to be true at all. You can ask it in text
| speech with typos and then append how you'd like the
| response to be phrased and it will follow the instructions.
| dingdingdang wrote:
| The title actually cringes me out a bit, it reads like early
| report titles in academia where young students (myself no doubt
| incl back when) try their hardest at making a title sound clever
| but in actuality only achieve obscuration of their own material.
| bilsbie wrote:
| Reminds me of psychohistory.
| dingdingdang wrote:
| Never read the Foundation series, the concept of
| psychohistory makes me want to though!
| blibble wrote:
| > How is AI reshaping the economy?
|
| oh I know this one!
|
| it's created mountains of systemic risk for absolutely no payoff
| whatsoever!
| andy_xor_andrew wrote:
| no payoff whatsoever? I just asked Claude to do a task that
| would have previously taken me four days. Then I got up and got
| lunch, and when I was back, it was done.
|
| I would never make the argument that there are no risks. But
| there's also no way you can make the argument there are no
| payoffs!
| blibble wrote:
| > I just asked Claude to do a task that would have previously
| taken me four days.
|
| I think this probably says more about you than the "AI"
| steve_adams_86 wrote:
| That's not a very constructive thought given you don't know
| what the task is or why it could have taken them days. In a
| field as large and complex as software, there are myriad
| reasons why any single person could find substantial time-
| saving opportunities with LLMs, and it doesn't have to
| point to their own inadequacies.
| siliconc0w wrote:
| Skimmed, some notes for a more 'bear' case:
|
| * value seems highly concentrated in a sliver of tasks - the top
| ten accounting for 32%, suggesting a fat long-tail where it may
| be less useful/relevant.
|
| * productivity drops to a more modest 1-1.2% productivity gain
| once you account for humans correcting AI failure. 1% is still
| plenty good, especially given the historical malaise here of only
| like 2% growth but it's not like industrial revolution good.
|
| * reliability wall - 70% success rate is still problematic and
| we're getting down to 50% with just 2+ hours of task duration or
| about "15 years" of schooling in terms of complexity for API. For
| web-based multi-turn it's a bit better but I'd imagine that would
| at least partly due to task-selection bias.
| xiphias2 wrote:
| ,,1% is still plenty good, especially given the historical
| malaise here of only like 2% growth but it's not like
| industrial revolution good.''
|
| You can't compare the speed of AI improvements to the speed of
| technical improvements during the industrial revolution.
| ChatGPT is 3 years old.
| storystarling wrote:
| I've found that architecting around that reliability wall is
| where the margins fall apart. You end up chaining verification
| steps and retries to get a usable result, which multiplies
| inference costs until the business case just doesn't work for a
| bootstrapped product.
| ossa-ma wrote:
| I'm not an economist so can someone explain whether this stat is
| significant:
|
| > a sustained increase of 1.0 percentage point per year for the
| next ten years would return US productivity growth to rates that
| prevailed in the late 1990s and early 2000s
|
| What can it be compared to? Is it on the same level of
| productivity growth as computers? The internet? Sliced bread?
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(page generated 2026-01-23 23:00 UTC)