One of the father's of quality, W. Edwards Deming came out very strong against Management by Objective, even though he was very statistically inclined. In his 14 points [0] he mentions Eliminate numerical quotas for the workforce and numerical goals for management..
His idea is you should focus on the journey (always improve) rather than artificial endpoints. It's a profound idea, and one I've sometimes struggled to come to grips with.
So how do you know whether you're always improving if you don't measure your performance at consistent points along the way? Just ask everyone if it felt like you improved, followed by a group hug and mutual back-patting?
Going by his theory... If you say, "I am paying you to produce 1,000 cars per month" then that's what you'll get. If instead you rely on intrinsic motivation, and improve the system, you will get more than 1,000, and they'll be higher quality.
This doesn't work everywhere. (Certainly not with Sales commission!) But it is worth thinking through the logical implications of it.
An important distinction. Thanks! And absolutely right, if the objective is to "do X" then you're setting yourself up for a plateau and for resentment every time you try to move that plateau. But if the objective is to "do X% better" then that's a natural exponential growth curve.
The article is terrible - it is effectively saying "being objective" is not good for achieving that "objective". This is complete non-sense without untangling the epistemic roots for said words, the author may have had.
It's apparent that it's actually saying that being too "greedy" (i.e too low a horizon) can be bad for achieving an objective. This is well known to both Control theorists, RL practitioners, and many other non-STEM people (in marketing/politics/sociology etc.).
This triviality has nothing at all to do with Zen or any of the things Westerners take for being "rustic" and "warm and fuzzy".
Have you read or watched what the picbreeder author is actually about? It's not about a greater horizon. It's that you only get "valuable results" by using a heuristic that only looks at the very next steps, and completely ignoring any goals that would lie further ahead. You could say that he's promoting a greedy search with very broad success parameters.
An example: You plan to be a millionaire, and you currently have nothing in the bank. How do you get there? Any plan would most probably not work, if executed in a rigid manner (or we would all look up the recipe on the internet and be millionaires). You end up trying all kinds of jobs, investments, take opportunities when they arise, etc.. and finally you realize that you probably will not ever make it. Or you get lucky and make your million - who knows. Picbreeder showed that it's quite rare to hit the very desired result you wanted.
However, if you were more flexible regarding your goal, at every step, then you might take the job that agrees the most with you, meet a lot of great people, travel if you are able, start a family.. and end up without a million in the bank but with a satisfying life situation. With pic breeder, certain shapes and beautiful pictures emerged that were not intended or planned from the start. The algorithm went along with whatever was there, and optimized on that.
Looking at the millionaire example again - if you already had 500k, then doubling that might not be that hard (?), or not that many steps away. People keep saying that the more money you have, the easier it is to earn - think opportunities like buying an apartment in a firesale and reselling it for 1.5 as much.
For me, it's a very counter intuitive way of looking at things. It goes very deep against the wanting of goals or things in our current society. OTOH, it somehow makes sense that things work this way, because every step in our step-by-step plans is SO dependent on things beyond our control. Agile development methods remind me of this very much: Try telling a customer not familiar with agile that the software she orders might look completely different than she imagines it right now - most will think you are crazy or want to cheat them. But you might recognize problems in every sprint, and adapt the end goal accordingly.
I find an interesting parallel with hill-climbing and local optima. In your example, the reason everyone isn't a millionaire is mostly to do with the fact that that's a very noisy problem space, there are far far too many random variables at play, not to mention there's a finite supply of money, it's literally impossible for everyone to be a millionaire (well, you could inflate the currency to the point where a million dollars is nearly worthless, but that's just playing semantic games).
To me, one of the big takeaways here is that it's important not to be so hyper-focused on the local problem space that you overlook potentially better solutions and end up at a local optimum to your overall detriment.
As for the rest of the article, it's mostly hand-wavy garbage.
> not to mention there's a finite supply of money, it's literally impossible for everyone to be a millionaire (well, you could inflate the currency to the point where a million dollars is nearly worthless, but that's just playing semantic games).
Most people who are millionaires don't get there by holding a million dollars in currency, they get there by holding assets worth a million dollars. This is not zero sum - assets can be created (and destroyed), and their value is assigned only at the time of transaction. The total value of all assets in the U.S. is significantly larger (by orders of magnitude) than the total amount of U.S. dollars available.
It isn't a question of actual dollars in circulation, you can always print more after all, it's a question of total economic value. All goods in circulation in the U.S. have a finite value, and it definitely is a zero sum game. You can add more goods and therefore value, but that can only happen at a certain rate (this would be tied into population growth, employment rate, and profit margins among other things). There are also close ties with median income as the value of goods tends to be tied directly to wealth distribution. Ultimately at any given time there is a finite amount of "wealth" to go around, if one person gets a bigger slice, then that means someone else has to take a smaller slice. People don't want to be millionaires because they have some unhealthy attraction to U.S. currency, they want to be millionaires because of the goods and services that they can trade that money for (or in many cases because they can use it for rent seeking to generate unearned income). The actual amount of currency in question is irrelevant, it's a question of access to those goods and services, and those goods and services are finite, therefore wealth is finite.
If economic value were zero sum, then economies would never grow.
>All goods in circulation in the U.S. have a finite value, and it definitely is a zero sum game.
Except I can create new goods, possibly for free (e.g. writing software, growing crops, mining materials) and directly increase the value of the economy. Contrary to zero sum.
>You can add more goods and therefore value, but that can only happen at a certain rate
Unless you want to try to argue that the rate is so low that the economy is *effectively zero sum in the short term, you've just contradicted yourself. If you can add value to the economy, it is fundamentally not zero sum.
You seem to be conflating the finiteness of wealth and value with the inability to create new wealth or value.
Now, that aside, one could argue that currency exchange itself is zero sum on short timeframes when new money is not printed, but market forces dynamically assign value to currency, such that the economy may still grow with a finite supply of money. Furthermore, I'd like to point out that generally when one purchases goods or services, even in the short term the transaction is unlikely to be zero sum, because goods and services can be used immediately to generate more wealth, and therefore are arguably worth more following the exchange.
More or less your first point, the rate of growth is so low, that over short term it's effectively zero sum.
Something else to consider is that in your example of "for free" wealth creation you're not actually getting any of that for free, that's a form of wealth transformation or transfer. Let me elaborate on that point using each of your examples. I'll start with mining as that's the simplest, in that case you're taking a natural resource (which is finite) and extracting it and refining it. You're having to pay your workers (and/or buy and maintain machines) in order to do so, so in part your redistributing the companies wealth to the workers and service providers your company does business with. In exchange you receive raw and/or processed minerals/metals. That might seem like wealth creation but it's really transformation, you've reduced the value of the land you extracted the material from and converted it into a transportable form. The value of that material might seem to be more, but that's only because you've invested value in extracting it, in other words you're passing on your cost of doing business. You haven't added value, the value was already there, you've simply converted it and invested some of your companies value into it, so when you sell it you're simply converting one form of wealth into another, you're converting the wealth of that processed material into cash wealth.
The situation with growing crops is similar, although part of what is being invested there is time. You might think, "well, time is infinite, there's always more time", but each persons time is finite and it has value, even if only to that person (opportunity cost), so once again you're doing a wealth transformation, you're transforming those workers time into money, and ground, seed, fertilizer, water, and sun into crops. When you sell those crops you're once again recouping your cost of doing business. Wealth hasn't been created from nothing, it was transferred and concentrated from a variety of sources. You might think, "well, what about the workers time, that's new wealth", only it isn't, there was a cost involved in those workers upbringing and living, so that's once again just a form of wealth transfer and transformation. Truly the only free wealth in the entire thing is the sun, although even that isn't infinite, even if it is free from the perspective of anyone on Earth (it might be more accurate to say it's wasted/destroyed if you don't use it). Ultimately there is no free lunch, entropy always wins.
Software is the most complicated one, as there's zero unit costs associated with it, but substantial development costs. Once again though, you're looking at wealth transformation/transfer. In the case of software you're transferring/transforming the developers, QA, and other workers personal knowledge and time into software. Similar to the workers in the previous example they've invested time and money into improving their knowledge and living, so you're really paying them for them to recoup their losses (wealth transfer) and then when you sell the software you're simply passing those expenses on to your customers.
Ultimately it's all about wealth transformation and transfer. There is finite natural wealth, it existed before humanity, and if humans vanished tomorrow it would continue to exist. Economies are mostly about taking the existing wealth and distributing, concentrating, and transforming it into forms that are more convenient for people. When you get down to it, the unit cost of a good is really it's intrinsic value, it's a form of wealth transformation. Profit margins on the other hand, are wealth transfer, you're transferring wealth from the purchaser to yourself. No value is actually being created. New wealth only comes from discovering new resources. Want to create wealth now? Do like Elon Musk and others are doing and take a look at asteroid mining.
pg (and many, many other entrepreneurs and investors) disagree vehemently, positing that startups are about wealth _creation_. if wealth isn't created, how has humanity's global standard of living so radically improved?
Some startups will create extra wealth, some will destroy wealth some will redistribute it.
Imagine I create a new shoe factory right next door to an existing shoe factory. After 10 years we find...
1) I failed, I lost all the investors money and had to close down. I destroyed the investors wealth.
2) I win, the next door factory has closed down and now I have all of their business. But I have exactly the same costs, sales, staff and so forth. So the profits come to me from now on instead of the neighbor. I have supplanted them, but consumers and the economy as a whole is no better off. Wealth is transferred to me as ongoing profits that would otherwise have gone next door.
3) I win, the next door factory has closed down and now I have all of their business. I produce the same output as they did but with less staff and lower costs. So consumers benefit from lower prices, the money they saved can be spent on other things, creating demand elsewhere. Wealth is transferred to me as ongoing profits that would otherwise have gone next door. Everyone wins except I employ less people than the neighbor so there is less employment. But the extra demand for other goods because of my lower prices means they get employment at other businesses!
Number 3 is why the UK, which used to employ 90% of people in agriculture before the industrial revolution, does not have 90% unemployment today, the people released from agriculture because of better productivity are freed to work in other sectors instead.
In the scenario where a startup destroys wealth, what they're really doing is redistributing it. It's not like they take the investors money, cash the cheques, then burn the cash.
Isn't there also at least a fourth and firth scenario, one where the new shoe factory wins but has larger costs than the old one (better marketing but worse cost control), and another scenario where both shoe factories thrive? What about one where they merge, or a holding company buys both and operates them both to produce different lines.
In some cases they actually do destroy wealth in the process of redistributing it.
For any startup that subsidizes its products below its costs it is possible for it to destroy value. If they produce something for $10 dollars then sell it for $8 to someone who derives $9 of value out of it, then they have transferred $1 of wealth to their customer and have destroyed $1 of wealth.
4) You win, The neighboring shop is still there, you have specialized and they have specialized and the available breadth of product in your category (shoes) has created consumer choice to capture a larger share of wallet.
That also implies that demand for other products has fallen, so that's just wealth redistribution (because you're taking a larger share of their wallet).
AIUI, it's about having an objective function which measures something other than the delta to a pre-defined goal, but rather a higher-level more abstract function.
Another phrase for it would be "unknown unknowns": if your success criteria are too focused, you'll miss out on solutions that you couldn't conceive of before they're discovered. The "Objective" criticised in this article is like a "known unknown".
More than that, even when they discovered an interesting result, they couldn't go back and create an objective based algorithm that could return to that result... even though it was known to be possible. (I mean, they obviously knew the specific steps taken, but they couldn't create an algorithm that could re-find them with a specific result in mind.)
It would be interesting to see if you could improve on the results supposedly disproving having an 'objective'. I haven't sat through the full 40 minutes of the video and I don't see any writeups on the Picbreeder website (which appears to have not had any news updates since 2011), so I am guessing that what he did was using a CNN image classifier and do greedy maximization over the various options on each step; it will surprise no one in RL that this does not work as it is not a convex problem. But a RL CNN trained to instead predict human choices (imitation learning) or do RL learning with rewards just from the final step (perhaps Christiano's preference learning setup?) might do much better.
After all, all the comments about the folly of greed apply just as well to choosing moves in Go, but you don't need to abandon 'the myth of winning' to win Go. It's simply about having an excellent heuristic for promising directions and keeping options open.
I my case, my greatest flaw in playing GO was losing sight of the objective - i.e. gaining more space everywhere. Instead I would zoom in too tightly on wherever the last few moves had happened; win battles and lose the war. I suspect that's very common in newbie GO players. But I still like the article, creativity is a different task with different pitfalls.
Interestingly, the main description of AlphaGo v2/Master's play by the Go players & experts on /r/baduk & commentaries elsewhere is exactly that: compared to the human Go players, it is very willing to disengage from a local fight to make a move elsewhere globally, often ending josekis early just to get in the first move elsewhere.
I'm confused, is it about "objective" as in the adjective, or about "objective" as "goal"? Perhaps my English is not good enough but I fail to see the first in the text.
> This is complete non-sense without untangling the epistemic roots for said words, the author may have had.
Ah, but you see when Plato was saying pharmakon (drug, poison) what he actually meant was pharmakos (scapegoat); since he didn't actually saypharmakos, by its absence that must be the true meaning!
This is why it's important to have passions outside of those that pay the bills. And, if your passions and finances are entangled, which is the goal for most, it's important to build structures that allow times of absolute creativity (time in the goalless path). A writer still must spend time editing his work, which is a different process than creating. So, if you have profit in the back of your mind throughout the process, as the essay notes, you will stifle yourself. If you have an editing process, where you line up your creative expressions with profit, you're basically doing what a writer does when he edits.
Bill Walsh's The Score Takes Care of Itself is a fun book that, as the title suggests, deals with this idea.
Think about Zuckerburg's wealth. If he had sat in his dorm with the goal of building a multi-billion dollar empire, do you think he would have started with "thefacebook"?
i felt the title was too over-reaching than one of the actual conclusions "Objectives can, ironically, be obstacles to innovation and creativity.".
key word for me is *can. Objectives are pretty good in some cases, but not all. Or perhaps, when they ran their machine learning, they needed to first run some unsupervised learning =)
It would be interesting to test this on academicians: take objectives off of them (grants, large number of publications; hell, even tenure!) and let them wander freely through their field of research. I have the impression this was normality decades ago.
Another interesting manifestation of the same idea is expounded by John Kay, under the title 'Obliquity'. He has a book on that topic, and also several hour-long YouTube talks.
The central theme is regarding how it is better to chase goals obliquely rather then head on, especially when goals correspond to holistic/unspecifiable things like "wellness". He has case studies of companies that managed to innovate or not, depending on how carried away they got with their objective.
The article made me realize I do this frequently. I keep an eye out for serendipity. Encountering new problems often makes me take up an adventure from months or years ago where I learned a new piece of technology or a method that _seemed_ like a dead end at the time, but becomes a stepping stone in hindsight.
A dead end only means you're looking at the wrong direction at _that_ moment.
Having spent a lot of time with PicBreeder, I suspect that the "ancestors look nothing like their descendants" thing is more an artifact of how our brains interpret images, rather than implying some deeper insight into how objectives affect the process.
There are AI projects that attempt to approximate a "natural image manifold" – essentially a blob in the space of possible images where you find things that look like photographs to humans. I think the PicBreeder thing has more to do with that; the set of images that people want to create occupies a relatively confined space within the set of all possible PicBreeder outputs. So working off of any previously built image is basically a "shortcut to the manifold", if you will.
Or to put it another way: when you consider the entire space of PicBreeder outputs, any existing image is much closer to whatever you want to make than starting from scratch.
Surely the human taking 70 steps to find an interesting image is _less_ aimless than the computer that took 30,000 steps and didn't find anything interesting? In other words a non-local goal was somehow forming in their mind drawing them down a particular path? Or am I missing something?
This is mostly a problem when your thinking about objectives admits only one at a time. Many more opportunities arise when we find an interesting compromise in full awareness of the conflicts among multiple objectives.
I've read most of the book and I am confused by the fact that it completely skips artificial evolution (especially obvious in the domestication of cats and dogs).
No it's not. Evolution itself does not have the objective of creating something.
Regarding evolution, having read both Kenneth's book and "The Blind Watchmaker" by Dawkins I can tell you that Kenneth rediscovers what Dawkins explained in his book in 1986.
The experiment Dawkins describes in his book resembles the picbreeder experiment a lot.
Wouldn't humans creating recognizable images by choosing a particular aberration that looks like something familiar be more akin to intelligent design? Without this intelligence and creativity to see something in each new breed and branch, coupled with the ability on the site to rank images and label images. The final images would have ever existed.
According to Dawkins, Evolution has two objectives. Optimizing survival and procreation. We saw how the randomness toward an objective failed to produce anything meaningful in this example so how is this similar to natural evolution?
the point is that you cannot design it. you're exploring the space looking at what is interesting. So if you're given a start image and an end image (an objective) you cannot reach the end image. In the case of pic-breeder you are playing the role of a fitness function not that of an intelligent designer.
The "objective" part is a bit confusing. Evolution doesn't have objectives like "create the turtle, elephant, and man". Which is what is meant by "The Myth of the Objective".
Evolution has two eyes on the path (optimizing survival and procreation) and none on objectives (concrete outcomes, i.e. specific organisms).
This sounds like anthropomorphizing (or at least teleologizing) evolution. "Evolution" is just the name we give to the observation that some random adaptations confer survival advantages and thus are seen more frequently in later generations. At no point is there any intention, direction, or goal.
> When you have one eye on the goal, you only have one eye on the path.
> Objectives can, ironically, be obstacles to innovation and creativity.
This, like much of the Zen worldview, is self-refuting. If objectives can be obstacles that leave me with only one eye on the path, then the new objective is just to focus on "the path" of innovation and creativity. My objective may have changed, but I still have an objective.
Another way of looking at it is that having both eyes on the path is a bi-product of not having an objective. You are not distracted by superficial goals. If you objective is to focus on the path, you now miss all the opportunities the paths lead to.
So how do you harness the knowledge that many of the best ideas that have been thought up weren't the original intention or objective. I don't get the point. I think this is saying something like, only fate will create something extraordinary. This is useless nonsense.
Most of the claims of the video and article seem to lead nowhere, or are commonly known and while mildly interesting, are easily explained by logical observation and analysis. Knowing them doesn't help get you anywhere (that would be an objective). If there is no objective to the video, then why watch it. This is starting to sound like some kind of relativism.
The success of PicBreeder is accomplished by individuals ability to see interesting things evolving and the vast number of real world similar objects they had to choose from. Of course an algorithm cannot replicate that because it is not creative. This does more to dis-prove natural evolution IMO because the images that took shape required creative intelligence to facilitate them doing so. As to the point of the final pictures only appearing when there was no particular objective, OK fair enough, but how does this help us? What new thing did we learn? We know that many inventions and innovations were discovered this way. Why is it an epiphany? The computer could not create a recognizable picture because it was only given one. If it had the google images library to match to, it would certainly come up with some very great pictures.
On the Living Image Project, The recognizable images didn't happen, because different people saw different things and voted different directions. This failed precisely because there was no objective. If the Living Image Project stated an objective (A teacup for example), it would have had far more success. This just goes to show that objectives are important because in the real world, there are needs. If the article and video was useful, it would have revealed something helpful about how to fill needs (objectives) in a better way. The majority of problems are solved with objectives in mind. This article and video never seem to recognize that. The conclusion almost seems to say that attempting to fill known needs is a problem in the world today.
In the Novelty search demo that was shown, the biped that used the novel behavior algorithm walked better than the farther distance algorithm only explains the constraints that the failing algorithms had. All it proves is that when an algorithm has more choices to explore, in many cases it did better. To me this would be like telling someone to build the best house, car, ETC but only use the knowledge from 3 books. Tell someone else to do the same but use the internet, unlimited books, Talk to people ETC. Should we be surprised at the result? Kenneth Stanley seemed to be, and seemed to think it revolutionary. What new thing does this teach us in practical terms? Nothing. More stepping stones mean a better result. This is common sense.
It is no wonder the National Science Foundation would not give this guy any money. He hasn't taught us anything new. I want my 30 minutes of life back.
His idea is you should focus on the journey (always improve) rather than artificial endpoints. It's a profound idea, and one I've sometimes struggled to come to grips with.
[0] http://asq.org/learn-about-quality/total-quality-management/...