Algorithmic Culture: Communication Theory + AI
INTRODUCTION
Ubiquitous in the contemporary world, AI algorithms power many of the technological tools that we use in daily life: they operate in the image processing and filtering functions of our cameras, in the newsfeed prioritization organizing our social media feeds, in search engine rankings, as well as text recommendation, cataloguing, data tracking, data analysis, and navigation systems, to name just a few of the many commonplace applications of AI.
Algorithmic Culture, the project I undertook as an AI Teaching Fellow, involved the development of a series of course modules addressing the how, when, and where of our everyday encounters with AI, the ways in which AI shapes social and cultural experiences and expressions, and the economic, political and environmental impacts of widespread digital communication.
Chief among others, the questions guiding the study concerned how culture changes when AI takes over the sorting and classifying activities heretofore the province of human beings, and what social and political functions an algorithmic culture serves. How do digital technologies affect our ways of seeing and knowing? 听How does our involvement in online worlds inform real-life situations? How is identity understood in the algorithmic age? How is the 鈥榮elf鈥 imagined and how is the social formed in the context of social networking? What are the environmental impacts of algorithmic culture? What are its biases? Can AI be used to foster a more sustainable environment and just society?
These course modules were designed to be integrated into a Communication Theory course, set to launch in the Fall of 2021. The materials presented here map the first two sections of a three-part course, and provide a description for the third. A work-in-progress, the current portfolio includes summaries of the topics to be discussed, as well as related reading/media materials for both students and teachers, and outlines for in-class exercises and assignments. The media presentations for individual lectures will be introduced as the course unfolds, added to the blog prepared for the class:
Part theoretical, part practical, Communication Theory (530-315) introduces students to the study of communication practices through a review of major communication theories and the conception, development and execution of a collaborative, media-based research-creation project. As defined, the course addresses the impact of AI on contemporary life as one of a number of other concerns related to changing models of communication, but the AI content will be expanded substantially for the Fall 2021 iteration.
Communication Theory (+AI) is organized as three integrated modules, each of which will introduce the student to major communication theories as they relate to algorithmic culture. The learning activities will involve readings/viewings, discussion, low-stakes writing exercises (reading responses, journal reflections, media analyses, etc.), and a series of assignments and research activities, scaffolded to culminate at the term鈥檚 end with the presentation of a collaborative media-based research-creation work. Each module will conclude with an activity (debate, discussion, presentation) that will allow students to engage the terminology and insight they鈥檝e gained from the material reviewed.
- COMMUNICATION THEORY DESCRIPTION
- RESEARCH CREATION PROJECT DESCRIPTION
- RESEARCH CREATION PROJECT TOPICS
The introductory section of the course looks at the landscape of digital communications with a view to understand how new digital tools shape contemporary cultural life. We鈥檒l start by familiarizing ourselves with the terminology and concepts defining the digital age: cloud computing, big data analytics, the Internet of Things (IoT), AI and algorithms, and discuss the role the digital plays in contemporary cultural expression. We鈥檒l also assess whether or not and how these technologies and processes advance or restrict cultural exchange and social participation.
To discern how culture might be understood, produced and experienced differently in the computational age, we will explore changes in our understanding of culture over time.
Additionally, we will review thinking about popular culture in political and economic terms 鈥 the different inflections of 鈥減opular鈥 or 鈥渕ass culture鈥 and 鈥渢he culture industry鈥 – and examine discourses on the political function of the popular. Does algorithmic culture require a rethinking of previous models of cultural participation that understood popular culture as a field for political exchange?
The concluding activity will involve a debate/discussion about 鈥榯he smartness mandate鈥 – focusing, in particular, on smart cities, smart homes, and smart phones. Students will be asked to consider the advantages and disadvantages of smart technologies weighing claims of efficiency and security against concerns for social welfare, equality, justice and privacy.
COMMUNICATION THEORIES:
Cultural Studies: E.M. Griffin 鈥淐ultural Studies of Stuart Hall,鈥 A First Look at Communications Theory, 8th ed. McGraw Hill, 2012 (pages 344 – 354)
The Culture Industry and the Frankfurt School: Nato Thompson 鈥淐ultural Studies Makes a World,鈥 Seeing Power: Art and Activism in the Age of Cultural Production, Melville House, 2015 (pages 3 – 21)
include computer or micro-controllers.听stores and processes information in data centres.听provides tools to analyze and make use of accumulated data.听(IoT) connects sensor-equipped devices to electronic communication networks. is a software capable of recognizing patterns. are rules to be followed in problem solving operations, especially by a computer.
In his book The Next Internet, Communications Professor Vincent Mosco argues that the first three components of contemporary communication 鈥渃omprise an increasingly integrated system that is accelerating the decline of a democratic, decentralized, and open-source Internet.鈥 As he suggests, although it 鈥渃an be a tool to expand democracy, empower people, provide for more of life鈥檚 necessities and advance social equality鈥 it is now primarily used to enlarge the commodification and militarization of the world.鈥
Discussion Prompt: The accompanying presentation will sketch the different ways in which the internet has been said to advance and limit social equality. 听Students will be asked to inventory the concrete ways in which they participate in 鈥榯he next internet鈥 and discuss whether it best serves their purposes, those of other agents, or if it has equal advantages for the Internet explorer and the data collector.
- Vincent Mosco, “The Next Internet” (1-14)
- Vincent Mosco,
al路go路rithm. /藞al伞蓹藢riT蜔H蓹m/
noun
- a process or set of rules to be followed in calculations or other problem-solving operations, especially by a computer. 鈥渁 basic听algorithm for诲颈惫颈蝉颈辞苍鈥.
Oxford Online
In the case of [the word] algorithm,听the technical specialists, the social scientists, and the broader public are using the word in different ways. For software engineers, algorithms are often quite simple things; for the broader public they are seen as something unattainably complex. For social scientists, algorithm lures us away from the technical meaning, offering an inscrutable artifact that nevertheless has some elusive and explanatory power.听
To chase the etymology of the word is to chase a ghost. It is often said that the term algorithm was coined to honor the contributions of ninth- century Persian mathematician Mu hammad ibn M奴s膩 al- Khw膩rizm墨, noted for having developed the fundamental techniques of algebra. It is probably more accurate to say that it developed from or with the word algorism, a formal term for the Hindu- Arabic decimal number system, which was some-times spelled algorithm, and which itself is said to derive from a French bastardization of a Latin bastardization of al- Khw膩rizm墨鈥檚 name, Algoritmi.
Tarelton Gillespie, 鈥淎lgorithm鈥澨 (18)
- Tarleton Gillespie, 鈥淎lgorithm鈥 (4 – 16)
- Farhad Manjoo and Nadieh Bremer 鈥溾
Discussion Prompt: The accompanying presentation will explore the Manjoo and Bremer visualization to understand how algorithms are used to track online activity. The follow-up discussion will consider how students use and understand the term algorithm. Are algorithms unattainably complex? Inscrutable artifacts? How does each student鈥檚 interpretation inform their understanding of algorithmic power?
This part of the module will introduce students to the field of cultural studies. Focusing on the contributions of Stuart Hall and Raymond Williams, we鈥檒l discuss the difference between a 鈥榤edia studies鈥 and a 鈥榗ultural studies鈥 approach to communications, and assess the ways in which culture and its productions have been understood over time.
Stuart Hall (1932 鈥 2014) was a Jamaican-born, British, Marxist cultural theorist who, along with Richard Hogarth and Raymond Williams, was one of the founding figures of the school of thought that is now known as British Cultural Studies or The Birmingham School of Cultural Studies. 听For Hall, culture was not something to simply appreciate or study, but a “critical site of social action and intervention, where power relations are both established and potentially unsettled” ().
Hall鈥檚 contributions to Communications studies are myriad, but of particular interest to our study of culture is his understanding of the importance of the popular as a site of political engagement. He ends his influential essay 鈥淣otes on the Deconstruction of the Popular鈥澨 explaining his interest in the subject of 鈥榯he popular鈥:
鈥popular culture is one of the sites where [the] struggle for and against a culture of the powerful is engaged: it is also the stake to be won or lost in that struggle. It is the arena of consent and resistance. It is partly where hegemony arises, and where it is secured. It is not a sphere where socialism, a socialist culture – already fully formed – might be simply ‘expressed’. But it is one of the places where socialism might be constituted. That is why ‘popular culture’ matters. Otherwise, to tell you the truth, I don’t give a damn about it.
Discussion Prompt: The lecture/presentation will elaborate Hall鈥檚 understanding of the hegemonic processes that media uses to 鈥渕anufacture consent.鈥 Excerpts from Achbar and Wintonick鈥檚 1992 film will be used as illustration. Our discussion will consider Hall鈥檚 argument that 鈥media hegemony is not a conscious plot, nor overtly coercive, and neither are its effects total鈥, to consider if and how media might be used to manufacture dissent.听
- E.M. Griffin 鈥淐ultural Studies of Stuart Hall鈥 (344 鈥 354)
- Excerpts from Mark Achbar and Peter Wintonick, Directors, 1992.
Raymond Williams听(1921-1988) was a Welsh, Marxist theorist who wrote about politics and the media and spent the major part of his academic career trying to understand the historical factors and political functions of culture.听He defined culture as the values, expressions and patterns of thoughts of members of a collective, as they are historically determined, shaped by the dominant economic and industrial modes of a given period.听
Williams鈥 approach to studying culture involved exploring shifts in the way in which the concept itself was understood. In听Keywords: A Vocabulary of Culture and Society听(1976) Williams chose 100 words related to cultural and social practices and phenomena, including the words culture and society, and traced transformations in their meaning over time. Some other entries in his keyword compendium include:听art, management, nature, underprivileged, industry, liberal, violence. Williams鈥 premise was that the value placed on a concept is formed through use and application and in relationship to other ideas, words and expressions, and that terms and concepts change as new uses and applications arise; uses and applications driven by historical and political factors. Although he did not live long enough to discuss culture in the digital age his approach to cultural analysis has endured and others have taken up the mantle. In Ted Striphus鈥 article 鈥淎lgorithmic Culture,鈥 discussed below, the author sketches changes in the meaning of three words that are central to discussions of digital culture: information, crowd and algorithm.
Discussion Prompt: The accompanying lecture/presentation will review the principles of the 鈥榗ultural studies鈥 approach discussed by Hall, with reference to Williams鈥 Keywords methodology, with the latter explained via the 鈥榢eyword鈥 choices that Ted Stiphus makes in his explanation of 鈥榓lgorithmic culture鈥. In groups, students will be tasked with choosing and explaining, three words that they associate with algorithmic culture?
In this part of the course, we鈥檒l look more closely at cultural production in the digital/algorithmic age and examine the concept of industrial culture, querying if arguments made by Theodor Adorno and Max Horkheimer about 鈥榯he cultural industries鈥 hold true today.
DIGITAL CULTURE
Orit Halpern, a sociologist and historian of science and technology explains digital culture from anthropological and biological perspectives.听From an anthropological perspective, culture 鈥渋s an ontology or something that characterizes a group of people.鈥 From the biological point of view, culture is 鈥渢he medium upon which bacteria or other organisms grow.鈥澨鼿alpern argues for an understanding of digital culture from a biological standpoint as a 鈥済rowth medium for the generation of particular forms of life鈥one which is also] biologically and historically mediated.鈥 What will grow and how it will grow is contextual.
What is digital culture? What are the potential and dangers of digital culture? What lies beyond digital cultures? What are the technological conditions of digital culture?
ALGORITHMIC CULTURE
Over the last 30 years or so, human beings have been delegating the work of culture 鈥 the sorting, classifying and hierarchizing of people, places, objects and ideas 鈥搃ncreasingly to computational processes. Such a shift significantly alters how the category culture has long been practiced, experienced and understood鈥
Ted Stiphus 鈥淎lgorithmic Culture鈥
In his discussion of 鈥淎lgorithmic Culture,鈥澨Ted Stiphus听considers the defining role that information technologies have played in refashioning cultural production. Expanding on Halpern鈥檚 and Williams鈥 definitions, he suggests that听鈥culture is fast becoming 鈥撎齣n domains ranging from retail to rental, search to social networking, and well beyond 鈥 the positive remainder resulting from specific information processing tasks, especially as they relate to the informatics of crowds. And in this sense, algorithms have significantly taken on what, at least since [Matthew] Arnold, has been one of culture鈥檚 chief responsibilities, namely, the task of 鈥榬eassembling the social鈥,听as Bruno Latour (2005) puts it 鈥 here 鈥using an array of analytical tools to discover statistical correlations within sprawling corpuses of data, correlations that would appear to unite otherwise disparate and dispersed aggregates of people鈥 (406).
Discussion: What does Stiphus mean when he says that culture has become the 鈥減ositive remainder鈥 of 鈥渋nformation processing tasks鈥 specifically 鈥渁s they relate to the informatics of crowds鈥? What does it mean to say that algorithms have taken on 鈥渙ne of culture鈥檚 chief responsibilities鈥eassembling the social鈥?
THE CULTURE INDUSTRY
In 1947, Theodor Adorno and Max Horkheimer, members of the Frankfurt School of Social and Cultural Research, coined the term 鈥榯he culture industry鈥 to distinguish the idea of a mass manufactured culture from a culture that defines the values and interests of the people, and to draw our attention to the ways in which culture has become commodified in the industrial age. Concerns were raised about the standardization of mass-produced cultural products, their lack of originality, innovation, higher purpose, and the utilitarian function of the mass-produced cultural work. Key to the success of mass culture was the use of mass media to seduce consumers into believing that their happiness and creativity could be satisfied with the consumption of the latest, most popular thing.
听The term听culture industry听(:听Kulturindustrie) was coined by the听听听(1903鈥1969) and听听(1895鈥1973), and was presented as critical vocabulary in the chapter “The Culture Industry: Enlightenment as Mass Deception”, of the book听听(1947), wherein they proposed that听听is akin to a factory producing standardized cultural goods鈥攆ilms, radio programmes, magazines, etc.鈥攖hat are used to manipulate听听into passivity.听Consumption of the easy pleasures of popular culture, made available by the听, renders people docile and content, no matter how difficult their听听circumstances.听The inherent danger of the culture industry is the cultivation of false psychological needs that can only be met and satisfied by the products of听; thus Adorno and Horkheimer especially perceived听听culture as dangerous to the more technically and intellectually difficult听. In contrast, true psychological needs are听,听, and genuine听, which refer to an earlier demarcation of human needs, established by听.
Wikipedia,
Writing about cultural production in the digital age, Nato Thompson calls Adorno and Horkheimer鈥檚 critique 鈥渂oth prophetic and reactionary.鈥 Prophetic because 鈥淎dorno and Horkheimer realized鈥hat this new form of cultural capitalism was becoming entangled with the bourgeois ideals of individualism and taste,鈥 and so understood that 鈥淸o]nce people accepted a cultural world produced by capital鈥t would be very difficult to get them to react against it鈥 (9-10). Their critique has been perceived as reactionary because of their wholesale dismissal of the value of mass-produced culture: they didn鈥檛 seem to appreciate the discrete ways in which culture is consumed, nor understand as Stuart Hall did, that its effects are not total. Certainly, Adorno and Horkheimer could not anticipate the extent to which cultural consumption would change in the digital age: the era of Web 2.0, 鈥榩rosumption鈥, sampling, hacking and commenting.听 Indeed, consumption has morphed into a different format for engagement 鈥 more participatory than passive. Our discussion of the 鈥algorithmic cultural industry鈥 will look at the ways in which capital succeeds and fails to cultivate and satisfy consumer needs in the algorithmic age.
Exercise: The Algorithmic Playlist: Read the following PDF of Omar Kholeif鈥檚 鈥楢lgorithmic Playlists鈥 with a view to make some of your own: Which Youtube videos do you re-watch? Which Netflix shows are recommended to you? What books does Amazon want you to buy? Music on Spotify? Facebook or Instagram friend suggestions? Does it matter that they have been recommended to you? Do they have meaning for you otherwise?
- Nato Nato Thompson 鈥淐ultural Studies Makes a World鈥 (pages 3 – 21)Studies Makes a World
- Geoff Cox, Joasia Krysa & Anya Lewin ed. 鈥.
- Omar Kholeif, 鈥淎lgorithmic Playlist 1 – 3鈥 (183 – 197)
A debate considering the problems and possibilities of smart technologies: smart phones, smart homes and smart cities.
This course module looks at the social implications of algorithmic culture. Divided in six parts, the first will view the Netflix film听The Social Dilemma and consider its critical response, so to evaluate how the dilemmas of social media are articulated in social discourse and to introduce students to the algorithmic processes at work in social media. Parts two and three will consider what it means to be social on social media, and how social media defines the collective. Taking Facebook as a case study we鈥檒l evaluate how social connections are engineered by the protocols of participation. In part four we will look at how data analytics identify the internet surfer and discuss how these identifications are understood and monetized. In part five we鈥檒l examine the reach of the networked society and the digital divide, with a view to understand who participates in networked communication and who is left by the wayside. The final, concluding section of this module will serve as a bridge between this module and the next, with an activity that examines the rise in technological surveillance practices world-wide. Students will be presented with a visualization of international surveillance sites – an interactive map compiling data on types of surveillance and source – 听and asked to conduct supplementary research to try to understand how this surveillance has been understood, received and/or resisted by the subjects surveilled.
听
COMMUNICATION THEORIES:
Symbolic Interactionism: E.M. Griffin, 鈥淪ymbolic Interactionism of George Herbert Mead,鈥 A First Look at Communications Theory, 8th ed. McGraw Hill, 2012 (pages 54 – 66)
Media Ecology: E.M. Griffin,鈥滿edia Ecology of Marshall McLuhan.鈥 A First Look at Communications Theory, 8th ed. McGraw Hill, 2012 (pages 321 鈥 331)
Networked Society: Robert Van Krieken, 鈥溾 April 12, 2016
Video:
鈥淲e tweet, we like, and we share鈥 but what are the consequences of our growing dependence on social media? As digital platforms increasingly become a lifeline to stay connected, Silicon Valley insiders reveal how social media is reprogramming civilization by exposing what鈥檚 hiding on the other side of your screen.鈥
The documentary film 鈥淭he Social Dilemma鈥 takes a unique approach addressing the social, psychological and political dynamics of social media, blending a dramatic, fictional narrative with more familiar documentary conventions: a story about a family crisis spawned by an 鈥榓ddiction鈥 to social media is interspersed with expert opinions by software engineers who have designed the social media platforms and processes that lie at the heart of the family crisis. 听The film has received a lot of critical attention 鈥 some good, some bad. Some critics agree with the filmmaker鈥檚 position on the dilemma facing social media users:
Technology鈥檚听promise to keep us connected has given rise to a host of unintended consequences that are catching up with us. Persuasive design techniques like push notifications and the endless scroll of your newsfeed have created a feedback loop that keeps us glued to our devices. Social media advertising gives anyone the opportunity to reach huge numbers of people with phenomenal ease, giving bad actors the tools to sow unrest and fuel political divisions. Algorithms promote content that sparks outrage, hate, and amplifies biases within the data that we feed them.
Others argue that the filmmakers do not understand how technology works:
For all of its values, and all of its flaws, the film鈥檚 diagnosis of social media is based on a fundamental misunderstanding of technology. Its recommended path to recovery, as a result, leads to a dead-end. Until we think of technology not as a tool but as a set of relations, we will never truly grasp the problems with which听The Social Dilemma听is concerned鈥
Niall Docherty
Responding to comments made by one of the film鈥檚 stars on The Joe Rogan show, Eric Scheske suggested that while the filmmaker鈥檚 concerns about the ways in which the film present the social media may echo themes in the writing of Communications scholars Marshall McLuhan and Neil Postman, neither McLuhan or Postman could have imagined how entangled we have become with our technologies.
The basic truth applied by听The Social Dilemma听is vintage McLuhan/Postman: The medium is the message, which means, 鈥淭he content conveyed by a medium (TV, radio, newspaper) doesn鈥檛 matter. The medium and its effects on us is what matters. Media affect us, regardless of their content. To a man with a hammer, everything looks like a nail. The mere carrying of a hammer affects how a person thinks, even if he doesn鈥檛 notice it.鈥
听Likewise, the Internet affects us, regardless of what we鈥檙e using it for. And it affects us in ways we don鈥檛 notice or appreciate. If we think we鈥檙e floating higher than everyone else because we don鈥檛 use the Internet to troll or view porn, we鈥檙e just kidding ourselves. We 鈥檙e being affected in the same way as the porning idiots.
听All that is vintage McLuhan/Postman. Harris is right to give them credit.
But there鈥檚 a lot more to听The Social Dilemma.
听McLuhan didn鈥檛 see this coming or if he did, he thought it might, at a certain level, be a good thing.
听At one point, Harris mentions that it鈥檚 almost like the algorithms are accessing our central nervous system. He obviously doesn鈥檛 consider that a good thing.
听
McLuhan, however, praised electronic technology because it had 鈥渙utered the central nervous system itself鈥 and had the potential of making us whole again. At other points, McLuhan expressed grave concerns, but for the most part, he was optimistic about our electronic future.
Eric Scheske, Is the Netflix Documentary a Paean to Marshall McLuhan?
More, as Scheske points out, although McLuhan and Postman may both subscribe to a 鈥樷 model of communication – where media act as mediums promoting the growth of human culture, and function as extensions of the human senses – they differ on one key point: McLuhan 鈥減raised electronic technology because it had 鈥榦utered the central nervous system itself; and had the potential of making us whole again,鈥 Postman was more circumspect. Focusing on television, he argued that 鈥淭V dumbs us down because it doesn鈥檛 engage us鈥he way print does by exercising our faculties of focus and thought, of stopping and re-reading, of thinking about what we鈥檝e read. 鈥 Where 鈥渟ocial media bring back engagement and participation, but it鈥檚 not voluntary and, therefore, the participation is illusory. We click and think we choose; we read and think we chose to read.鈥
Discussion Prompts: Our conversation will begin discussing the difference between thinking about social media as a tool, versus thinking about it as a relation; and then explore听 the concept of 鈥榤edia ecology鈥 by summing McLuhan鈥檚 and Postman鈥檚 positions on electronic technology. Discussion will consider how these scholars would understand and respond to the impact of social media and new, smart communication technologies on the human sensorium.
- M. Griffin, 鈥淢edia Ecology of Marshall McLuhan.鈥 A First Look at Communications Theory, 8th ed. McGraw Hill, 2012 (pages 321 鈥 331)
- Niall Docherty, 鈥?鈥
- Eric Scheske, 鈥?鈥
- Richard Seymour, 鈥,鈥
Concerned with the impact of algorithmic culture on social life, we鈥檒l discuss how identity and subjectivity might be conceived and produced through our encounters with algorithms, how the collective is imagined and the social assembled through networked exchange.
A term coined by Communication and IT Professor Taina Bucher, 鈥減rogrammed sociality鈥 refers to the manner through which friendships are programmatically organized and shaped by social networks. Facebook offers the perfect illustration of programmed sociality. The platform simulates and reconfigures existing notions of friendship, orchestrating the kinds and qualities of connections made to boost traffic on the site. This is friendship with benefits, but for whom?
We will explore how Facebook works to orchestrate friendship and community, how friendship is understood in social networking terms, and how the social takes form in and through social media.
Ben Grosser on the Facebook Demetricator: 鈥淭he Facebook interface is filled with numbers. These numbers, or metrics, measure and present our social value and activity, enumerating friends, likes, comments, and more. Facebook Demetricator allows you to hide these metrics. No longer is the focus on how many friends you have or on how much they like your status, but on who they are and what they said. Friend counts disappear.鈥
Journal Exercise: Use Grosser鈥檚 Facebook Demetricator for one week; take note of how many times you check metrics and in which circumstances. Reflect on the quantitative versus qualitative value you place on your social exchange
听
In the digital age, in addition to how we usually self-identify – naming and presenting ourselves as we want to be known and seen – 听our identities are algorithmically produced and mostly beyond our control or benefit. Every time we initiate a Google search or log onto a social network, streaming service or commercial website, streams of data are generated and collected, including search terms, the locations of devices, time stamps, operating systems, the applications we use and how and when we use them. Then, data collected from these online stops, shops and clicks are measured against previous search histories 鈥 ours and others accessing the same site and those others鈥 others鈥 data 鈥 to determine degrees of our correspondence to 鈥榤easurable types鈥: 鈥榤an,鈥 鈥榳oman,鈥 鈥榪ueer,鈥 鈥榮traight,鈥 鈥榦ld,鈥 鈥榶oung,鈥 鈥榳hite,鈥 鈥楤lack鈥 and so on. Then the advertisers (or governments) arrive to do their work.听More, these identities are not stable. Each subsequent search situates our data in relation to myriad others and their others.听听And so it goes.听听As digital scholar John Cheney-Lippold suggests, 鈥渨e are now ourselves, plus layers upon additional layers of鈥 algorithmic identities鈥 (5)
Cheney-Lippold also argues that the dynamics of identity construction in the digital age finds a degree of commonality with the thinking of Judith Butler on the subject of gender performativity, where the stability of gender identity is called into question, but without the self-determination that she imagined for the actual performing subject (25).
DISCUSSION PROMPT: The presentation will make use of James Bridle鈥檚 Citizenship Ex project to explain the concept of the 鈥榤easurable type鈥, with subsequent discussion querying how听algorithmic identities intersect with real lives and how exactly the categories of sex, gender, race and class matter in the algorithmic age.
- Lidia Pereira, 鈥溾 Object Oriented Subject, September 2017
- James Bridle ;
听
The other side of the 鈥榮ocial dilemma鈥 is the role played by social media in building community 鈥 shaping the language and discourse through which we find common interests and define ourselves in relation to the group. This part of the course explores the ways in which social platforms are used to shape social discourse and introduces the student to the theory of 鈥榮ymbolic interaction鈥 developed by philosopher George Herbert Mead in the philosophy department at the University of Chicago in the 1920s.
The term 鈥榮ymbolic interaction鈥 describes a theory of communication that imagines human communication as a dialogue: 鈥淸t]he ongoing use of language and gestures in anticipation of how the other will react; a conversation鈥 (Griffin, 54).听 Mead鈥檚 theory isolated three main features of inter-personal communication: people respond to others, both animate and non-animate beings, based on the meaning that they assign them; these meanings are shaped by social interaction, negotiated through the use of language or 鈥榮ymbolic naming鈥; and, these symbols are modified by an individual鈥檚 mental processing 鈥 what they think of the shared meaning, how they think that they should respond, with what symbolic interaction of their own: this is known as self-talk.
Mead鈥檚 concept of the self follows from these interactionist principles: the self is created imagining how we look to the other person. This 鈥渓ooking-glass self鈥 is socially constructed. 鈥淲e are not born with senses of oneself. Rather, selves arise in interaction with others. I can only experience myself in relation to others; absent interaction with others, I cannot be a self鈥擨 cannot emerge as someone鈥 (Shepherd 24).
The premises behind 鈥檚 documentary filmmaking suggests that symbolic interactionism is alive and well in the world of social media. Her practice involves culling content from hundreds of YouTube videos and reassembling these to draw a picture of American society forged through the common interests, language and symbolic expressions of YouTube vloggers. The most striking features of her work describe the common conventions of online expression 鈥 video to video the performers adopt similar strategies of self-presentation 鈥 and illustrate the consistency of the verbal language used to address the subject at hand.
How does the work relate to algorithmic culture?
The work Bookchin has done for the last decade lies somewhere between a collaboration with and intervention into Google鈥檚 algorithms. Bookchin digs into online databases to collect videos, and by varying search terms and going deep into search results, aims to circumvent the search鈥檚 algorithmic biases. She rescues videos lost in the cacophony or buried by secret algorithms that favor more 鈥渟hareable鈥 data.
听Algorithm-based recommendations offer people films, books, or knowledge based on past choices, providing what the algorithm thinks they want. Like algorithms, her montages suggest relationships between different sets of data, but unlike algorithms, which are invisible and individualized, she make her biases visible through editing and montage, and the semantic relationships she creates reveal larger social truths that go beyond the individual.
YouTube鈥檚 algorithms organize videos by popularity, tags, and titles. They can鈥檛 easily detect subtext or irony, falsehoods, or disinformation. Any politics, preferences,
ethics鈥攐r lack thereof 鈥攅mbedded in the algorithms are company secrets. Bookchin鈥檚 intervention aims to highlight our algorithmic condition, how we come to see and know what we do though automated algorithmic mediation, as well as to underscore the
value of embodied, situated, creative human intelligence and perspectives.
From the symposium pamphlet, Network Effects
Discussion Prompt: After discussing Mead鈥檚 theory of 听symbolic interactionism as illustrated in and by Bookchin鈥檚 work, we鈥檒l consider the importance of self-talk in symbolic interaction on social media. Students will be asked to discuss their own experience of symbolic interaction in social media.听
- Natalie Bookchin, , 2009 / (2016)/ 2012/2017)
- Natalie Bookchin, Network Effects – Natalie Bookchin: Media Works 2008-2017, (PAGES 2-3)
- Angela Maiello. 鈥淩e-Editing the American Crisis: Natalie Bookchin鈥檚 Montaged Portraits,鈥 DVD Portraits of America; Two Films By Natalie Bookchin, Icarus Films 2017
- M. Griffin, 鈥淪ymbolic Interactionism of George Herbert Mead,鈥 A First Look at Communications Theory, 8th ed. McGraw Hill, 2012 (page 54 – 66)
听
The concept 鈥渘etworked society鈥 was first introduced by Jan van Dijk in his 1991 Dutch book听De Netwerkmaatschappij听(The Network Society) and further developed by Manuel Castells in听The Rise of the Network Society听(1996): the term refers to a society that is connected by mass and telecommunication networks听).
As Castells explains, although social networks are not new, 鈥渢he key factor that distinguishes the network society is that the use of ICTs helps to create and sustain far-flung networks in which new kinds of social relationships are created鈥 (. According to Castells, three processes led to the emergence of this new social structure in the late 20th century:
- the restructuring of industrial economies to accommodate an open market approach
- the freedom-oriented cultural movements of the late 1960s and early 1970s, including the civil rights movement, the feminist movement and the environmental movement
- the revolution in information and communication technologies
A key aspect of the network society concept is that specific societies (whether nation states or local communities) are deeply affected by inclusion in and exclusion from the global networks that structure production, consumption, communication and power. Castells鈥 hypothesis is that exclusion is not just a phenomenon that will be gradually wiped out as technological change embraces everyone on the planet, as in the case that everyone has a mobile phone, for example. He argues that exclusion is a built-in, structural feature of the network society.
听In part this is because networks are based on inclusion and exclusion. Networks function on the basis of incorporating people and resources that are valuable to their task and excluding other people, territories and activities that have little or no value for the performance of those tasks (Castells 2004 p. 23). Different networks have different rationales and geographies of exclusion and exclusion 鈥 for example, Silicon Valley engineers occupy very different social and territorial spaces from criminal networks.
The most fundamental divides in the network society according to Castells (2004 p. 29) are the division of labour and the poverty trap that we discussed earlier in the context of globalisation. He characterises these as the divide between 鈥榯hose who are the source of innovation and value to the network society, those who merely carry out instructions, and those who are irrelevant whether as workers (not enough education, living in marginal areas with inadequate infrastructure for participation in global production) or as consumers (too poor to be part of the global market).鈥
Managing Knowledge and Communication for Development 鈥 鈥淯nit 1 Introduction to Knowledge, Communication & Development:听鈥
听It鈥檚 important to look at the听鈥渄igital divide鈥 in terms of the degrees and reasons for exclusion involved:
It was traditionally considered to be a question of having or not having access,听but with a global听听penetration of over 95%, it is becoming a relative inequality between those who have more and less bandwidth and more or less skills. Conceptualizations of the digital divide have been described as 鈥渨ho, with which characteristics, connects how to what鈥:
- Who is the subject that connects: individuals, organizations, enterprises, schools, hospitals, countries, etc.
- Which characteristics听or attributes are distinguished to describe the divide: income, education, age, geographic location, motivation, reason not to use, etc.
- How sophisticated is the usage: mere access, retrieval, interactivity, intensive and extensive in usage, innovative contributions, etc.
- To what does听the subject connect: fixed or mobile, Internet or telephony, digital TV, broadband, etc.
Wikipedia with help from Bart Pursel, 鈥溾 in听Information, Technology, People, Penn State University, n.d.
Discussion: Castells argues that exclusion is a built-in, structural feature of the network society. Why and how is exclusion built-in? Discuss.
- 听(August 19, 2019)
- Robert Van Krieken, 鈥溾
- Wikipedia with help from Bart Pursel, 鈥溾 in听Information, Technology, People, Penn State University, n.d.
The final activity for this section of the course will involve the class in a group research project looking at how artificial intelligence is used as a form of governmental surveillance, gathering and monitoring information on its citizens. Our survey will engage the 鈥 prepared by the Carnegie Endowment for International Peace to explore the different digital tools used for these purposes.
SURVEILLANCE SURVEY: DESCRIPTION
(in progress)
Module III will explore the differences between lens-based representation and data visualization; how each form has been understood and engaged. In four parts, we will: 1) survey the prehistory of dataset production, looking at the early photographic archives as a historical means of social engineering, and examine the contemporary racial and social biases of contemporary archives/datasets at work in facial recognition software; 2) explore how digital technologies have challenged the documentary value of lens-based imaging; 3) consider the role and value of nonhuman photography in the production of knowledge; 4) and evaluate whether or not and how data visualization can make historical phenomena intelligible and meaningful. The concluding activity will consider how processes of visualization have changed in the computational age.
COMMUNICATION THEORY:
PRELIMINARY BIBLIOGRAPHY
Taina Bucher, 鈥淣etworking, or What the Social Means in Social Media.鈥 Social Media + Society April-June 2015: 1鈥2
Natalie Bookchin, Network Effects –听 Natalie Bookchin: Media Works 2008-2017
Niall Docherty, 鈥淢ore than tools: who is responsible for the social听dilemma?.鈥 October 2020听 Social Media Collective,
Stephen Feldstein 鈥淭he Global Expansion of AI Surveillance鈥 (September 2019). https://carnegieendowment.org/2019/09/17/global-expansion-of-ai-surveillance-pub-79847
Tarleton Gillespie, 鈥淎lgorithm鈥 in Benjamin Peters, ed. Digital Keywords: A Vocabulary of Information, Society and Culture, Princeton University, 2016 (pages 4 – 16 of 352 pages)
E.M. Griffin 鈥淐ultural Studies of Stuart Hall,鈥 鈥淪ymbolic Interactionism of George Herbert Mead鈥 鈥淢edia Ecology of Marshall McLuhan,鈥 and 鈥淪emiotics of Roland Barthes,鈥 听A First Look at Communications Theory, 8th ed. McGraw Hill, 2012
Stuart Hall, “Notes on Deconstructing ‘The Popular’,” People’s History and Socialist Theory, Raphael Samuel (ed.), London: Kegan Paul-Routledge, 1981, pp. 231-5, 237-9.
Orit Halpern, Robert Mitchell, and Bernard Dionysius Geoghegan . 鈥淭he Smartness Mandate: Notes toward a Critique.鈥 Grey Room 68 (2017): 106鈥29.
Carolyn Kane, 鈥淒ancing Machines: An Interview with Natalie Bookchin,鈥 Rhizome, May 27, 2009
Omar Kholeif, 鈥淎lgorithmic Playlist 1 – 3鈥 in Goodbye, World! Looking at Art in the Digital age.Sternberg Press, 2018.
Farhad Manjoo and Nadieh Bremer 鈥淚 Visited 47 Sites. Hundreds of Trackers Followed Me.鈥 By (August 23, 2019)
Vincent Mosco, 鈥淭he Next Internet,鈥 Becoming Digital: Toward a Post-Internet Society. Emerald Publishing, 2017
Lidia Pereira, 鈥淪oft Biopolitics (Measurable Type)鈥 Object Oriented Subject, September 2017
Scheske, Eric. 鈥淚s the Netflix Documentary a Paean to Marshall McLuhan?鈥 The Daily Eudemon, November 13, 2020. .听
Richard Seymour, 鈥淣o, Social Media Isn鈥檛 Destroying Civilization,鈥 Jacobian, September 9, 2020
Ted Stiphus 鈥淎lgorithmic Culture鈥澨European Journal of Cultural Studies听(2015), Vol. 18 (4-5) 395鈥412
Nato Thompson 鈥淐ultural Studies Makes a World,鈥 Seeing Power: Art and Activism in the Age of Cultural Production, Melville House, 2015 (pages 3 – 21 of 197 pages)
Wikipedia with help from Bart Pursel, 鈥淭he Digital Divide鈥 in Information, Technology, People, Penn State University, n.d.听