The Confidence Man

Posted on March 18, 2016 by Sarah Shugars

In 1849, the New York Herald reported on the arrest of a gentleman by the name of William Thompson.

I use the term ‘gentleman’ here broadly. As the Herald reported:

For the last few months a man has been traveling about the city…he would go up to a perfect stranger in the street, and being a man of genteel appearance, would easily command an interview. Upon this interview he would say after some little conversation, “have you confidence in me to trust me with your watch until to-morrow;” the stranger at this novel request, supposing him to be some old acquaintance not at that moment recollected, allows him to take the watch, thus placing “confidence” in the honesty of the stranger, who walks off laughing and the other supposing it to be a joke allows him so to do. In this way many have been duped…

To those who had heard of these strange interactions, Thompson was known as the “Confidence Man.”

He was, in fact, the first “confidence man” – a term which has sense been colloquially shortened to “con man.”

Coding The English Language

Posted on March 17, 2016 by Sarah Shugars

I have been quite busy this week trying to capture all the rules of the English language.

As you might suspect, this is a non-trivial task.

Having benefited from being a native English speaker and having studied far more regular languages (Latin and Japanese), I always knew that English was a crazy mishmash of rules – but I find I am getting a whole knew appreciation for it’s complexity.

As it stands, my grammar – which has a tiny vocabulary and only rudimentary sentences – has nearly 500 rules. Every time I try to generalize, I find those nagging English exceptions which create a cascade of special case rules.

All this highlights how impressive the advances of Natural Language Processing are – correcting spelling and grammar is hardly easy, much less building an assistant such as Siri which can understand what you say.

It also seems to highlight the concerns of the natural language philosophers – when constructing a thought as an expressible sentences is so hard, how can we be confident our meanings are understood?

Of course, our meanings are very often not understood, which leads to no end of drama and miscommunication. But, putting basic miscommunications aside, what does it really mean to communicate or to understand another person?

Ludwig Wittgenstein poses this questions frequently throughout his work. In Philosophical Investigations he tests numerous thought experiments. If I say I am in pain and you have experienced pain, do I understand your pain?

For practical purposes, we generally have to act as if we understand each other, whether or not some deeper philosophical measure of True understanding has been met.

Wittgenstein also uses a lovely metaphor to describe the complex architecture of human language:

“Our language can be regarded as an ancient city: a maze of little streets and squares, of old and new houses, of houses with extensions from various periods, and all this surrounded by a multitude of new suburbs with straight and regular streets and uniform houses.”

The Benefits of Inefficiency

Posted on March 16, 2016 by Sarah Shugars

Political scientist Markus Prior has long argued that inefficiency benefits democracy. In much of his work studying the effects of media on political knowledge and participation, Prior has found that an inefficient media environment – in which people have little choice over their entertainment options – is actually conducive to improving political knowledge.

In Efficient Choice, Inefficient Democracy?, Prior explains: “Yet while a sizable segment of the population watches television primarily to be entertained, and not to obtain political information, this does not necessarily imply that this segment is not also exposed to news. When only broadcast television is available, the audience is captive and, to a certain extent, watches whatever is offered on the few television channels. Audience research has confirmed a two-stage model according to which people first decide to watch television and then pick the available program they like best.”

That is, when few media choices are available, people tend to tune in for entertainment purposes. If news is the only thing that’s on, they’ll watch that over turning the TV off.

In a highly efficient media environment, however, people can navigate directly to their program of choice. Some people may choose to informational sources for entertainment, but the majority of people will be able to avoid exposure to any news, seeing only the specific programming they are interested in. (I should mention here that much of Prior’s data is drawn from the U.S. context.)

As Prior further outlines in Post-Broadcast Democracy, an inefficient media environment therefore promotes what Prior calls “by-product learning”: people learn about current events whether they want to or not. Like the pop song you learn at the grocery store, inefficient environments lead to exposure to topics you wouldn’t explore yourself.

Interestingly, it seems that a similar effect may take place in the context of group problem solving.

In a problem-solving setting, efficiency can be considered as a measure of communication quality. In the most efficient setting, all members of a group would share the exact same knowledge; in an inefficient setting group members wouldn’t communicate at all.

Now imagine this group is confronted with a problem and works together to find the best solution they can.

As outlined by David Lazer and Allan Friedman, this context can be described as a trade off between exploration and exploitation: if someone in your group has a solution that seems pretty good, your group may want to exploit that solution in order to reap the benefits it provides. If everyone’s solution seems pretty mediocre, you may want to explore and look for additional options.

Since you have neither infinite time nor infinite resources, you can’t do both. You have to choose which option will ultimately result in the best solution.

The challenge here is that the globally optimal solution is hard to identify. In a bumpy solution landscape, a good solution may simply point to a local optimum, not to the best solution you can find.

This raises the question: is it better have an efficient network where members of a group can easily share and disperse information, or is better to have an inefficient network where information sharing is hard and information dispersal is slow?

Interestingly, this is an open research question which has seen mixed results.

Intuition seems to indicate that efficient information sharing would be good – allowing a group to seamlessly coordinate. But, there’s also some indication that inefficiency is better – encouraging more exploration and therefore a more diverse set of possible solutions. The risk is that a group with an efficient communications network will actually converge on a local optimum – taking the first good option available, rather than taking the time to fully explore for the global optimum.

The Nature of Technology

Posted on March 15, 2016 by Sarah Shugars

I recently finished reading W. Brian Arthur’s The Nature of Technology, which explores what technology is and how it evolves.

Evolves is an intentional word here; the concept is at the core of Arthur’s argument. Technology is not a passive thing which only grows in spurts of genius inspiration – it is a complex system which is continuously growing, changing, and – indeed – evolving.

Arthur writes that he means the term evolution literally – technology builds itself from itself, growing and improving through the novel combination of existing tools – but he is clear that the process of evolution does not imply that technology is alive.

“…To say that technology creates itself does not imply it has any consciousness, or that it uses humans somehow in some sinister way for its own purposes,” he writes. “The collective of technology builds itself from itself with the agency of human inventors and developers much as a coral reef builds itself from the activities of small organisms.”

Borrowing from Humberto Maturana and Fransisco Varela, Arthur describes this process as autopoiesis, self-creating.

This is a bold claim.

To consider technology as self-creating changes our relationship with the phenomenon. It is not some disparate set of tools which occasionally benefits from the contributions of our best thinkers; it is a growing body of interconnected skills and knowledge which can be infinitely combined and recombined into increasingly complex approaches.

The idea may also be surprising. An iPhone 6 may clearly have evolved from an earlier model, which in turn may owe its heritage to previous computer technology – but what relationship does a modern cell phone have with our earliest tools of rocks and fire?

In Arthur’s reckoning, with a complete inventory of technological innovations one could fully reconstruct a technological evolutionary tree – showing just how each innovation emerged by connecting its predecessors.

This concept may seem odd, but Arthur makes a compelling case for it – outlining several examples of engineering problem solving which essentially boil down to applying existing solutions to novel problems.

Furthermore, Arthur explains that this technological innovation doesn’t occur in a vacuum – not only does it require the constant input of human agency, it grows from humanity’s continual “capturing” of physical phenomena.

“At the very start of technological time, we directly picked up and used phenomena: the heat of fire, the sharpness of flaked obsidian, the momentum of a stone in motion. All that we have achieved since comes from harnessing these and other phenomena, and combining the pieces that result,” Arthur argues.

Through this process of exploring our environment and iteratively using the tools we discover to further explore our environment, technology evolves and builds on itself.

Arthur concludes that “this account of the self-creation of technology should give us a different feeling about technology.” He explains:

“We begin to get a feeling of ancestry, of a vast body of things that give rise to things, of things that add to the collection and disappear from it. The process by which this happens is neither uniform not smooth; it shows bursts of accretion and avalanches of replacement. It continually explores into the unknown, continually uncovers novel phenomena, continually creates novelty. And it is organic: the new layers form on top of the old, and creations and replacements overlap in time. In its collective sense, technology is not nearly a catalog of individual parts. It is a metabolic chemistry, an almost limitless collective of entities that interact to produce new entities – and further needs. And we should not forget that needs drive the evolution of technology every bit as much as the possibilities for fresh combination and the unearthing of phenomena. Without the presence of unmet needs, nothing novel would appear in technology.”

In the end, I suppose we should not be surprised by the idea of technology’s evolution. It is a human-generated system; as complex and dynamic as any social system. It is vast, ever-changing, and at times unpredictable – but ultimately, at its core, technology is very human.

The ‘There’ There

Posted on March 14, 2016 by Sarah Shugars

In 1933, after visiting her hometown of Oakland, CA, Gertrude Stein remarked that “there is no there there.”

Among many in the much maligned city, accustomed to defending themselves against such abrasive attacks, the remark has often been taken as a slight: as if Oakland were such a wasteland as to be little more than a desolate limbo.

Our more privileged neighbors across the bay have certainly said worse.

But this reading misrepresents the sentiment.

Stein had moved to Paris in 1903. She returned to her hometown thirty years later to find the city developed and her childhood home destroyed.

She wrote:

…anyway what was the use of my having come from Oakland it was not natural to have come from there yes write about it if I like or anything if I like but not there, there is no there there. …but not there, there is no there there. … Ah Thirteenth Avenue was the same it was shabby and overgrown. … Not of course the house, the house the big house and the big garden and the eucalyptus trees and the rose hedge naturally were not there any longer existing, what was the use …

Stein lived in Oakland from six to seventeen. When she returned she found it was not the city she had left behind – and she was not the person who had left it.

There was no there there.

Stein writes of the loss of place as the loss of of something more – the loss of memory, the loss of identity, a meaningful loss of self.

“When you live there you know it so well that it is like an identity a thing that is so much a thing that it could not ever be any other thing,” Stein writes.

And then, one day, you return to find that this thing which you knew so well has become another thing.

You don’t recognize it; and, surprisingly, it doesn’t recognize you.

Or, perhaps worse yet, you do recognize it. You know every corner, every nuanced shade. You are intimately acquainted with the place, yet find yourself a stranger. You find that you know these details not at they are, but only as they were. Every sight becomes a haunting memory of the past. A faded ghost just beyond reach.

This is how I read Stein when she writes that there’s no there there.

Oakland as a place is really just an aside. Surely lacking in the luster of Paris, perhaps shabby and overgrown (I say with great love), but really just a place that was not the place she expected.

It was not natural – how could she have come from this place which was not her place? Where was that big house? Those Eucalyptus trees? The rose hedge and the big garden? Where was that life she had left behind?

And who was she, this strange person visiting this strange place?

The dissonance in place led to a dissonance in self.

Oh, how time goes by.

But there is a there there. Stein had become a new person, just as Oakland had become a new city. The confluence of the new can be unsettling; can be distressing; but ultimately – it is just the growth of life.

The there you remember is replaced by a new there – cherished by new generations and new children who will grow up, travel, and return home to find their there no longer there.

No there there, and yet – still there.

Initial Questions about Online Deliberation

Posted on March 3, 2016 by Sarah Shugars

While last semester I looked at gender representation in comic books by analyzing a network of superheroes, this semester I’m taking my research down a different path.

Through my Ph.D. I ultimately hope to develop quantitative methods for describing and measuring the quality of political and civic deliberation.

To that end, this semester, I’ll be looking at data from a popular political blog aimed at providing a space for political conversation. I have scraped this website’s entire corpus of nearly 30,000 posts from 2004 through the present, including posts and comments from 4,435 unique users.

From this, I plan to build a network of interactions – who comments on whose posts? Who recommends whose posts? Are there sub-communities within this larger online community?

Additionally, as I build my skill set in Natural Language Processing, I hope to do some basic text analysis on the content of posts and comments, looking for variation in word choice between communities as well as comparing the content of different types of posts – for example, are there keywords that would predict how many comments a post will get?

No doubt more questions will come up along the way, but as I dive into this data, these are some of the questions I’m thinking about.

Randomly Generated Poetry

Posted on March 2, 2016 by Sarah Shugars

I’ve had a great deal of fun today building a random sentence generator which draws on a list of words provided to me. (Possibly, it seems, from the script of Monty Python and the Holy Grail.)

The sentences produced are strangely rhythmic and at times insightful, possessed of a certain unique poetry:

every land drinks this weight.
each quest rides Guinevere.
the sun rides any servant?
any chalice rides no defeater.
a winter carries each fruit.
the swallow is any sovereign.

every swallow covers that quest!
each home covers any defeater!
the land is a king!

this land rides that home?
another master covers any master.

another horse drinks this king!
every horse drinks this castle.

another chalice rides the story.
Dingo drinks another master!
every sovereign is a swallow!
any land carries each pound!
that husk carries the master!

every land has every winter.
no master carries any pound.
this castle rides a castle!
any home has that winter.
Arthur is every defeater.

a land near no land of a corner of each home has the master for another home.

that land has no home.
each sun has Patsy.
the horse drinks each king.
this quest has no defeater.
Patsy has the castle.

a story rides the land.

that weariest story frequently is another hardest corner!

a harder sun is the harder land?

Natural Language Processing

Posted on March 1, 2016 by Sarah Shugars

I’ve been taking a great class this semester in Natural Language Processing – a computer science field which deals, as you may have guessed, with the processing of “natural” language. NLP is the foundation of technologies like spellcheck, automatic translation (a work in progress!), and Siri.

Essentially, you feed a bunch of human-generated text into a computer and it gives you something in response, with the “something” varying greatly based on what you’re trying to do.

A few weeks ago I deleted all the vowels from the Declaration of Independence.

(And then nondeterministically put them back in).

But at more sophisticated levels, you can analyze the sentiment of a text, mimic human dialogue, or generate new text in the style of a given author. Eventually, I hope to use NLP techniques to process transcripts of political and civic dialogue, but for now I’m enjoying learning the basics of the field.

The fundamentals of NLP are fascinating – in our native language, we each easily construct our own sentences and relatively easily interpret the sentiment and meaning of other’s sentences. We’re generally familiar with the basic syntax and parts of speech in our native language, but generally we don’t give these much thought as we communicate with those around us.

And, as spoken languages are living languages, in casual conversation we effortlessly change the rules and adapt to new words and styles.

One might think that teaching a computer all the rules of grammar as well as the flexibly of our unspoken rules would be quite complicated. And that’s true to some extent, but more generally the challenge of computer-interfaced language is just different.

ELIZA, one of the early successful NLP programs, is relatively simple. Programmed to respond to human-typed input as a Rogerian psychotherapist, ELIZA is based off an algorithm of pattern-matching. You say, “I am sad,” and ELIZA responds, “I’m sorry you are sad.”

On the other hand, satire and sarcasm continue to elude NLP programs…such humor is just too subtle to capture in rules, I suppose.

The rules for a given NLP program can become quite elaborate and yet, the underlying theory is relatively simple: you start at the beginning of a sentence, and then explore a set of rules with each rule given with a certain probability. When you reach an end symbol (eg, a period), you are done.

Exit, Voice, and Presidential Elections

Posted on February 29, 2016 by Sarah Shugars

In spring 2003, I was living in Japan.

That’s where I was when the Unites States invaded Iraq for “Operation Iraqi Freedom” as it was colorfully named by my government.

Throughout the months I lived abroad, I tried to keep up on the news from home; daily scouring reports from the U.S., the U.K., and Japan. The flavor of news coming out of each country was markedly different – the U.S. blindly patriotic, the U.K. supportingly reserved, Japan politely disapproving.

The details and word variation between articles told remarkably different stories, and I hoped, I suppose, that by reading multiple accounts I could somehow triangulate the truth.

The news coming out of the U.S. was particularly disturbing.

It was as though the whole nation had gone mad.

Other countries reported stories of schools being bombed by U.S. troops; my country was on some tear about Freedom Fries.

This was in the infancy of the blogosphere, so apart from the few people I kept in touch with over AOL Instant Messenger, my only sense for public opinion back home came from the sycophantic mainstream media. A media which has, in fact, somewhat reformed in recent years in response to its catastrophic failure of that time.

And perhaps this is why I’m inclined to sigh whenever someone declares that they will move to Canada, or, perhaps, the moon, should someone they strongly dislike be elected President.

I heard that a lot when President George W. Bush won reelection, and I’m hearing it a lot now.

It’s hardly a solution.

I hardly mean to imply that the Iraq War would have played out differently had I not been abroad; but it seems fairly certain that such warmongering tendencies would only be worse should all progressives decide to leave.

At the very least – I have to say – let’s not leave the nuclear launch codes behind.

In Exit, Voice, and Loyalty, Albert O. Hirschman outlines the three ways in which a person might interact with an organization, community, or state. As you may have guessed, the options are: exit, voice, and loyalty.

A person might stay loyal to an organization and support it’s views and actions; a person might exit an organization, leaving its undesirable policies in search of greener pastures; or a person might exercise voice: speaking up and fighting to make the organization the way they’d like it to be.

There are, of course, many instances throughout human history where people have been forced to exit for fear of their lives and wellbeing. One report estimates that there are nearly 60 million refugees in the world today. Theirs was not an exit taken lightly.

But the situation in the United States – while disheartening – is hardly so harsh.

I know most people are joking when they speak of plans to move away, and yet – it is a troubling sign of resignation.

We may not be the unparalleled superpower we might fancy ourselves to be, but we are still a nation which wields the potential for great harm or good.

If elections don’t go the way we like, it shouldn’t be cause to flee, but rather a call to action: our voices would be needed more than ever.

The (Re)Emergence of American Hate

Posted on February 25, 2016 by Sarah Shugars

A certain presidential candidate, known for his racist, sexist, and otherwise outlandish rhetoric has recently won his third primary.

And if it wasn’t disturbing enough that people in KKK robes showed up to support him at the Nevada primary – an action which may or may not have been a poorly executed protest – one of the country’s most notorious white supremacist leaders unofficially endorsed this candidate today saying that anything other than voting for him was ‘treason to your heritage’.

Now, I have a general policy of not giving space to hate groups – which thrive on the attention generated by their shocking acts, but this is getting too serious to ignore.

But, here’s the thing – it’s not the idea that a particularly distasteful candidate might actually become president that I find so alarming. It’s the fact that he genuinely has so much popular support.

Donald Trump is making it acceptable to be a racist again.

Of course, racism has long been alive and well in this country. It never really died the quiet death we hoped it would. Through the activism of 60s and the “colorblindness” of the 90s, we just shoved it into the closet, hoping it would never spill out again.

In 1925, the KKK had “as many as 4 million members,” a number which shrank dramatically following the civil rights movement. The Southern Poverty Law Center estimates the group at 4,000-5,000 members today.

Of course, I still think the number of members is about 4-5 thousand more than I’d hope to see in my country – but that membership become even more disturbing when you consider that there are normative social pressures likely to prevent people from expressing their believes.

That is, our country is full of closeted racists.

Racists who aren’t closeted any more.

Earlier this week, the New York Times reported that 74% of South Carolina Republican primary voters favor “temporarily barring Muslims who are not citizens from entering the United States.”

Furthermore, a recent poll by Public Policy Polling found that in addition to barring Muslims, “31% [of Trump supporters] would support a ban on homosexuals entering the United States as well, something no more than 17% of anyone else’s voters think is a good idea.”

Again, 0% would be a better figure here.

The New York Times also reports that, “Nearly 20 percent of Mr. Trump’s voters disagreed with Abraham Lincoln’s Emancipation Proclamation, which freed slaves in the Southern states during the Civil War.”

This is profoundly disturbing.

I’d almost prefer to blame this all on Donald Trump. If we can only stop him from winning the Presidency, then all our racial problems will be solved.

But here’s the thing: Trump is the symptom, not the disease.

A significant number – a significant number – of white Americans seem ready to re-don their white robes. Americans who otherwise are not entirely unlike myself.

I find that terrifying, and I’m hardly the most at risk.

It is not enough to wave our hands, to hope that the Republican establishment comes through with blocking a Trump nomination. We have to recognize that there is a growing racist sentiment – or, perhaps, a growing willingness to express that sentiment.

My greatest concern is not that Trump will be elected – it’s that even after he is eventually defeated, this profoundly, openly racist faction of Americans will continue to grow.

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