This is an extremely important article to read for professionals of all sorts, not just freelancers.
It's an issue that I struggle with nearly daily. I can't convince customers to pay me what I'm worth, because they can't judge my true value. Meanwhile, they'll happily pay Deloitte or Accenture 3x as much as what I charge, and then take the misguided ramblings of a junior-sold-as-senior at face value, not knowing the difference.
> I’ve noticed that in nearly every skill tree I’ve climbed, there comes a point where you begin to notice certain nuances of skill that novices not only don’t notice, but that you cannot articulate using the commonly accepted vocabulary of the skill.
This happened to me just over the last month or so. I was trying to explain to a CTO how horrifically wrong it is to plumb their entire cloud network through just a pair of virtual machines for "security". I just could not make him understand that 5 milliseconds of additional latency in the era where microseconds are an eternity is a disaster for a veritable smorgasbord of upcoming projects. It just. Would. Not. Sink. In.
To some people, "micro" and "milli" sound the same. Latency just doesn't compute as a thing to be concerned about.
I've spent my career performance tuning, but then how do I explain this to people who think a 60-second timeout is a performance problem best solved by buying another million dollars worth of kit?
The article jumps between martial arts and the world of finance, so I'll jump to another example: AI playing games.
When I watched AlphaZero play chess, I was just a tiny bit impressed. I watched it beat the Go grandmaster and I was not very impressed. Then I watched it play Dota 2 -- in which I've sunk several thousand hours -- and holy crap. Wow! It was suddenly terrifying how good it was, because I could judge the nuance of what it was doing.
> To some people, "micro" and "milli" sound the same
To be fair, it almost is. Both units are used to talk about times of about the same size. Using both in the same sentence is like mixing meters and feet. It's much clearer to say e.g. 1500us vs 3us; or 1.5ms vs 0.003ms.
The reason things take minutes is because people ignore order of magnitude diffences when they're insignificant, (it doesn't matter if X takes 10ms instead of 0.1ms), and then over time someone builds on that and makes the same assumption (it doesn't matter if it takes 100ms, when it could take 1ms, followed by it doesn't matter if it takes 10s). Avoiding these order of magnitude differencdz early on is the best way to ensure you don't end up with a SPA that takes 15 seconds to populate a list with 20 items in it.
The lack of expertise here is confirming the point of the article.
I'm not mixing units.
Milliseconds and microseconds are both measured in units of seconds.
The milli- and micro- prefixes are orders of magnitude. They're scales, not units.
When a scientist starts talking about measurements accurate to attoseconds, I sit up and take notice.
The number in front doesn't make a difference. It's the "atto" that raises my eyebrows.
Back to computing:
I had a debate here with someone who claimed that 128-bit floats are required for some chip layout codes. I questioned that, because a 32-bit number can subdivide the side-length of a chip down to sub-atomic resolution, and a 64-bit float can model the wiggles of the hadrons making up the atomic nuclei!
To some people, 128-bit sounds "twice as good as 64-bit".
To experts, it's... umm... a sign you've made a mistake.
We can absolutely go into a long side-discussion about units and how most imperial units are also clearly just a constant-factor away from SI units and nobody would argue they are the same unit, but I don't think any of that actually matters. It's semantics.
When you are an expert, nearly by definition the average person you're talking to is less well read on the subject than you, the expert. Because of this, it's extremely important to be able to communicate with clarity and patience.
Your expertise doesn't matter if you can't make yourself understood, and it's not reasonable to expect people around you to share your expertise, so you need to adapt the message.
Communication in general is easier the fewer concepts you invoke. In almost all situations it's better to be mostly correct and well understood than to be perfectly correct and not understood at all.
Even if you can expect most people to have an understanding of SI units, far fewer will have an intuition for them (because they aren't working with them daily). Everyone has a basic intuition for big numbers though, so if you want to say "this is bad", show them a big number; the bigger the better.
It can still be correct and make a well founded argument, but presentation matters a lot more than you'd think for convincing someone. In increasing order of likelihood it will convince anyone:
The new solution adds a 15ms latency, whereas our usual requests have a 2us latency.
The new solution adds a 15ms latency, whereas our usual requests have 0.002ms latency.
The new solution is a factor 7.5e3 slower than the existing solution, which has a 2 microsecond latency.
The new solution is 7,500 times slower than the existing solution, which has a 2 microsecond latency.
The new solution is 75,000% slower than the existing solution, which has a 2 microsecond latency.
What is said is basically identical in each version, but the presentation puts an increasing emphasis on just how big a difference this is by literally showing a big number.
I whole heartedly disagree. Micrometers and millimetres are very, very different and that should be obvious to anyone that uses grams and kgs, or meters and km everyday. Microseconds and milliseconds are obviously different orders of magnitude, that's sort of the whole point of SI prefixes.
That CTO is just doesn't sound qualified for the job.
I felt the context was really far down the stack, so services that lots of other services would be depending on was how I read it. The places I want fast, high volume and never failing cause so much depends on a red wheelbarrow.
It sounds like you were just telling the CTO "this is wrong" instead of offering an alternative solution?
If that's the case it's not surprising it didn't sink in. You're just giving him another problem.
> I've spent my career performance tuning, but then how do I explain this to people who think a 60-second timeout is a performance problem best solved by buying another million dollars worth of kit?
I'm surprised you've spent your career doing this and you still haven't figured out how to get people to listen to you.
Making your work legible to others feels as important as the work itself.
> I'm surprised you've spent your career doing this and you still haven't figured out how to get people to listen to you.
This is the point of the article, which you appear to have missed.
There's a point where it becomes essentially impossible to articulate the differences to the lay person. Or for that matter, someone actually quite skilled, but not a "master".
It's not a lack of skill on the part of the expert, it's the lack of skill on the part of everybody else.
But is this really the point of the article? The article argues that it is difficult to identify expertise. However, the situation you describe is one where (if I read you correctly) not your expertise was questioned but your recommendation. If there wasn’t any tangible difference between the CTO’s and your suggested course of action on a metric that he as a customer cared about, then maybe his proposal was indeed the better one? And yes, probably he didn’t care about the exact latencies in the system, but he would probably care about customer retention, system availability, etc.?
I'm finding this entire line of discussion incredibly curious because not only does it confirm my original argument and the that of the article, but it hammers the point home.
Everything you've just said is gibberish to a master.
It's like making a straight-faced argument that setting the speed limit to 1 mph on a motorway might make perfect sense, and the traffic engineer is actually at fault for not making it clear that this is nonsense.
I get that you don't see the ridiculousness of 50 microseconds vs 5 milliseconds, but that's the point.
You don't see it, and you start making random arguments untethered from reality.
The fact that you are blind to it, unlike being blind to 1 mph vs 65 mph is the entire point.
You may have driven thousands of hours. You have don't have thousands of hours of network performance tuning expertise.
Both of us wouldn't be able to even begin to understand the complaints Ayrton Senna might make about how the steering is too "crunchy" at the extremes or that the brake strength imbalance is shifting the car about.
There's levels of expertise, and if two people are too far apart, meaningful communication between them becomes impossible.
Really does sound like you have difficulties with communicating your points that do not have to do with external factors, but with your actual skill at communicating. Experts manage to successfully argue fine points to laypersons all the time to non experts in every field. You are coming across as deflective.
He is not deflective. Your comments are rather dense. The orthodoxy of ‘changing frame’ and ‘putting it in a language they understand’ is layman drivel. It is not always possible to do so and it is overwhelmingly untractable if you eskew the fundamental reasons in a discussion with a non-expert that insists on technical justification and just doesn’t take your cookie-cutter time/money/competitive advantage talking points and can’t provide you with specifics that can be quantified.
What real life project only involves experts on specific field? Are you working on toy problems? Isn't there cost/benefit analysis to everything? If I understand something well, I can explain it to non-experts in understandable way. If I can't, then I probably lack full grasp of the topic
> I can explain it to non-experts in understandable way
Ok? But you are required to motivate a decision that is based on terms, conditions, probabilities, consequences that can only be encoded at knowledge-level A. When projected down to knowledge-level C, it sounds like "otherwise bad things might happen".
The jargon is not what matters. The logic of the decision is not meaningful or believable without knowledge of the "physics of the system" at level A.
Most people understand nuclear bombs in layman terms, and they understand them intuitively from watching videos and pictures. Without videos and pictures, no one would care.
It's the job of an expert to communicate their understanding of the world in a way that motivates non experts to make the correct the decision. If an expert isn't successful in this, they need to improve their methods of communication. Everything else is an excuse.
This presumes that the expert shouldn’t be the one making the decision.
Law firms are run by lawyers. The chief of surgery is a surgeon. Architecture firms are run by architects at the top.
Why is it that in IT it is expected that all management of IT is “non technical” to the point of not understanding what they’re hearing from direct reports!?
Would it be normal in your mind for a chemical plant foreman in charge of the process to not know what atoms are!?
If I were to guess, I would say an average 4th grader knows the difference between nano, milli or micro seconds. Understanding the magnitude might not be the problem for the CTO. But why should the CTO care? How does it translate to his business requirements? That's your job to explain, no?
> If I were to guess, I would say an average 4th grader knows the difference between nano, milli or micro seconds.
Have you ever spent any significant time in an environment where most people are not (children of) college graduates? Because this is absurd. The average person who has just finished a year of high school physics probably can’t tell you those.
So it’s 100x more latency, but why does that matter for the business? Your CTO may be wondering about that. As yet, that answer doesn’t seem to have been provided in this thread. (Not that it needs to be answered here; perhaps it was explained to the CTO and they’re just that dense.)
The person who was talking about this optimization should know that they should provide context.
Do they work for a high frequency trading firm? Do they make a CRUD app which has few users and (as much as I hate that) "they can wait even 5 seconds".
If the person does not give context then they dont explain well..
On a side note: for me the problem seems to be not the speed, but the choke point - just 2 servers (with no redudancy?). What one or both go down?
But again: is the CTO really not able to spot the expertise or is the expert so detached that he can’t translate between the worlds anymore? I find it much easier to believe that the CTO fully understands that he has an expert in front of him who knows what he is talking about but doesn’t see the relevance of the recommendation. My doctor might tell me that I should eat more vegetables and I’m fully convinced of the doctor’s expertise, but I might still not follow the advice
> Everything you've just said is gibberish to a master
That is rather a condescending take: calling yourself a master and calling their words gibberish is hardly thoughtful dialogue. Other parts of your comment are equally bad “ untethered from reality” should not be written. Someone is trying to engage with you and you are dismissing them by using very charged words. Even worse you are demonstrating poor communications skills - that point being questioned elsewhere in the thread. I hope you can learn to listen to others politely even when you disagree, and please try to follow https://news.ycombinator.com/newsguidelines.html :
Be kind. Don't be snarky. Converse curiously; don't cross-examine. Edit out swipes. Comments should get more thoughtful and substantive, not less, as a topic gets more divisive. When disagreeing, please reply to the argument instead of calling names. "That is idiotic; 1 + 1 is 2, not 3" can be shortened to "1 + 1 is 2, not 3." Please don't fulminate. Please don't sneer.
I see this so often: engineers who think it’s demeaning to explain deeply technical things in business terms, so they refuse. Like it’s somehow noble to only speak one language.
> engineers who think it’s demeaning to explain deeply technical things in business terms, so they refuse
I can, and have, explained 'deeply technical things' in 'business terms'. And people understood. Then made a bad/poor/wrong choice anyway, because... "well... all those things you're saying might happen, they might not. Or... it may not happen for months or years, and we already committed to date X for project Y".
I can tell people the cost of punting on 'deeply technical thing' will be enormous, like... "this will require doubling the dept headcount and stopping all new progress for 6-12 months". Then offer alternatives. Then get summarily ignored, and watch things crash months later, and the dept is then stuck for months scrambling to understand all the problems they could have avoided. The decision maker who decided for extremely short term gain? They're gone (sometimes of their own choosing, sometimes not).
The "risks" can seem wildly out of touch with reality, but many times if you're making poor choices you do hit the "worst case scenario" wall. Colleague has been contracting inside a shop on and off for a few years. He indicated "if we don't do X, we will not be able to do any new feature development for at least 18 months". And... closing in on 4 years later, they've not shipped any substantial new features (some bug fixes, but that's about it).
I've seen this happen once up close, and have seen inside other companies and got the war stories from others.
Does this happen every single time? Of course not. But even if you can confidently and correctly and pleasingly describe deep tech things to business folks in their own language, showing the pros/cons/costs/risks... that doesn't mean they will take your side. Saving face, hitting deadlines at all costs, and other factors weight on decisions, and you can't control that. You can control where and how you work though.
My equivalent of this was finding a brand new SAN array had been formatted wrong. It was nearly empty and unused so it would have been a 5-minute job to format 99% of it and shuffle the in-use 1% around so that the rest can be fixed too.
Both the storage vendor tech and I vehemently argued for solving this immediately but were told to “do it later”.
I pointed out that “later” would be when it is full and has 10K production users using it 24/7. Hence any reformatting would be a six-month project requiring additional kit for the scratch space needed. Not to mention the risk!
It sounds like you cannot convince them based on merit, because they simply do not understand you and the language you speak. It sounds like you need to change tack, convince them you're an expert in $field without using words and prhases from $field; keep your secrets and knowledge, feed them some generic drivel. Maybe hire someone that can help you with your sales pitch.
I mean who would be convinced by an “expert” who can’t explain to a non-expert?
Yes, maybe I desperately need to frobulize the macrowublitz to avoid pracknation, but I’ll wait for someone who can explain why it’s a high priority to achieve my goals.
That is very much not the point of the article. The article is very focused on exploring the idea of identifying expertise and only briefly mentions money in the beginning of the piece.
Cedric explicitly directs people to another article which discusses how this idea relates to money: "Bellotti’s observations are worth reading in their entirety, especially if you’re interested in the actionable implications of the idea. But I’d like to take this property of expertise in another direction. Now that we know that expertise is more legible to experts, could we perhaps invert this observation and turn it into a goal by itself? Could you turn this into something that helps you acquire expertise?".
If two nearly identical wallets (very minor, but noticeable differences) are placed on a counter and one is significantly more expensive... how would you expect those wallets to sell?
I would expect both of them to sell out. The people looking for a higher quality product will immediately go for the more expensive product, and the remaining wallets would sell to people who just need a wallet.
> The people looking for a higher quality product will immediately go for the more expensive product
It is more complicated than that. There is no guarantee that the more expensive wallet is also the higher-quality product. The people looking for a higher-quality product can be classified into those who can measure the quality well (perhaps by observing those minor differences), and those who have to use less effective proxies of quality (like price).
This day and age we can make our own inflation.
We are all free to pay as much or as little for wallet as we would like.
So we all shop by price, quality, or availability.
> When I watched AlphaZero play chess, I was just a tiny bit impressed. I watched it beat the Go grandmaster and I was not very impressed. Then I watched it play Dota 2 -- in which I've sunk several thousand hours -- and holy crap. Wow! It was suddenly terrifying how good it was, because I could judge the nuance of what it was doing
Funny, my game of choice is StarCraft 2 and when I watched AlphaStar beat StarCraft 2 pros I was significantly less impressed than when I watched AlphaGo beat Lee Sedol at Go.
You should be more impressed knowing that that AlphaStar was handicapped. Its clicking was rate-limited and its inputs were delayed by something like 150 milliseconds to make it "fair" for the humans.
If you remove those limits, it would absolutely wipe the floor with the twitching corpse of any human player.
I saw it play Warcraft 2 without the limiters, and it was just ridiculous. It would dance the units around and keep using them with 1 hp left for many minutes and then heal them back up juuuuust enough to take exactly one hit from an enemy.
But not having human reaction time in a real-time game isn't interesting. And the strategies that arise from that aren't either. If anything, human-level I/O constraints should make the AI more impressive because it's actually playing the same game.
The handicapping was very ineffective. AlphaStar had 250-300+ APM and it was basically 100% effective APM. Pros have 300-400+ APM, but their effective APM is much lower due to spam patterns and checking production among other things.
Almost everyone in the community seemed to agree AlphaStar was very unfair. Things like a 3 way surround and performing blink micro on individual Stalkers on opposite sides of the screen are completely inhuman.
This is also what made the Dota 2 bots feel somewhat disappointing. Of course perfect mechanical skill beats humans. Watching the SF mid 1v1 matches illustrated this very clearly to me. The AI chipped the player down with perfect AAs, then finished them off with perfect distance razes.
The bots weren't 100% mechanical skill, but it was a large enough proportion that it was uninteresting.
My knowledge of Starcraft 2 is pretty limited so this is my lack of expertise speaking but it always felt like a strange choice to demonstrate AI skill. Even limiting the AI to human level actions per minute - so much of the game seems to about efficient multitasking which obviously computers are good at.
> Meanwhile, they'll happily pay Deloitte or Accenture 3x as much as what I charge, and then take the misguided ramblings of a junior-sold-as-senior at face value, not knowing the difference.
This is so true.
It's also very difficult to stop as the consultancy gets the project and the client doesn't get to interview the people who actually turn up.
> Meanwhile, they'll happily pay Deloitte or Accenture 3x as much as what I charge, and then take the misguided ramblings of a junior-sold-as-senior at face value, not knowing the difference.
The main selling point is that big 4/8/16 have standard process, that does not really work, but gives the impression of "high quality" to clients, who are not technical.
>I’ve noticed that in nearly every skill tree I’ve climbed, there comes a point where you begin to notice certain nuances of skill that novices not only don’t notice, but that you cannot articulate using the commonly accepted vocabulary of the skill.
I've encountered this, and what works is re-framing it in terms they'll understand. Things that are universally understood are: time, money, and competition.
In this case, the "micro" and "milli" pitch is technical minutiae and is not what I'm referring to when I say "time". These are more effective frames:
>If we do this, it will save/cost us months/years/dollars...
>If we do this, the performance hit will knock out our competitive advantage, which we'll have to make up for it with something else, which will cost time/money...
>This thing is insufficient for our customer's needs, which will cause our customers to seek out competitors, which will cause us to lose money...
>This thing is too complex and will require additional training and is error-prone, which will cost us time and money...
In addition to those, for every decision you refute, recommend a superior alternative, and again, frame it in terms of time and money.
Now, this won't be a one-sided thing, you'll likely get into a conversation, and a lot of "why's" will try to extract that technical minutiae answer from you, which you might want to mention at some point in the exchange, but don't give it up easily, and do not emphasize it. Make sure you continue to emphasize the more convincing frames: time and money.
"take the misguided ramblings of a junior-sold-as-senior at face value, not knowing the difference"
Based on my experiences, I'm throughly convinced that most of the time the consultants will tell management what they want to hear. If management doesn't like the answer then they go to someone else. How likely it is that they will accept an unwanted opinion from a consultant is solely based on prestige.
Isn't it possible that you may not understand the CTO's priorities? Security is clearly essential to him, and performance is essential to you. I don't doubt there are other ways to satisfy both criteria, but frankly, it just doesn't sound like the CTO cared about those milliseconds.
That came up too. The security aspect of the product does less than nothing: not only does it fail to encrypt data end-to-end, it uses public ip addresses for both the control and data plane. Those public endpoints had an unauthenticated RCE vulnerability recently.
It’s a staggeringly bad product and it blew my mind now it was impossible to convince anyone of this.
We used pictures, for crying out loud. We did all the things everyone here has been helpfully suggesting. Talking about business consequences (dire), costs (enormous), risks (massive), etc…
The response was: “the sales guy from the vendor assured me it’s all fine. This is just your opinion.”
The causal chain of a->b->c was just not sinking in.
The CTO he could not judge anyone’s expertise not just mine — he also couldn’t judge the lack of expertise by the vendor and their sales team.
So he chose based on who has the nicer suit, the shiniest smile, etc…
// I just could not make him understand that 5 milliseconds of additional latency in the era where microseconds are an eternity is a disaster for a veritable smorgasbord of upcoming projects. It just. Would. Not. Sink. In.
Does this company do something where this latency would be noticeable? Can you give an example of business impact that would result from it?
If you can, why don't you?
If you can't, then sounds like it doesn't matter.
The CTO didn't get to be the CTO by optimizing the irrelevant.
I agree that's ideal but probably wouldn't expect a latency optimization expert to understand my business well enough to do that and that's fine. But I -would- expect them to say something on the level of: "this is the kinda latency that will prevent you from ever moving to a cloud desktop" or "at this level of latency, you are going to suffer X second delay every time you interact with a complex web app like Jira" or "you are an HFT firm and I know that your competitors are at about 1% of your latency." Then let your client decide if this is something that matters to them. Quite different than "wow the CTO is too dumb to understand my genius"
That was my exact reaction too. There’s a reason python and other “slow” languages are dominating. Very few industries require that kind speed, and even fewer require it at the cost of simplifying code or architecture.
In my experience the CTO got to be CTO because they’re friends with the CEO, the board, etc, rather than their own technical ability being superior than the seniors/leads under them. And that goes for me too, when I was CTO. It’s a position, it doesn’t have any inherent guarantee of ability to avoid optimising the irrelevant: some will, some won’t.
> Then I watched it play Dota 2 -- in which I've sunk several thousand hours -- and holy crap
Fascinating. I’ve never professionally worked in what it sounds like you do, so I was moderately agreeing with you until this.
I’ve played Dota likely as long as you in addition to playing at a semi pro level (placing well in a couple official pro qualifying tournaments as well as playing pubs with the players the AI played against) and I couldn’t disagree more.
It was impressive, but it’s main advantage came from its inhuman reaction times. They added some buffer but still didn’t account for 5 players working in perfect unison. That kind of coordination is an enormous advantage in a game like Dota. I left roughly feeling like I do now about AI - very impressive, but way over hyped and only sold to people that don’t truly get Dota.
It's interesting that you bring up Dota because I find that it's a ready example of the vocab point failing. When you listen to pros talk, they misuse words and concepts all the time but it doesn't matter because the other pros listening get the 'feel' of what they're saying.
(I'm not a pro or anything, just high rank, but to use myself as an example) I try to make an effort to use the correct words when explaining things to friends. But even I find myself saying things like 'just look at the [lane] creeps' to explain what I want my laning partner to do and then I realise how unhelpful it is. Because when they see the creeps they don't understand what I see.
I have a couple of similar experiences. I've spent >1,500 hours playing Team Fortress 2 and can recognize things that other gamer friends just can't see. I'm still not good at TF2, but I can recognize great playing.
Years ago I was active in Tae Kwon Do and achieved black-belt status. One time, during a sparing match with my teacher, I was astounded to be able to spot a hole in his defense. In fact, I was so distracted by my perception that I completely froze and he scored a point. I like to think that my seeing that hole gave me a glimpse into what it might be like to be good at TDK. I still think about that experience to this day.
The trick I use for myself is, if all I could see is binary (this is too easy, how hard can it be, or it is impossible), then I'm either too novice or I'm an true expert in this particular subject matter. As Bruce Lee put it, a punch is a punch [1]. I'm still hoping to be the latter
There is clearly a major problem with this in SV. A lot of people seem to confuse confidence with expertise, and fail to grasp that a scary proportion of the time the individual is so confident because they don’t understand the problems with what they are doing.
Furthermore, modern software management practice doesn’t want this because it wants replaceable cogs. If you can recognize expertise you have to appreciate that teams where everyone is good at everything are nonsensical, and that you need actual balanced mixes of personalities and specialists, which makes hiring a far harder problem. As such recognizing expertise is very much not the order of the day.
Wouldn't it be better to hire a mixture of specialists and generalists especially today when diversity should be focused in thought rather than looks. Someone not me said that specialists are a master of one and connector of none.
Sure, ideally. In the real world hiring managers have to take what they can get from the applications that come in. And in a rapidly changing industry the specialists that you need today might be useless in two years. One approach that can work in some organizations is to hire mostly generalists as employees, and bring in specialists when needed as temporary contractors.
> Furthermore, modern software management practice doesn’t want this because it wants replaceable cogs
In my mind that was always just an excuse to hire as many people as possible to grow their org and get promoted to n+1. But hey it worked with 0% rates!
Expertise makes sense in larger teams and companies. The smaller you are the more one person has to do. The larger ypu are the more you can afford to have a few people who are absolute experts of a small section but can't make a project complete end to end. But at a large enough company it doesn't matter.
If you have 10 engineers, you need generalists.if you have 1000 engineers, generalists generally are smart people who are potential experts, but not really that useful.
I actually think ageism is a huge component of this.
In classical engineering fields, experience was highly valued. In some it still is. In civil engineering, no 24 year old will be able to bullshit their way into senior level roles. It just doesn't happen. The senior guys get more and more valuable. A big part of that is that it's very hard to bullshit your way through that field without at least 6-8 years of experience, and by then you'll hopefully have been humbled enough not to try and bullshit it.
I think missteps and mistakes hit differently when someone traceably stamps their name on a finished product and takes personal liability for it in perpetuity.
I've seen this happen in my career. In a previous life we hired a person just out of college into a "Senior" developer role. Sure, the person was smart but they didn't have the experience, they hadn't made the mistakes or seen the outcomes of various decisions to be called "Senior".
I've struggled since then describing why I felt this way and I think the essay helps immensely. In my recollection that developer didn't reach a software vocab point and couldn't really understand the difference. The pain point for me was that I could spot the difference and no one (in management) really cared.
There are people who consider software written, I mean painted, or as they say modelled, in the language of e.g. Simulink to be of higher value than other representations of code.
The reason for this is probably different use of the same terms. Some code might be tested within an implementation of a model of the real environment. That is a frequent use-case used to sell graphical languages. The term model is used for two different things: The model of the real world to allow testing and for the implementation of the solution in a graphical language. Of course developers in those environments are Klingons like we all are, no real effort for tests, and only the graphical solution remains. But it is perceived as if it had all the positive attributes of a solution tested in a simulated reality. And therefore something modelled is better, because it is modelled.
I think this is still doing it a disservice. You don't test a code with a model of the real environment. You execute the code, which was modeling something.
Consider, "F=ma" is a mathematical model relating force to mass and acceleration. You can test this by dropping several things each from the same height and seeing that the force linearly increases based on the mass of what you are dropping. Similarly, you could test the model by accelerating something to a halt at different speeds and seeing how much force is imparted into it.
Is that not a "model" because it is not necessarily graphical?
So, similarly, much CRUD software can be seen as modeling different agents in an overall system and what happens when they interact in certain ways.
Edit: I want to add that I think I see where you are coming from. Many treatments of graphical models like to hold them up as a special form of modeling.
> Is that not a "model" because it is not necessarily graphical?
For some people model==graphical, usually mechanical/electrical engineers, not software-engineers. Engineers maintain the holy "model", and the translation to lowly code is a job for the lowest-bidding software person.
Maybe it wasn't clear, but I do not agree with that point of view, and tried to explain how I think people may have found their belief.
I assumed the parent^4 was labeling their code model in an attempt to elevate themself to the ranks of the code painters.
I'm curious on this. Do you have links that go over this? I've not seen a hard distinction that models are graphical, pretty much ever. The very idea of "machine learning models" flies in the face of that, as I've rarely seen machine learning models presented in a graphical way.
Best I can think in this direction, is UML? But that is an odd one, because it isn't that "models" are graphical, but those are specifically models of code artifacts. A model of another modeling language, as it were.
Reading back over the top comment, I assumed that the poster meant they started seeing their coding as modeling of a problem domain. Not that they weren't still coding, somewhat.
Disclosure, I was an EE way back when. We had plenty of numerical models for how things worked. We even had verilog to model circuits using what looks a lot like "traditional" software.
That all said, if I just haven't kept up and "model" is moving in meaning, I wouldn't be too shocked. :D
I guess it is limited to specific industries. Check the product description of Mathworks Simulink, which has many examples of things rightfully called model. In reality though (I don't have a reference for that, just my own observation) it is almost exclusively used as a graphical coding tool and the graphical code is called the model.
A case of cargo-cult. Attempt to apply the practice but badly (use the tool, but not the way its use is advertized), and use the terms for use of the tool instead of the practice, reserving it for that to promote their beloved tool over alternative approaches.
If anything it’s more important. Without it you cannot separate its confabulation from its useful output.
Knowing when to use what tool, how to do it properly and to what extent takes expertise as well.
Carpenters and craftsmen in general are infinitely more productive with woodworking and related tools than I will ever be. My destiny is assembling IKEA cupboards. The same principle will apply with AI tools. Sure you can whip up something, but a specialist will do it infinitely better in 1/100th of the time with the same tools.
Guess who will be employed to make use of said tools?
Probably not the best comparison, as a carpenter or craftsmen can't tell a LLM something to build X out of wood and have it come out mostly OK (yet?). Anyone can tell ChatGPT to write some code to do X, not just expert programmers. It may not be perfect, but it's only going to get better, no?
This metaphor is not about the tools so much as it is about the nature of expertise and its effect on the results of said tools.
Someone with expertise will use any tools, including GPT, in ways a novice can’t even understand. Same tools, different outputs. Not the tools, because basically anyone has access, but the one using it will determine the outcome. In a capitalist society you will have to compete otherwise known as staying employed.
Someone with expertise can hook up AIs in ways and with a velocity that will leave amateurs in the dust. The amateurs will still be fiddling around with “prompts” and Googling or ChatGPT’ing what “latent” means while the expert has working systems ready to go.
I don’t see this chasm getting smaller. These tools magnify your inherent (in)competency. Try to compete with a professional artist competent with Stable Diffusion if you want a taste of that.
This is a good question, and I don't think you should be downvoted.
It is important for several reasons:
- As other commenters pointed out, filtering, adapting and integrating ChatGPT output has a better ROI with experts.
- An expert will know the ROI of using ChatGPT, including on the long run, and can assess if it's worth it or not. A non expert will use it for as long as it works, and can hit a wall of technical debts accumulated from the GPT usage that will now sunk the cost of the entire operation.
- Expertise comes with a lot of implicit knowledge that ChatGPT doesn't access to.
- ChatGPT doesn't learn from mistakes in the way humans does. And humans don't share the mistakes they made as much. And experts have made all the mistakes.
- ChatGPT tries very hard not to not be opinionated, or to have an opinion that will offend the least amount of people. IRL though, you want opinionated takes.
There are, however, many situations where being an expert to benefit from ChatGPT is no required. I also find that sometimes being an expert prevents me from getting the most of ChatGPT, because I stick to what I know instead of embracing novel workflows. I have a friend coding things with repeated ChatGPT copy/paste loops over days, and they have done great things with it.
Yeah. ChatGPT has no expertise at all, just a huge amount of knowledge.
Because there are two parts in expertise: pure knowledge, and a set of weighed criteria to evaluate things. This second part is what I think TFA calls "tacit" knowledge. This stuff is a job for neural networks, but more for Alpha0 than for ChatGPT - although it does probably that under the hood, but it's an expertise used to string together questions and answers. That's enough to give the illusion of expertise, but you still face the problem how evaluating that artificial expert. There are many reports that ChatGPT can be "slightly wrong" that only experts can really spot. You can have ChatGPT do your boilerplate code or bulk work if you are an expert in the field.
I personally think of this part of expertise as the expert's "intuition". This intuition is indeed sometimes difficult to communicate. Sometimes because it comes from various experiences, and describing those experiences in enough details would take far too long. Sometimes A just "feels" better than B because those criteria and weights are subconscious; pretty much like you apply a certain amount of force to lift an object because you have subconsciously evaluated its weight (either with material density and shape, or from memory because you've lifted similar things before) - and sometimes you are surprised because it is magnetized or it the box has been emptied.
However, my criteria to evaluate expertise is still how well the expert can explain something to me - that is, if they are good teachers. This also an unreliable proxy like the "vocab point" of TFA. Not everyone is a good teacher, and impostors or poseurs can make you feel like you understand when they are actually bullshitting you.
ChatGPT could be a good (enough) teacher that can help you becoming an expert (partly because of the fact checking work you'll have to do, something you normally don't have to do with an actual teacher), but ChatGPT as an expert, it is a no-no in my book.
great article and well supported (loved the tennis example).
i can't help but notice that Cedric (author of commoncog, and a friend) is accumulating a good body of work exploring knowledge and expertise acquisition. is this something that is generically applicable or are we reading convincing-sounding text generated by a very advanced human expertise language model? I guess the only way to know for sure is for Cedric to open up a coaching practice and see the results?
great substack and podcast (love the guests you have on)
i can't help but notice that Swyx (author of latent space) is accumulating a body of work exploring LLMs and covering AI progress. is this something that is analysis by an expert or are we reading convincing-sounding text generated by a very advanced AI hype language model? I guess the only way to know for sure is for Swyx to train an LLM or do deep learning research and see the results?
This relates closely to Anders Ericsson's theory of expert performance through deliberate practice. The article discusses the role of nuanced domain-specific vocabulary to describe elements of expertise before pivoting to subsume it all under the rubric of _models_. This is exactly how Ericsson sees deliberate practice working - by building extraordinarily detailed and nuanced neurocognitive models and being able to draw on them readily (and often unconsciously) in performance.
The problem with the author's tennis anecdote about Roger Federer's 2017 career resurgence is that in reality it had more to do with the top player Novak Djokovic's elbow injury than with Federer's backhand.
I understand the intent, but this article seems to be arguing for an Emperor's New Clothes scenario where no one can identify the value of something except for a vanishingly small number of people.
It's some economic variant of the tree falling in the forest analogy: if a service has quality but no one can recognize it does it have value?
It strikes me as a recipe for regulatory capture and overcredentialing.
Value ultimately lies in the purchaser, not the producer.
Maybe it depends on the market but this seemed to be arguing for something dangerous to me.
> Value ultimately lies in the purchaser, not the producer.
I'm not entirely convinced that this holds, in practice. It makes sense for rational purchasers with perfect and complete information, but that is never true in reality, and it ignored all cognitive biases that humans use to make decisions, including being misled by advertisment.
For example, the tobacco industry can scream all they want that smoking does not cause cancer, but being loud about it does not make it true. Initially, people didn't even like smoking because of the bad taste, but massive advertising campaigns including paying celebrities to smoke in public changed the perception of the value of smoking. In a similar manner, after acquiring all major sources of diamonds and inflating their prices, advertisement convinced the public that a man absolutely needs a ring with a diamond to "prove" their love to their bride. Same for the food industry and sugar, you know where I am going.
All of these are examples of "value" created by producers by misleading customers that their product is good and not harmful for them. But facts don't become true or false just because everybody believes in them. People can believe false things, and no matter what they do or say, those things remain false.
Not to mention that immediate value for individuals can have considerable negative value in the long-term for society. Think at the huge resources we spend on finding cures for cancer and obesity, just because we sell addictive stuff and pretend that people "want" those. If you consider society as a whole, this appears to be an extremely inefficient use of resources.
Loved the post. Just to add to the principal observation about the vocab point — One thing I’ve noticed is that experts who can communicate/teach well are very effective at getting you to the vocab point (to the extent possible without experience) quickly! And once you reach the vocab point, the field is legible enough that you have the means to organize deliberate practice and interpret experience (if you want to go towards mastery) or delegate details (if you don’t need them). I wonder if this provokes any more thoughts from you.
I'm glad you were able to articulate this idea so clearly. I think similar advice which maybe isn't so clear is to try to avoid "being the smartest person in the room".
On the topic, I'm reminded of coworkers talking about the most recent Super Bowl (I think, I don't follow sports) which included commentary from players who played as quarterbacks in the same season. One of the things my coworkers mentioned was how interesting it was to hear them talk about the game because they used unfamiliar terms.
There are some teachers of Samatha meditation, a Buddhist concentration meditation, that teach that you at any point are meditating at one of ten stages. This is both about skill as well as about factors like how agitated your mind is in general. And these stages seem to have very well-defined descriptions: for example one stage might be differentiated from the previous one by overcoming drowsiness. This is very helpful since some people teach meditation by just telling you how to do it but not (in fact sometimes actively avoiding) how you can evaluate where you are and how you are doing. Then the practice becomes just about “being present” and other slogans that might be wholly non-actionable.
It’s also very difficult to protest this kind of approach (edit: the non-goal approach) since merely mentioning things like "goal" or "evaluation" will trigger someone’s knee-jerk you’re-doing-it-wrong reaction, even though what they practice might be completely different to what you are doing or trying to achieve.
Not directly related to the article but I had two amusing encounters with expertise recently.
I sat next to an Econ professor (at an Ivy) on a flight. I told him I had worked at a hedge fund, and he was like "wow, I could never put myself in a situation where my living depended on my economic theories being right."
A good friend of mine is a kinda-famous evolutionary biologist. He's in his mid-40s now, unmarried and doesn't have kids, and likely none on the horizon.
In the economist case, what does it mean that in his expert opinion, he wouldn't trust his own expert opinion! In the biologist case, what does it mean to be one of the world's leading experts on "evolutionary biology" and yet completely fail to pass your own genes?
What's most interesting to me is that neither of these scenarios strike us as "super wrong." I can imagine most people wouldn't hesitate to attend a class taught by either one of these guys, while we'd avoid analogous situations (eg: we wouldn't use a broke financial advisor or fly on an airplane whose designer refuses to set foot on it.) What's the difference?
As far as the economist. I suspect he understands that they're theories, thus, to some extent guesses. Some data might support it, but does it hold true in every case? Probably not. Does it hold true in most cases? Maybe not. Would he bet money, effectively what a hedge fund does in my very limited experience here? Sounds like no.
This to me sounds like a simple example of he understands the limitations of his work!
As for your evolutionary biologist friend. Being interested in evolutionary biology does not mean you are inherently someone that wants to be a parent. These are very very different things. Besides, evolutionary biology impacts more than just humans, it impacts every species. Being a parent comes with a great responsibility. Someone could just as easily be a really big fan of dogs, but not want one because of the responsibility or the costs, or similar.
Yup, your explanation resonates with what I think are the superficial reasons society is accepting of both of these cases. You have to think a little bit deeper to feel why this might be problematic.
If the economist weighs the risk to not put too much stock in these theories (no pun intended actually), why does he not likewise hesitate to teach these theories to his students? Like "I don't believe 100% that this is how the world works enough to bet my own money, but I am going to tell hundreds of students every year this is how the world works."
The biologist story is subtler. One could argue that failure to become a parent signals that you deeply, fundamentally, don't get biology - despite your superficial interest and theoretical knowledge? Like, you may talk about zygotes all day but you failed to make one...
Maybe the difference between economists and biologists vs financial advisors and engineers is that we expect the later to have skin in the game but for some reason allow the former to not have to.
I don't really agree with any of that. You seem to be really trying hard to draw lines to make these seem more than they are.
Economics is complicated because at a fundamental level you're trying to understand people and their decisions. Sorry but you're really never going to "solve" that problem. Stuff will forever be a theory.
You are also assuming that the economist is teaching this and saying "this is how it works, it's 100% accurate" and not starting off with "this is a theory, and we work towards making it better over time with new data and new ideas." Just because something may not be 100% perfect does not mean you don't strive to improve what you have and you won't improve what you have if you just let it rot on the vine and not teach the next generation.
The biology one is even more convoluted. Having an _interest_ in something does not mean you have to "be" the interest. A simple example, I work to live, not live to work. I am not my work. My work is only here to support me living my life. You are claiming that the biologist is a failure because they didn't want, or couldn't, create offspring despite their interest being in evolutionary biology. That's some kind of weird argument to make there man...
> I don't believe 100% that this is how the world works enough to bet my own money, but I am going to tell hundreds of students every year this is how the world works
This is a fundamental misunderstanding of what a good professor does. If the economist acts in this way, they have failed as a teacher, not as an expert in economics. Likewise I think you have a fundamental misunderstanding of economics as a science - it's not one, and it sounds like the economist was making a quip at the predictive weakness of the field overall.
> The biologist story is subtler.
No, it's not. You're just having to push harder to keep it afloat.
> One could argue that failure to become a parent signals that you deeply, fundamentally, don't get biology
One would be wildly wrong to make that argument. Once again, I think this shows a deep lack of understanding on your part of the field itself and what it means to study a field. And also what it means to have a child as a human, honestly.
> economists and biologists vs financial advisors and engineers is that we expect the later to have skin in the game but for some reason allow the former to not have to
Is this not obvious? You're reaching very hard to dig at researchers in a way that indicates you don't know what research actually is. Or maybe you're defensive of the work you do? I shouldn't speculate too hard here or I risk also being this wrong.
> One could argue that failure to become a parent signals that you deeply, fundamentally, don't get biology - despite your superficial interest and theoretical knowledge? Like, you may talk about zygotes all day but you failed to make one...
So farm animals understand biology better than the biologist does?
I see zero problem with having no children and studying evolution. You don’t need to become superconductive to study the physics of superconductivity. You don’t need to become infected by every virus to study virology, and you definietly don’t need to be a virus to be a good virologist. So why would you need to pass on your genes to study evolution?
You can also be an expert on healthy food, but don't have the self control to actually follow your own advice.
In the end, those are 2 different domains. Knowing a certain theory and overcoming all the limitations of applying those are very different.
Let me give you another example: Formula 1 or MotoGP. The engineers are not driving the thing, and the drivers are not engineering it. Claiming that one needs to be able to be a master in the other is weird.
> I am questioning if you can be considered "expert" if you profoundly fail at the topic of your field.
You are confusing the person with the field of study.
This confusion is more obvious if you think about the superconductor/ expert on superconduction example.
A superconductor is a material which conducts direct current with near zero resistance. You can test if something is a superconductor by aligator clipping a voltage source on it and measuring the resistance.
An expert on superconductors is a person who is knowledgeable about the phenomenon of superconduction. You can test if someone is such an expert by asking them questions about what materials are superconducting, under what circumstances they are, what phenomena can be observed during super conducting and etc etc.
If you get confused and clip the aligator clips on the expert you will measure a larger than zero resistance. If you start asking quiz questions from a superconductive material about superconductivity you will observe that it does not answer any of them.
These two things are fundamentally different. You can be good at one while miserably failing the other, or vice versa.
Similarly someone who studies evolutionary biology is someone who studies the effect of evolution on different kind of living things. They are good at predicting things which they can prove later either experimentally, or with observations about creatures and their circumstances. It has nothing to do with the act of procreation. A disembodied AI can be an expert at evolutionary biology as long as it has good theories on the topic which it can support with relevant evidence.
Through two practical examples. Someone who is good at surviving at evolutionary timescales is for example a person with a handfull of healthy, and fit children. Each of them carrying a mutation which makes their female offspring (daughters, grand-daughters and so on) have a tiny bit wider hips thus increasing their chances of having uncomplicated births, thus increasing the chances of having lots of lots of offspring a tiny bit.
Someone who is good at studying evolutionary biology for example might be able to explain why animals trapped on an island all over the world seem to change in a way that their offspring becomes smaller in stature.
Mixing up these two is as silly as measuring the resistance of your superconductivity experts.
In the case of the economist, he may have the best theories but it doesn't mean it's correct. He is likely saying his theories have too much uncertainties.
In the case of the evolutionary biologist, successful procreation does not require any knowledge of biology.
When it comes to planes, there is a high correlation between the quality of the plane and the quality of the design.
// successful procreation does not require any knowledge of biology.
Maybe this is a good point. I would argue that a high school kid who knocks up his girlfriend has demonstrated a better intuitive grasp of biology than my PhD friend.
Just to be clear, there are many aspects of biology that that professor is ignoring on a regular basis that you’ve elided (hibernation, molting, limb regeneration, etc). What specifically about procreation is important enough to call that individual’s expertise into question?
Not even a little. The high school students are slaves to unconscious drives in their bodies and that's not even related to having an understanding of biology. Or do you say that a world expert in biology who would rather spend their time furthering studies than raising a child actually knows less about biology than rabbits? Your arguments aren't making any sense.
Your conflating understanding biology and performing biology is very odd.
A bacterium can perform cell division, but it can't explain it. The evolutionary biologist's job isn't to personally have sex, it's to explain what happens when many generations of organisms do so.
>what does it mean to be one of the world's leading experts on "evolutionary biology" and yet completely fail to pass your own genes?
It means he sees the difference between a biological imperative and a moral imperative - who says he's "supposed" to pass on his genes? A strand of deoxyribonucleic acid? Is this judgement exhibited exclusively by proteins, or can a chunk of plastic also judge you for not knocking a girl up?
I'd venture the difference is being a professor vs. a practitioner. To profess is to talk and teach and expand the opportunities of the discipline by lodging the ideas in peoples minds. A practitioner is someone who actually does something, but it doesn't really scale much past their own ability to physically do it. They have a practice. One plants, the other harvests. Such a good question to pose though.
I can tie these together. Even if the biologist is in favor of eugenics (selective breeding of humans) he probably also knows that we are not good judges of overall fitness. The econ guy may have some great ideas, but he knows the difference between theory and practice. In both cases they "know what they don't know". On a more personal level, maybe the biologist just wants to follow his heart (which is actually the correct move), and the economist likes to play it safe?
"You do you" is the correct answer in almost every case. Evolution does not pre-select and deliberately make copies. It's a process where individuals do their thing and let the chips fall where they may. The process takes care of the rest.
> What's most interesting to me is that neither of these scenarios strike us as "super wrong.
I don't think they are wrong at all. That's what I would expect. In my experience, one of the marks of being an expert in a subject is being very aware of the limits of their knowledge and expertise in it.
the difference is that academic research is several degrees of abstraction removed from real world applications.
the economist might not specialize in theories about why, when, or how much specific assets go up or down. even if he did, he might not have the skills to make actionable predictions from messy input data. doesn't mean his theories are wrong, just that someone else needs to bridge the gap between theory and application.
evolutionary biology has almost nothing to do with being a good parent. I don't think this even requires an explanation.
the financial advisor is the exact opposite. managing personal finances is the exact problem they are supposed to help you solve. if they can't do it for themselves, that's a pretty strong reason to doubt they can do it for you.
> the economist might not specialize in theories about why, when, or how much specific assets go up or down. even if he did, he might not have the skills to make actionable predictions from messy input data. doesn't mean his theories are wrong, just that someone else needs to bridge the gap between theory and application.
On top of that, it's not uncommon that experts understand the risks, unknowns and potential other choices better than early level practictioners.
I actually would hesitate to take a course from an economist who doesn't have a track record of making accurate predictions in the real world (not necessarily about trading specifically). Most of econ has always been unscientific bunk that isn't even useful for practical modeling. Why waste any time learning it unless you need the course to meet arbitrary graduation requirements or something?
Unlike you, an evolutionary biologist knows that if enough of his siblings and cousins have children, the probability is very high that most of his genes have been passed on even if he wasn't the one to do it. Also, only 50% of your own get passed on per child, so it's entirely possible more of your genes were passed on by other people even if you have a child or two.
Experts can see all the gradients in ability and will extrapolate how far they are from the top, but all novices know is how far they are from the bottom. If those distance estimates are biased, it’d lead to novices overestimating ability and experts underestimating
I really regret how hard of a hold the Dunning-Kruger report has had on our generation. Worse, it seems every reference trying to point out that it is, in fact, not saying what people think it says just reinforces folks believe that it says what they want it to say. :(
for me, path to expertise is knowing the "language", "practicing maturity," and system 1 mastery of a topic.
i think expertise is "mastery of system 1(ref Daniel Kahneman) of a topic." which means identifying more "patterns" through "practice and observation." the patterns capture both the rights and the wrongs.
the entry to any subject is "learning the language" of the subject. what comes next is to become "mature."
maturity is based on amount of practice in a big and unbiased search space, the ability to play with subject and identifying primitive constructs, ability to criticize and seeing the weaknesses,
the measuring method for maturity level is amount of "simplicity," "freedom", "flexibility", "speed", and "ability to identify the essence" that the system one adheres to bring.
excerpt from Saunders Mac Lane "category theory for working mathematician."
"many properties of mathematical construction can be identified using universal mapping properties."
see how simple the definition is?
// Customers tends not to be experts. So after a certain level of skill has been achieved, any improvements that are made through experience are invisible to the people you’re selling to.
The relevant question is - does it matter? The Formula 1 pit crew is more expert than the mechanics at the Toyota dealership in ways I can't appreciate - but does it matter for my Highlander's oil change?
The answer might be "Yes, the F1 crew will do it in a way that prolongs the life of your engine" (I care about that!) or "Yes, the F1 crew will change your oil in 20% of the time" (I may or may not care about saving a few minutes every 6 months) or "No, you won't notice a difference but they are just more expert" (in which case I totally don't care!)
Part of expertise is ability to articulate its relevance to a given situation. Your customer may need help in validating your expertise, but at least start with the claim of what you can do.
F1 pit crew members are highly trained athletes who specialize in fast tire changes. Many of them are recruited from other sports based on strength, speed, and agility. They often have no real experience as automotive technicians.
F1 teams do have world class mechanics but most of them aren't part of the pit crews.
>Many of them are recruited from other sports based on strength, speed, and agility.
This is not true at all. F1 pit crews are mechanics who have worked with cars in other motorsport racing series/feeder series and worked their way up to an F1 team.
I think the point is when reaching higher levels of expertise is not to try and convince existing customers to move up the ladder with you, it's that you need to find an entirely new set of customers who need that level of expertise and appreciate the difference. It's not about explaining - there's a quantum leap between levels.
It might be trite, but as a contractor walking my rate up over 10 years, I found it interesting.
I agree on "forget your existing low level customers" and I think you're hitting on one of the growth paths but there's another one.
The path you are hitting on implies the client/employer already knows what they need and are gatekeeping on it. It's great to be able to get past those gates - ie, if you've grown yourself into a FAANG-caliber engineer, go interview at Google, but in this case Google already knows what they need and what that looks like.
The line from the article that I cited is the other dynamic - where the client doesn't know what they need. You're right that might be because they are a low level client and don't actually need your expertise (what you mentioned) but it may also be the case that they do badly need you but can't recognize it because of your relative difference in levels.
In general, the higher your level, the more likely it is that even otherwise high-level people will not understand the nuance of what you can bring to them. In that case, there's the sales process that should kick in, and by sales I simply mean helping the client see that they have a problem and that they would be much better off if that problem was solved, and that you're a rare breed who can do it.
That's a good point, and the sales education process is definitely important. It's a fine line between "let's step back and look at your actual pain points" and "what else can I upsell you on while I have your attention?", that customers are very wary of crossing.
I'd wager a large portion social embarrassment is when a person ostensibly believes they have competence in a certain realm but do not. Being aware of yourself and how your peaks and valleys are perceived is the foundation of charisma.
If it quacks like a duck - it must be a duck. Not really.
> In every profession there’s a point where further improvements in skills are so subtle that the difference between one level and another can only be appreciated by another expert
Goal defines the benchmark for proficiency.
Better tennis player scores. Better software engineer writes more space/time efficient code or solves business problem faster (whichever the objective). Better writer gets more views or inbound sales or whatever the goal is.
If you get better at achieving ever greater goals, then your expertise is growing. No amount of luck can compensate for a lack of expertise.
Enjoyable read that definitely touches on something real.
I was struck by the anecdote that Herbie Hancock tells in the linked video though. He misheard some advice from someone he respected, took it to heart and it changed the way he played.
I notice that this seems to work in opposition to the idea of a vocab point where high level practitioners are talking about real concrete experiences they are having that the lay man can't understand until they level up.
The way I think it worked in this case, is that as you go up the ladder of skill, you start seeing and thinking in more abstract, metaphorical terms. For a beginning student, you're focused on the mechanics, for the master, you're focused on what it means and how it relates to the human experience. This means that a master can apply an a metaphor that the beginner can't even understand. Indeed, Herbie Hancock can apply a metaphor that nobody else could even imagine had any relevance at all.
Perhaps rather than 'vocab point' we should talk about 'metaphor point'.
There is a huge problem with this idea, it suggests that a competent critic has usable skill in an area. This is obviously false.
Moreover I see it as a huge problem in our current environment of easy access to Youtube explainers of everything. In my areas of expertise I come across many more people that 'talk the talk' than can actually 'walk the walk'.
A chef must be judged on dishes they produce, a dancer on their performances, and a software developer on working code.
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[ 2.9 ms ] story [ 248 ms ] threadIt's an issue that I struggle with nearly daily. I can't convince customers to pay me what I'm worth, because they can't judge my true value. Meanwhile, they'll happily pay Deloitte or Accenture 3x as much as what I charge, and then take the misguided ramblings of a junior-sold-as-senior at face value, not knowing the difference.
> I’ve noticed that in nearly every skill tree I’ve climbed, there comes a point where you begin to notice certain nuances of skill that novices not only don’t notice, but that you cannot articulate using the commonly accepted vocabulary of the skill.
This happened to me just over the last month or so. I was trying to explain to a CTO how horrifically wrong it is to plumb their entire cloud network through just a pair of virtual machines for "security". I just could not make him understand that 5 milliseconds of additional latency in the era where microseconds are an eternity is a disaster for a veritable smorgasbord of upcoming projects. It just. Would. Not. Sink. In.
To some people, "micro" and "milli" sound the same. Latency just doesn't compute as a thing to be concerned about.
I've spent my career performance tuning, but then how do I explain this to people who think a 60-second timeout is a performance problem best solved by buying another million dollars worth of kit?
The article jumps between martial arts and the world of finance, so I'll jump to another example: AI playing games.
When I watched AlphaZero play chess, I was just a tiny bit impressed. I watched it beat the Go grandmaster and I was not very impressed. Then I watched it play Dota 2 -- in which I've sunk several thousand hours -- and holy crap. Wow! It was suddenly terrifying how good it was, because I could judge the nuance of what it was doing.
To be fair, it almost is. Both units are used to talk about times of about the same size. Using both in the same sentence is like mixing meters and feet. It's much clearer to say e.g. 1500us vs 3us; or 1.5ms vs 0.003ms.
Don't mix units when making a comparison.
I'm not mixing units.
Milliseconds and microseconds are both measured in units of seconds.
The milli- and micro- prefixes are orders of magnitude. They're scales, not units.
When a scientist starts talking about measurements accurate to attoseconds, I sit up and take notice.
The number in front doesn't make a difference. It's the "atto" that raises my eyebrows.
Back to computing:
I had a debate here with someone who claimed that 128-bit floats are required for some chip layout codes. I questioned that, because a 32-bit number can subdivide the side-length of a chip down to sub-atomic resolution, and a 64-bit float can model the wiggles of the hadrons making up the atomic nuclei!
To some people, 128-bit sounds "twice as good as 64-bit".
To experts, it's... umm... a sign you've made a mistake.
When you are an expert, nearly by definition the average person you're talking to is less well read on the subject than you, the expert. Because of this, it's extremely important to be able to communicate with clarity and patience.
Your expertise doesn't matter if you can't make yourself understood, and it's not reasonable to expect people around you to share your expertise, so you need to adapt the message.
Communication in general is easier the fewer concepts you invoke. In almost all situations it's better to be mostly correct and well understood than to be perfectly correct and not understood at all.
Even if you can expect most people to have an understanding of SI units, far fewer will have an intuition for them (because they aren't working with them daily). Everyone has a basic intuition for big numbers though, so if you want to say "this is bad", show them a big number; the bigger the better.
It can still be correct and make a well founded argument, but presentation matters a lot more than you'd think for convincing someone. In increasing order of likelihood it will convince anyone:
The new solution adds a 15ms latency, whereas our usual requests have a 2us latency.
The new solution adds a 15ms latency, whereas our usual requests have 0.002ms latency.
The new solution is a factor 7.5e3 slower than the existing solution, which has a 2 microsecond latency.
The new solution is 7,500 times slower than the existing solution, which has a 2 microsecond latency.
The new solution is 75,000% slower than the existing solution, which has a 2 microsecond latency.
What is said is basically identical in each version, but the presentation puts an increasing emphasis on just how big a difference this is by literally showing a big number.
Edit: aww, ninja edit takes away all the fun :/
You know I have a degree in theoretical physics so I really should get this stuff right, but before I've had my morning coffee all bets are off :P
That CTO is just doesn't sound qualified for the job.
Context matters, not everywhere 5ms more makes difference.
I get where you are coming from, but the amount of work you can do in 5ms is mindblowing.
If that's the case it's not surprising it didn't sink in. You're just giving him another problem.
> I've spent my career performance tuning, but then how do I explain this to people who think a 60-second timeout is a performance problem best solved by buying another million dollars worth of kit?
I'm surprised you've spent your career doing this and you still haven't figured out how to get people to listen to you.
Making your work legible to others feels as important as the work itself.
> I'm surprised you've spent your career doing this and you still haven't figured out how to get people to listen to you.
This is the point of the article, which you appear to have missed.
There's a point where it becomes essentially impossible to articulate the differences to the lay person. Or for that matter, someone actually quite skilled, but not a "master".
It's not a lack of skill on the part of the expert, it's the lack of skill on the part of everybody else.
Everything you've just said is gibberish to a master.
It's like making a straight-faced argument that setting the speed limit to 1 mph on a motorway might make perfect sense, and the traffic engineer is actually at fault for not making it clear that this is nonsense.
I get that you don't see the ridiculousness of 50 microseconds vs 5 milliseconds, but that's the point.
You don't see it, and you start making random arguments untethered from reality.
The fact that you are blind to it, unlike being blind to 1 mph vs 65 mph is the entire point.
You may have driven thousands of hours. You have don't have thousands of hours of network performance tuning expertise.
Both of us wouldn't be able to even begin to understand the complaints Ayrton Senna might make about how the steering is too "crunchy" at the extremes or that the brake strength imbalance is shifting the car about.
There's levels of expertise, and if two people are too far apart, meaningful communication between them becomes impossible.
Ok? But you are required to motivate a decision that is based on terms, conditions, probabilities, consequences that can only be encoded at knowledge-level A. When projected down to knowledge-level C, it sounds like "otherwise bad things might happen".
The jargon is not what matters. The logic of the decision is not meaningful or believable without knowledge of the "physics of the system" at level A.
Most people understand nuclear bombs in layman terms, and they understand them intuitively from watching videos and pictures. Without videos and pictures, no one would care.
Law firms are run by lawyers. The chief of surgery is a surgeon. Architecture firms are run by architects at the top.
Why is it that in IT it is expected that all management of IT is “non technical” to the point of not understanding what they’re hearing from direct reports!?
Would it be normal in your mind for a chemical plant foreman in charge of the process to not know what atoms are!?
Have you ever spent any significant time in an environment where most people are not (children of) college graduates? Because this is absurd. The average person who has just finished a year of high school physics probably can’t tell you those.
So it’s 100x more latency, but why does that matter for the business? Your CTO may be wondering about that. As yet, that answer doesn’t seem to have been provided in this thread. (Not that it needs to be answered here; perhaps it was explained to the CTO and they’re just that dense.)
Do they work for a high frequency trading firm? Do they make a CRUD app which has few users and (as much as I hate that) "they can wait even 5 seconds".
If the person does not give context then they dont explain well..
On a side note: for me the problem seems to be not the speed, but the choke point - just 2 servers (with no redudancy?). What one or both go down?
You've disproved this yourself earlier in this comment. You made an analogy to explain a concept to a non-expert.
It is entirely on you to make yourself understood to non-experts. It is both possible and extremely important.
That is rather a condescending take: calling yourself a master and calling their words gibberish is hardly thoughtful dialogue. Other parts of your comment are equally bad “ untethered from reality” should not be written. Someone is trying to engage with you and you are dismissing them by using very charged words. Even worse you are demonstrating poor communications skills - that point being questioned elsewhere in the thread. I hope you can learn to listen to others politely even when you disagree, and please try to follow https://news.ycombinator.com/newsguidelines.html :
> It's not a lack of skill on the part of the expert, it's the lack of skill on the part of everybody else
This is a very poor frame of reference. It's not other people's fault they cannot understand the value you provide, it's your fault.
The thing that tends to bother engineers is that articulating your value (I.e. sales and marketing) is generally orthogonal to your key competencies.
I can, and have, explained 'deeply technical things' in 'business terms'. And people understood. Then made a bad/poor/wrong choice anyway, because... "well... all those things you're saying might happen, they might not. Or... it may not happen for months or years, and we already committed to date X for project Y".
I can tell people the cost of punting on 'deeply technical thing' will be enormous, like... "this will require doubling the dept headcount and stopping all new progress for 6-12 months". Then offer alternatives. Then get summarily ignored, and watch things crash months later, and the dept is then stuck for months scrambling to understand all the problems they could have avoided. The decision maker who decided for extremely short term gain? They're gone (sometimes of their own choosing, sometimes not).
The "risks" can seem wildly out of touch with reality, but many times if you're making poor choices you do hit the "worst case scenario" wall. Colleague has been contracting inside a shop on and off for a few years. He indicated "if we don't do X, we will not be able to do any new feature development for at least 18 months". And... closing in on 4 years later, they've not shipped any substantial new features (some bug fixes, but that's about it).
I've seen this happen once up close, and have seen inside other companies and got the war stories from others.
Does this happen every single time? Of course not. But even if you can confidently and correctly and pleasingly describe deep tech things to business folks in their own language, showing the pros/cons/costs/risks... that doesn't mean they will take your side. Saving face, hitting deadlines at all costs, and other factors weight on decisions, and you can't control that. You can control where and how you work though.
Both the storage vendor tech and I vehemently argued for solving this immediately but were told to “do it later”.
I pointed out that “later” would be when it is full and has 10K production users using it 24/7. Hence any reformatting would be a six-month project requiring additional kit for the scratch space needed. Not to mention the risk!
I was wrong. It took 12 months.
The position is that intentionally being a bad communicator guarantees poor results most of the time.
Same way that not driving drunk does not guarantee you won’t get in a wreck.
Yes, maybe I desperately need to frobulize the macrowublitz to avoid pracknation, but I’ll wait for someone who can explain why it’s a high priority to achieve my goals.
Cedric explicitly directs people to another article which discusses how this idea relates to money: "Bellotti’s observations are worth reading in their entirety, especially if you’re interested in the actionable implications of the idea. But I’d like to take this property of expertise in another direction. Now that we know that expertise is more legible to experts, could we perhaps invert this observation and turn it into a goal by itself? Could you turn this into something that helps you acquire expertise?".
I would expect both of them to sell out. The people looking for a higher quality product will immediately go for the more expensive product, and the remaining wallets would sell to people who just need a wallet.
It is more complicated than that. There is no guarantee that the more expensive wallet is also the higher-quality product. The people looking for a higher-quality product can be classified into those who can measure the quality well (perhaps by observing those minor differences), and those who have to use less effective proxies of quality (like price).
Funny, my game of choice is StarCraft 2 and when I watched AlphaStar beat StarCraft 2 pros I was significantly less impressed than when I watched AlphaGo beat Lee Sedol at Go.
If you remove those limits, it would absolutely wipe the floor with the twitching corpse of any human player.
I saw it play Warcraft 2 without the limiters, and it was just ridiculous. It would dance the units around and keep using them with 1 hp left for many minutes and then heal them back up juuuuust enough to take exactly one hit from an enemy.
Almost everyone in the community seemed to agree AlphaStar was very unfair. Things like a 3 way surround and performing blink micro on individual Stalkers on opposite sides of the screen are completely inhuman.
This is also what made the Dota 2 bots feel somewhat disappointing. Of course perfect mechanical skill beats humans. Watching the SF mid 1v1 matches illustrated this very clearly to me. The AI chipped the player down with perfect AAs, then finished them off with perfect distance razes.
The bots weren't 100% mechanical skill, but it was a large enough proportion that it was uninteresting.
This is so true.
It's also very difficult to stop as the consultancy gets the project and the client doesn't get to interview the people who actually turn up.
The main selling point is that big 4/8/16 have standard process, that does not really work, but gives the impression of "high quality" to clients, who are not technical.
I've encountered this, and what works is re-framing it in terms they'll understand. Things that are universally understood are: time, money, and competition.
In this case, the "micro" and "milli" pitch is technical minutiae and is not what I'm referring to when I say "time". These are more effective frames:
>If we do this, it will save/cost us months/years/dollars...
>If we do this, the performance hit will knock out our competitive advantage, which we'll have to make up for it with something else, which will cost time/money...
>This thing is insufficient for our customer's needs, which will cause our customers to seek out competitors, which will cause us to lose money...
>This thing is too complex and will require additional training and is error-prone, which will cost us time and money...
In addition to those, for every decision you refute, recommend a superior alternative, and again, frame it in terms of time and money.
Now, this won't be a one-sided thing, you'll likely get into a conversation, and a lot of "why's" will try to extract that technical minutiae answer from you, which you might want to mention at some point in the exchange, but don't give it up easily, and do not emphasize it. Make sure you continue to emphasize the more convincing frames: time and money.
Based on my experiences, I'm throughly convinced that most of the time the consultants will tell management what they want to hear. If management doesn't like the answer then they go to someone else. How likely it is that they will accept an unwanted opinion from a consultant is solely based on prestige.
Read all the horror stories of shitty software or ERP implementations. Often it is the consultant's fault - since they are technically weak.
It’s a staggeringly bad product and it blew my mind now it was impossible to convince anyone of this.
We used pictures, for crying out loud. We did all the things everyone here has been helpfully suggesting. Talking about business consequences (dire), costs (enormous), risks (massive), etc…
The response was: “the sales guy from the vendor assured me it’s all fine. This is just your opinion.”
The causal chain of a->b->c was just not sinking in.
The CTO he could not judge anyone’s expertise not just mine — he also couldn’t judge the lack of expertise by the vendor and their sales team.
So he chose based on who has the nicer suit, the shiniest smile, etc…
Does this company do something where this latency would be noticeable? Can you give an example of business impact that would result from it?
If you can, why don't you? If you can't, then sounds like it doesn't matter.
The CTO didn't get to be the CTO by optimizing the irrelevant.
Fascinating. I’ve never professionally worked in what it sounds like you do, so I was moderately agreeing with you until this.
I’ve played Dota likely as long as you in addition to playing at a semi pro level (placing well in a couple official pro qualifying tournaments as well as playing pubs with the players the AI played against) and I couldn’t disagree more.
It was impressive, but it’s main advantage came from its inhuman reaction times. They added some buffer but still didn’t account for 5 players working in perfect unison. That kind of coordination is an enormous advantage in a game like Dota. I left roughly feeling like I do now about AI - very impressive, but way over hyped and only sold to people that don’t truly get Dota.
(I'm not a pro or anything, just high rank, but to use myself as an example) I try to make an effort to use the correct words when explaining things to friends. But even I find myself saying things like 'just look at the [lane] creeps' to explain what I want my laning partner to do and then I realise how unhelpful it is. Because when they see the creeps they don't understand what I see.
Years ago I was active in Tae Kwon Do and achieved black-belt status. One time, during a sparing match with my teacher, I was astounded to be able to spot a hole in his defense. In fact, I was so distracted by my perception that I completely froze and he scored a point. I like to think that my seeing that hole gave me a glimpse into what it might be like to be good at TDK. I still think about that experience to this day.
1. https://brucelee.com/podcast-blog/2017/6/21/51-the-three-sta...
Furthermore, modern software management practice doesn’t want this because it wants replaceable cogs. If you can recognize expertise you have to appreciate that teams where everyone is good at everything are nonsensical, and that you need actual balanced mixes of personalities and specialists, which makes hiring a far harder problem. As such recognizing expertise is very much not the order of the day.
"Thinking Fast and Slow" has a whole chapter on this with ample evidence
In my mind that was always just an excuse to hire as many people as possible to grow their org and get promoted to n+1. But hey it worked with 0% rates!
If you have 10 engineers, you need generalists.if you have 1000 engineers, generalists generally are smart people who are potential experts, but not really that useful.
In classical engineering fields, experience was highly valued. In some it still is. In civil engineering, no 24 year old will be able to bullshit their way into senior level roles. It just doesn't happen. The senior guys get more and more valuable. A big part of that is that it's very hard to bullshit your way through that field without at least 6-8 years of experience, and by then you'll hopefully have been humbled enough not to try and bullshit it.
I think missteps and mistakes hit differently when someone traceably stamps their name on a finished product and takes personal liability for it in perpetuity.
I've struggled since then describing why I felt this way and I think the essay helps immensely. In my recollection that developer didn't reach a software vocab point and couldn't really understand the difference. The pain point for me was that I could spot the difference and no one (in management) really cared.
In software world such a word for me was "modeling"
It no longer was "coding", "programming", I started modeling real world
The reason for this is probably different use of the same terms. Some code might be tested within an implementation of a model of the real environment. That is a frequent use-case used to sell graphical languages. The term model is used for two different things: The model of the real world to allow testing and for the implementation of the solution in a graphical language. Of course developers in those environments are Klingons like we all are, no real effort for tests, and only the graphical solution remains. But it is perceived as if it had all the positive attributes of a solution tested in a simulated reality. And therefore something modelled is better, because it is modelled.
Consider, "F=ma" is a mathematical model relating force to mass and acceleration. You can test this by dropping several things each from the same height and seeing that the force linearly increases based on the mass of what you are dropping. Similarly, you could test the model by accelerating something to a halt at different speeds and seeing how much force is imparted into it.
Is that not a "model" because it is not necessarily graphical?
So, similarly, much CRUD software can be seen as modeling different agents in an overall system and what happens when they interact in certain ways.
Edit: I want to add that I think I see where you are coming from. Many treatments of graphical models like to hold them up as a special form of modeling.
For some people model==graphical, usually mechanical/electrical engineers, not software-engineers. Engineers maintain the holy "model", and the translation to lowly code is a job for the lowest-bidding software person.
Maybe it wasn't clear, but I do not agree with that point of view, and tried to explain how I think people may have found their belief.
I assumed the parent^4 was labeling their code model in an attempt to elevate themself to the ranks of the code painters.
Best I can think in this direction, is UML? But that is an odd one, because it isn't that "models" are graphical, but those are specifically models of code artifacts. A model of another modeling language, as it were.
Reading back over the top comment, I assumed that the poster meant they started seeing their coding as modeling of a problem domain. Not that they weren't still coding, somewhat.
Disclosure, I was an EE way back when. We had plenty of numerical models for how things worked. We even had verilog to model circuits using what looks a lot like "traditional" software.
That all said, if I just haven't kept up and "model" is moving in meaning, I wouldn't be too shocked. :D
A case of cargo-cult. Attempt to apply the practice but badly (use the tool, but not the way its use is advertized), and use the terms for use of the tool instead of the practice, reserving it for that to promote their beloved tool over alternative approaches.
Knowing when to use what tool, how to do it properly and to what extent takes expertise as well.
Carpenters and craftsmen in general are infinitely more productive with woodworking and related tools than I will ever be. My destiny is assembling IKEA cupboards. The same principle will apply with AI tools. Sure you can whip up something, but a specialist will do it infinitely better in 1/100th of the time with the same tools.
Guess who will be employed to make use of said tools?
Someone with expertise will use any tools, including GPT, in ways a novice can’t even understand. Same tools, different outputs. Not the tools, because basically anyone has access, but the one using it will determine the outcome. In a capitalist society you will have to compete otherwise known as staying employed.
Someone with expertise can hook up AIs in ways and with a velocity that will leave amateurs in the dust. The amateurs will still be fiddling around with “prompts” and Googling or ChatGPT’ing what “latent” means while the expert has working systems ready to go.
I don’t see this chasm getting smaller. These tools magnify your inherent (in)competency. Try to compete with a professional artist competent with Stable Diffusion if you want a taste of that.
It is important for several reasons:
- As other commenters pointed out, filtering, adapting and integrating ChatGPT output has a better ROI with experts.
- An expert will know the ROI of using ChatGPT, including on the long run, and can assess if it's worth it or not. A non expert will use it for as long as it works, and can hit a wall of technical debts accumulated from the GPT usage that will now sunk the cost of the entire operation.
- Expertise comes with a lot of implicit knowledge that ChatGPT doesn't access to.
- ChatGPT doesn't learn from mistakes in the way humans does. And humans don't share the mistakes they made as much. And experts have made all the mistakes.
- ChatGPT tries very hard not to not be opinionated, or to have an opinion that will offend the least amount of people. IRL though, you want opinionated takes.
There are, however, many situations where being an expert to benefit from ChatGPT is no required. I also find that sometimes being an expert prevents me from getting the most of ChatGPT, because I stick to what I know instead of embracing novel workflows. I have a friend coding things with repeated ChatGPT copy/paste loops over days, and they have done great things with it.
Because there are two parts in expertise: pure knowledge, and a set of weighed criteria to evaluate things. This second part is what I think TFA calls "tacit" knowledge. This stuff is a job for neural networks, but more for Alpha0 than for ChatGPT - although it does probably that under the hood, but it's an expertise used to string together questions and answers. That's enough to give the illusion of expertise, but you still face the problem how evaluating that artificial expert. There are many reports that ChatGPT can be "slightly wrong" that only experts can really spot. You can have ChatGPT do your boilerplate code or bulk work if you are an expert in the field.
I personally think of this part of expertise as the expert's "intuition". This intuition is indeed sometimes difficult to communicate. Sometimes because it comes from various experiences, and describing those experiences in enough details would take far too long. Sometimes A just "feels" better than B because those criteria and weights are subconscious; pretty much like you apply a certain amount of force to lift an object because you have subconsciously evaluated its weight (either with material density and shape, or from memory because you've lifted similar things before) - and sometimes you are surprised because it is magnetized or it the box has been emptied.
However, my criteria to evaluate expertise is still how well the expert can explain something to me - that is, if they are good teachers. This also an unreliable proxy like the "vocab point" of TFA. Not everyone is a good teacher, and impostors or poseurs can make you feel like you understand when they are actually bullshitting you.
ChatGPT could be a good (enough) teacher that can help you becoming an expert (partly because of the fact checking work you'll have to do, something you normally don't have to do with an actual teacher), but ChatGPT as an expert, it is a no-no in my book.
i can't help but notice that Cedric (author of commoncog, and a friend) is accumulating a good body of work exploring knowledge and expertise acquisition. is this something that is generically applicable or are we reading convincing-sounding text generated by a very advanced human expertise language model? I guess the only way to know for sure is for Cedric to open up a coaching practice and see the results?
i can't help but notice that Swyx (author of latent space) is accumulating a body of work exploring LLMs and covering AI progress. is this something that is analysis by an expert or are we reading convincing-sounding text generated by a very advanced AI hype language model? I guess the only way to know for sure is for Swyx to train an LLM or do deep learning research and see the results?
https://web.media.mit.edu/~minsky/papers/NegExp.mss.txt
https://news.ycombinator.com/item?id=30930985
Ability to see expertise is a milestone worth aiming for - https://news.ycombinator.com/item?id=30930985 - April 2022 (18 comments)
"In 2017, Djokovic suffered from an elbow injury that weakened his results until the 2018 Wimbledon Championships, where he won the title while ranked No. 21 in the world." https://en.wikipedia.org/wiki/Novak_Djokovic#Career_statisti...
It's some economic variant of the tree falling in the forest analogy: if a service has quality but no one can recognize it does it have value?
It strikes me as a recipe for regulatory capture and overcredentialing.
Value ultimately lies in the purchaser, not the producer.
Maybe it depends on the market but this seemed to be arguing for something dangerous to me.
I'm not entirely convinced that this holds, in practice. It makes sense for rational purchasers with perfect and complete information, but that is never true in reality, and it ignored all cognitive biases that humans use to make decisions, including being misled by advertisment.
For example, the tobacco industry can scream all they want that smoking does not cause cancer, but being loud about it does not make it true. Initially, people didn't even like smoking because of the bad taste, but massive advertising campaigns including paying celebrities to smoke in public changed the perception of the value of smoking. In a similar manner, after acquiring all major sources of diamonds and inflating their prices, advertisement convinced the public that a man absolutely needs a ring with a diamond to "prove" their love to their bride. Same for the food industry and sugar, you know where I am going.
All of these are examples of "value" created by producers by misleading customers that their product is good and not harmful for them. But facts don't become true or false just because everybody believes in them. People can believe false things, and no matter what they do or say, those things remain false.
Not to mention that immediate value for individuals can have considerable negative value in the long-term for society. Think at the huge resources we spend on finding cures for cancer and obesity, just because we sell addictive stuff and pretend that people "want" those. If you consider society as a whole, this appears to be an extremely inefficient use of resources.
As an update, I temporarily relocated to a different city and spent four months training Judo for five hours every day and have since reached the vocab point for the sport. That experiment was covered here: https://commoncog.com/expertise-acceleration-experiment-judo... and https://commoncog.com/mental-strength-judo-life/
On the topic, I'm reminded of coworkers talking about the most recent Super Bowl (I think, I don't follow sports) which included commentary from players who played as quarterbacks in the same season. One of the things my coworkers mentioned was how interesting it was to hear them talk about the game because they used unfamiliar terms.
It’s also very difficult to protest this kind of approach (edit: the non-goal approach) since merely mentioning things like "goal" or "evaluation" will trigger someone’s knee-jerk you’re-doing-it-wrong reaction, even though what they practice might be completely different to what you are doing or trying to achieve.
I sat next to an Econ professor (at an Ivy) on a flight. I told him I had worked at a hedge fund, and he was like "wow, I could never put myself in a situation where my living depended on my economic theories being right."
A good friend of mine is a kinda-famous evolutionary biologist. He's in his mid-40s now, unmarried and doesn't have kids, and likely none on the horizon.
In the economist case, what does it mean that in his expert opinion, he wouldn't trust his own expert opinion! In the biologist case, what does it mean to be one of the world's leading experts on "evolutionary biology" and yet completely fail to pass your own genes?
What's most interesting to me is that neither of these scenarios strike us as "super wrong." I can imagine most people wouldn't hesitate to attend a class taught by either one of these guys, while we'd avoid analogous situations (eg: we wouldn't use a broke financial advisor or fly on an airplane whose designer refuses to set foot on it.) What's the difference?
This to me sounds like a simple example of he understands the limitations of his work!
As for your evolutionary biologist friend. Being interested in evolutionary biology does not mean you are inherently someone that wants to be a parent. These are very very different things. Besides, evolutionary biology impacts more than just humans, it impacts every species. Being a parent comes with a great responsibility. Someone could just as easily be a really big fan of dogs, but not want one because of the responsibility or the costs, or similar.
If the economist weighs the risk to not put too much stock in these theories (no pun intended actually), why does he not likewise hesitate to teach these theories to his students? Like "I don't believe 100% that this is how the world works enough to bet my own money, but I am going to tell hundreds of students every year this is how the world works."
The biologist story is subtler. One could argue that failure to become a parent signals that you deeply, fundamentally, don't get biology - despite your superficial interest and theoretical knowledge? Like, you may talk about zygotes all day but you failed to make one...
Maybe the difference between economists and biologists vs financial advisors and engineers is that we expect the later to have skin in the game but for some reason allow the former to not have to.
Economics is complicated because at a fundamental level you're trying to understand people and their decisions. Sorry but you're really never going to "solve" that problem. Stuff will forever be a theory.
You are also assuming that the economist is teaching this and saying "this is how it works, it's 100% accurate" and not starting off with "this is a theory, and we work towards making it better over time with new data and new ideas." Just because something may not be 100% perfect does not mean you don't strive to improve what you have and you won't improve what you have if you just let it rot on the vine and not teach the next generation.
The biology one is even more convoluted. Having an _interest_ in something does not mean you have to "be" the interest. A simple example, I work to live, not live to work. I am not my work. My work is only here to support me living my life. You are claiming that the biologist is a failure because they didn't want, or couldn't, create offspring despite their interest being in evolutionary biology. That's some kind of weird argument to make there man...
Would you expect experts in criminal psychology to be serial killers?
> I don't believe 100% that this is how the world works enough to bet my own money, but I am going to tell hundreds of students every year this is how the world works
This is a fundamental misunderstanding of what a good professor does. If the economist acts in this way, they have failed as a teacher, not as an expert in economics. Likewise I think you have a fundamental misunderstanding of economics as a science - it's not one, and it sounds like the economist was making a quip at the predictive weakness of the field overall.
> The biologist story is subtler.
No, it's not. You're just having to push harder to keep it afloat.
> One could argue that failure to become a parent signals that you deeply, fundamentally, don't get biology
One would be wildly wrong to make that argument. Once again, I think this shows a deep lack of understanding on your part of the field itself and what it means to study a field. And also what it means to have a child as a human, honestly.
> economists and biologists vs financial advisors and engineers is that we expect the later to have skin in the game but for some reason allow the former to not have to
Is this not obvious? You're reaching very hard to dig at researchers in a way that indicates you don't know what research actually is. Or maybe you're defensive of the work you do? I shouldn't speculate too hard here or I risk also being this wrong.
This is complete and utter nonsense.
So farm animals understand biology better than the biologist does?
You can study whatever you want, I am questioning if you can be considered "expert" if you profoundly fail at the topic of your field.
In the end, those are 2 different domains. Knowing a certain theory and overcoming all the limitations of applying those are very different.
Let me give you another example: Formula 1 or MotoGP. The engineers are not driving the thing, and the drivers are not engineering it. Claiming that one needs to be able to be a master in the other is weird.
You are confusing the person with the field of study.
This confusion is more obvious if you think about the superconductor/ expert on superconduction example.
A superconductor is a material which conducts direct current with near zero resistance. You can test if something is a superconductor by aligator clipping a voltage source on it and measuring the resistance.
An expert on superconductors is a person who is knowledgeable about the phenomenon of superconduction. You can test if someone is such an expert by asking them questions about what materials are superconducting, under what circumstances they are, what phenomena can be observed during super conducting and etc etc.
If you get confused and clip the aligator clips on the expert you will measure a larger than zero resistance. If you start asking quiz questions from a superconductive material about superconductivity you will observe that it does not answer any of them.
These two things are fundamentally different. You can be good at one while miserably failing the other, or vice versa.
Similarly someone who studies evolutionary biology is someone who studies the effect of evolution on different kind of living things. They are good at predicting things which they can prove later either experimentally, or with observations about creatures and their circumstances. It has nothing to do with the act of procreation. A disembodied AI can be an expert at evolutionary biology as long as it has good theories on the topic which it can support with relevant evidence.
Through two practical examples. Someone who is good at surviving at evolutionary timescales is for example a person with a handfull of healthy, and fit children. Each of them carrying a mutation which makes their female offspring (daughters, grand-daughters and so on) have a tiny bit wider hips thus increasing their chances of having uncomplicated births, thus increasing the chances of having lots of lots of offspring a tiny bit.
Someone who is good at studying evolutionary biology for example might be able to explain why animals trapped on an island all over the world seem to change in a way that their offspring becomes smaller in stature.
Mixing up these two is as silly as measuring the resistance of your superconductivity experts.
In the case of the evolutionary biologist, successful procreation does not require any knowledge of biology.
When it comes to planes, there is a high correlation between the quality of the plane and the quality of the design.
Maybe this is a good point. I would argue that a high school kid who knocks up his girlfriend has demonstrated a better intuitive grasp of biology than my PhD friend.
Not even a little. The high school students are slaves to unconscious drives in their bodies and that's not even related to having an understanding of biology. Or do you say that a world expert in biology who would rather spend their time furthering studies than raising a child actually knows less about biology than rabbits? Your arguments aren't making any sense.
A bacterium can perform cell division, but it can't explain it. The evolutionary biologist's job isn't to personally have sex, it's to explain what happens when many generations of organisms do so.
It means he sees the difference between a biological imperative and a moral imperative - who says he's "supposed" to pass on his genes? A strand of deoxyribonucleic acid? Is this judgement exhibited exclusively by proteins, or can a chunk of plastic also judge you for not knocking a girl up?
This sentiment was so elegantly expressed and struck a chord. Thank you for that.
"You do you" is the correct answer in almost every case. Evolution does not pre-select and deliberately make copies. It's a process where individuals do their thing and let the chips fall where they may. The process takes care of the rest.
I don't think they are wrong at all. That's what I would expect. In my experience, one of the marks of being an expert in a subject is being very aware of the limits of their knowledge and expertise in it.
the economist might not specialize in theories about why, when, or how much specific assets go up or down. even if he did, he might not have the skills to make actionable predictions from messy input data. doesn't mean his theories are wrong, just that someone else needs to bridge the gap between theory and application.
evolutionary biology has almost nothing to do with being a good parent. I don't think this even requires an explanation.
the financial advisor is the exact opposite. managing personal finances is the exact problem they are supposed to help you solve. if they can't do it for themselves, that's a pretty strong reason to doubt they can do it for you.
On top of that, it's not uncommon that experts understand the risks, unknowns and potential other choices better than early level practictioners.
Experts can see all the gradients in ability and will extrapolate how far they are from the top, but all novices know is how far they are from the bottom. If those distance estimates are biased, it’d lead to novices overestimating ability and experts underestimating
i think expertise is "mastery of system 1(ref Daniel Kahneman) of a topic." which means identifying more "patterns" through "practice and observation." the patterns capture both the rights and the wrongs.
the entry to any subject is "learning the language" of the subject. what comes next is to become "mature." maturity is based on amount of practice in a big and unbiased search space, the ability to play with subject and identifying primitive constructs, ability to criticize and seeing the weaknesses,
the measuring method for maturity level is amount of "simplicity," "freedom", "flexibility", "speed", and "ability to identify the essence" that the system one adheres to bring.
excerpt from Saunders Mac Lane "category theory for working mathematician." "many properties of mathematical construction can be identified using universal mapping properties." see how simple the definition is?
The relevant question is - does it matter? The Formula 1 pit crew is more expert than the mechanics at the Toyota dealership in ways I can't appreciate - but does it matter for my Highlander's oil change?
The answer might be "Yes, the F1 crew will do it in a way that prolongs the life of your engine" (I care about that!) or "Yes, the F1 crew will change your oil in 20% of the time" (I may or may not care about saving a few minutes every 6 months) or "No, you won't notice a difference but they are just more expert" (in which case I totally don't care!)
Part of expertise is ability to articulate its relevance to a given situation. Your customer may need help in validating your expertise, but at least start with the claim of what you can do.
F1 teams do have world class mechanics but most of them aren't part of the pit crews.
This is not true at all. F1 pit crews are mechanics who have worked with cars in other motorsport racing series/feeder series and worked their way up to an F1 team.
It might be trite, but as a contractor walking my rate up over 10 years, I found it interesting.
The path you are hitting on implies the client/employer already knows what they need and are gatekeeping on it. It's great to be able to get past those gates - ie, if you've grown yourself into a FAANG-caliber engineer, go interview at Google, but in this case Google already knows what they need and what that looks like.
The line from the article that I cited is the other dynamic - where the client doesn't know what they need. You're right that might be because they are a low level client and don't actually need your expertise (what you mentioned) but it may also be the case that they do badly need you but can't recognize it because of your relative difference in levels.
In general, the higher your level, the more likely it is that even otherwise high-level people will not understand the nuance of what you can bring to them. In that case, there's the sales process that should kick in, and by sales I simply mean helping the client see that they have a problem and that they would be much better off if that problem was solved, and that you're a rare breed who can do it.
> In every profession there’s a point where further improvements in skills are so subtle that the difference between one level and another can only be appreciated by another expert
Goal defines the benchmark for proficiency.
Better tennis player scores. Better software engineer writes more space/time efficient code or solves business problem faster (whichever the objective). Better writer gets more views or inbound sales or whatever the goal is.
If you get better at achieving ever greater goals, then your expertise is growing. No amount of luck can compensate for a lack of expertise.
I was struck by the anecdote that Herbie Hancock tells in the linked video though. He misheard some advice from someone he respected, took it to heart and it changed the way he played.
I notice that this seems to work in opposition to the idea of a vocab point where high level practitioners are talking about real concrete experiences they are having that the lay man can't understand until they level up.
The way I think it worked in this case, is that as you go up the ladder of skill, you start seeing and thinking in more abstract, metaphorical terms. For a beginning student, you're focused on the mechanics, for the master, you're focused on what it means and how it relates to the human experience. This means that a master can apply an a metaphor that the beginner can't even understand. Indeed, Herbie Hancock can apply a metaphor that nobody else could even imagine had any relevance at all.
Perhaps rather than 'vocab point' we should talk about 'metaphor point'.
Moreover I see it as a huge problem in our current environment of easy access to Youtube explainers of everything. In my areas of expertise I come across many more people that 'talk the talk' than can actually 'walk the walk'.
A chef must be judged on dishes they produce, a dancer on their performances, and a software developer on working code.