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Why Greatness Cannot Be Planned: The Myth of the Objective Paperback – 18 May 2015
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Why does modern life revolve around objectives? From how science is funded, to improving how children are educated -- and nearly everything in-between -- our society has become obsessed with a seductive illusion: that greatness results from doggedly measuring improvement in the relentless pursuit of an ambitious goal. In Why Greatness Cannot Be Planned, Stanley and Lehman begin with a surprising scientific discovery in artificial intelligence that leads ultimately to the conclusion that the objective obsession has gone too far. They make the case that great achievement can't be bottled up into mechanical metrics; that innovation is not driven by narrowly focused heroic effort; and that we would be wiser (and the outcomes better) if instead we whole-heartedly embraced serendipitous discovery and playful creativity.
Controversial at its heart, yet refreshingly provocative, this book challenges readers to consider life without a destination and discovery without a compass.
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“It is a very nicely written and enjoyable book, aimed at a general readership. It is also surely worthwhile reading for Artificial Intelligence (AI) researchers, particularly for those of us working in genetic programming. … I recommend Why Greatness Cannot be Planned. It is definitely unique within the evolutionary computation community.” (Leonardo Trujillo, Genetic Programming and Evolvable Machines, Vol. 16, 2015)
"What is your ultimate goal -- your true objective -- when you pick up a book? The authors of this one believe that there may be no objective at all involved, just a diffuse feeling that a book can change the way you look at the world. They may be right." (Prof. Christos Papadimitriou, University of California, Berkeley and Co-author of the New York Times Best Seller "Logicomix")"One of the original aspirations of Artificial Intelligence researchers was to help all of us, as thinking beings, understand ourselves better. Stanley and Lehman are among the few who have managed to achieve this. In this book they not only shed light on a glaring bias in the way we approach the creation of intelligent machines, but have also identified this bias at work in many aspects of our society. It is not every day that a technical book so clearly reveals something new about how we live our own lives and how we might enrich them. I cherish such a rarity, and I urge others to as well." ( Prof. Josh Bongard, University of Vermont)
"The ideas in this book have revolutionized the field of evolving artificial intelligence. They also help explain why biological evolution, science, and human culture are creative, endlessly innovative processes. Stanley and Lehman's theories are helpful for anyone who wants to foster a culture of innovation in their organization and within their own mind." (Prof. Jeff Clune, University of Wyoming)"Objectives in our lives and careers, and the endeavor to achieve them, can sometimes cause stress and feelings of underachievement. But do we always need objectives? This book challenges common beliefs in our culture and society, revealing indisputable evidence that the biggest discoveries in the arts and sciences are not driven by objectives. The reading provides an uplifting new perspective on creativity, innovation, and happiness." (Andrea Soltoggio, Lecturer in Computer Science, Loughborough University)
- ASIN : 3319155237
- Publisher : Springer; 2015th edition (18 May 2015)
- Language : English
- Paperback : 150 pages
- ISBN-10 : 9783319155234
- ISBN-13 : 978-3319155234
- Dimensions : 15.49 x 0.91 x 23.5 cm
- Best Sellers Rank: 304,641 in Books (See Top 100 in Books)
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They give the analogy of stepping stones across a lake shrouded in mist. Peering into the distance to identify a sequence of steps to a far-off goal is not only over-ambitious, but potentially harmful, they suggest.
For example, vacuum tubes were invented with no inkling of their potential use in computation, but proved crucial in creating the first computers. The computer became possible only because it had not been a goal — as no one would have anticipated vacuum tubes’ key role.
Technological discoveries generally build on elements that weren’t made with them in mind, they argue, since “the steps that lead to great invention aren’t likely to resemble great invention”. The means aren’t like the ends — the lake is foggy and the stepping stone paths are windy.
Much better to go one step at a time, discarding distant objectives for an alternative focus. But what can guide us if not goals? The authors are computer scientists, and develop their argument from their research into “non-objective” search algorithms.
An objective approach to search is goal-directed. Trying to reach the end of a maze, for example, such an algorithm will deem most successful those routes that end up closest to the finish. Mazes, though, are deceptively complex environments — an objective search will often get stuck down blind alleys that leads towards (but not all the way to) the finish.
An alternative is to seek novelty. This way, once an area has been explored (no matter how close it appears to be to the maze’s end), other routes will be sought. This ultimately leads to much more successful maze completion than objective-led searches.
Non-objective algorithms (such as novelty search) aren’t just for solving mazes, they argue. Any complex environment can be framed as a search — whether for scientific discoveries, technological innovation, or artistic creations. Even organisations and institutions, they suggest, are subject to the same dynamics of deception when pursuing far-off goals.
They are careful to acknowledge, though, that in many circumstances goal-directed behaviour is appropriate — as long as the objective is “one stepping-stone away”.
As they put it:
“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.”
This suggests the need for humility on our part (as Samuel Arbesman does in Overcomplicated: Technology at the Limits of Comprehension with respect to technology). Much of the world is simply beyond our full control, and we would do better to recognise this than use goals as a false compass. Rather than always seeking ways to get where we want to be (and rarely succeeding), perhaps we might simply explore the world from where we are.
To conduct some novelty search yourself, check out their website Picbreeder (http://picbreeder.org/), where users evolve images. Or you could seek novelty elsewhere in your life, whether a new activity, striking up a new conversation, or going somewhere you’ve never been. You never know where it might lead.
But a greedy algorithm fails for complicated problems: in your maze, you will initially get closer to your goal, but you will sooner or later get stuck in a dead end. To escape the maze, you will have to abandon your simplistic approach of heading directly towards the exit, and instead, you will need to move away from your goal in the short term. The path to success has many twists and turns.
More sophisticated search algorithms employ a combination of "exploration" (wandering around looking for a good approach and avoiding the dead ends) and greedy "exploitation" (finding something good and locally making it better). The skill is in balancing these two processes: too much exploration and you never achieve anything except by chance; too much exploitation and you get trapped in dead ends.
Stanley and Lehman are computer scientists who have taken this insight—that to achieve your goal, heading directly towards it is rarely the best approach, and in some cases may even be the worst approach—and applied it more widely. The real world is hugely more complicated than a puzzle maze, yet many management practices employ greedy algorithms: reach your (complicated, ill-defined, distant, changing) goal by moving directly towards it. Yet no matter how much you improve candlewax and wicks, you will never achieve electric lighting; no matter how many trees you climb, you will never reach the moon.
This slim book is one long discussion of why our current obsession with objective setting, with a pure greedy exploitation-only approach is not a good idea. We need more exploration in our management, research and education, if we are not to get stuck in dead ends, and the authors set out how this could be achieved.