Garden Park, Evanston, Illinois

(Note–this was originally written in February, 2000–but has been updated and reworked for this post.. )

The climbing tree is gone.

One of my most cherished places is simply gone.  I cannot believe it.

There are pictures of me as a small child on that climbing tree.  It was a giant willow that jutted out from the ground at such a slight angle, that even I, as a four-year old, could clamber up on it alone and without help.  The attachment I have for that tree has never left me.  Through my adolescence and even into adulthood, whenever I needed to ponder something, I would make my way to Garden Park and visit the climbing tree.

And now, it is gone.

The climbing tree was located in a relatively small park in extreme southeastern Evanston.  Only a quarter of a mile from the Chicago border, it is one of the many lakefront parks stretching along Lake Michigan, but unlike many of them, it is rather secluded and off the beaten path.  On many maps, it isn’t marked and many of my friends didn’t even know it existed.  For me, however, it was always something important, something sacred.

Perhaps because of this deeply personal connection, I had never thought about the park in any objective sense.  By that, I mean that I had never tried to put the park in any kind of larger context, to understand the park as the construct of both civilization and nature, which is what it is.  When I last visited the park, I tried to move beyond my subjective attachments and to view it with different eyes.  This park has its own history, its own story.

Perhaps that would console me.

I doubted it.

The History of Garden Park

The plot of lakefront property that is now Garden Park was not always a park.  In fact, it was not even always on the lakefront.  Fifteen thousand years ago, this part of the upper Midwest was covered with ice that was hundreds if not thousands of feet thick.  This had been the state of affairs for tens of thousands of years and only started to change around twelve thousand years ago as the ice age came to a close.  Over time, the ice melted and drained into what would eventually be called Lake Michigan.

At this stage, our plot of land was no longer under ice, but neither was it shoreline.  It was now part of the lake.  Until the last couple of thousand years, the original shoreline was a mile to the west, where it met up with an elevated length of land now aptly named Ridge Street.  As the water gradually retreated, the area between the ridge and the lake became a swamp like much of the southwestern edge of Lake Michigan.

This swampy landscape, along with much of northern Illinois, was to become the home of the Potawatomi Indians.  For a long time they practiced limited agriculture as well as hunting and gathering.  When the first Europeans—the French—arrived in the 1700s, a network of fur trading was established.  This state of affairs continued until the English and then the Americans took “control” of the land.  By the 1830s, the State Government of Illinois needed funds, and they decided that land sales were the way to satisfy this need.  The Potawatomies were first asked to leave. Then they were driven from the land.  A small part of this area became Garden Park.

Former Potawatomi lands were then sold to various farmers and businessmen and were soon incorporated into townships.  Evanston—incorporated in 1863—did not originally contain the area that would become Garden Park.  This land was part of the South Evanston Township, which had been incorporated in 1873.  South Evanston was a different type of community than Evanston.  It had lower taxes, was more densely populated, and had a working class feel to it that was distinct from Evanston’s mix of middle and upper-class businessmen.  This fact is important, because when South Evanston was annexed to Evanston in 1892, much less of the land had been reserved for parks than in the rest of Evanston.  The only significant portion of land that was still available for parks was along the swampy lakefront, and it is probably for this reason that Garden Park exists at all.

By the 1950s, Evanston had become a large and progressive city.  The city government was concerned with the insufficient parkland within its borders and had begun to appropriate more funds towards purchasing plots for park creation.  In 1959, Evanston purchased a 100- by 180-foot plot of land along the lakeshore from Mrs. Donovan Y. Erickson for $30,000.  This plot already bordered one of Evanston’s public parks and together these parcels of land would form the future Garden Park.

Attaining its final borders was the beginning, not the end, of the changes that Garden Park would experience.  In the 1960s and early 1970s, Evanston proceeded to engage in park improvement throughout the city, and playgrounds were added to numerous parks.  It was shortly thereafter that I began to visit Garden Park.  My family lived in one of the apartment complexes in southeast Evanston-over on Hinman St.–and it was one of the few parks within walking distance.  Even after we moved away to extreme northwest Evanston and I had grown into a teenager, I would ride my bike down to the park.  I would find peace by sitting on the rocks, listening to the surf, looking south to the “radioactive orange” glow of Chicago at night, and by climbing up my favorite tree as I had done as a child.

It is now the year 2000, and the climbing tree is gone.

The Structure of Garden Park

Garden Park is located in southeast Evanston along the lakefront.  Specifically, it is at the end of Sheridan Court.  Along the south side of Sheridan court are apartment complexes that are four stories high.  These continue along Sheridan Court as it curves south for a block and rejoins Sheridan Street.  Along the north side are four houses of relatively modern design.  Past these four houses, one comes to the gated entrance of Garden Park.  Here, the sidewalk ends, literally. Only a much smaller gravel path remains for those who wish to proceed further along the lakefront.

Garden Park is roughly rectangular with a small “add-on” in the southeast corner.  The main portion of the park is approximately 300- (N-S) by 180-feet (E-W), while the “add-on” is 120-(N-S) by 60-feet (E-W).  The park is bounded on the East by a line of whitish-gray barrier rocks that protect it from Lake Michigan, on the South by a brown wooden fence, on the West by the various fences of the houses that border it, and on the north by another fence separating it from a plot of land that seems to function as a private park for very exclusive Evanstonians.

Entering the park from the non-gated entrance of the “add-on,” I find a picnic area.  There are 3 tables chained to the ground, 2 built-in grills, and a scattering of young trees.  Otherwise, this area merely contains grass and is fairly empty.  Proceeding north from here, I encounter the playground.  The ground here is elevated in comparison of the rest of the park, most likely designed to keep this area drained of water.  It is bordered with wood planks and is filled with wood chips that certainly have to be replaced each year.  Within the playground, there are 3 apparatuses.  To the west is the metallic swing-set.  To the north is a sandbox formed in the shape of a boat.  In the Southeast is a wooden contraption that is also in the shape of a ship and which contains a slide. North of the playground, the ground lowers again and is fairly empty until the northern edge of the park.  Interesting, however, is the qualitative change that takes place in the barrier rocks at this point.  Up until the playground, the tops of the barrier rocks were rather rough and pointed.  After the playground, they become much smoother, and flatter.  Here, they are easy to climb upon and perfect for sitting upon.  It seems strange to think that they would have been purposely designed this way, but it also seems strange to think that this layout is merely coincidental.

At the northern edge of the park is a metallic chain-link fence that is bordered on both sides by numerous small trees and bushes.  This area, along with the barrier rocks of the northeast corner, form the most secluded area of the park.  As I walk west, the park becomes less and less secluded until one reaches the open space of the northwest corner.  I start to walk back south towards the main entrance, and I cannot help but walk under the great willow tree that dominates the northern area of the park.  Its trunk diameter must be at least 4 feet and it is by far the largest tree in the park.  The ground underneath it is fairly devoid of grass.  Moving further south, there are two items to notice.  On the right, there is a park bench with two streetlights on either side.  On the left is a depression.  It is downhill from the playground, and at the moment, it is filled with water from melted snow.  It is the lowest point in the park and probably becomes a miniature pond every time it rains heavily.

Continuing south, there is open grass until I encounter another old tree.  This one appears to be a maple.  It does not dominate the area as the willow does, and there is grass up to its edge.  Proceeding a bit further to the south, I arrive at the main entrance to the park.  Here, there is the concrete water-fountain that is characteristic to Evanston parks—even if it only functions during the summer.  There is also the standard brown wooden sign with the yellow lettering proclaiming this to be “Garden Park—City of Evanston.”  There are well-trimmed bushes in front of the sign and a small stone path to the closed entrance gate of the park.

Something is missing.

The climbing tree is gone.

The Life of Garden Park

If you think about it, parks are pretty interesting.  For the city dweller, they are supposed to represent a bit of nature, a place where one can escape “civilization” for a tiny while.  They are patches of greenery amongst the asphalt, bricks, and metal of the city.  They are a place for children to play.  They have been—so it might seem–preserved from development.

This is a lie, though.

Parks are constructs and are every bit as “unnatural” as the buildings and streets that surround them.  The parks in Evanston are not spots of nature that are allowed to develop on their own.  They are carefully managed by the Evanston Park District, and each year the park district does its best to make the parks easily accessible to the inhabitants of Evanston.  Furthermore, humans are constantly in the park and contribute to its form.  Their presence adds to, subtracts from, or changes elements within the park.  In this sense, parks represent a fascinating example of how humans perceive and interface not only with nature itself, but more accurately with their preconceived notions of what nature should be.

With regard to the social life of Garden Park, summer is where it’s at. Children are everywhere.  They run around, trample upon the grass, scramble on the playground, throw the wood chips to and fro, and climb upon the rocks.  Their families also picnic, using the grills and filling the trash cans.  At night, the teenagers come out.  They visit the park, perhaps as a means to “escape”  the watchful eyes of their parents.  They, too, play on the playground, climb and write graffiti upon the rocks, and seek out the darker recesses of the park, whether for the purpose of illegal activities or just to ponder their own troubled teenage worlds.

At semi-regular intervals, the park service eventually comes to “beautify” the park.  They cut the grass that has grown despite the trampling.  They add new wood chips to the playground.  They trim the park bushes and try to thwart the “wild” bushes that attempt to grow amongst the barrier rocks.

Occasionally, they cut down trees.

During the cold months, this activity declines, but is not absent.  Walking through the park, I come across other human artifacts. Signifiers of human practices.  Because of the snow, I can see who else had been in the park.  Not only humans have been here, but animals too.  Along the entire edge of the park were the tracks of humans along with the paw prints of dogs.  It seems that the park serves as a perfect area for walking the local dogs.  Not surprisingly, as I approached the secluded northern end of the park, the number of illegal piles of dog feces increased until I had to be very careful of where I was stepping.

But dog walking was not the only activity there.  I saw that the slide had been used from the amount of sand that appeared splayed out at its bottom on top of the snow.  Additionally, in the northeast corner of the park, I found the signs of more adult interlopers: a crushed can of Budweiser beer amongst the rocks and a used condom lying on the ground near the northern fence.  It seems that the park has a healthy nightlife.

Despite the flurry of human activity in the park, the effects of nature are not entirely absent.  They were only a bit more hidden.  Looking over the edge of the barrier rocks–as the surf crashed upon it–I noticed that the rocks at the bottom of the barrier were smaller and smoother.  The water was washing them away, very gradually.  Also on the far side of the barrier were bushes growing amongst the rocks.  Here, they had escaped the pruning of the park service and were allowed to grow to their full capacity.  Nature will reclaim this place, given enough time, and only the constant vigilance of the park service and the money of the Evanston city council will keep the lake from overrunning Garden Park.

Between the enduring rhythms of nature and the conscious constructions of humans, there is tension, but also possibility.  Although I may not want to admit it, death is part of nature and it is likely that the climbing tree was already somewhat old when I was a child.  Willows only live for around 40 years, and most likely, my tree became sick at some point.

Most likely, it began to die.

This is what I tell myself.

This is how it must have been.

This is the reason that my climbing tree is gone.

And, perhaps, it is the reason why they planted a new tree there.

One that hopefully will become a climbing tree for someone else.

Posted in beauty, History | Tagged , , , , , , , , , | Leave a comment

Change, the cloud, and virtual brain damage.

… or perhaps the evolving relationships between centralization, efficiency, and security.

Things are really starting to change.

Fast.

I say this not just because I’m on my way to becoming an old person (I went past 40 trips around the sun last year), but because I’ve noticed a few significant shifts in the past year or so–or rather I’ve reflected on the massive shifts that have been happening–and at the limits that are starting to appear in physical reality in some areas–and not in others.

So let me give a few data points to provide context.

1. In Fall 2008, I started teaching freshmen engineers how to write.  In this, I made them write research papers on some sort of important engineering topic.  Back at that date, the idea of wind turbines seemed rather new to the students–and there seemed still to be a lot of debate over whether they were feasible.  Solar power, at the time, seemed even more pie in the sky.

Originally from zzzoffshore-wind-power-7259

Originally from zzzoffshore-wind-power-7259

However, over the past 5 years, this has changed.  Wind Turbines went from being seen as weird hippy eyesores on the environment to being almost reliable and a clear choice as at least part of our energy production system.  One can note that since 2008, total installed windpower has doubled, and in places like Spain, it is now the 4th largest source of electricity, just a bit behind coal.

Watching my students choice of research topics, it’s also clear that solar power–while not yet quite as developed–has also grown by leaps and bounds.  Instead of it just being seen as something that needs 20 years more development, you have a huge variety of solar topics and solar cell developments (nanostructures for silicon cells, dye-based solar cells, thin film organic solar cells) and you have clear economic analysis that shows solar power parity with standard coal power within the next decade or so.

This is big fucking change.  Pay attention people.

2. Information/communication-wise, the change has been even faster.  Thinking back, when I started college in 1990, email was new and not everyone at college had an account.

While I was an undergrad, the first web browser came into existence–Mosaic–developed at NCSA, which was a building only about 5 blocks from where I was living at the time.  Cell phones were still rare in the US at that time, but the web started to take off, and soon there was Netscape.

All of this ran over 2400baud modems.. then 9600baud, then 12.8k and then 52.8k modems over the phone lines.

By the time I got back from Germany in 1999, the internet was moving beyond the colleges and into the wider realm of the world, but most people still didn’t have email, and only the hippest businesses had webpages.

In 2000, “google” still was an arcane term meaning 1 x 10^100.   By 2004, Google was handling 87% of all the search requests on the web and by 2006 the verb “to google” was added to the Oxford English Dictionary.

Then came facebook.  Launched in 2004, it was opened to anyone over age 13 by 2006.  I didn’t join, until goaded by my students in November 2008–after the election of Barak Obama.

Looking back, it now seems hard to think of society without these things.. and to marvel at how much richer and more interconnected they have allowed me to become to various people and to the broad swath of information that is out there.

And this is without even mentioning the huge rise in cell phone.  In 1997, less than 1 in 5 people had them in the US, now there are more cell phone subscriptions than people here.  That dynamic–and the merging of computing and these phones in smartphones– has generated the creation of a whole other swath of technologies and networks–twitter, for example–that are driving a push  towards an ever more networked society.

Today, we hear about the switch to “the cloud” for computing services and data storage. Based on the integration of mobile networking, google searching/computing and data storage, and the desire for people to be connected at every instant of their life with access to their data anywhere, the cloud seems like a smart solution to this.

And, in many ways, it is.  It is true that the growth of this kind of virtualization of our data and computing away from the specific hardware located in our homes does provide certain kinds of access and efficiency that were never possible before.  Or rather, this kind of increase in efficiency has happened before–think about the invention of the telephone and how much that increased communication speed and efficiency.

The cloud just takes that to a new level with the added abilities of our massive new reliance on computing power.

And yet, part of me is leery of all of this.  While I might appreciate the cloud as a way to back up my files in a secure place in case some sort of natural catastrophe were to specifically happen to my home, I don’t feel comfortable relying upon it 100% for all of my computing or storage needs–and I’m not all that enthused to buy into it so fast.

Now–perhaps this is just some kind of “old person” stubbornness to embrace the new technology.. but I’m not so sure.  Things like Microsoft’s introduction of Microsoft 365–where you buy a subscription to the software where you pay them every year to use their products, without ever really owning the software–seem like a clear outgrowth of this kind of cloud model and also seem like what these companies want the futre to be like.

In essence, a very decentralized model of computing–with each person using their personal computer, having their own files, and own copies of software in their possession… in their ownership… is being changed and replaced.  In its stead, you are getting people with the equivalent of fancy terminals that will access their files and software from some other location, where the actual processing can be done more efficiently.

And–a I said above–that makes a certain kind of sense.  In my mind, the analogy of an animal having a “brain” that does most of the decision-making and sensory input perception, amongst other things, has been shown to be orders of magnitude more effective at accomplishing various kinds of tasks.  It’s a lot quicker and more efficient at handling communication and it can adapt to various conditions a lot faster.

The Cloud, in certain ways, would be very much like the way the brain is a centralized and complex system for handling certain kinds of tasks.

But this analogy also points out a major weakness of both systems.

Namely, any creature that relies upon this brain for getting around in the world effectively really doesn’t do so well if this brain is damaged or destroyed.  In fact, brain damage–which is not that hard to inflict–is one of the quickest ways of utterly disabling and ending such a being.

What does that tell us about a society that comes to rely upon this kind of information network for its functioning?

Well, it tells me that we ought to be MIGHTY careful about such systems and figure out ways of making sure they are utterly robust and reliable, because the use of them seems more and more like a conscious attempt to put all of our eggs in just one big virtual basket.

That doesn’t sit well with me.  In an age where we are rediscovering the possibility of decentralized and distributed power generation through wind, solar, and other more renewable systems–the choice to start centralizing our information systems seems like a move in the wrong direction.

Perhaps this is incorrect, though.  Perhaps distributed power generation–the equivalent of muscles and even more specifically mitochondria in each cell of our body–does make sense when connected to concentrated information processing systems (our brains).

I’ll have to ponder this a bit more.. but it seems like something that more people should be pondering also…and some of them do seem to be..

Posted in Writing and Communication | Tagged , , , , , , | Leave a comment

Map Lust

So I’ve always loved maps.  I think it began in kindergarten at Ronald Knox Montessori school when I used to trace maps of the world because there were “puzzle” maps where you could take the pieces out and then trace the different countries.  They had this not just for the US–but for each and every continent.

This imprinted itself on my 3-6 year old brain in a primal way and it has never left.  Although I never majored in Geography, the love of maps certainly got its fair hearing in my love of history, international relations, and military history.  I even wrote my personal statement/essay on my fascination with maps for my application to Harvey Mudd, which was a hardcore engineering school.

And I got in. (although I then went to a different school…)

Anyway–a couple weeks back I came across an awesome map in my blog reading.  It was either at Andrew Sullivan or at Talking Points Memo–but the map was generated by the idea of rearranging US State boundaries so that they would each have an equal population.  The point of this was to try and rectify the inequalities in voting power that have come about because of how each state–no matter how big or large–has 2 senators and how even in the House of Representatives, you have a range between 500k to 900k per Representative district because of the fixed number of seats.

In other words–votes are not necessarily equal.

Here is the map that was presented:

At first glance, this is pretty cool.  You see how some current states have to be merged with a number of others just to become 1 new state (with about 6.2 million people).. whereas other states get broken up into a number of other states (Chicago/Cook County +Dupage county would be it’s own state…).

Now–I wasn’t actually all that entranced with the name choices–but that’s relatively arbitrary.  If you go and google “map of 50 states with equal population” (or at least if you are me and do this…), you can find a number of maps that do the same trick as above.  One map that was done in 2010 by the same guy has names that I like better–but which is not all that different.

Now.. while this idea is cool when you glance at it–with a little bit of thought, one can see how unworkable this would become in practice.  Crucially, this map may have equal populations now, but 10 years from now, and worse, 20 years from now it would have to be redrawn again as populations shifted.

Now–maybe that doesn’t sound so bad, but any business owner and lawyer might be able to tell you how crazy it would be to suddenly find yourself in a new state being subjected to different state laws, different tax rates, and entirely new legislative/political alignments.

That would be madness.

It would also not just be an economic nightmare, but could easily be a personal one.  Take Illinois and Wisconsin, for example.  These two states have radically different divorce laws related to the custody of children.  In IL, it is almost always single custody and from what I’ve heard–it’s usually with the mother.  In WI, on the other hand, the default is joint custody and joint placement if both parents live within the same school district.  The only reason why there would not be joint custody in WI is that there is some legally compelling reason (namely a criminal record of child abuse) for their not to be.

Now what would happen in the above map situation if the boundary suddenly changed every 10 years and couples who were not doing well found themselves in a district with a different set divorce laws.  It could get nasty fast.  Furthermore, considering that they’d need lawyers, you’d see vast migrations of lawyers following state boundaries any time there was a census and realignment.

This just would not work.  Cool idea to think over–but it wouldn’t work in practice.

A better solution would be just to abolish the senate entirely and to have an expandable number of representatives to be based on multiples of the state with the lowest population.  Currently, that is Wyoming with only around 575,000 people.  Take that number–i.e. set 575,000=1 Representative–and then do the math.  This would, for example change the number of representatives for the 50 states as follows:
State/Current Representatives/New Representatives
Total/ 435/544
California/53/66
Texas/32/45
New York/29/34
Florida/25/34
Illinois/19/22
Pennsylvania/19/22
Ohio/18/20
Georgia/13/17
Michigan/15/17
North Carolina 13/17
New Jersey 13/15
Virginia/11/14
Washington/9/12
Massachusetts/10/12
Arizona/8/11
Indiana/9/11
Tennessee/9/11
Missouri/9/10
Maryland/8/10
Wisconsin/8/10
Minnesota/8/10
Colorado/7/9
Alabama/7/8
South Carolina/6/8
Louisiana/7/8
Kentucky/6/8
Oregon/5/7
Oklahoma/5/7
Connecticut/5/6
Iowa/5/5
Mississippi/4/5
Arkansas/4/5
Kansas/4/5
Utah/3/5
Nevada/3/5
New Mexico/3/4
Nebraska/3/3
West Virginia3/3
Idaho/2/3
Hawaii/2/2
New Hampshire/2/2
Rhode Island/2/2
Montana/1/2
Delaware/1/2
South Dakota/1/1
Alaska/1/1
North Dakota/1/1
District of Columbia/0/1
Vermont/1/1
Wyoming/1/1

Now.. that would still have some issues–the vote totals would not be 100% equivalent everywhere.. but they’d be a lot better.

Interestingly–if you were to use the new numbers as the electoral votes of each state (remember we abolished the senate), the result would have been 345-199, Obama over Romney–which was pretty close to the actual result (332-203).

And that’s what I have to say about maps today.. time to go get some other housework done.

 

Posted in Images and Visualization, Uncategorized | Tagged , , , , | 1 Comment

Rape Culture must die.

This post is not like the others on here–but it is needed.. because the culture we live in.. a culture that not only tolerates rape, but even celebrates it and promotes it at times (often, but not always, with plausible deniability..)… must fucking change.

It must change now.

If you don’t believe me, go read the evidence here..

Posted in Human Nature and Mind | Tagged , , | Leave a comment

Calculation, Perception, and Intelligence

Is your brain a computer?

Obviously, it’s not made out of silicon, but is your brain just a biological calculator that determines your actions by doing some kind of calculation?

Many people seem to think so, but I’ve never been sold on this idea. As much as I love doing calculations–hell, my last name means something on the order of “skill with calculation” or “skill with numbers”–I have always been a bit skeptical about what I saw as an attempt to oversimplify the processes that made up human behavior.  Some recent reading I’ve done has shed some interesting light on this state of affairs and I thought it would be useful to hash through this a bit. Importantly, this reading occurred after I had my original thoughts that led to the previous games versus stories post.

Above all, the reading that set me thinking along these lines was a biography of Alan Turing by Andrew Hodges titled Enigma. Turing, in case you didn’t know, is widely considered the person who created the fundamentals ideas at the heart of the digital computer, computer science and artificial intelligence.  He was a British Mathematician who provided a renowned answer to one of Hilbert’s Entscheidungsprobleme and whose work always retained a connection to the concrete world of mechanical calculation.  He also was at the heart of the British cryptanalysis group that broke the German codes during the war, greatly helping the Allied war effort.

Reading Hodges book about Turing, one picks up on the fact that Turing was always very interested in what basic human intelligence was and he wanted ways to define and (eventually) test for it. One of the crucial ways that Turing defined intelligence was the ability to strategize and play games.  In particular Turing thought the ability to play Chess was a measure of intelligence and he long worked at developing early electronic calculating machines to play chess against human competitors.

In other words, the earliest computer game ever was chess.

Which is fitting, considering that it is within recent memory that computers finally became good enough to consistently beat skilled human chess masters.  From that disputed accomplishment of “Deep Blue” back in 1997, we more recently saw the rise of “Watson” on the game show Jeopardy.  With these developments, the talk about machine “intelligence” grew. People impressed with Watson spoke of how it showed that “intelligence is tied to an ability to appropriately find relevant information in a very large memory.”

But is that really intelligence?  Is intelligence really only about retrieving information quickly and calculating a decision based on that information?

I’ll admit that certain kinds of activities require those kinds of skills.  Playing a game–which Chess and Jeopardy both clearly require that kind of skillset, but games are a very particular kind of activity.  Specifically, they are an activity where you know the rules in advance.  Actions are specified in a clearly defined way, which allows the determination–in a binary/logical fashion–of their application and achievement.

This is a very artificial state of affairs.  Most human activities are not purely games where rules are yes/no kinds of things.  Most human activities are messier, are filled with unclear ambiguities, and the rules are dynamic and under constant negotiation and change.

In other words, instead of chess, most of reality is more like this:
calvinball

What I’m getting at is that computers such as Deep Blue and Watson were great at doing their specified task, but they were not capable of adapting to rules changes–if someone had tried to make them–much less to creatively develop new rules on the fly.

The idea of “Intelligence as a game”, in other words, ignores major elements of human intelligence–such as creativity and spontaneity–that are essential elements to what it means to be human. (In fact, many of these elements are not just apparent in humans, but in many other life forms “down to” creatures like Octopi and other mollusks…)

To use an analogy–Deep Blue and Watson were exceptionally good tools.  They were like exquisitely sharp automatic saws that were better at cutting through things than ever before.

But as cool as they were as saws, they were still just saws.  If you asked them to pound something together, they would be failures.  If you asked them to screw something together or to pry something apart or to carefully sand something, they would be failures.

And never mind about asking them to design you the house that you were building.

Just like a bandsaw is not an architect, the calculation of sums and differences is not a sufficient model of intelligence.  While I have no doubts that, with a lot of work, computers can be improved to better succeed at something as artificial as a turing test (which is just a particular kind of game), I do not think we’re going to see truly intelligent machines any time soon, much less ones that are nearly as resource efficient as humans are.

But what about Perception?  Why is that in the title?

Originally, I had no intention of talking about perception while tackling the issue of calculation and intelligence, but it was again through my recent reading that I was instigated to address this issue.

Specifically, this past week I was rereading Richard Dawkins’ The Ancestor’s Tale, and I came across a telling remark by Dawkins in The Platypus’ Tale.  In that episode, Dawkins talks about how the platypus uses a network of electrically sensitive cells along its bill to find food in the dark, murky ponds in which it lives. In a very real sense, it uses a kind of radar to find food.

Now, the way that Dawkins describes this process on page 199 is so,

When any animal, such as a freshwater shrimp which is a typical platypus prey, uses its muscles, weak electric fields are inevitably generated. With sufficiently sensitive apparatus these can be detected, especially in water. Given dedicated computer power to handle data from a large array of such sensors, the source of the electric fields can be calculated. Platypuses don’t, of course, calculate as a mathematician or a computer would. But at some level in their brain the equivalent of a calculation is done, and the result is that they catch their prey.

My question is, why does Dawkins consider such an activity a “calculation’ at all?  While it is true that human radar requires the use of computers to do a lot of calculations to understand the signals involved in radar, that is because we consciously created the system that way.  Large arrays of electronic signals are turned into numbers and then complicated additions and subtractions are done on these signals to provide a result.  The reason it is done this way is because computers are just giant calculators and they can only work with numbers!  Asking a computer to perceive the changing signals is impossible. Computers don’t and cannot perceive anything, because they lack the capacity to do anything other than calculate.

It would be like expecting an eye to smell.

So what has happened here?

Well, Dawkins has reversed the story. Specifically:

1. In the real world, platypuses developed the ability to find food creatures by perceiving their electrical fields.  How that perception is built/constructed/registered in their is still not entirely known.

2. Much later on, however, humans managed to recreate this process using machinery that relied upon a process involving the very fast calculation of sums and differences by a particular kind of machine.

3. Humans then discovered that platypuses were achieving the same kind of result as this machine process.

4. Humans then decide that platypuses must be doing the same kind of thing as their machines.

The flaw in this logic should be clear.  Humans have managed to simulate a biological activity using machines, and have then decided that the intrinsic methods used in their simulation must be how the biological process works.

That’s just weak sauce, though.  More importantly, this kind of thing happens all the time and it underlies many of the problems that I find with a lot of discussions about artificial intelligence, free will, determinism, and a number of other things.

This problem is not surprising to me, I must say, because as I’ve written about before (using George Lakoff’s concepts), humans tend to understand their world by movtivated applications of metaphorical concepts residing in their brains.  In this case, Dawkins has long been a huge computer guy–his use of computers, algorithms, and calculations to understand and explain evolution goes back to the 1970′s–and it’s not surprising that he would apply this model here.   More broadly, humans have long used machinery–well at least since the 1600′s–to shape their understanding of how the mind works.  If you watch cartoons from teh 1940′s, for example, the little thought bubbles used gears, pulleys, and the like to represent human thought.  Today, we use computers and think of memory as a hard drive and intelligence as a kind of processor.

But these models–the more we find out about the brain–aren’t all that accurate.  Human memory does not work like computer memory. It is not stored as a concrete listing of symbolic description of events that are stored in one particular place of some biological FAT table.  Instead, they are constructed things–where elements of memory are distributed throughout the brain in a fashion where they overlap with similar or associated memories.  When they are recalled, they are then imaginatively reconstructed.  Recognition of this is one of the reasons why eyewitness testimony is not considered as strong as it once was.

To conclude, I would argue that what goes on in human brains is still not all that well understood.  There are numerous competing theories–but fundamental questions of whether the brain is really like the computer model that people hav applied to it so readily seem to be coming apart at the seems the more people learn about the brain.  In addition, fundamental conceptual ideas–such as whether perception is a calculation or is just something ENTIRELY DIFFERENT need a bit more attention–because it strikes me that perception itself, rather than calculation seems like a more likely candidate as the origin and generator of consciousness and intelligence than calculation–which seems like a very useful, but later, acquisition of the human mind.

And now–it’s time for a nap.

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Games and Stories….

This nom has been sitting on a sticky note for months now.  It is good that it sat on that sticky note.. as more thoughts, connections, and ideas have become stuck to it in that time.

Before I get to it, however, let me give you my numbers–as I have in the past–and then use them later.

1,028,600.
69.04
1410
729.50

For those who are new to this blog, the numbers represent the following:
# of push ups I’ve done since Jan. 1st, 1998
# of push ups/day I’ve done per day averaged over my entire life
# of pull ups/chin ups I’ve done since Jan 1st, 2013
Ratio of Push ups/pull ups.

These numbers are important to me–they are both calculations and they say something about me over time.  But more on that later.

Why do I want to talk about games and stories?  Well, it occurred to me one day that both of these things are mental activities that are often pretty central to how humans interact with themselves, with each other, and with the society around them.  Not only are these two topics actual activities that people do, but they are also some of the core concepts in how people perceive life and the world.

Sometimes life is a game to play.

Sometimes it is a story you tell yourself.

And it struck me that these things are actually pretty different ways of dealing with the world–even if they are both very important and central ways of understanding our experiences.

But what are they?  Well, as Thomas Hobbes notes in the beginning of The Leviathan, good thinking requires good definition of terms from the outset, or else we are just making a collection of nonsense sounds signifying nothing.

What is a game?
RiskGame-101

Games are pretty common in our experience.  Kids make up games and play them and a lot of social interaction and learning seems to be in the form of games.   In general, we talk of “playing games,” and using that understanding, we could  note that game playing is not just a human thing–it could be–at least loosely–extended to a much wider range of animals–especially mammals–as when you watch two cats play with each other.

But what makes up a game?  Well, going back to the etymology of “game,” we find that the noun comes from “gaman” and is a common germanic word meaning something like “joy, glee, sport, merriment” and that it comes from the prefix “ga,” meaning “collective/together,”(it’s the “e” in enough and the “ge” used to form the beginning of most past participles in German.. ) and “mann” meaning “person”–so that the original meaning was a “people together…”

And what happens when you get a group of people together–well, a common activity is for some of them to play together–and to compete with each other in some way while doing it.  Perhaps they are just playing tag and chasing each other.. or maybe they are throwing rocks to see how far they can get them.

This is what humans do.  It is part of our social make up from deep, deep down–and it underlies a lot of our cultural make up.

If we go look at reasonable definitions of what a game is, you get the following:

game is structured playing, usually undertaken for enjoyment and sometimes used as an educational tool. Games are distinct from work, which is usually carried out for remuneration, and from art, which is more often an expression of aesthetic or ideological elements. However, the distinction is not clear-cut, and many games are also considered to be work (such as professional players of spectator sports/games) or art (such as jigsaw puzzles or games involving an artistic layout such as Mahjongsolitaire, or some video games).

Key components of games are goals, ruleschallenge, and interaction. Games generally involve mental or physical stimulation, and often both. Many games help develop practical skills, serve as a form of exercise, or otherwise perform an educationalsimulational, or psychological role.

Attested as early as 2600 BC,[1][2] games are a universal part of human experience and present in all cultures. The Royal Game of UrSenet, and Mancala are some of the oldest known games.”

Synthesizing this information, the key elements that appear in games are:

1. that there are rules that limit them;
2. that there is competition or challenge involved in them;
3. and that they involve interactivity–either between multiple humans or a human and objects.

These elements are important to keep in mind.  They very much define what constitutes the kinds of activities that we understand as “games.”  An unspoken addendum to these elements would be that games involve calculation.  They involve decision-making–either conscious or unconscious–and that a good part of the power of playing games comes from the experience of us executing a strategy or of  performing according to our own wishes and will.  By playing, we create ownership over the game in this way.

It’s also pretty easy to see how/why we the connection between “game” and “play” exists.  The verb “to play” originally meant to “move rapidly, occupy or busy oneself, exercise; frolic; make sport of, mock; perform music” and came from a West Germanic root that basically meant “to occupy oneself about” (think of how current Americans occupy themselves with sports games!) and from an earlier indoeuropean root meaning “to engage with.”

Games have no purpose unless they are played.. unless we occupy ourselves with them and engage in them.

Game-playing is part of what makes us human.

But only part.

Not everything is a game, for we also live in a world of stories.

caterpilar

I’ve spoken a lot about stories on this blog–because the importance of stories in my life has become much more clear as I got older.  I’ve even thought about the differences between puzzle-like and story-like structuring in languages–which doesn’t seem too far off of the comparison I’m making here…

But I don’t think I’ve ever done my usual etymological trick on the word “story” itself before.

About time I did that then.

“Story” comes to us by way of French “estorie,” which itself comes from earlier Latin and Greek words.  At first, it wasn’t really separate from “history” and both of them meant “an account of some happening.”   Delving deeper into the meaning of the original words, one finds that it comes from Greek “histor,” which meant,  “wise man, judge,” from PIE *wid-tor-, from root *weid- ”to know,” literally “to see.”

The proto-indo-european root–*weid–is the root of Latin “visio/onis,” from which we have “vision,” but it is also the root of good old English words “wit,” “witty,” and the archaic “to wit,” which meant “to know,” and which has clear German cognates in their verb “wissen”==to know, and their noun, Wissenschaft (literally “Knowledge-scape”), which is their word for “Science.”

In any case, it is helpful to think on this root meaning of the terms that developed overtime to describe our conceptions and practice of a “story.”  A story is an account of something–but this meaning comes from a greek “wise man”–and how does one become wise? By seeing things and coming to know them over time.

In this basic and underlying meaning–a story is composed of knowledge–but it also has a clear time aspect, a duration, that implies both an accumulation of knowledge by someone–and a particular sequence of events.

In this, one might note, a story is very unlike a game.  Games–while they have rules that govern the sequence of certain actions–have the element of random chance/occurrence built into them at some level–for if a game’s actions were entirely foreordained, we usually wouldn’t consider it to be a very entertaining game.  It is the unexpected aspect.. driven by the competition inherent in a game that gives most people excitement and entertainment.

Of course, not everything in a story is known in advance.  The person reading or hearing a story is often entertained because they do not yet know the sequence of events to come–but this lack of knowledge is only true for one side of the storytelling.  The teller of the tale.. whether it is an author who wrote the story in the past or someone speaking it in person.. that storyteller already knows the sequence, and that is what gives them power, for they have the knowledge already and the excitement comes from hearing the tale.. from the transferral and acquisition of this knowledge in ourselves.

Comparatively then, we can see another big difference between a game and a story–namely that in a game the participants are equal–at least in theory if not in practice–whereas in a story, there is an asymmetrical relationship between the teller and the listener.

As we noted above, a game is played, while here we speak of a story being told. Looking at the verb, “to tell,” we find that old English tellan meant “to reckon, calculate, consider, account,” which fits with the use of the term “teller” in banking (a bank teller counts your money..) and in the German cognate “zahlen” which means to count.. (erzaehlen means “to tell” as we use it.. ).   However, the deeper indoeuropean root of “to tell” connects it intimately with our conception of a story, for it comes from root *taljanan, which means “to mention in order.”

I’d like to start to close this by pointing noting that both games and stories also function as a kind of mental construct that we often apply to understanding the world around us.  Sometimes these applications to reality are clear mappings–such as when we are literally playing a game or telling a story to someone, but other times they are more metaphorical.  We like to talk about people “playing head games,” or that “life is a game”–and when we do that we are imposing a certain kind of understanding on the world–we are implicitly arguing that there are rules governing behavior, that there is a competition going on, and that we are part of this interaction in some way.

Sometimes this is true–but sometimes it isn’t–and it can be helpful to take a step back and make sure that we aren’t imposing these understandings on reality when they don’t really apply. Perhaps someone else isn’t playing a game with us.. but perhaps we just want to compete with them and so we turn it into a game.   This can happen in work situations quite easily.

This can be dangerous if we’re not careful depending on the situation–because games have winners and losers–and we can turn those who might be our partners into our opponents.

Stories also play special roles in our lives–we tell ourselves stories to make sense of our lives because they can give us meaning.  Religions our usually a group of stories that accomplish this goal–but even without any supernatural overtones, people use stories to understand the world.  They use these stories as models for understanding what’s going on around them or for inspiration for what to do next.

However, the “storyline” concept can also be misapplied to our lives.  For example, sometimes we convince ourselves that things that are happening in our lives are just following a particular storyline–implying that certain endings are foreordained–when, in reality, things are a lot more fluid and are dependent upon our interactions with reality to determine the outcomes.  In these instances–where we are actually creating the story as we go along–we may actually be much more in a kind of “game-like” situation than we know–and ignoring the chances for shaping the outcome of the game may end up to our detriment.

Also, sometimes shit just happens.  People often want to figure out why this shit happened, and they create a story to explain it–that it was destined to happen or because someone was scheming to make it happen–when in reality, it was just a result of factors way beyond our ability to control.

Here, we need to be careful about letting our own self-storytelling get ahead of ourselves and letting it create an understanding of the world that is following a storyline that has more to do with our own desires and wants than with the actual facts at hand.

Finally, let me end by going back to the numbers at the beginning of this post.  These numbers signify actions of mine–physical actions involving exertions upon my part.  In some ways, these numbers are the result of a game I play against myself–calculations that I make daily to see where I can push myself.  In other ways, these numbers tell a story, for they are but one instance of a long sequence of numbers that cover a significant portion of my life, and there are people who now actually follow my progress.  In that, they tell part of the story of my life.

Thus, it is not that games and stories are utterly separate things all the time.  Sometimes they are just different approaches that we can take to the same subject matter.

Other times.. times which I will elaborate upon in subsequent posts, they are truly different.. and we must be careful to understand the differences lest we deceive ourselves.

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Numbers–The Power….

So, yesterday I talked about Numbers and how they figure into my personal definition of myself.  It was a discussion of how numbers create some of the meaning in my life.

Today, I want to give an example of how people use numbers in a completely different manner.  In specific, I want to show how people use numbers as a means of creating arguments/supporting arguments and how they try to draw upon the “power” that numbers often possess to many audiences.

This power, not surprisingly, derives from the association that numbers have with quantification and the idea that quantification is a kind of “objective” process, and therefore, true.  While this association between quantification, objectivity, and truth may seem obvious in a world filled with high-tech electronics, information technology, and data-driven search engines at our beck and call–one should not take such claims for granted, and should instead understand that this current state of belief in numbers is just as much of a construct of history as the technologies that we associate with it.  A good treatment of such ideas can be found in Theodore Porter’s book, Trust in Numbers: The Pursuit of Objectivity in Science and Public Life.  I came across this book during my prelims (which were focused on,  the History of the Enlightenment, The History of the Applied Social Sciences, and The History of Technology), and it has some cool stuff in it.

It is academic prose though–so be forewarned..

Now.. back to the story.  Rather than talk in the abstract about the power of numbers, what I really want to focus on is how this kind of power was applied to tell a certain kind of story and to push readers to a certain conclusion.

This story, my dear readers, began a couple weeks after the 2012 American Presidential Election, and it came about as I was reading my favorite political blog–hell, my favorite blog overall–namely Andrew Sullivan’s The Daily Dish.
In my daily perusal on Nov. 26th, I came across the following article–titled: The Politics of Fertility.  

Now–in this blog post, Andrew & crew linked to another online article–by Lauren Sandler–that made the argument that the state-by-state election results could best be predicted by the fertility rate in a state–and that the correlation argued that larger family size/fertility rates–implying a kind of support for “family values“–meant more support for Republicans, while lower fertility rates meant more support for Democrats.

laurengraphic1

In fact, the title of Lauren Sandler’s original blog post was, “Tell Me a State’s Fertility Rate, and I’ll Tell you how it voted” and in that article, the basic claim is demonstrated in a graphic and a table that claim to show that states with fertility rates over 70 voted Republican, whereas states with fertility rates under 60 voted for Obama. One of the graphics is shown above. She followed up this graphic with a table that came from Governmental CDC data.

laurentable1

 

 

Now–before we go any further, I think that it’s worth doing a bit of thinking about the numbers that are assembled in these graphics.  Remember, the claim is that these numbers make it easy to understand the reality around us–and that they simplify this reality in a way because they supposedly show us an underlying pattern that was obscured by all the messy details of reality.

Does this claim hold up to reality?

If you stop and think about the meaning of these numbers–if you try to understand the numbers and analyze where they come from, then the argument starts to break down pretty quickly.  Some points to think about:

1. What about Hawaii?  If you go look at the initial Map, one sees that Hawaii had a fertility rate over 70, and yet it voted for Obama.  So the “over 70 rule” is not hard by any means.

2. If you look more specifically at the states that voted for Obama, the correlation between low fertility rates and support for Obama is all across the board.  For example, New Hampshire has a really low fertility rate, and yet it voted for Obama by only a 5.8% margin.  New York–with a much higher fertility rate–voted for Obama by 26%.  Additionally, while Vermont and New Hampshire’s fertility rates were nearly equal, Vermont voted for Obama by nearly 36%–or over 6x the difference of New Hampshire.  Similarly, you can see that New York and Florida had nearly the same fertility rate, and yet Florida barely went for Obama 50.0% to 49.1%, whereas in New York, it was 62.6% to 36%.

3. If you actually then look at the tables, you can easily notice two problematic issues in the column marked “total fertility rate over 70″: first, that they include two Republican states whose fertility rates are under 70 (Texas and Wyoming)–even if just barely so–but they do not include Hawaii in there, even though it’s fertility is over 70–because that would disrupt part of the heading of the column–namely that “all romney states.”

Thinking further on fertility rates, one might remember having heard somewhere that minority groups tend to have higher fertility rates than whites and that this is the reason that the white majority in this country is diminishing.  With this in mind, one might then also note that this election clearly showed that minorities voted OVERWHELMINGLY for Obama.

So–you have an article stating that high fertility rates mean votes for Republicans–and yet those groups that have the highest fertility rates vote strongly for Obama?

Something really odd is going on here.

Specifically, what it points to is that the notion that a state’s fertility rate is really a bogus measure to use–as the causation between having a high birth/fertility rate in a subgroup does not correspond to greater support for Republican ideals at all. Actually, a close reading of the data (see pages 7 especially) leads to exactly the opposite conclusion–namely that the majority of groups with a high birth rate–at least ethnically–were much bigger supporters of Obama than of Romney.

So–the numbers do have power–but the problem here was that someone was trying to use the power of numbers to make a particular argument and claim that wasn’t actually supported by the numbers.  Instead, they were misusing the numbers because they didn’t spend the time to grok the context or real meaning of them.

Now this might be a fine place to end the story, but in reality, there was one very big twist left in this tale.  As I noted at the outset, originally I came across this article by reading Andrew Sullivan’s blog, where–without much comment–he represents the claims made by the Sandler blog post.  Importantly, he and his crew included the map graphic that she had used–and I’ll include a screenshot of it here:

redhawaii2

Now look very carefully at the map on this post.  Compare it to this map:

laurengraphic1

Do you notice a difference?

Something has changed.

The President’s birth state has turned Republican Red.

How did that happen?

Overall, I’m still puzzling over the exact process that occurred between the blog post by Sandler–that has all the errors that I’ve noted, but which doesn’t mis-color Hawaii–and the final Daily Dish presentation where it appears that someone physically altered the image to correspond with the original blogpost’s argument, even though that meant lying about reality.

Numbers have power because they can be used in helpful ways to teach us about the external world.

But that accuracy is not a given.

People can lie with numbers–and they do.

In the end, the best strategy is to always make sure you understand the meaning of the numbers–to push further so that you can make the numbers make sense–otherwise, you may just be allowing someone to lie to you in yet another way…

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