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December 8 - December 29, 2024
The process of setting an objective, attempting to achieve it, and measuring progress along the way has become the primary route to achievement in our culture.
Objectives are well and good when they are sufficiently modest, but things get a lot more complicated when they’re more ambitious. In fact, objectives actually become obstacles towards more exciting achievements, like those involving discovery, creativity, invention, or innovation—or even achieving true happiness. In other words (and here is the paradox), the greatest achievements become less likely when they are made objectives.
The problem is that the stepping stone does not resemble the final product.
Sometimes the best way to achieve something great is to stop trying to achieve a particular great thing. In other words, greatness is possible if you are willing to stop demanding what that greatness should be.
Being open and flexible to opportunity is sometimes more important than knowing what you’re trying to do.
A peer-reviewed study found that nearly two thirds of adults attribute some aspect of their career choice to serendipity [22].
To arrive somewhere remarkable we must be willing to hold many paths open without knowing where they might lead.
That may seem obvious because subjecting a cell to an IQ test (or any intelligence test) is unquestionably ridiculous. But the fact that it is ridiculous is exactly the point, and is why this experiment should ring alarm bells for anyone who still believes in the myth of the objective. Is it any less ridiculous to search for skulls on Picbreeder by comparing the image you’re currently breeding to a skull? Is it any less ridiculous to try to achieve any far-off, ambitious objective by measuring how close it is to our best candidate so far? What this thought experiment exposes is that the
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Are there actual examples of this? It seems like the "ambitious" goals the authors discuss would not be formulated at all, making the point moot
Just as Ken could only evolve the Picbreeder Car by not trying to evolve a car, so could nature only produce us by not trying to evolve us.
So far, this sounds absurd and baseless
we should be careful when objective tales are spun around open-ended constraints like “survive and reproduce,” because meeting a constraint is much different from what is usually meant by objective-driven achievement.
Almost no prerequisite to any major invention was invented with that invention in mind.
Great invention is defined by the realization that the prerequisites are in place, laid before us by predecessors with entirely unrelated ambitions, just waiting to be combined and enhanced.
Rather than thinking of the future as a destination, it becomes a road, a path of undefined potential.
Behind any serendipitous discovery there’s nearly always an open-minded thinker with a strong gut feeling for what plan will yield the most interesting results.
Objective-driven search is much different: A car with a more efficient engine is always more efficient than a car with a less efficient engine, no matter when either of them was invented. The point is that what’s better and what’s worse doesn’t change when searching for an objective. Because novelty search can’t provide such a consistent notion of bad and good, it also can’t provide an ordering from bad to good. But it does in fact provide a more interesting ordering: from simple to complex.
Because eventually you have to acquire some kind of knowledge to continue to produce novelty, it means that novelty search is a kind of information accumulator about the world in which it takes place.
In the usual interpretation of evolution, innovations like eyes or lungs might be considered objective improvements, increasing a creature’s ability to survive. But they can also be viewed as the inevitable tendency of a search with no final objective to accumulate information about its world.
In a sense, over eons our bodies have become a kind of encyclopedia of facts about the universe in which they exist.
The behaviors that really become stepping stones to further behaviors are the ones that respect how the world actually works. Driving to work leads to more possibilities for novelty than crawling there, because your entire day isn’t consumed by traveling to and from your job. So given both options, a search for novelty would tend to focus on driving to work rather than crawling because it’s a better stepping stone.
In short, the best way to create novelty is to exploit the way the world really works and accumulate information about it.
While divergence abandons the comfort of probing only in one predetermined direction, it is no coincidence that the term divergent thinking is associated with creativity and innovation.
the reach of novelty search is greater but not unlimited. This result raises a deep question: What can be done then for the most complicated problems, what approach is left that can consistently solve them? Maybe there isn’t really a satisfying answer to this question.
Then why include it in the book?
a famous principle called the No Free Lunch Theorem by David Wolpert and William Macready showed that there is no overall best algorithm for searching, not over all possible optimization problems [57]. In fact, it turns out that improving a search process to reach certain objectives will always hurt its performance on a different set of problems.
The main point is that the treasure hunter can be harnessed to create and discover innovative concepts that otherwise would never exist. The interactive catalog is just one possible application (Chaps. 7 and 8 will hint at other applications of the idea). More importantly, the interactive catalog demonstrates that this way of thinking can yield new approaches to innovation that aren’t based on traditional design principles.
Search is at its most awesome when it has no unified objective. Just look at natural evolution, at human innovation, at Picbreeder, or at novelty search. These are not all the same process, and some are more grandiose than others, but they do share the single unifying theme that they have no objective.
D. H. Wolpert and W. Macready, “No free lunch theorems for optimization,” IEEE Transactions on Evolutionary Computation, vol. 1, pp. 67–82, 1997.CrossRef
For example, the quote beginning this chapter echoes Campbell’s law, which is well known in the social sciences [58]: “The more any quantitative social indicator is used for social decision-making, the more subject it will be to corruption pressures and the more apt it will be to distort and corrupt the social processes it is intended to monitor.”
A more poisonous and extreme form of Campbell’s law is the problem of perverse incentives. Strangely, sometimes rewards or measures chosen to make things better actually make them far worse.
As we begin to discuss human society, of course we should proceed with special care. It’s not every day that an insight first uncovered in an online picture-breeding website ends up informing cultural behavior. Congress doesn’t traditionally legislate based on the latest breakthroughs in mathematical theory.
measuring performance against any ambitious objective leads to deception,
In fact, rather than assessment, perhaps the best way to organize teaching is as a giant treasure hunt for the best approaches.
Hundreds of years later, after narrowly missing out on being the first explorers to reach the South Pole, Robert Falcon Scott and his men ran out of food on their attempted return to civilization, tragically freezing to death [79]. The stories of early explorers grab us. There’s something enthralling about the raw danger and untapped potential of the unexplored.
there’s trouble lurking behind the apparent common sense—the main effect of the system is to reward consensus. In other words, the more the reviewers agree that the proposal is excellent, the more likely it is that the agency will fund it. The problem is that consensus often works directly against exploring stepping stones.
Note that we’re not suggesting that all-around poor proposals should be funded.
This argument ties into objectives because rewarding consensus is based on objective thinking. In the objective view, the more that experts agree that a path is worth taking, the more likely we should take it. The agreed path is an objective choice because people agree with its destination. The amount of agreement among experts provides a measure of the best destination—it’s a kind of objective evidence.
But we’re not suggesting that all scientists should work in isolation.
The problem once again is that it can be short-sighted to judge an individual stepping stone by a criterion better suited to the whole system. Ultimately the aims for science as a whole are to uncover deep and transformative truths—but it may not matter at all if any particular project is transformative.
Although created for purely mathematical purposes, a particular branch of abstract algebra called group theory nonetheless has practical applications in both chemistry [92] and physics [93].
As usual, you might ask how we can so smugly idolize stepping stones without knowing where they lead. But that’s just the fading whisper of objective thinking.
Some research should be pursued simply because it’s interesting, even if it’s entirely unclear where it may end up.
There are plenty of arguments for avoiding the holographic TV company, but one of the biggest is that at some level we all know that holographic TV is many stepping stones in the future.
It’s easy to find dramatic examples of serendipitous chains of stepping stones in the history of art and design. For example, in painting, Impressionism led to Expressionism, which led to Surrealism.
When you think about abandoning objectives, it might seem particularly difficult to follow through because no one wants to wander aimlessly through the world. Without objectives, the only remaining options might appear random or pointless. In this context, you might think that doing nothing might be just as good as trying your best. But that would be to misread the deeper implications of this book. All of us have an uncanny instinct for sniffing potential wherever it might lead. That very human skill does not require an objective, which is why freeing ourselves from this objective straitjacket
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No reasonable person would suggest that all objectives should be wiped entirely from the Earth.
The time when we might want to change our behavior is when we begin to trespass beyond the familiar, when the hope is for greatness, discovery, deep insight, or radical innovation.
So while it may feel that we’re being asked to give up something sacred, we never really had it anyway. No great breeder could intentionally steer evolution from single-celled organisms to multi-billion neuron brains, no matter the time allowed. No Stone Age genius could build a computer, and no modern-day master could build a time machine. Clinging to grandiose objectives like those offers no real escape from the unimaginable complexity of the search space, that great unknown.
if you want to be a treasure hunter without a specific objective, then there is a special kind of clue—when something feels interesting. That may sound simple, but the lesson behind it is deeper. It means that you can go treasure hunting by following your instinct for the interesting, not because you know where you’re going, but because you feel the potential in where you are right now. Even just accepting that this treasure-hunting approach makes sense is important. It opposes so many of the messages we receive today from our culture that say you need an objective to achieve anything
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That isn’t to say that ambitious objectives can never be achieved.
So while flight was an objective for many failed visionaries over hundreds of years, it was when the bicycle-makers realized that planes are bicycles in the sky that it actually happened [105].
Judgmentalism is the natural habitat of the objective-seeker, always worried about where everyone else will end up.
