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Brain, Mind and Cognition

Essay

Emergence

The Connected Lives of Ants, Brains, Cities and Software

by Steven Berlin Johnson

The book < Emergence: The Connected Lives of Ants, Brains, Cities and Software >, is

written by Steven Berlin Johnson and published in 2001.

In this book Johnson refers to the ability of low–level components of a system to self-

organize into higher-level systems. He says that this self–organizing is not controlled from

the outside, like a boss telling his employees what to do. No, it is more like something

stemming from the bottom up. It seems like it is already existing, like a natural law or

something intuitional.

The book is divided in three big parts. Debunking “The Myth of the Ant Queen”, Johnson

tells of the research done in urban studies, neuroscience, and computer games that shows

there is no need for a leader or pacemaker to get things going.

He begins with an amoebalike slime mold cell, which combines, under certain

circumstances, with other thousands of neighbors to become an even bigger / greater

complex creature with even intelligence.

So, Japanese scientists created circumstances in which a slime mold found the shortest

route through a maze.

I can’t mention one concept I liked the most out of this book, because there were no real

concepts, but also a lot of interesting views were given. Now I want to talk about a view.

Starting with the ant colonies, where every ant operates on its own by a set of low level

rules and feedback from its neighbors. Johnson presents five fundamental principles to

support his hypothesis:

More is different:

A critical mass of ants is necessary for useful statistical averages to emerge. You

need more than just a few ants to call it a colony.

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Ignorance is useful:

It's not necessary that each ant has a map of the colony's best interests. Such ideas

would have a negative outcome on the colony as a whole. Simplicity of individuals is

beneficial.

Encourage random encounters:

Ants use feedback from encountering the activities of other ants to usefully change

their behavior. The same goes for humans in urban areas have a positive effect

on the emergence of cities by their encounters in public areas.

Look for patterns:

Ants follow so called trails of pheromones left over by other ants of the colony. The

same goes for programmers, which have modeled this behavior when creating

computer software. That emerges from very simple programs that leave digital

pheromone trails of their own behind.

Pay attention to your neighbors:

For example: When an ant notices that his fellow ants are foraging, he will

change his activity.

From ant colonies, he comes to building cities and that this is also an example how humans

inherit this emergence behavior. It is pretty surprising how much in our daily life is intelligent

and self-organizing. Especially, Manchester is very fascinating for me, because it is not

easy to structure the life with so many people in a very small place. It is necessary to

ensure enough food and work, but also the enormous power consumption at certain times

of day and the removal of wastes require a high mass on structure and organization.

After that he comes to the world-wide-web, called global web, where he cites Slashdot.org,

a news aggregation website that directly engages its users to control the quality of its

content.

You can say the users are like the ants and so Slashdot has all the elements of an

emergent system, which contains positive and negative feedback, structured randomness,

neighbor interactions and decentralized control.

Another great part in the book is the influence of the media and the video games in our

society. A lot of people are more or less stuck in a not real world. For example Johnson was

mentioning SimCity and Sims. These are one of the first games, which children gave the

opportunity of building a city or becoming a person, which they want to be.

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Not only children are fascinated or influenced by those video games, also older people are

controlled by today’s media.

Before he gives a forecast, the author talks about the gestures, which is another kind of

communication. After that he talks about the mirror neurons and mind reading, which have

an immense amount to teach us about our talents and limitations as a species.

In the end I can say, this book doesn't stimulate me in a way that I would try to get more in

this material or to build intelligent systems. It takes me in the different direction, because it

showed me new points on how to look at the whole situation, that it is not always the best to

have so much technical equipment.

Now, I want to come back to the video game and media topic. Johnson talks about the

influence of media and the global web and how it changes our life. He, for example,

mentions video games and that already the young ones do have a lot of them and are more

or less stuck in a not real world. When I look at myself, and look at today's world, it's gotten

even worse than at the time Johnson was talking about. Especially, Johnson mentions the

game SimCity, which was very funny for me, because this was one of the first games I

played on the computer. So a lot of moments of my childhood came up, which I totally

forgot. So, nearly everybody has a smartphone or a tablet and is using it all the time. For

example, chatting in facebook or google+, or just getting help at daily life situations, like

navigation or to get reminded that you have an meeting and so on. The point what I try to

tell is that you don't have to think anymore, you're iPhone is doing that.

Finally I want to compare the three books, which we have read in the course Brain, Mind

and Cognition. In the first book < On Intelligence >, Hawkins tries to tell his understanding

of intelligence to the reader. He wants that the reader understand what he is talking about

and that in a way, which convince the reader. In the second book, < Embodied Cognition >,

Shapiro listed a lot of concepts to define embodied cognition, or in other words, to give an

introduction into embodied cognition.

In the current book, Johnson tries to deliver an historical and natural understanding of the

sort of the collective phenomenon that has exploded virally in our wired world today.

So this book is not like the other two, it is not a technical book, where you estimate some

complicated explanations about technical stuff. In contrast, this book is about a lot of things

you already know or have heard of.

Brain, Mind and Cognition

Essay

EMERGENCE

THE CONNECTED LIVES OF ANTS, BRAINS, CITIES, AND

SOFTWARE

by Steven Johnson

The book "emergence" has a completely different approach to explain the issues of

"intelligence" and "brain", as the books "On Intelligence" and "Embodied Cognition"

before. The book "Emergence" is primarily concerned with the theme of "self-

organization". Johnson not only dealt with the self-organization in ants, but also with

how brains, cities, and software structure itself.

In the beginning Steven Johnson introduces one of the emergent world’s crowning

achievements: the colony behavior of social insects such as ants and termites. After

that he gives an overview of emergence as we currently understand it. Hence, his

focus is on the following topics: neighbor interaction, pattern recognition, feedback,

and indirect control. In the last section Johnson looks to the future of artificial

emergences and speculates on what will happen when our media experiences and

political movements are largely shaped by bottom-up forces, and not top down ones.

In the introduction, Johnson talks about Toshiyuki Nakagoki. Nakagoki announced

that he had trained an amoebalike organism called slime mold to find the shortest

route through a maze. After that I was not sure what this topic has to do with

intelligence. So, after I had read the book completely, I know what the author wants

to say with the example of the slime mold cells. Today’s technical science tries to

replicate the natural behavior. Not only our body builds new things, like cells, but also

ant colonies, cities and software developed itself…

This book shows me a very interesting kind of thinking about intelligence. It is very

surprising how much in our daily life is intelligent and self-organized. The “building” of

cities, for example Manchester is very fascinating for me, because it is not easy to

structure the life with so many people in a very small place. It is necessary to ensure

enough food and work, but also the enormous power consumption at certain times of

day and the removal of wastes require a high mass on structure and organization.

However, the bad side of the development of self-organized-systems, like a city as

Manchester may not be forgotten.

Major General Charles James Napier wrote: “Manchester is the chimney of the world.

Rich rascals, poor rogues, drunken ragamuffins and prostitutes from moral. … What

a place! The entrance to hell, realized.”

Now I want to talk about these parts of the books, which impressed me, the most.

It is very difficult to mention one part, because I think in the book exists no concept,

which I can mention yet. Only the combination of the different examples of ants, cities

and software inspire me.

Another part of the book, which animates me to think more about the human

behavior, are the five fundamental principles, which are important for an ant colony:

- More is different.

- Ignorance is useful.

- Encourage random encounters.

- Look for patterns in the sign.

- Pay attention to your neighbors

It’s fascinating how ant colonies work together. But we don’t forget, that without this

rules an ant colony do not exist. This also shows us how different people are in

relation to ants. In my opinion it would be not false to use one or other of this

principles.

In addition to the behavior of ant colonies, I was interested in the part in the book that

was written about software. Especially, video games have a great influence in our

daily life. While it is known to everyone, that this kind of entertainment is used by

many people. However, the fewest are aware of what the consequences are for each

individual. Even children at a young age have a Nintendo and later they spend most

of their time on video games like Sims or SimCity. This people live in their own world,

but this world is not real. I think this is one of the bad sites of intelligence.

It is frustrating to see how the media of today and the global web influence us and we

don’t do anything against it. Johnson mentioned in his book, that the people are

controlled by the media in which they are interested and in which not. But the theme

of the gestures and the specific neurons, mirror neurons, which give statements

about the talent or the limits of talent to make each, are very spellbinding too.

After I referred which one is the most appealing or interesting idea to me, I come to

one of the most self appearing questions you ask yourself after reading this book. If

Johnson´ book stimulate thoughts inside of me about what it takes to build intelligent

technical systems? To ask in accurate words, do I feel like I can build intelligent

technical systems respectively do I want spend more time in this issue in my future?

No, I feel about this book unconvinced to get further into the topic. On the one hand it

makes fun to read Johnson’s book and this book gives me some new points, about

which I don’t think before. The behavior of ant colonies is one, which show me some

opportunities, which we people can learn.

On the other hand I know a lot about what he wrote. The video games and the media

today is a part, better to say a problem, which the most people know. Exactly,

because so many people know the bad site of this kind of entertainment and media, it

would be so inapprehensible for me, why nobody does something against. Of course

it is awesome, that software are so self-organized and so powerful, but this concept

could be danger someday.

In conclusion it can be said that this is a very attractive research field, which needs

more time to be fully understood. However, it should be ensured that the power of

self-organization is not out of hand and is dangerous. I think one reason for the

enthusiasm in videogames and big cities is the film industry, which shows us, what

the people wish in relation to intelligent machines.

In the book “Emergence” you get a good overview of self-organization-systems and

about the application in fields like ant colonies, cities and software.

In comprehension to the Hawkins book, Johnson only talks about things, which

everybody knows, because he wrote about the daily life. He doesn’t speak about

technical things. On the contrary Hawkins talks about a lot of difficult ideas in

reference to artificial intelligence. In contrary to these two books, in the book

“Embodied Cognition” the author tries to give an introduction into embodied cognition

by mentioning a lot of different concepts from many people. Shapiro wasn’t interested

in convincing the reader about a certain topic.

In the end I want to say, I liked that book to read. I have not yet addressed this issue

and I will probably not, but I still get another view. Specifically, I was pretty happy

about Johnson not writing that much technical stuff.

The book has shown that the most “systems” don’t need a leader. Indeed, in case of

the ant colonies exist an ant queen, but this queen don’t leads or structures the ant

colony. The ant queen is only a hatchery. Johnson explained this well in chapter “The

Myth of the Ant Queen”.

I am most surprised about how much actually lies behind the concept of intelligence

and how much different it is depending on which species you are looking at. Every

book, which I had read in the seminar “Brain, Mind, and Cognition”, shows me a new

way of thinking about intelligent systems. It is very fascinating, that intelligence is

everywhere in our world.

So, I learned not only technical systems could be intelligent. Every species and every

system has their own way to be intelligent.

But now, what is intelligence exactly? And what more could be intelligent?

Emergence - Steven Johnson Book Report

This book was a very pleasant read mostly due to the way the author arranged the chapters, the ideas and the examples.

I liked how the book started presenting the idea on emergence from a very simple perspective: “The movement from low-level rules to higher level sophistication is what we call emergence.”. To be honest I wasn’t able to quite grasp the true meaning of emergence until reading the book; nor did any dictionary give any definition in this manner. The other “thing” which made the book more appealing were the examples like the foraging ants, the software examples (the web or the software which creates optimal sorting algorithms) or the commercials (at the end of the book).

Coming back to the idea of emergence. This I consider to be the main idea presented in the book and what makes it really interesting is how it is displayed from more than one angle.

The way how settlements were formed, how small villages become cities by “solving the local problems”, how “these local decisions combine to form the macro-behavior of the urban explosion” is a thorough example of emergence. I was impressed to see the first example of the city of Manchester, how the people there organized themselves, and I think, that this way of doing it, combined with some sort of reviewing each other’s work (a system which could borrow the ideas from slashdot creator) could really change (here change could translate in drastically improve) the way we live. Although I think this would never, not in a million years, happen due to the power some high-ranked people would loose, but I guess this is a topic for another discussion and a bit off topic to our goal of creating intelligent systems. Although this might be a thing to keep in mind as we, in the following years would develop such systems, there are people in general afraid of “gadgets” which could steal their work place.

When the author first started to talk about emergence in the WEB I was really interested to see how he perceives this. I agree one hundred percent with him about the fact that the world wide web is not an emergent system, as it is mentioned in the book “Emergence isn’t some mystical force that comes into being when agents collaborate.”. The main issue here is the lack of organization. I reckon we can go around this total chaos which is in the web today; guys at Google or Yahoo or others have been doing this for more than

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a decade, but it would still not be able to form an intelligent system/network able to aid us. As it is written in the book, it is precisely the feedback which the WEB lacks, because services like HTML are one-way.

As I was reading thorough the chapter talking about the web, the solution found by the slashdot founder I could not start to think what about we start developing some sort of emergent big network which will later on replace the heap of protocols and all the hardware we have today to keep our internet working. This is just one of many narrow minded applications of intelligent systems, but it would make them scale so nice and adapt in close to real time (this is due to the fact that the processing power would not be an issue). After taking care of the traffic and using this time, spent developing the protocols, as practice we can move on to building a smart network, as it is written in the book: “an adaptive information network capable of complex pattern recognition”. Also I really liked the idea of considering the world wide web as more like a tool to create the metadata which would enable a self-organization of all the present media. The ideas presented about the TVs and how easy it will be to log into some service you are currently using and stumble upon the series Sopranos, for example, just because you are a member of a certain fan group could turn out to be quite a game changer in the entertainment business.

From here we can only start asking questions as how far can we go, are we able to build a system which “is able to actually appreciate the patterns” they find in music, or other forms of art.

I liked how the author described feedback, either positive or negative, as being one of the key parts of an emergent system. Having read the previous two books, it was clear to me that feedback is important and it should be part of the process, but in this book I reckon its purposes are better presented.

Now the question arises in my head: if an emergent system is also intelligent. I believe that the condition which is put in the feedback loop will define it’s usefulness, thus making it intelligent. I have used here the term intelligent in the manner that not only it is able to detect and learn new patterns in an adaptive way, but it is able to actually use the intelligence to some extent. Reading the book, going through the examples given, I came to understand that the condition put there can make a huge difference. And what would be a fun way to do is to modify it to our needs by making many tryouts and experimenting, thus creating an emergent system around this problem. This can certainly be done since nowadays the problem of lack of computing power is fading away.

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Another interesting question would be how to define such “working ants” in a system which we want to become intelligent. Also it is important to define the very basic set of rules the individuals which will define the way they interact. As we see in the example with the ants, one key factor is the ability of ants to count the ants it encounters as it searches for food.

Reading this book I feel that there are a lot of steps made in the right direction of a truly intelligent system. Traces are seen throughout the small things like slashdot or the software which created fast sorting algorithms. But there is another point which can be helpful: self-awareness.

The idea of self-awareness as a byproduct of the mind-reading skills of humans seems to be logic, but of course I think this area needs more research. Although scientists have discovered the “mirror neurons” and found an explanation to how they work, the step from here to self-awareness is a big one. It needs to be broken in more steps and properly explained. We maybe miss some points which can help us better understand and may even unravel other questions on how to implement such a feature.

To sum up the things I consider to be the most important are: the bottoms-up way of organization, the feedback loop and the filters/algorithms which promote or demote …. as I understand, this is called emergence. All these three ingredients are presented in the book, especially in the last chapter with all the examples given. What made the ending even better to me is the fact that it presented ideas which are already kind of under development/in testing.

Out of the whole examples presented in the last part, I mostly enjoyed the one with companies using a model other than the traditional top-down, where a CEO, directors and local managers make the decisions. The corporate should have a structure like the Slashdot quality filters, where the CEO would merely be tweaking the algorithm that promotes or demotes based on quality of work. Most important, the vision of the company would come from below, “out of the ever-shifting alliances of smaller groups”. The management would simply provide the feedback mechanism. To put it in a more fun way to say, this idea is crazy enough that it might work …. creating an intelligent and self-aware company.

Also I would like to say that I am keen on reading some of the books which were mentioned, at least chapters if not the whole books.

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„Emergence: The Connected Lives of Ants, Brains, Cities, and Software“, Steven Johnson's book on systems deriving their intelligence from the interaction of their „dumber“ parts, generally was a very good read, making it difficult to nail down a single most interesting thought or concept.Generally, the first third of the book with it's look on city neighborhoods, ants and mold held a lot of fascinating ideas – only to be followed by an amusing, yet not really helpful year 2001 look on the internet.Having followed discussions on the “swarm stupidity” of sites like Wikipedia, and having basically grown up with search engines like Google, as well as the day to day use of portals using user rating, made the second third of the book appear a bit ridiculous to me. This greatly improved in the last third of the book though, with it's still state of the art look on video games and the future of the net.But which of these concepts did strike me as the most promising? I guess it is the concept of emergence itself, and the realization on how many levels it comes to bear, that struck me.As an engineer, my fascination with humans only grew the more I learned about man-made systems. Even applications and machines sophisticated for their time always were predictable as soon as one understood them well enough – computer games like “Creatures” with their self-learning abilities, robots imitating humans, virtual agents. All of them ceased to surprise me at some point, once I got behind the algorithms guiding them. Not so for humans – or even “simple” lifeforms as ants, which never stopped to amaze me in their unpredictable, yet very structured way. Nature's power to adapt, and to produce unimaginable numbers of beings with so very different opinions, approaches to problems and abilities, still is a fact I cherish like a child.And Johnson's work managed to shed some light for me into why these biological systems sponsor the abilities they have, why manmade solutions dont. No matter how many role-playing games or world simulations I played, they never fully gave me the feeling of really mirroring a world as we know it – emergence, in my opinion, is why.What modern computer games are missing – even more so than the year 2001 computer games, I'm afraid, is the interaction of single parts of a system through rules which one becomes a seamless part of. Instead, most games are structured like a calculating algorithm: Once you reach point x, reaction y happens. No simulation can ever mimic the fun of watching a group of people discuss current politics, with their group dynamics and underlying rules of conversation, or even the fascination of watching an anthill for a few minutes.And even though he was missing 10 years of internet culture that have passed since the writing of the book, Johnson efficiently predicted the results emergence might bring to spaces like the YouTube comment-function. Being a nuisance and a daily source of amusement to me at the same time, I never quite

thought about why people behaved the way they did on the internet – or was at least content with the answer that anonymity brought out the worst in some people. Seeing a face-to-face conversation as a series of feedback loops – loops that are missing in online discussions – is a masterpiece of observation in my opinion. And gives a lot of answers on how the web should maybe develop in the future, which websites might see a rise in popularity and what functions might be needed – even though Johnson blatantly leaves out the discussion about privacy. The question is only scratched in some short paragraphs, and mostly seen as unimportant and backwards in it's way, though some ideas how the boring conformity, for example of news sites using feedback loops, can be prevented.The explanation of emergence did not fascinate me in the same way as the previous books did – be it Hawking's profound knowledge of the topics and his way of winning readers for them, or Shapiro's broad spectrum of topics scratched. It was that feeling of having to nod one's head while reading, with the explanations perfectly fitting everyday life. Living in a big city, I always pondered why some suburbs tended to attract a certain kind of people, and how the dense sidewalk-environment changed the way people interacted with each other – just to have the ideas served on a silver plate by Johnson. Even though ne book never quite had me in it's grip as much as “On Intelligence” had, it still left me with a content feeling of understanding, and a different view on everyday “systems”. And a healthy doubt about whether these systems really benefit from a hierarchical order and a 'leader' – much like the famous example of bird flocks, for which complex top-down control engineering theories exist – and every single one of them seems to be great, but not the same thing nature accomplished with a bunch of brains the size of a walnut.

When it comes to conveying these ideas to the building of intelligent machines, the first thing that comes to my mind is playfulness. What “Emergence” (together with Hawkings book) tought me is to sometimes forget the rigid structure of programming, and try out possible solutions. Or, to put it this way: Sometimes complex matters require a solution too sophisticated for a single programmer, or even a team of programmers to understand. Current Android phones, according to the media, feature enough code to keep a single programmer analyzing for 40 years. Why not find solutions on this scale through emergence, by trying out the single parts and their underlying rules and tweaking small factors to reach a desired goal? This even perfectly blends in with “model pupil” modern strategies like neuronal network or Darwinian “survival of the fittest” algorithms, as Johnson correctly pointed out.Some systems, of course, will not or only marginally benefit from such an approach, in the same way that too much unchecked emergent behavior leaves users in computer games with a feeling of just watching, but not being part of

the game anymore. Careful choice of the right places to implement the ideas won might be a crucial topic here.On the other hand, special care has to be taken to understand emergent behavior when altering systems. Even with people like Johnson understanding the principle of internet 'trolls' a decade ago, modern day web-conversations suffer from the same problems he outlined in the book till today. Time is wasted and bad blood created through lack of understanding of emergent systems and feedback loops in this case – in the same way beneficial emergent behavior might be squashed by alterations to an intelligent system. Or, when designing an intelligent system, emergence might be the missing component to create intelligent behavior closer to human or animal behavior – which robot would not want to have the mind-reading powers explained in the book when conversing with a stranger?This advantage might come at a price though: Understanding.Even though one might understand the underlying principles of an emergent system and find solutions through this, as said above, the final result of such a project might be totally gibberish even to experienced programmers in spite of it's undoubtable efficiency. Whether this problem will be solved in the near future, I do not dare to guess.But just because bottom-up emergent systems are sometimes counter-intuitive to humans, and therefore more complex to understand, does no mean they should be avoided if possible. Our denial of such approaches might very well be a reason for the lack of the I-robot like entities and super smart computers predicted 40 years ago – though it might also be the reason for the non-existence of unpredictable, nearly “evil” computer-beings like HAL-9000 in “2001: A space odyssey”. Though such “wizards apprentice” scenarios are far from happening right now, some measures have to be taken to ensure controllability.In any case, emergent principles will have a growing influence over the next years – many of the developments Johnson predicted are already altering the world around us. Mega-cities with all their advantages and drawbacks host most of todays population, making correct assumptions about city building invaluable. The mass media is even more fractured and decentralized than in 2001, with the exception of great news-factories like DPA supplying big newspapers with the ever same news every day. And the music- and video industry suffers as much from the heirs of Napster as it benefits from them, complaining about loss in album sales as well as profiting from viral marketing and videos. Anyone up to designing an intelligent technical system will have to cope with these principles – whether he wants it or not.

Essay No. 3

Rui Ding

Martrikel-Nr. : 03644142

Ants — and slime mold — are more interesting, and more intelligent, than I ever would have guessed. Their intelligence isn’t the same as human intelligence, as I wouldn’t exactly say slime mold or ants are sentient. What they do possess is a kind of “swarm intelligence” or emergence.

Emergence is a term for describing a self-organized, ‘whole is greater than the sum of the parts’ type situation. That is the case with slime mold, which functions both as tiny individual specks and a coagulated mess of well, slime. The individual bits, without a leader or any recognizable capacity for intelligence, nevertheless communicate with each other, and coalescing and breaking apart again as environmental conditions warrant.

Johnson spends a lot of time disabusing readers of the notion of the necessity for individually-intelligent components. There doesn’t need to be a slime leader telling all the other tiny bits of slime what to do. Here I will quote the example in the book. The queen ant doesn’t actually order the other ants around; they follow pheromone trails and act in the colonies’ best interest. Ants can follow these pheromone trails to food sources, but they are also used by individual ants to figure out if it is a good idea to switch from foraging duty to garbage disposal. Ant colonies can be a dozen years old, and

older ant colonies are “smarter” than younger colonies — even though the only ant who lives longer than a year is the queen. (In some species, the males live for so short a time, they are born without jaws to chew food with.) Humans have a hard time seeing this kind of intelligence, and of embracing emergence, because emergence is about lack of control, of letting systems regulate themselves, and evolving from the consequences — not how people in groups usually approach problem-solving.

Cities exhibit the same kind of group intelligence. For evidence, talks about how neighborhoods work — the silk district of Florence being in the same location for hundreds of years for instance, or the importance of the sidewalk as communications routes. Businesses clustering together benefit from the economics of agglomeration, yet they tend to evolve naturally, and not by urban planning from on high. Johnson relies on Jane Jacobs’s The Death and Life of Great American Cities for much of his argument here. Human beings can easily miss the emergent intelligence of cities, because we think on too-small a scale. Decades may not reveal the patterns in the chaos, but a hundred years or 500 years will.

Software that has been produced by generations of evolution instead of hours of caffeine-induced coding is an interesting idea. It has been done, though it remains to be seen if growing “code gardens” will catch on. Some software seeks to model the real-world behavior of slime mold — and then there are the Sims. The Sims is based on emergent principles though emergence needs to be hobbled for a good game, as otherwise the player

wouldn’t have much to do.

Johnson raises some great questions, and his willingness to write about the web — which mutates much faster than a book can go from green light to paperback — is important, yet is it also where the ground is less firm. He refers to the web as “feedback-intolerant” and links working as one-way pointers. While this is true for much of the web, it isn’t true for the whole web. While I am loathe to appear in the “blogs will change world” camp, I do think they have potential for changing the web. I would not describe successful blogs as feedback-intolerant, or blind to incoming links: successful blogs can generate communication. It would be interesting to see what Johnson would say about blogs, and what questions he would think to ask about, and of them.

He ends his book with an acknowledgement of the best questions are nowhere near being answered:

Are there new scales to conquer, new revolutions that will make the top-down revolutions of the industrial age look minor by comparison? On the hundred-year scale, or the scale of millennia, there may be no question more interesting, and no question harder to answer.

Emergence is a good book that generates questions, opens a new perspective on intelligence. I like it very much. And this book is easier than the last one. The examples in this book is easy to understand, like the game The Sims. When I was young, it was my favourite game.

EMERGENCE by Steven Johnson

“Local information can lead to global wisdom” (p.79)

It has been a long time since my father introduced me to the game of Chess, but the

memory of the same still remains perfectly intact within me. The checked board with the

uniquely shaped 32 black and white pieces looked more or less like an army, and so it

was when my father explained me the various rules of the same, how the pawns, the

knights, the rooks, and the bishops move and then told me “Trap the King and you win”.

The game unfolds, the pawns move, the bishops move, the player waits for another’s

turn, and the game goes on. A story emerges, and one of the kings is trapped, and the

game ends. The same happened with Monopoly and Checkers.

Not even once did it cross my mind that how could such small wooden pieces, following

simple rules come up with a meaningful story, until I read this book. Turning through

the pages made me realize how ignorant I was to this wonderful phenomenon of

emergence. Emergence was all around me but owing to the basic human nature to

constantly look for hierarchical structure in any system disabled me to observe it. I

sincerely thank Mr. Steven Johnson for introducing this beautiful bottom-up approach,

which glued me to this book and was the idea I liked the most in this book.

Human intelligence is just a measure of our evolutionary success. A peek into the insect

world, and we realize there are small beings on this planet which exhibit such a

capability which is far beyond their capabilities. The piece of information which

completely broke the stereotype myth of the Queen Ant amazed me. With no frontal lobe

or any cortex, the ants with the support of only chemical substances like pheromones

and constant feedback from their neighbors carry out the activities of foraging, dumping,

and guarding excellently. With only the local information and some rules at their

disposal, such creatures, which in no way can perceive the global picture, bring about a

global change which is reflected in their colonies. There is no leader, no central force

driving such colonies, yet, the ants work with a collective intelligence trying to perceive

the global picture and emerge as a colony.

Some days back I was watching a video on human cloning, wherein I saw how an

embryo emerges from a cell. Such an admirable process happens within us every single

day. The cells in our body are continuously cooperating in order to make us ‘us’. We are

nothing without them. Even though the cells in our body lack the bird’s eye view of the

whole organism which houses them, yet these cells find out their place in the organism,

it learns from its neighbors and together the cells come together to bring about different

variations. A cell looks around to what its neighbors are doing and starts doing the same

thing. However, at the same time, many cells are also dying and new cells are taking

their place, and yet even after many years we are still we. Nothing makes us feel within

us that we have changed! How does this happen! Every cell in the body carries a

complete copy of the genome so no cell has to wait for instructions. It has to figure out

on its own by interacting with its neighbors, looking for feedback. We are yet another

example of how emergence plays its role in nature.

As we all know that the brain is a decentralized entity. Neurons, like any other cell in our

body, work on the same principle of listening to feedback. There is no central entity in

the brain telling the neurons when to fire and when to remain silent. Neurons, with only

their dendrites, axons, the nuclei and various neurotransmitters come together to

preserve our personality.

Three years back, my family shifted to a new place. When we used to visit the place

around six years back, there was nothing except for barren land. As people started to

build houses, the barren land turned into a small road. Soon, the small roads started to

come together to form big streets. With big streets and more connectivity, many more

people started to come in. Small markets emerged into bigger supermarkets. Now, when

I visit my parents, we often talk about the time, when only our house could be seen on

the once barren land. Houses lead to neighborhoods, society follows and soon from a

small village a city emerges. It all goes back to the old saying “From little things big

things grow”.

Building Intelligent Systems

The phenomenon of emergence has given birth to many wonderful things. Ants in our

gardens, flock of birds flying over us and we ourselves are exceptional examples of the

same. Some cities evolve as one of the best in the world and still there are some which

fail to even qualify as cities.

The importance of connectionism and feedback is what I found the most important

message of this book. We have come a long way since the book was written. Emergence

has crept into software designing and gaming. We witness emergence in solutions of

problems like the “travelling salesman problem”. Immense research is put into neural

networks, trying to simulate them with high deep connectivity and feedback

mechanisms. There are certainly some systems capable of recognizing patterns and

sounds. Take for example YouTube, we hear some songs and the next time we login we

get recommendations. We log into facebook, and with one look on the chat window, we

know if the people we want to talk to are online or not. The system tries to learn from

the feedback the user provides. All what the servers are doing are trying to learn from

the user requested earlier. It all comes down to the fact as stated by Jeff Hawkins in “On

Intelligence” that intelligence is nothing but a prediction of future events based on past

experiences and present input.

It was reported that software mimicking the emergence behavior of slime mold was

successful in designing the train networks of Tokyo and also in highway construction in

Canada. There are numerous sensors capable of inertial measurements and satellite

navigation working on dense data and feedback. People have come up with softwares

and games capable of emulating the emergent behavior

If such a small emergent behavior found in nature could be put to such an efficient use,

just imagine the possibility of simulating such a structure on machines, machines which

are trying to adapt themselves to changing environment, communicating with

neighbors, learning from feedback but of course following some set of rules. All it takes

is a little interface of nature with technology.

We should not forget that the immense growth in technology is not the work of a single

brain. It is the work of more than a million brains working out there, presenting ideas,

waiting for response, correcting them and again presenting, which has enabled this

immense growth of technology.

But what I fail to understand that is though emergence leads to global wisdom, does not

it undermines one’s conscience? How would a world where many sentient and not

ignorant individuals following a set of rules come together randomly, searching for

neighbors and looking for feedback look like? We can just play and watch.

Emergence – Collective intelligence by simple local actions

“The connected lives of ants, brains, cities and software” – the tagline of the book Emergence by

Steven Johnson looks like a collection of words making no immediate meaning. What a way to

commence an incredible journey into the world of emergence? It is really amazing how the

author recognizes the similarity in working of a number completely uncorrelated entities like ant

colonies, cities, the world wide web and of course the human brain. This for me justifies the fact

that human brain is very good at recognizing patterns. The author’s ability to correlate the

behaviors of these disparate entities and bring them under a single umbrella of emergence is

commendable.

I feel that this book has introduced us to a new way of looking at things. Whether this is the way

ahead is another issue which I would like to discuss further in this essay. The single most

appealing idea for me is the only idea that the author focuses in the entire book, the idea of

“Emergence of a macrobehavior from interaction among the entities of a system each having a

distinct microbehavior”. It is a kind of synergic effect caused under certain conditions. The

author underlines following important factors for observing such an effect, namely

Scale – There should be sufficiently large number of interacting entities.

Simplicity – Each of the interacting entities should follow simple rules. They have only

local knowledge and no idea of the emerging global behavior.

Randomness – It is important that each of these interacting entities go about doing their

jobs without any central control. This allows for random interactions in the system.

Patterns – Recognizing pattern and learning from it is essential for emergence.

Feedback – There should be a feedback mechanism among the interacting entities.

Author takes an approach of explaining the above concepts with the help of various examples

scaling from ants to the World Wide Web. Consider the case of ant colonies where they go about

performing their duties (foraging, waste disposal etc) without a commander instructing them

what to do. It is fascinating to know that each ant decides what it has to do on the basis of

frequency of semiochemical substance it senses. Here, each ant by itself does not have the global

knowledge of the state of the colony. But, a global behavior emerges from the microbehavior of

each member of the colony.

Similar behavior could be observed in many other contexts. A slime mould integrates into a

cluster under favorable conditions but remains as single cell organism when the environment is

hostile. The cities we live in show emergent behavior by forming neighborhoods. Yet another

interesting thing is that the emergent behavior is passed on from one generation to the next.

Though the idea of emergence is intriguing, we have to take a cautious approach when the author

tries to explain that the working of human brain based on this theory. We have a large number of

neurons which are interacting with each other in the human brain and each neuron itself does not

have a complete global knowledge or self awareness. There is an electrochemical feedback

mechanism among the interacting neurons just as in case of ants. These points contribute to the

fact that our intelligence is indeed the macrobehavior that emerges from the microbehavior of

individual neurons. The behavior of mirror neurons and human’s ability to recognize patterns

adds up to the cause. But, as the author himself admits, it is not possible to predict the

macrobehavior before it actually emerges. I feel that this unpredictability leaves some doubts

about the fact that our intelligence is a result of emergence. Emergence theory gives a new

perspective of looking into functioning of the human brain. But, it cannot yet be conclusively

proved that the brain works this way.

Yet another application of emergence theory that impressed me is software development. The

idea of software development using genetic algorithm is very interesting. Instead of giving line

to line instruction of how to accomplish a task, the programmer just gives a master code (or

genome) and set the parameters for genetic fitness of the code. Different algorithms evolve over

time and according to Darwin’s theory, the fittest survive over the weak ones. Danny Hill’s

number sorting experiments prove that this way of programming results in the emergence of the

best algorithm.

Other applications of emergence include game development and pattern recognition in the

WWW. I feel that the use of emergence theory had generated a revolution in the gaming

industry. The sheer unpredictability of behavior of entities has allowed game developers to

embrace this approach in order to develop games which proceed based on the skills of the gamer.

This effect of personalization is also used by a number of websites in order to provide targeted

advertisements, relevant search results and personalized news content. The personalization of

web has its own pros and cons. Nevertheless, it serves to bring a little order into the chaotic

world of the WWW.

Now coming to the question of design of intelligent machines using the concept of emergence,

the author himself has given some heads up into this. Whether it is the development of better

software or making the web a bit more organized, use of emergence has already proved to be

very useful. But the question still remains whether the systems have become more “Intelligent”

by the use of emergence theory. It again boils down to the question what intelligence actually

means.

I feel that use of emergence theory must be the way ahead for designing intelligent machines.

There are a number of reasons to support this argument. Firstly, this approach is not algorithm

based which should be the case if you are trying to design any system which should react as a

human would. The design of such systems would involve setting up of initial parameters, the

master code instead of designing each and every action. Another reason is that by designing a

system using this approach we will allow the behavior to evolve following the principles of

Darwin’s theory as our own brains have over the years. I feel that this is the best way we could

simulate the invariance behavior of our brains. This is a distributed approach without any central

command. The programmer himself will not command the machine but allow it to decide its

behavior based on the current situation.

But there are some drawbacks following this approach. First of all is the unpredictability of the

emergent behavior. It is difficult to control such a system once we start it with a certain set of

initial conditions. As the author himself explains, a positive feedback could blow the system out

of its limits. One might argue that the availability of a number of simulation tools could make it

possible for us to track and control behavior of the system. But as in case of a video game, each

iteration leads to a different result which makes the system susceptible to malfunction. I feel that

there is a lot to be done in this field before we could apply it to safely critical applications.

In conclusion, I feel that Emergence is definitely a good way of approaching the problem of

designing intelligent machines. But more has to be done in this field to make this approach fool

proof and secure.

Essay

In this essay I am going to express my thoughts about the 3rd

book of t course, namely

the “Emergence”, written by Steven Johnson. It is certainly impossible to avoid comparison

and drawing parallels between this one and the previously discussed books. The very first

thing about it is the fact that “Emergence”, unlike “Embodied Cognition”, but similar to “On

Intelligence”, was written by the person, who is exited with his research area and his major

purpose seems to be to inspire the reader, not to teach him. Since the course is aimed to be

thought-provoking, such a format is very suitable, I think. But there is a bad moment about

this style: being targeted to an average reader, it omits the deep explanations of the concept of

Emergence, remaining only on the surface layer throughout the book. That is, the author’s

explanations are not exhaustive, and the book left a lot of questions unanswered.

The most interesting idea for me was the main subject of the book, namely the self-

organization. It has been a hot topic in many research areas during the last decades, not only

in the biology where the author’s thread of narration has started, but also in some

technological areas, e.g. wireless networking. The key challenge, related to emergence, is not

even the fact it is difficult to understand. On the first place, it is difficult to admit its existence,

and the author exemplifies it very well throughout the book. The trap of conventional top-

down approach prevents us from looking on a system as on the self-organizing one. To my

mind, this trap has been following us during the whole human history: even the ancient people

tried to explain the natural conditions or elements by inventing the gods and mythology.

Similar things happened through the science history. I would say, it is besause top-down

approach is easier and, therefore, very tempting. Exactly the same happened during the first

attempts to explore the human mind and cognition: the introduction of spirit or soul could be,

in general, another exposure of the same top-down approach. People tried to find an instance,

which is controlling all our thoughts and responsible for all our deeds.

One can even go further, in the topic of designing artificial intelligence. How did the

first attempts to build an intelligent machine look like? In the beginning people tried to model

the systems based on the predefined rules of programming languages, mathematic and

computational logic. This is what was called “standard cognitive science” in the Shapiro’s

“Embodied Cognition”. The straightforward approach was dominating in system design. In

order to create a system capable of handling a particular task, e.g. image recognition or data

processing, the whole system logic had to be defined in advance, including all possible states.

That is, the program just followed the logic of the creator, and if there appeared a case, which

had not been foreseen, the program would commit an error.

I think, if we abstract away, this conventional approach to system design could be also

an example of a top-down trap. The programmer is exactly this “top” force, which is

controlling the whole process and organizing everything. It seems obvious to me that this

approach failed: even if successful in some cases, it wasn’t efficient and smart at all.

In this respect, the shift to self-learning systems and neural networks, as a tool for

system design, appears to be very progressive to me; it is a great step in the right direction. At

the end of the book, the author gives a very good hint, “we should to give up control”, and let

the system do and create something by itself.

Another topic, I intensively thought of after reading the book, was the self-

consciousness. Since there is no clear definition of this term, the ways to understand it differs

a lot. The biologist, psychologist and the IT specialist may have a very different view of the

topic. In this respect, the idea introduced by the author (maybe it wasn’t his original idea, but

I firstly read it in this book), was very interesting to me. The point is, if I got it right, that

understanding the existence of yourself is nothing else than understanding the existence of the

others. Now, when I think about it, it seems to be obvious – knowing your mind means being

able to separate it from the other minds, to find the limits – but it was not that trivial for me to

accept this idea.

The terms consciousness and intelligence are closely related to each other. We cannot

reason about or discuss our mind without being beforehand aware of our existence. Therefore,

if we interpolate the human intelligence on the artificial intelligence, the question how to

build an intelligent technical system is also a question how to build a self-aware system. Of

course, it is a controversial statement, especially in the light of the absence of widely accepted

definition of intelligence; some people may argue that being intelligent has nothing to do with

the self-awareness. But, to my mind, consciousness, if not an intelligence itself, is at least an

essential part of it. And in that respect, we should think of a system, which would be capable

of recognizing the limits of itself, and, if thinking in terms of the author’s theory, it

immediately follows that such a system must be able to recognize and understand the other

similar, or even different, systems.

Summarizing, I can say that the book was surely worth reading. I carried out several

lessons from it, which can be applied in the field of building an intelligent machines. First, we

should be aware of the trap of the top-down paradigm. I do not want to state with it that the

top-down approach is always wrong: while being inappropriate explanation for some

concepts, it shown a very good performance in other cases. The point here is not to restrict

yourself to one approach, not to limit the imagination. The only way to discover the truth

(which is not necessary one-sided) is the trial-error way: try, fail and try again.

The next important thing I have learned from the “Emergence” is that the human

intelligence is not the only kind of intelligence. That is, the self-organizing systems, describe

in the book, starting from ant colonies and up to our media environment, are also intelligent in

a particular sense, and maybe this could be the right way to approach the understanding of

cognitive process in our minds, by considering it as being a self-organizing system.