Why Storm Troopers Can’t Shoot

Posted on May 2, 2016 by Sarah Shugars

It’s a well-known fact that imperial storm troopers have terrible aim.

While their failure logistically supports the plot of Star Wars – they would be dramatically different stories if all our heroes just died – there are numerous fan theories on the subject. Perhaps the helmets provide poor visibility (possibly due to cut backs after the Empire took over). Perhaps the troopers were ordered not to hit our heroes – after all, we know they were allowed to escape the Death Star in a trap to reveal the rebel base. Another theory argues that storm troopers miss for the same reason that real, well-trained, combat soldiers do – when it’s a human person standing in front of you, it’s just not that easy to shoot.

But, as I was thinking about it this weekend – as you’re wont on the first day off after a long semester – what if storm troopers have intentionally bad aim? Not that they were ordered to miss or are otherwise consciously choosing to miss – but what if the storm trooper clones are intentionally designed to be poor shots?

Let’s back up a bit.

Before they were the imperial storm troopers of the Galactic Empire, these soldiers were the clone army of the dying Galactic Republic. Replicated from the DNA of legendary bounty hunter Jango Fett, we know – if you’re willing to sit through the prequels – that the clones were genetically modified to reach adulthood faster and to be more subservient and loyal than they would have been otherwise.

In the animated Clone Wars series it is striking just how inhuman the clones are considered. They aren’t treated as people, with independent personalities and intrinsic worth. They are treated as cannon fodder; necessary man power needed to crush the separatists seeking to break from the Republic, but little more human than the droid army they oppose.

This is, in fact, the real the beauty, if you will, of the clone army – unlike ‘real’ lifeforms, they are entirely disposable.

And if you’re building a disposable army, do you want to empower them to overthrow you?

Given the clear power imbalance and injustice faced by the clones, it seems unwise to make them too capable. Far safer it would be to encase them in tough, Mandalorian inspired armor, and send them out as meat shields to take the shots which might otherwise hit a more valued person. In this way, you could breed an army capable of meeting your needs, with little risk of servants’ uprising.

And exactly what needs are the clones fulfilling?

Well, that depends on who you ask, I suppose. The Republic embraced the clones as a ready-made army, conveniently on hand just as numerous worlds declared their independence and plunged the Republic into war. The Republic needed bodies – they needed weapons they could send to fight droid armies, and they needed soldiers whose deaths wouldn’t cause the war fatigue typically associated with such loss. In the Jedi they had powerful generals and leaders, capable of remarkable feats. What they needed was an infantry for these skilled warriors to lead – a disposable army that could counter the opposing disposable army, while the leaders faced off in proper combat.

But, of course, the Jedi aren’t the ones who ordered the creation of the clone army. While the order supposedly came from Jedi Master Sifo-Dyas, given that his death preceded that order, presumably the clone army was the vision of some Sith Lord, whether that be Darth Sidious or the mysterious Supreme Leader Snoke we met in Episode 7.

Breeding clones to be less formidable warriors fits neatly into the Empire’s plans. The clones are durable but generally harmless soldiers. A Jedi would never see a (successful) attack from them coming.

Interestingly, the infamous Order 66 which ultimately caused the clones to turn on their Jedi masters was revealed in Clone Wars to be programmed into their DNA. This makes them the perfect Trojan horse – literally unable to hit things until a genetic order takes control. Once the Jedi are virtually eliminated, the order is lifted and the clones go back to being unable to aim – as we meet them in Episode 4.

Following the fall of the Republic, the Empire began replacing clones with conscripted soldiers, forcing them to undergo rigorous training from an early age. While this may be an indication of the high cost of clone soldiers, it may also be an indication of the inadequacy of the original clones. The Empire, though, may have still have aimed to develop sub-optimal storm troopers through their training program. The Empire, I’m sure, would have no qualms in poorly training a disposable army – and they would certainly be cautious about giving such underlings too much training and power.

A Spring Ditty

Posted on April 26, 2016 by Sarah Shugars

It’s pouring rain,
You’re watering your lawn.
Good thing
We’re not in
a drought.

Learning

Posted on April 19, 2016 by Sarah Shugars

I wonder if the process of learning is like…sediment on a shore.

That doesn’t sound very glamorous, but it feels appropriate somehow. A wave comes in, carrying all sorts of knowledge – far more than one person could possibly manage. It’s a little overwhelming. You might lose your footing. Or recklessly risk being swept out to sea.

It’s exhilarating.

And then the wave recedes, eclectic flotsam left in its wake.

You gather up what bits you can; painfully little compared to the vast sea before you. And you wait for the next wave to come in; awash with possibilities.

A good class is like a good book: once you finish it, you want to read it again; to rediscover its mysteries anew.

Fitness Landscapes and Probability Distributions

Posted on April 15, 2016 by Sarah Shugars

Imagine trying to solve a problem of unknown complexity. You have to start somewhere, so you try a solution more or less at random. If you’re lucky, you know enough about the situation to start with an educated guess.

Regardless of how successful – or unsuccessful – your attempt was, you learn something about the best way to tackle the problem.

Next time you do a little bit better.

Perhaps there are other people around you trying to solve the same or similar problems. You can learn from their efforts as well.

Eventually you converge on what seems like the best possible solution, and then, problem solved, you keep deploying the same solution.

In several disciplines, this process can be described as exploring a fitness landscape. There are optimal solutions, really bad solutions, and everything in-between. Some combination of a priori knowledge and learned exploration gives you an intuition of what the fitness looks like.

Imagine the quick calculations you do in your head when trying to figure out how long it will take you to get somewhere. If you’ve gone there before, you might have a sense of the average length of travel. If you’re familiar with an areas traffic patterns you might have a sense of how much traffic to expect, or what routes to avoid. You may also have a sense of whether it would be more socially proper to arrive a little bit late or a little bit early.

You almost effortlessly predict an optimal solution to a complex problem.

There’s a great deal of interesting research being done to understand how individuals and groups explore or exploit these complex landscapes. As a matter of simplicity in an already challenging problem, it is common to study problems for which an optimal solution is universally an optimal solution.

That is – if every person had perfect knowledge of the fitness landscape, they would each make the same normative judgements about what solutions are “good.”

For my own research interests, this is an important piece of the challenge. One’s definition of “good” or “optimal” is a crucial piece of what policy solutions one might seek – or, more generally, how one might interpret the “fitness landscape.”

If two or more people are exploring the same landscape but have different normative judgements as to what is optimal, this poses a huge challenge.

One solution to this challenge is to hope for the convergence of opinion – so a group may not start with normative agreement on the fitness landscape, but with good deliberation they will come to collective agreement eventually.

There’s a great deal of social science research looking at how consensus forms in groups, with an eye towards possible biases and poorly-formed consensus. Does a group agree with the loudest voice in the room? Does it converge on whatever idea was most popular before discussion began? Did it give full attention and weight to all possible alternative before a final decision was reached?

Yet, on top of all the things that could go wrong in consensus forming, one of the most disconcerting thoughts is that such ideal consensus is not possible at all.

Examining such a question means understanding just what causes a person’s opinion to form in they first place – an understanding, I’m afraid, we are quite far from.

Some opinions may be formed on the spot, with no clear reason why. Other opinions may have cemented through some past series of experiences.

But here’s a thought experiment – imagine dozens of clones of the same person, each starting their life in an identical setting. With every event they encounter – on whatever time scale you prefer – the effect of that experience on them is given by some probability distribution.

If one were so inclined, you could build your favorite sense of nature vs. nurture into this probability distribution.

After some series of n events, the people produced…would be different?

If that were to be the case – even among a starting group with all the same initial conditions, it would pose a significant challenge to the idea of consensus, and ultimately would require some method to make sense of overlapping conceptions of a similar fitness landscape.

Jessica Jones and the Banality of Evil

Posted on March 21, 2016 by Sarah Shugars

Most of the characters in Marvel’s Netflix show Jessica Jones are not very Good – in the deeper, capital-G sense of the word.

They’re not very good people.

Some are certainly worse than others, and some are even moderately good, but few, if any, stand out as paragons of virtue. Indeed, the main villain of the story – Zebediah Killgrave, who uses his powers of mind-control to manipulate people for his violent and disturbing ends – is hardly the tale’s only bad guy.

He is simply the most powerful.

Early on in the season, Jones’ friend Trish Walker laments Kilgrave’s egoism: Men and power, it’s seriously a disease.

Kilgrave is dangerous not because he’s a depraved, disturbed individual – but rather it is his power which makes him dangerous. Another man with the same power might be just as villainous, and Kilgrave without his powers would be just another unremarkable man.

Indeed, over the course of the season we see this transformation to power take place in Officer Will Simpson, who spirals out of control as he becomes increasing reliant on a drug that boosts his adrenaline.

It’s not just the drug that makes Simpson a menace: his personality had always veered towards anger and violence. Rather the addition of a superhuman ability transforms him from unremarkably disagreeable to near-supervillian status.

Yes, all women, the whole season seems to scream.

In many way, these themes remind me of Hannah Arendt’s famous reflections on the “banality of evil,” from Eichmann in Jerusalem.

While in no way defending Eichmann – who was clearly immoral and depraved – in the end, Arendt finds him wholly unremarkable – a bureaucratic man whose terrible acts were driven by his own uncaring quest for power. In the setting of Nazi German, Eichmann unleashed great evil – but without the power of his position and context, he would have been just another, unremarkable, power-hungry man.

As Arendt writes:

In the face of death he had found the cliché used in funeral oratory. Under the gallows his memory played him the last trick he was “elated” and he forgot that this was his own funeral. It was as though in those last minutes he was summing up the lesson that this long course in human wickedness had taught us – the lesson of the fearsome word-and-thought-defying banality of evil.

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.

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?

Hard Work and/or Intelligence

Posted on February 22, 2016 by Sarah Shugars

In early 2015, a team of researchers released intriguing findings from their study on gender distributions across academic disciplines.

They were curious why there is so much variation in gender representation across academia – disparity which is far from restricted to the STEM disciplines.

Women make up “approximately half of all Ph.D.’s in molecular biology and neuroscience in the United States, but fewer than 20% of all Ph.D.’s in physics and computer science.” Furthermore, women earn more than 70% of all Ph.D.’s in art history and psychology, but fewer than 35% of all Ph.D.’s in economics and philosophy.

So the problem is not simply one of raw representation.

Trying to get at the root causes of these variations, the team surveyed faculty, postdoctoral fellows, and graduate students from 30 disciplines across the United States – asking what qualities it takes to succeed in the respondents field.

Ultimately, they found that “women are underrepresented in fields whose practitioners believe that raw, innate talent is the main requirement for success.”

There is, of course, no reason to believe that women have, on average, less raw talent then men – but rather that women fail to advance in fields where raw talent – rather than hard work – is seen as a key factor for success.

It’s beyond the scope of this study to explain why the “extent to which practitioners of a discipline believe that success depends on sheer brilliance is a strong predictor” of gender representation. Though they do offer a few potential explanations:

The practitioners of disciplines that emphasize raw aptitude may doubt that women possess this sort of aptitude and may therefore exhibit biases against them. The emphasis on raw aptitude may activate the negative stereotypes in women’s own minds, making them vulnerable to stereotype threat. If women internalize the stereotypes, they may also decide that these fields are not for them. As a result of these processes, women may be less represented in “brilliance-required” fields.

In some ways, these explanations evoke the so-called “confidence gap” – the idea that women are more likely to attribute their success to good fortune or especially hard work; not to real achievement.

As the authors of The Confidence Code write, “Compared with men, women don’t consider themselves as ready for promotions, they predict they’ll do worse on tests, and they generally underestimate their abilities.”

Perhaps women shy away from these “brilliance-required” disciplines because – regardless of their actual talent – they simply don’t have the confidence required to pursue them.

….Or maybe they get pushed out by overbearing, patriarchal peers.

It’s hard to say. But I’ve been thinking about this 2014 study recently because I’ve found – as a first year Ph.D. student – that I am now constantly attributing my classroom success to hard work.

I’d hardly say that I’m brilliant, but I can work hard and figure stuff out along the way. I’d generally be inclined to attribute that sentiment to my working class background, but it’s interesting to think there may be a gender component there as well.

This all comes, of course, with an important word of caution: Too often, the solution to the confidence gap is seen as somehow “fixing” women – getting them to have the same high levels of confidence as the most self-aggrandizing of their male peers.

This is hardly a solution.

So let me be clear: it is not women who are broken, it’s the academy.

Learning Styles and Physics (or: Embracing Uncertainty)

Posted on February 11, 2016 by Sarah Shugars

Being back in the classroom as a student has given me lots of opportunities to reflect on different learning styles. Or, perhaps, more accurately, on my own learning style.

I tend to give my undergraduate field of physics a lot of credit in developing my academic style – though, I suppose, it’s equally possible that this happened the other way around: that my initial learning style attracted me to physics in the first place.

But, regardless of the order of these items, I find that I am deeply comfortable with a high level of uncertainty in my learning process.

You can see, perhaps, why I think I may have gotten that from physics. Physics is complex, and messy, and, of course, deeply uncertain.

Most importantly, this uncertainty isn’t a mark of incompleteness or failure. Rather, the uncertainty is an inherent, integral part of the system. There is no Truth, only collections of probabilities.

It’s a feature, not a bug.

I’ve noticed myself frequently taking this approach while learning. I’m taking a fantastic Computer Science class right now for which I would be tempted to flippantly say that I have no idea what is going on.

Like Schrödinger’s cat, that statement is both true an untrue. Until observed directly, it is caught miraculously, simultaneously, equally, in both states.

I have no idea what is going on, but I’m totally keeping up.

And I don’t think it’s simply a matter of confidence – my inability to articulate at which extreme I lie isn’t just a problem of trusting my own talent in this area. While, of course, it’s impossible to fully disambiguate the two, it honestly feels most accurate to embrace both states: I have no idea what is going on, but I am totally keeping up.

While I have only a passing familiarity with the works of pedagogical theory, I don’t recall ever hearing anyone describe education in this way. (Please send me your resources if you have!).

I used to think of learning as an incremental, deliberate process – like climbing a latter or building a staircase. Each step of knowledge brought you a little closer to understanding.

Perhaps this is just the difference of being in a Ph.D. program, but I’ve come to rather think of learning as this:

Knowledge is a hazy, uncertain cloud. The process of learning isn’t simply building “towards” something, but rather it’s the process of coalescing and clarifying that cloud. It’s about feeling around for the edges; finding the shapes and patterns hidden within.

Someone told me recently that physics can learn anything. I don’t know if that’s true, but I do think that there’s something to accepting this state of uncertainty. To be comfortable being lost in foggy haze that you can neither articulate nor truly understand…but to stand in that cloud and find the patience to slowly, incrementally, find meaning in the noise –

Like bring a picture into focus.

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