Reflecting on Service

I was very honored to receive Northeastern’s Outstanding Graduate Student Award in the area of community service. As part of that award, I was asked to write a statement of my personal philosophy regarding service. To be honest, I found the prompt challenging as I don’t really consider most of my efforts “service” in the traditional sense — I’d be more inclined towards Harry Boyte’s term of public work — nevertheless, here is what I wrote:

This world is what we make it. Our societies, our monuments, our every day encounters – these are the product of human energy and interaction. In a very real sense, we build this world; we shape it in ways both great and terrible. As individuals, we are limited and finite, but together our collective capacity spans the long arc of human civilization. With this awesome power weighing upon our collective shoulders, we are left with a seeming simple but important question:

What should we do?

The brevity of this question belies its depth; each word has an important role to play:

  • What: What are the specific actions to be taken?
  • Should: What are the right actions and what are the right criteria for determining those actions?
  • We: Literally you and I. The humans writing and reading this letter. We each have a role to play in shaping the world around us. Our voices, perspectives, and actions matter. And of course:
  • Do: It is not enough to determine the appropriate actions, we must actually take them.

I like this question because it gives agency to both individuals and the communities to which they belong. As members of a society we should neither act with blind individualism – doing whatever we want whenever we want it – nor should we completely withdraw from public life, abdicating our responsibility to add our unique ideas and perspectives to the collective challenge of tackling complicated problems.

We each have a responsibility to share our voices; to roll up our sleeves and engage in the work; but perhaps even more importantly – we have a responsibility to ensure that the voices of those around us are heard; to build spaces where everyone can participate.

This duality is important because as individuals we play different roles in different contexts. As a first-generation-to-college woman in a STEM discipline, I’ve spent much of my life being told that my voice didn’t matter, that Ididn’t matter. Yet, as a highly educated white person, I still benefit from a lot of power and privilege. All of those identities are integral to who I am, and they each come into play in different settings – sometimes I need to be loud and vocal, and sometimes I’d do better to let others speak. At the end of the day, it isn’t about me – it’s about the strength of our collective endeavors.

This essay is supposed present my personal philosophy of service. As you may have gathered by now, I have a hard time with that prompt. To me, the word “service” invokes images of parachuting in for short-term efforts – ideally under the auspices of someone from the community who actually knows what’s needed. There is nothing wrong with that type of service; it’s important work if done well. But I prefer Harry Boyte’s term “public work.” We are each members of many, overlapping communities and our collective work is needed to build and maintain those communities. It is “service” insofar as it is service to the collective good, but it is work– it is the time, energy, and thought that goes into co-creating our shared world.

My personally philosophy, then is to perpetually ask, answer, and act on the question of “what should we do?” I put my energy towards building relationships of mutual trust, I put my time towards the collective work we agree must be done, and I put my financial resources towards causes I don’t personally have the expertise to support. I do my best to be a good citizen of my many communities – to listen, learn from, and support others while they listen, learn from, and support me. I try to build spaces where everyone knows they are welcome, where conflict doesn’t fester, and everyone accepts each other’s good intentions. To engage to the best of my ability in the unglamorous, every day tasks of associated life.

John Dewey writes that we must all “learn to be human” – that we must each develop “an effective sense of being an individually distinctive member of a community; one who understands and appreciates its beliefs, desires and methods, and who contributes to a further conversion of organic powers into human resources and values.” I am continually learning to be human.  I just want to get good things doFacebooktwittergoogle_plusredditlinkedintumblrmail

Polarization, heuristics, and the 24 hour news cycle

Skeptics of the democratic ideal of self governance often point to the almost laughable impracticality of the vision. People are simply bad at being knowledgeable and making well-informed judgements.

Notably, this concern needn’t inherently be a slight. While the most elitist of skeptics will judgmentally decry the dreadful specter of “the masses” for perceived failings of willful ignorance or stupidity, some scholars offer a more nuanced view.

Consider, for example, the post-WWI writing of journalist Walter Lippmann. While his rhetorical flourishes reasonably earned him a reputation as an elitist and a technocrat, the full thread of his argument is much more subtle.

Lippmann – who had been intimately acquainted with propaganda efforts during the war – was notoriously concerned about giving too much power to “the public;” that “uninformed, sporadic mass of men” who will “arrive in the middle of the third act and will leave before the last curtain, having stayed just long enough perhaps to decide who is the hero and who the villain of the piece.”

But despite the colorful imagery, his argument wasn’t that the vast mass of men were too lazy or stupid to be entrusted with the vital task of democracy. Rather, his argument was simply that  no single person could ever have the capacity to be all-knowledgeable on all things.

There is just too much.

Reasonably lacking in the time to perfectly master all of human knowledge, every single person is left to make the best decisions they can by drawing heavily from existing knowledge, perceptions, and instincts.

Lippmann, incidentally, coined the word “stereotype” to describe the phenomenon.

As social psychologists will tell you, “stereotyping” is not inherently bad. As beings constantly bombarded by information, we literally couldn’t function if we constantly had to reconstruct our basic understanding of everyday objects and encounters. We couldn’t live without heuristics.

But, they can also become problematic if we become too rooted in our thinking, if we don’t have or take the time to periodically push past our heuristics.

Political polarization is just one example of this. It is too easy, too easy, to heuristically label people who agree with you as “good” and people who disagree with you as “bad.” A mild version of this may be helpful in some cases of electoral politics – knowing that a candidate of party X supports the political platform I generally support is arguably meaningful information. But it most certainly becomes problematic when this heuristic labeling seeps into our every day life and every day encounters.

Markus Prior argues that polarization is an outcome of an increasingly efficient media environment. When people aren’t all “accidentally” exposed to the same evening news – as they were when the evening news was literally the only thing on TV – people tend to self-select into separate, biased news spheres.

Perhaps worse, they self-select out of news consumption all together. After all, there are far more enjoyable things to watch than the constant depressing drudgery of current events.

This causes a perfect storm for polarization – most people are generally uniformed, and when they peak their head up to get a sense of what’s going on, they make quick judgements inferred from a media outlet specially curated to cater to their existing beliefs.

There’s a reasonable amount of psychological and political literature to reinforce this story, but, I think, we lose something if we forget the Lippmann view.

The problem, Lippmann would argue, is not the stereotypes themselves, it’s the thoughtless and broad application of them which results from not having enough time to do otherwise.

In other words, while the wide variety of media options may lend themselves to polarization, the constant, 24-hour avalanche of news coverage is perhaps a bigger problem. It is literally impossible to keep up, to take it all in and study every issue in a thoughtful, non-biased way.

In the absence of time for such activity, and buried in our own personal pressures of work of and life, we adapt as best we can by making quick, vaguely informed decisions motivated largely by our pre-existing beliefs.

It’s not that “the public” can’t be trusted, Lippmann would argue, it’s that we all put too much faith in our own ability to rise above such challenges. It is always “other people” who are politically foolish. We – and the people we agree with – are, of course, more enlightened.

As if anyone has the ability to keep up with all the news.


Social and Algorithmic Bias

A commonly lamented problem in machine learning is that algorithms are biased. This bias can come from different sources and be expressed in different ways, sometimes benignly and sometimes dramatically.

I don’t disagree that there is bias in these algorithms, but I’m inclined to argue that in some senses, this is a feature rather than a bug. That is: all methodical choices are biased, all data are biased, and all models are wrong, strictly speaking. The problem of bias in research is not new, and the current wave of despair is simply a reframing of this problem with automated approaches as the culprit.

To be clear, there are serious cases in which algorithmic biases have led to deeply problematic outcomes. For example, when a proprietary, black box algorithm regularly suggests stricter sentencing for black defendants and those suggestions are taken to be unbiased, informed wisdom – that is not something to be taken lightly.

But what I appreciate about the bias of algorithmic methods is the visibility of their bias; that is – it gives us a starting point for questioning, and hopefully addressing, the inherent social biases. Biases that we might otherwise be blind to, given our own personal embedding in the social context.

After all, strictly speaking, an algorithm isn’t biased; its human users are. Humans choose what information becomes recorded data and they choose which data to feed into an algorithm. Fundamentally, humans – both specific researchers and through the broader social context – chose what counts as information.

As urban planner Bent Flyvbjerg writes: Power is knowledge. Those with power not only hold the potential for censorship, but they play a critical role in determining what counts as knowledge. In his ethnographic work in rural appalachia, John Gaventa similarly argues that a society’s power dynamics become so deeply entrenched that the people embedded in that society no longer recognize these power dynamics at all. They take for granted a shared version of fact and reality which is far from the unbiased Truth we might hope for – rather it is a reality shaped by the role of power itself.

In some ways, algorithmic methods may exacerbate this problem – as algorithmic bias is applied to documents resulting from social bias – but a skepticism of automated approaches opens the door to deeper conversations about biases of all forms.

Ted Underwood argues that computational algorithms need to be fundamentally understood as tools of philosophical discourse, as “a way of reasoning.” These algorithms, even something as seemingly benign as rank-ordered search results – deeply shape what information is available and how it is perceived.

I’m inclined to agree with Underwood’s sentiment, but to expand his argument broadly to a diverse set of research methods. Good scientists question their own biases and they question the biases in their methods – whether those methods are computational or not. All methods have bias. All data are biased.

Automated methods, with their black-box aesthetic and hopefully well-documented Git pages,  may make it easier to do bad science, but for good scientists, they convincingly raise the specter of bias, implicit and explicit, in methods and data.

And those are concerns all researchers should be thinking about.



Opinion Change

While there are differing views on whether or not a person’s opinions are likely to change, there’s a general sense of “opinion change” as some clear and discrete thing: one moment I think X, and the next moment I think Y…or perhaps, more conservatively, not X.

Coming to opinion change from a deliberation background, I’m not at all convinced that this is the right framework to be thinking in.

Perhaps in a debate the goal is to move your opponent from one discrete position to another, or to convincingly argue that your discrete position is better than another. But in deliberation – which very well may include aspects of debate – the very notion of “opinion change” seems misplaced.

I think of deliberation more as process of collaborative storytelling: you don’t know the ending a priori. You create the ending, collectively and uniquely. A different group would tell a different story.

As the story unfolds, you may shift your voice and alter your contributions, but the X -> Y model of “opinion change” doesn’t seem to fit at all. 

The challenge, perhaps, is that standard conceptions of opinion change take it as a zero-sum game. One person wins and another person loses. Or no one changes their mind and the whole conversation was a waste.

But deliberation isn’t like that. It is creative and generative. It is a collective endeavor through which ideas are born, not a competitive setting with winners and losers. In deliberation, all participants leave changed from the experience. They come to think about things in new ways and have the opportunity to look at an issue from a new perspective.

They may or may not leave with the same policy position they had going in, but either way, something subtle has changed. A change that may effect their future interactions and future judgements.

Standard conceptions of “opinion change” as a toggle switch are just too narrow to capture the rich, transformative interplay of deliberation.


Adversary Democracy

There’s a long tradition in computer science, largely originating from cryptography, of designing with a generic adversary in mind.

Code should be able to handle the mistaken input of a thoughtless user and should remain robust in worse-case scenarios. The motivation for this approach is simple: programming for ideal users and ideal cases will quickly go awry in the messy world of practical applications. Programming against a malicious or incompetent adversary will make your code better.

This presents an interesting divergence from deliberative theory, where participants are arguably hoped to be as close to ideal as reasonably possible.

If people can be thoughtful, open-minded, and eager to discover the truth through debate, then deliberation can be transformative. If they enter discussion as “tolerant gladiators,” to borrow a phrase from Huckfeldt, and argue with the goal of convincing others and being convinced when it is appropriate, as Mercier and Landemore write, then we can have a rich and robust society.

Skeptics respond that this is too idealistic a vision. People are just not that virtuous and unbiased. At least, not in the numbers required for a functioning deliberative democracy.

Deliberative democrats continually rebuff this claim. Mansbridge, for example, draws a distinction between adversary democracy and unitary democracy. Adversary democrats not only have hesitancies about the capacities of humankind, but more fundamentally, they believe political life can only exist as a zero-sum game.

In every community decision, in every group interaction, someone wins and someone loses. With this epistemic frame, any shortcomings of humanity are actually besides the point: the best you can do is try to make the distribution of wins and loses as just as possible.

Mansbridge and others strongly argue against this framing. Political life – associated living – is not zero-sum. By engaging in deliberation, by reasoning together, people can collectively build new approaches and solutions which remain out of reach in the adversarial paradigm.

It is not about winning or losing; it is not even about compromise. Deliberation transforms the values and beliefs of participants and gives them space to co-create their worlds together.

I believe whole heartedly in this vision. Politics isn’t zero-sum – or at least doesn’t have to be – and deliberation can serve as a powerful vehicle for collective leadership.

But I am left wondering – do adversarial models have no place at all?

This seems somewhat unlikely, given the current inundation of adversarial political relationships. Yet, the prevailing wisdom among deliberative democrats is that current democratic failings result primarily are primarily epistemic in nature – that if we collectively shift how we think about politics we can build the unitary systems Mansbridge describes.

It seems, though, that the computer science model might have some value here. Imagine an adversary who is wholly uninterested in dialogue. Engaging them in deliberation is more challenging than overcoming their biases or social power, rather they actively engage in trying to make deliberation fail.

There are a lot of great frameworks for deliberation, there’s a lot you can accomplish with structure and moderators.

But if someone is deadset on being adversarial – if they actively don’t want to participate and threaten the wellbeing of other participants – I don’t see how deliberation can survive.

That’s not necessarily fatal to deliberation, though – I still believe strongly in the critical role this work has to play in our democracy, and I would still fancy myself a deliberative democrat who sees this approach as the cornerstone for a healthy democracy.

But sometimes you have adversaries who don’t want to play by the rules. Who don’t want to co-create or reason with others. They just want to destroy.

And for that you need a whole other approach of advocacy, protest, and resistance.


Is Dialogue Enough?

There’s a certain narrative about deliberative democrats which paints them as hopeless idealists.

John Dewey is perhaps the quintessential example of this – he writes passionately about the “great community,” and was steadfast in his belief that humanity could and would achieve this sublime state. While broadly agreeing with critics such as Lippmann as to the modern problems of civil society, the optimism of Dewey’s solutions is notably divergent.

The problem, he argued, was not that average people did not have the capacity to properly govern themselves, but rather that civic infrastructure did not fully allow them to exercise this capacity. Given robust civic education and institutions which genuinely encourage and incorporate citizen participation, humanity could achieve great things. In short, we have the capacity to self govern, we simply need to trust ourselves.

This optimism is echoed in the works of Habermas, who writes prolifically about the power of ideal dialogue to build ideal societies. He envisions salons and coffeehouses where citizens engage in passionate debates about what is right and just. “Moral argumentation,” he writes in Moral Consciousness and Communicative Action, “serves to settle conflicts of action by consensual means.”

In short, citizens engaging in meaningful debate about moral issues will eventually come to agree on what is right. The solution which emerges from such a process is intrinsically moral thanks to the collaborative filtering of discussants and it is bolstered by the rich process of debate which led to the consensus.

The enthusiastic visions of Dewey, Habermas, and other pragmatists may be inspiring, but they rightfully earn a lot of skepticism. Is such ideal dialogue even possible? Perhaps our moral divisions are ultimately intractable.

Most troubling to me are the concerns raised by Sanders, Frasier, and others. These visions of the Great Society, and the roadmap for how we get there do not give proper care to the role of power.

In an imperialist white supremacist capitalist patriarchy – to borrow a phrase from bell hooks – it is not enough to encourage people to enter deliberation with an open mind. It is not enough to teach core civic values. The structural inequality of society will pervert deliberation amongst even well-meaning participants.

I am particularly fond of this critique from Sanders: “If we assume that deliberation cannot proceed without the realization of mutual respect, and deliberation appears to be proceeding, we may even mistakenly decide that conditions of mutual respect have been achieved by deliberators.”

Such false deliberation – which leaves those in power with a claim to moral consensus when none was achieved – is arguably even worse than a state with no deliberation and no appearance of legitimacy.

Fraser builds off Habermas, arguing that these rich conversations don’t happen merely in a single, mainstream public sphere. Rather, the public sphere as we encounter it is deeply restrictive – despite claims to the contrary, not everyone gets a voice. Thus, we also have counter-publics – smaller communities where those who are blocked from the mainstream can engage safely and fully in the sort of discussions Habermas envisions. The counter-publics can and do influence the mainstream, but they are constantly pushed to the fringes by a society which doesn’t want them.

These critiques of deliberation also point to a deeper challenge: dialogue only works when all parties are willing to enter and participate in good faith.

You can’t engage in dialogue with someone who wants to destroy you.

This concern is never satisfactorily addressed by Dewey or by Habermas. They both engage deeply with questions of manipulation, force, and instrumental action, but they seem content to believe that such problems can be dealt with effectively and are not too deeply interwoven into our social fabric.

A skeptic would argue that these concerns point to a sizable gap in their philosophy – if dialogue only works in ideal conditions, then dialogue necessarily cannot be enough.

In the face of racist, anti-semitic, and other harshly vitriolic rhetoric, other tactics are necessary. Dialogue could never be enough.

I imagine Dewey wouldn’t give up on his Great Community so easily, though. Perhaps he under appreciated the danger of hate groups, but he would have believed in humanity’s ability to navigate these waters. He would have believed that even the worst among us could learn to participate thoughtfully in productive dialogue.

Dewey’s vision seems impossibly far off these days. Few, if any of use, seem prepared to be citizens capable of constructing the Great Community. There are good reasons by skeptical of his claims.

But I’m not ready to give up on dialogue just yet, and here I think is where a network perspective can be valuable. As long as we have connections between all elements of our communities, dialogue may be possible. Perhaps every person cannot – and should not, for their own self-care – engage in dialogue with every other person. But if allies serve as the bridges, if those positioned to do have the difficult conversations with the hate-filled fringe, if we truly believe that no one is born to hate, perhaps then we could build the Great Community and, inch by inch, bend the moral arc of the universe towards justice.


On Hate and Love

It has been a difficult few days. Following the violent white supremacist rally which took place this weekend, I am angry, heartbroken, ashamed, unsurprised, and resolutely full of an overwhelming sense of love.

There is too much hate in this world; I choose love.

To be clear, love is not a passive emotion. It is not a empty gesture intended to claim allyship. As Dr. King teaches us, love is not “emotional bosh.” Rather “a strong, demanding love…is ultimately the only answer to mankind’s problems.”

In the face of a world that knows such terrible hate, love is a defiant act. It is a way of living, being, and interacting. Love is a way of fighting. Love, as Dr. King says, is how we “implementing the demands of justice.”

I choose love.

Elie Wiesel, too, spoke to the transformative power of love when, nearly 20 years after Dr. King, he noted that “the opposite of love is not hate, it’s indifference.”

Indifference is a passive act. It is the quiet comfort of moderates who enable the deep injustices of the status quo with their silence and complicity while patting themselves on the back for staying beyond the messy fray. Indifference is to cede your power, to abdicate your responsibly, to accept things as they are with a half-hearted shrug, but what could I do?

Indifference is to give up on love.

If we’re being honest with ourselves, the hateful acts our country saw this weekend could have happened in any American city. Our problems are not restricted to a single party, a single region, or a single demographic. The blistering hate we saw on display was merely the articulation of a wound we have collectively let fester far too long.

All of us who benefit in some way under the current status quo bear responsibility for these atrocities. We may hate the perpetrators and everything they stand for, but we haven’t done enough to respond. We’ve chosen for too long the smooth path of indifference.

It is time to choose love.

It is not an easy road. A passionate dedication to the type of love Dr. King espoused requires strength, courage, and heartbreak. There’s a reason civil rights educator and activist Myles Horton titled his autobiography The Long Haul.

There is so much work to be done, and on dark days like to today, the entire task can feel hopeless. Love may be right, but it is far easier to settle in to indifference.

When confronted with hopeless tasks, I like to remember Camus’ inspired description of Sisyphus, the Greek man mythically condemned to “ceaselessly rolling a rock to the top of a mountain” for all eternity.

It is the quintessential futile task. His work will never be accomplished. Yet despite the dreadfulness of his fate, Camus describes Sisyphus as proud and unbroken; despite it all, he is impuissant et révolté (powerless and rebellious).

That is how I feel on days like today. There is so much to do, and so little I can hope to accomplish. I am utterly powerless, an insignificant piece in the larger social machine. There is nothing for me but the thankless strain of rolling a boulder, or the foolish optimism of tilting at windmills. The task we face is just too great.

Yet, despite this powerlessness, despite my own petty insignificance, I remain steadfastly rebellious. I remain committed to love.

And I will send that love into the world with everything I’ve got. I will speak out against hate, and I will love passionately, radically, and unapologetically. I will not be broken by the enormity of the task. Hate is too great a burden to bear; indifference too superficial a comfort. Amidst the pain, the hate, and the fear, the greatest thing I can do is this:

I choose love.


Facts/Values/Strategies Conference

I will offline tomorrow, attending the Facts/Values/Strategies mini-conference co-hosted by Tufts’ University’s Tisch College of Civic Life and The Good Society, the journal of civic studies for which I serve as an editor.

In preparation for this conference, I’ve been reading the conference papers – which each seek to integrate facts, values, and strategies in conceiving of citizen’s roles in civil society. The papers have been engaging and inspiring, and I’m looking forward to a day and a half of dialogue digging into these topics.

The framing statement for the conference is below:
Current global crises of democracy raise fundamental questions about how citizens can be responsible and effective actors, whether they are combating racism in the United States, protecting human rights in the Middle East, or addressing climate change. If “citizens” are people who strive to leave their communities greater and more beautiful (as in the Athenian citizen’s oath), then their thinking must combine facts, values, and strategies, because all three must influence any wise decision. Mainstream scholarship distinguishes facts, values, and strategies, assigning them to different branches of the academy. Many critics have noted the philosophical shortcomings of the fact/value distinction, but citizens need accounts of how facts, values, and strategies can be recombined, both in theory and in practice. John Dewey, Hannah Arendt, Mahatma Gandhi, Jürgen Habermas, Amartya Sen—and many other theorists of citizenship—have offered such accounts.

Actual civic movements also combine facts, values, and strategies in distinctive ways. For instance, the American Civil Rights Movement used the language of prophesy, and Second Wave Feminism strategically advocated new ways of knowing.

These papers propose theoretical, methodological, historical, and empirical responses and case-studies related to the question: how should citizens put facts, values, and strategies together?


Re-Learning to be Human

I’m returning from a two-week blogging hiatus – the first of several I will be taking over the summer months.

This break was prompted by the madness of finals week: when my blogging devolves into posting snippets of homework assignments, it feels appropriate to take some time off. And then  I decided to take the following week off as well. I was, I decided, in the most general sense of the term, on vacation.

I wasn’t lying on a beach somewhere or taking in the tourist sites, but rather I was staring at the wall, staring at my desk, catching up with people, completing miscellaneous errands, and fundamentally trying to remember how I normally live my life.

Most probably due my emersion in deliberative literature, the phrase that most came to mind this past week was Dewey’s expression, learning to be human.

“To learn to be human,” Dewey writes, “is to develop through the give-and-take of communication an effective sense of being an individually distinctive member of a community; one who understands and appreciates its beliefs, desires and methods, and who contributes to a further conversion of organic powers into human resources and values.”

Like much of Dewey’s writing, the expression comes dangerously close to an impossibly lofty, grandiose vision.

On its face, it seems almost absurdly metaphorical – are humans not born human? In what sense, then, might a human learn to be human?

Dewey argues that what we call “human” is much more than a collection of biological traits. Rather, being human, in it’s most fundamental sense, is essentially a social construct: “everything which is distinctively human is learned.”

Yes, we must indeed “learn to be human.”

And if this sounds absurd, I recommend reflecting on the expression the next time you emerge from an intensely focused cocoon. When you can’t remember what time you normally get up or what you’re supposed to do when you feel hungry. When you have this vague sense that you used to have friends, but you haven’t actually spoken to any of them in weeks. When you’re trying to remember your priorities in life, or maybe just trying to remember how to determine your priorities. When you have no real sense of what’s going on around you, just the unmistakable sense that things have been going on.

When you realize you’ve cordoned yourself so far off from society that you actually need to reintegrate before you can meaningfully engage –

That’s when you’re learning – or relearning, perhaps – what it means to be human.

And as Dewey argues, this isn’t something we can do by ourselves; one does not learn to be human alone. Rather, learning to be human is a fundamentally social endeavor, an ongoing process through which we each learn how to act and interact. It is the every day work of learning and growing; of becoming who we are.


Computational Models of Cultural Systems

Computational approaches to studying the broader social context can be found in work on the emergence and diffusion of communities in cultural system. Spicer makes an anthropological appeal for the study of such systems, arguing that cultural change can only be properly considered in relation to more stable elements of culture. These persistent cultural elements, he argues, can best be understood as ‘identity systems,’ in which individuals bestow meaning to symbols. Spicer notes that there are collective identity systems (i.e., culture) as well as individual systems, and chooses to focus his attention on the former. Spicer talks about these systems in implicitly network terms: identity systems capture “relationships between human beings and their cultural products” (Spicer, 1971). To the extent that individuals share the same relationships with the same cultural products, they are united under a common culture; they are, as Spicer says, “a people.”

Axelrod presents a more robust mathematical model for studying these cultural systems. Similar to Schelling’s dynamic models of segregation, Axelrod imagines individuals interacting through processes of social influence and social selection (Axelrod, 1997). Agents are described with n-length vectors, with each element initialized to a value between 0 and m. The elements of the vector represent cultural dimensions (features), and the value of each element represents an individual’s state along that dimension (traits). Two individuals with the exact same vector are said to share a culture, while, in general, agents are considered culturally similar to the extent to which they hold the same trait for the same feature. Agents on a grid are then allowed to interact: two neighboring agents are selected at random. With a probability equal to their cultural similarity, the agents interact. An interaction consists of selecting a random feature on which the agents differ (if there is one), and updating one agent’s trait on this feature to its neighbor’s trait on that feature. This simple model captures both the process of choice homophily, as agents are more likely to interact with similar agents, and the process of social influence, as interacting agents become more similar over time. Perhaps the most surprising finding of Axelrod’s approach is just how complex this cultural system turns out to be. Despite the model’s simple rules, he finds that it is difficult to predict the ultimate number of stable cultural regions based on the system’s n and m parameters.

This concept of modeling cultural convergence through simple social processes has maintained a foothold in the literature and has been slowly gaining more widespread attention. Bednar and Page take a game theoretic approach, imagining agents who must play multiple cognitively taxing games simultaneously. Their finding that in these scenarios “culturally distinct behavior is likely and in many cases unavoidable” (Bednar & Page, 2007) is notable because classic game-theoretic models fail to explain the emergence of culture at all: rather rational agents simply maximize their utility and move on. In their simultaneous game scenarios, however, cognitively limited agents adopt the strategies that can best be applied across the tasks they face. Cultures, then, emerge as “agents evolve behaviors in strategic environments.” This finding underscores Granovetter’s argument of embeddedness (M. Granovetter, 1985): distinctive cultures emerge because regional contexts influence adaptive choices, which in turn influence an agent’s environment.

Moving beyond Axelrod’s grid implementation, Flache and Macy (Flache & Macy, 2011) consider agent interaction on the small world network proposed by Watts and Strogatz (Watts & Strogatz, 1998). This model randomly rewires a grid with select long-distance ties. Following Granovetter’s strength of weak ties theory (M. S. Granovetter, 1973), the rewired edges in the Watts-Strogatz model should bridge clusters and promote cultural diffusion. Flache and Macy also introduce the notion of the valiance of interaction, considering social influence along dimensions of assimilation and differentiation, and taking social selection to consist of either attraction or xenophobia. In systems with only positively-valenced interaction (assimilation and attraction), they find that the ‘weak’ ties have the expected result: cultural signals diffuse and the system tends towards cultural integration. However, introduction of negatively valenced interactions (differentiation and xenophobia), leads to cultural polarization; resulting in deep disagreement between communities which themselves have high internal consensus.