15.02.24
LECTURE 2
Information Society
Frank Webster questions the concept
Theorists look at information as quantitative
The semantic definition of information says it is meaningful non-semantic view deals with the amount of information
# Claude Shanon and Warren Weaver’s (1964) information theory
Talks about quantity, measurement
Ignores semantic content
# Stoiner (1990 : 21)
Information is independent outfits content
# Rozak (1986)
Information can be coded, transmitted
It too ignores semantic content
# In an information society semantics and quality are important
What sort of information? Who? What?
Questioning the meaning and dynamics
# 5 Definitions/characteristics of information society
1. Technological
Breakthrough in processing, storage, transformation
Application of IT
Reduction of cost of computer
Computerization of telecommunications
Convergence of computer and telecom
Connection of computers learning to “network society”
Objections
Problem of measurement
How much IT is required? (only IT or other dimension!)
When does industrial society turn to an information society?
Technological determinism
There are other dimensions
2. Economic
Fritz Machlup: The Production and Distribution of Knowledge in the United States (1962)
Distinguished 5 broad industry groups which contribute 29% of the economy and are attached with information
Marc Porat (1977): primary, secondary, non-information sectors
The US is an information-based society due to 46%
Problem
Every industry deals with information
Qualitative worth is difficult to measure
3. Occupational
Changes in occupation (blue collar to white)
Frequently combined with economic measures
Marc Porat shows in the late 1960s 50% of labor was information sector
Three categories: 1st, 2nd and 3rd
4. Spatial
Connect locations, in consequence, have dramatic effects
Game of exclusion/inclusion
* Anthony Giddens: “Time-space compression”
David Harvey: spatialization
Objection/Problem
What’s new?
When is a network a network?
5. Cultural
Media-saturated society, post-truth society
Extra-ordinary increase in the information
A collapse of meaning because of diverse directions, fast changes, and contradictions
High quantity with loss of quality/semantics
Jean Baudrillard (1983): ‘More info-less meaning’
Jean Baudrillard (1981): Simulacra and Simulation
Issues to discuss
Definitions are both underdeveloped and imprecise
What constitutes and how to distinguish the information society?
29.02.24
LECTURE 2
Objectives (Theories of the information society)
Herbert Schiller vs Manuel Castell
Herbert Schiller
The (critical) political-economic perspective of the information society
Marxist theorist
Most prominent critical theorist based in North America
Books: Who Knows? (1981), Information and the Crisis in Economy (1984), Culture (1989)
Critical political economists: focus on praxis rather than theory only
Information and advanced capitalism: Herbert Schiller
The modern era witnessed an unprecedented proliferation of images and information facilitated by new media technologies
Information is capitalized
Information is commodity
Marxist historical materialism: history helps to predict the future
#Key-arguments:
Market criteria - information and communication technologies are shaped by market pressure
It is a commodity that can be bought and sold
Class inequalities - information rich vs information poor
Corporate capitalism - more in private companies than in public
#Objections:
Lack of practical proposals; only explanation
Simplistic class analysis: ignores, gender, race, etc
All-or-nothing view
Perception of consumerism
Individuals can see through
Consumer goods can provide pleasure
Manuel Castell
Information and Urban Change
Books: The informational city (1989), The rise of the network society (1996)
Central thesis: a combination of capitalist restructuring and technological innovation
Objections:
Technological determinism: overlooks intertwined nature
No clear division between the two modes
The capitalist mode of production created the informational mode of development
# Information flow
Network society, global integration of economic activities, de-centralization of ideas and centralization of decision-making
# Class structure in the informational city
Underclass - no access to information/not an information worker (information-rich/poor), class polarization, urban dualism
# Information city is a postmodern city
Gentrification, coexistence, restructuring towards consumption, hedonistic society
Schiller and Castell
Difference - cause of social change
*Castell: information technology
*Schiller: Capitalism in advanced version
Similarities - both talked of technological development
# Fourth world: excluded from information
07.03.24
LECTURE 3
Artificial intelligence (AI) in the creative industries (CI)
# AI techniques enable machines to perform tasks that typically require some degree of human-like intelligence
# AI encompasses codes, techniques, algorithms, and data that enable a computer system to develop and emulate human-like behavior and make decisions similar or better than humans
e.g. web search, surgery, text/content, production, smart home
General AI or strong AI - when a machine exhibits full human intelligence
Narrow or weak AI - when technologies are limited to specific tasks or domains
# Past: model-driven AI - nature of the application is studied and a model is mathematically formed to describe it
# From the mid-1950s to the late 1980s: based on symbolic AI, assuming humans use symbols to represent problems, intended to produce general human-like intelligence in a machine
# Present: Data-dependent AI, directed at specific sub-problems
AI and CI
# AI accomplishments rely on the conformity of data [rule-driven]
# Creativity often exploits human imagination to drive original ideas that may not follow general rules
# Basically, creatives have a lifetime of experience to build on, enabling them to think ‘outside of the box’ and ask ‘what if’ questions that cannot readily be addressed by constrained rules
AI and Algorithms
# Modern AI technologies are based on machine learning
# algorithm - data processing method/procedure
An algorithm is any well-defined computational procedure that takes some values or set of values as input and produces some values as output
ML Algorithms
# ML employs computational methods to ‘learn’ information directly from large amounts of example data without relying on a predetermined equation or model
# more data given = improved performance
# Three types of ML
Supervised ML: builds a mathematical model from labeled data that contains both inputs and desired outputs
Semi-supervised ML: employs a limited set of labeled data, usually a large amount of unlabeled data
Unsupervised learning: model the problems of unlabeled data
Self-supervised learning and/or reinforcement learning: learn from trial and error and are effectively self-supervised, self-trained
Neural Network
# Modern ML methods have their roots in the early computational model of a neuron
# Artificial neurons receive inputs, weigh them, and pass them through an activation function, resembling the action potential of biological neurons
# multilayer perception (MLP): MLP is a basic form of artificial neural network (ANN) with multiple layers, typically including one input layer, one hidden layer and one output layer. Neurons in each layer are fully connected with each other
Deep Learning (Deep Neural Network)
# Deep learning is a subset of machine learning utilizes deep artificial neural networks (DNNs) which have multiple hidden layers of neuron collection [deep = many hidden layers of neuron collection]
CNN, GAN
AI for the Creative Industries
Creativity [= ability to produce original and unusual ideas, or to make something new or imaginative, Cambridge]
# Creative tasks generally require some degree of original thinking, extensive experience, and understanding of the audience.
# Production tasks are in general, more repetitive or predictable, making them more amenable to being performed by machine
# Nex Rembrandt (2016), Gum Gum, Botnik
Five major categories of AI application in CI
Content creation
Script and movie generation
Sunspring (2016), It's No Game (2017), Scriptbook
Journalism and text generation
Music gemeration
Image generation
Animation
Augmented, virtual and mixed reality
Deep fakes
Content and captions
Information analysis
Text generation
Advertising and film analysis
Content retrival: automatic annotation
Recommendation services
Intelligent assistants
Content enhancement and post production workflows
Contrast enhancement
Colorization
Upscaling imagaery (super-resolution methods)
Restoration
Inpainting
Visual special effects (VFX)
Information extraction and enhancement
Segmentation
Recognition
Salient object detection
Tracking
Image fusion
3D reconstruction and rendering
Data compression
Growing demand for visual content
Deep learning in compression
# Challenges: ethical issues, fakes and bias
Ethics and AI
Dignum (2018), Boston and Yudkowsky (2014)
Ethics by design
Ethics in design
Ethics for design
AI, Power and Politics
# Knowledge is power: Who owns it? Who controls?
# National security, strategies, impact on the workforce, privacy, surveillance, data governance
14.03.24
LECTURE 4
Objectives:
Big data
Implications in media
# Critical question for Big Data (2012); Boyd & Crawford
Big Data
# Emergence of Big data era – various academic disciplines seek access to vast amounts of data for analysis
Big data = data sets large enough to require supercomputers to analyze [earlier definition]
But what once required such machines can now be analyzed on desktop computers with standard software
Now big data is more about a capacity to search, aggregate, and cross-reference large data sets
Refers to the ability to gather, analyze, and link massive data sets
Boyd and Crawford (2012) defined Big data as cultural (post-modern), technological (technology-oriented), and scholarly (scholars are working on this)
# This resets the interplay of–
Technology: maximizing computation power and algorithmic accuracy to gather, analyze, link, and compare large data sets
Analysis: drawing large data sets to identify patterns in order to make political, economic, social, technical, and legal claims
Mythology: the widespread belief that the larger the sample the higher form of intelligence and knowledge
Truth
Objectivity
Accuracy
– Boyd and Crawford (2012) busted this myth
# 1984 by George Orwell: Big Brother is watching you
Jeremy Bentham/ Foucault : Panopticon
Social media is a manifestation of Big Brother
# Six propositions by Boyd and Crawford
The definition of knowledge is changed
Like Fordism revolutionized manufacturing, Big data is transforming knowledge creation and research methodologies
Qualitative undermines qualitative people by blaming that it is subjective, qualitative undermines quantitative by blaming that not everything is quantifiable
Big data emerged as a system of knowledge that can change the objective of knowledge
Creates a radical shift in how we think about research and hints toward a computational method
This leads to more computational/ quantitative methods
More pressure on quantification
But not everyone is accepting quantitative methods
Berry (2011): too much information lacks the regulating force of philosophy
100 does not mean anything without context (100 cow/ man?)
Computationality might be understood as an ontotheology creating a new ontological “epoch” instead of philosophy
In research, some are ontological [= nature of a thing] questions, some are epistemological [= the means/ methods of knowing it] questions
It’s essential to question the limitations of big data
Claims of objectivity are misleading
Subjectivity is big data: despite the claim. Who is claiming this? - researcher. That’s how it is subjective
Claims are based on individual observations and choices. All researchers are interpreters of data
Data errors and readability → biases and limitations
Social media sites: not everyone shares the truth
Bigger data is not always better data
Methodological rigor and challenges
Doesn’t mean methodological issues are irrelevant, understanding sample quality remains crucial [sampling, randomness/ representativeness]
Twitter/FB data
Big data/ whole data (not everyone uses social media)
Uncertain sample sources (different accounts by one individual/ protected account)
Some accounts are bots
Large data sets magnify existing errors
Loses meaning if taken out of context
Traditional social network analysis → surveys, interviews, observations
Big data → articulated [=based on specific contacts] and behavioral [=communication patterns and interactions] networks derived from digital traces
Big data’s ability to represent relationships with graphs does not mean the information is equivalent to traditional process
Accessibility does not ensure ethical issues
FB users research in 2006
Supposedly anonymous data is released to the world, allowing other researchers to explore and analyze
However, it was possible to deanonymize parts of the data sets
Issues raised for scholars
What is the status of so-called ‘public’ data on social media sites?
Can it simply be used, without requesting permission?
What constitutes the best ethical practice of researchers?
Institutional Review Boards (IRBs)/ Ethical Review Boards
Access to publicly accessible content does not justify nonconsensual uses
The difference between being in public and being public
Big data studies raise questions about truth, control, and power
Limited access creates new digital divides
Limited to and often controlled by social media companies
Who gets access? For what purpose? In what context? And with what constraints?
Big data rich and big data poor
21.03.24
LECTURE 5
Platformization
Objective:
Platform and platformization
Why platformization? How? Role of the state and market?
Platformization of cultural production.
# Helmond (2015). Niebord (2018)
# Platform - Facebook Development Platform, Meta for Developers
Facebook is a multisided platform (users, advertisers, and 3rd parties)
# Web 2.0 companies introduced a broader meaning of the term
Computational: something to build upon and innovate from
Political: a place from which to speak and be heard (a space for expression and influence)
Figurative: representing abstract promise and practical opportunity
Architectural: designed to enable open expression rather than imposing restrictions like a gatekeeper. E.g. Youtube - inclusive spaces for creative expression, rather than expressive or limited structures
# Platform = programmability
Can be reprogrammed and customized and enriched
# Application programming interface (APIs)
User Generated Content - academic focus for media studies
Level 1 (access API): read, write, or delete data [flicker]
Level 2 (plug-in API): develop new functions into UI [Facebook]
Level 3 (runtime environment API): run 3rd third-party app within [windows]
# Web 2.0: the web as platform
user interface + software interface
# Platformization
process to make programmable
use the data of the ‘users’
decentralize data production and recentralize data collection
websites enabled programmability in ways:
Extensible Markup Language
Separating content and presentation
Facilitates machine-readable interchangeable data
Enabling dynamic content between websites and external databases
Modularization
Connecting/ dividing into parts
Interfacing with databases
Two-way data flows between websites and FB's database
# Dual logic of platformization
Expansion of social media platforms into web
The presentation of external data to fit the format
Questions to ask
Why platformization?
Profit motive (FB stealing data)
Who controls?
Big companies
What are the roles of the state? Markets? World organizations?
“platforms are new barons of information capitalism”
How did the Google/Facebook monopoly happen?
Neo-liberalism allowed
Platformization of Cultural Production
# Contingent
# involves a shift in market structure, governance frameworks infrastructure
# Digital news platform, digital games
Theorizing platformization
Business studies: multisided market
Political economy: platform power and politics
Software studies: computational infrastructures
# Three dimensions of platformization
Shifting market: two-sided to multisided, winner-take-all
Changing governance: impacted CI's autonomy, global platforms clash with local values, impacting cultural/ artistic expression, difficult to challenge policy
Infrastructural platform: dependencies on platform technology and governance policy (‘infrastructural capture’), news - platformed distribution of individual content, game-optimized
Question:
How the political economy of CI is transformed through platformization?
25.04.24
LECTURE 6
DIGITAL DIVIDE
Objective(s)
To learn and discuss
■ The concepts of digital divide (DD)
■ Levels of digital divide
■ Discourses on the digital divide
■ DD measurement tools/ techniques
■ It's consequences
Social divide
■ Inequalities regarding the opportunities and advantages of the various social groups within a society.
DEFINITION OF DIGITAL DIVIDE
■ Chen and Wellman (2003) suggest a conceptualization based on factors of access and use, weighted by socioeconomic status, gender, life stage, and geographic location.
■ Bridges.org (2001) proposes considering the number of users or computers, infrastructure access, affordability, training, relevant content, information technology (IT) sector (size of ICT sector and integration into existing industries), poverty, and demographic lines (geography, race, age, religion, gender, and disability).
■ Lack of Initial Definition:
Many indices related to the digital divide do not begin by defining and conceptualizing it upfront. Instead, they start by identifying variables and indicator levels, potentially overlooking what is most meaningful in a specific context.
■ It's crucial for efforts to address the digital divide to consider the specific context in which disparities exist, rather than solely focusing on measurable variables.
■ This approach ensures that interventions are tailored to address the most pressing issues within a given community or population.
DIGITAL DIVIDE VAN DIJK,J. (2003).
■A gap between people in terms of access and use of digital technologies
■Information haves and have-nots (See Joe Morehead, 2000)
■ Exists between north and south, western and oriental countries, and within counties
■ There is a digital divide in every nation/ country
■Access - different types
■ Usage- who uses it effectively or not, skills
■ Income, education, age, gender, and ethnicity have impacts/matters on/in DD
CONCEPT OF ACCESS, AND BARRIERS
■ Access- having a computer and a network connection?
■ According to Van Dijk (1999), there are four types of access: Mental, material, skills, usage
■ Four kinds of barriers that limit people's access to digital technology
■ Lack of elementary digital experience lack of interest, computer anxiety, and unattractiveness of the new technology
■ No possession of computers and network connections
■ Lack of digital skills - insufficient user friendliness and inadequate education or social support
■ Lack of significant usage opportunities
■ Public opinion and policy often focus solely on material access, assuming that providing computers and internet access solves the problem.
■ Mental barriers and inadequate digital skills are often overlooked or seen as temporary issues.
■ Differential usage of technology is disregarded, seen as a personal choice rather than a societal concern.
MENTAL ACCESS BARRIER
Reasons for not using the internet or digital technology include
■ older people, those with lower education levels, and women, express a lack of motivation to connect to the internet or use digital technology.
*not feeling the need for it,
→ not liking it, finding it too expensive, or lacking the skills to use it effectively.
■ Emotional and subjective factors contribute to the lack of digital skills, leading to feelings of insecurity, exclusion, and computer anxiety.
DIGITAL SKILLS
■ Types of Digital Skills:
Operational Skills: Ability to use digital equipment; hardware, and software.
✓ Informational Skills: Ability to search for information effectively; searching for information using digital tools.
✓ Strategic Skills: Ability to use information for personal goals and position, to achieve something.
■ Digital skills are not primarily related to educational levels. Instead, age and gender play a more significant role.
Influencing Factors in Digital Skills Acquisition:
Computer experience at work.
Specific hobbies.
Having a family with school-aged children.
■ In Western societies - The rise of the usage gap
■ In Oriental societies - Material gap - haves and have nots
OPINIONS/ DISCOURSES ABOUT THE DIGITAL DIVIDE
■ Denial of Digital Divide:
Some (people in power) argue that there's no digital divide, citing high adoption rates of computers and the internet. They believe that market forces will naturally solve any issues.
■ Belief in Disappearing Divides:
Another viewpoint suggests that any current divides will soon disappear as technology becomes more widespread (technology costs coming down) and affordable. They argue that early adopters pave the way for wider access.
This is partially a correct argument. Because,
New media exists with old media (people buy tv and laptop both)
Computer gets outdated fast, requires update, updating means more cost.
■ Emphasis on Growing Divides:
Left-wing political forces and progressive organizations emphasize the persistence and growth of the digital divide. They see it as exacerbating existing inequalities and argue for intervention to address these disparities. Society is unequal, It will worsen.
■ Recognition of Differentiation:
Some theories of the information or network society suggest that while some divides may diminish, new ones will emerge based on knowledge and education disparities. This perspective acknowledges the complexity and dynamism of the digital divide.
■ Complexity and Dynamics:
Overall, the interpretations of the digital divide range from denial to recognition of its complexity and impact on society.
The divide is seen as multifaceted, with various factors influencing access and usage, and its effects are dynamic, evolving with technological advancements and societal changes.
MEASURING DIGITAL DIVIDE
■ Karine Barzilai-Nahon (2006) discussed about six features/ indicators to measure digital divide.
→ Infrastructure access
* Affordability
Use
* Social and governmental constraints/support
* Sociodemographic factors
AFFORDABILITY
In comparison/ relative to other expenditures and average income, three layers
■ Physical layer (infrastructure affordability): Can one afford computer/ bandwidth etc.?
■ Logical layer (applications and software): Can one afford apps/ softs (we use crack versions)
■ Content layer: Can one afford content? [Western tv- has to pay, ours not needed to pay], Streaming services
SOCIAL AND GOVERNMENTAL CONSTRAINTS/SUPPORT
Does the society/ govt. encourage DT?
■ Training: arrange training?
■ Helps actively?
■ Support/ suppression/ apathy?
■ Investment and funding?
Intervention is needed at social, governmental (national), and international) to reduce DD.
SOCIODEMOGRAPHIC FACTORS
■Socioeconomic status
■ Gender-Man dominates?
■ Age - older generation, less likely to use DT?
■ Education: School/ College/ University level?
■ Geographic dispersion/ distribution not every area has access to DT
■ Race/ Ethnic diversity- indigenous// tribal communities, minorities have less access (within them, rich has more access than poor), race in western countries (Black vs white)
■Religiosity may not be accepted by the people, as orthodox people are against birth control in BD [nothing related to DT is found yet]
■ Language - Internet is dominated by English, need more Bangla content and websites
USE
People's use of DT
■ Frequency: How frequently people use DT
■Time: How much time they use in online?
■ Purpose: Why they be in online? Entertainment/educational/ economic purpose?
■ Users' skills: do they have skills?
■ Autonomy of use: do they have to go to a certain location/can they use anywhere (cyber café/ wi-fi zone/ home)
LEVELS OF DIGITAL DIVIDE
■ According to van Deursen and Helsper (2015) - three levels of digital divide
■ First-Level Digital Divide:
* Focuses on individuals' access to ICT infrastructure, including dimensions like autonomy and continuity of access.
*** In our country- less people have access (38.9% people have internet connection)
In western countries more people have access
As more people gained access to this infrastructure, attention shifted to second-level divides.
• Third-Level Digital Divide:
Differs from first and second-level divides
Strategic access
If people have ability to transform their access to internet/DT into some purposes
If they have capacity to apply that for their benefit which may be in
Economic outcome job, e-commerce
✔ Social outcome - building meaningful friend network
✔ Political outcome - Online activism, political discussion, voting
✔ Health outcome - Is there any health benefit - doctor/ medicine access?
✔ Educational - outcome online courses
In societies with near-universal internet access, third-level divides have become more prominent.
DIGITAL INEQUALITY
■ DiMaggio and Hargittai (2001), suggest that the term "digital inequality" better captures the complexity of inequalities relevant to understanding the differences in access and use of information technologies.
■ Digital inequality considers variation on five dimensions:
differences in the technical apparatus people use to access the Internet, [type of devices (e.g., smartphones, computers, tablets)]
location of access (i.e. autonomy of use, access from home, work, public libraries, or other locations),
DIGITAL INEQUALITY DIMENSIONS
the extent of one's social support networks, (guidance, assistance, and resources from family, friends, or communities to navigate digital tools effectively)
the types of uses to which one puts the medium, (from basic activities like communication and information seeking to more advanced uses such as online education, e-commerce, or social networking) and
one's level of skill (technical skills, digital literacy, and the ability to navigate and utilize various online platforms effectively).
CONSEQUENCES OF DD
■ Every society has digital divide. When western society has divides, then Eastern society has bigger/ larger divides.
■ Students could not do online classes on pandemic time
■ When DD exists, some people are left behind.
■ In network/ information society, inequality increases, inequality in terms of digital access [e.g. online tickets only, for rail communication, Eid 2023]
SCREENING
■ Without a Net: The Digital Divide in America (2017) by Rory Kennedy [57 Minutes]
■ Available at: https://vimeo.com/281278048
09.05.24
LECTURE 8
Privacy and Surveillance
Objectives:
to discuss and learn about surveillance society/capitalism
The politics of algorithmic face recognition
# We are living in the age of a new form of capitalism, surveillance capitalism - Shoshana Zuboff
# Capitalism: a mechanism through which a small group of people accumulates wealth, exploiting others to maximize profit.
# Surveillance capitalism: the unethical (one-sided) claiming of private human experiences as free raw material for transition into behavioral data (Zuboff)
# the widespread collection and commodification of personal data by corporations.
# This form of information capitalism aims to predict and modify human behavior as a means to provide revenue and market control
# Surveillance capitalism challenges democratic norms and deports in key ways from the centuries-long evolution of market capitalism
Big Data Sources
-> Computer-mediated economic transactions arise from a variety of computer-mediated institutional and trans-institutional systems
-> data from billions of sensors embedded in a widening range of objects, bodies, and places (smart sensors and internet-enabled devices, drones, wearables, self-driving cars, nanoparticles)
-> corporate and government databases (banks, payment-clearing intermediaries, credit rating agencies, airlines, tax and census records, health care operations, credit card, insurance, pharmaceuticals, and telecom companies, etc.)
-> Private and public surveillance cameras, including everything from smartphones to satellites, street view on Google Earth
-> Google searches, iPod's music
Case study: facial recognition system
# an algorithmic surveillance system/technology
# Introduction of automated systems for the direct monitoring of human beings based on physical traits unique to individual
# biometric identification systems include gait recognition: fingerprint and palmprint recognition, and iris recognition
# Facial recognition is a silent technology
embedded
passive
surveillance is obscure
FRS Process
# process - image capture - recognition software - sent to the database for identification - image is matched with pre-stored data or not
# Facial recognition algorithms - two types
-> image template algorithms
-> geometry features
The politics of face recognition tech
# Langdon Winner (1980) argues that technology is political
# because technology by its very design, includes certain interests and excludes others
# Every technology is the result of political decision
# Bueno (2020), explored the politics of algorithmic face recognition technologies utilizing Deleuze and Guttan's notion of facility
Types of FRT
# Kelly Gates (2011) contends that facial recognition techs can be classified in two major types:
facial identification: linking the image to a face to a concrete individual
facial analysis: extracting info from the face
Types of Algorithm
# According to Hannah Fry (2018), there are two types of algorithm
Rule-based algorithms - designed by a programmer
ML algorithm - training process
# Facial recognition through ML involves training algorithms on large datasets
# machine themselves do not explain anything - one needs to analyze the collective apparatuses of which the machines are just one component [Gilles Deleuze, 1995]
Criticisms of FRT
# phrenology or craniology - skull structure
# physiognomy - face reading
# problems - misrecognition
~ google's photo app - classified African Americans as gorillas
~ Nikon's camera software - identified Asian people as 'blinking'
~ more controversial issue: criminal profiling and 'predictive' crime technologies - algorithms tend to classify African Americans with a higher probability of committing a crime - identifying potential criminals - machine bias [mug shots, police sketch]
~ technology is part of a political process
~ solution - a properly trained algorithm would be 'less racist' but it is not easy
~ algorithms are not neutral technology but instead a social mechanism
Ideological function of algorithmic technology
Gebm (2018) analyzed the training data sets of three major gender indications to avoid image image discon
??.24
LECTURE 9
Objective: cyber security and risk
# Information has been considered a significant aspect of power, diplomacy, and armed conflict for a long time
# Due to the proliferation of ICT in all aspects of life in post post-industrialist societies, since the 1990s, information’s role in international…
# We feel insecure in online systems because people want our information
# Information is the key resource in business, politics, conflict, and diplomacy
# Information security is congruent/similar/corresponding to industrial and national security
# When everything is digital, it is a matter of national security
# In war, a big part is cyber war
# Obtaining security information is a key challenge
# Cyberspace - key means of information - in a risk of insecurity
# Cyberspace has both virtual and physical elements
# The terms cyberspace and internet are used interchangeably
# But cyberspace encompasses more than just the internet
# The internet started as ARPANET in the 1960s
# It was not built with security in mind
# Cybersecurity is both about the insecurity created through cyberspace and about the technical and nontechnical practices of making it (more) secure
# Cyber attacks are the main focus of the cyber security discourse
# Attackers are called hackers
# The umbrella term for all hacker tools is malware (malicious+software): viruses, worms, trojan horses
# Main goal - full system control, delay, disrupt, corrupt, exploit, destroy, steal or modify information
# The most dangerous malware is tailored to a specific target for high-effect
# The large majority of attacks remain fairly unsophisticated and go after small or medium-sized targets
3 discourses of cybersecurity - technical, cybercrime/espionage, cyber warfare
Technical discourse
The cybersecurity discourse was never static because the technical aspects of information infrastructure are constantly evolving
Concerned with malware and system intrusion
Main referent object: computer, computer networks
Attacking took in work: Morris Worm 1980
Consequence: CERT
Prevention: technical measures
Cybercrime and cyber espionage
Closely related to technical discourse
Cybercrime: any crime that involves computers and networks, like a release of malware or spam, fraud, etc
Notions of computer-related economic crimes determine the discussion of computer misuse
Main actors: law enforcement, intelligence
Main referent object: business networks, classified information
Three trends
Semi and organized crime: theft etc
Cyber espionage: penetration of gov and business computer systems e.g. china to the west
BD bank either swift code problem or inside compromisation?
Prevention: (i) Legal tools, we need to develop laws/ICT acts, (ii) infrastructures
Military-civil defense discourse: cyber-war
The Gulf War of 1991 created a watershed in US military thinking about cyber war
Physical force alone was not sufficient but was complemented by the ability to win the information war
US vs China over Taiwan issue: semiconductor industry
Information is completely a military measure
Cyber warfare is a fuzzy area because it is done but hidden, nobody takes responsibility
1999: NATO against Yugoslavia
Stuxnet: US vs Iran
Three terms related to cyber-warfare
Cyber offense: first attack
Cuber defense: protection system
Cyber deterrence: both parties are capable
Types of cybercrime
Identity theft, cyberbullying, cyberstalking, phishing, ransomware
Deepfake and Disinformation
Highly realistic and difficult to detect digital audio and video content
Widely used to spread fake information
Product of AI, based on deep learning [deepfakes web, reface, my heritage]
Misinformation: false or inaccurate information— getting facts wrong
Disinformation: false information, deliberately intended to mislead
Commercial and free deep fake services: used in politics, war
To expose: having forensic technology, that can detect fake content, authenticate content before spreading it, sharing after checking
Studying digital security to understand Bangladesh's perspective
23.05.24
LECTURE 10
Hegel's notion of subject, object
Labour in capitalism
# In class societies, labor is organized in such a way that product of labor and surplus labor, exceeding what's necessary for basic needs, is appropriate and owned by a dominant/capitalist class
# Labours sell labor powers as commodity to the capital/profit
# Commodification = use value → exchange value
# Surplus labor: which is not paid but one put labor to produce
Market
Surplus labor → profit
# This process leads to various forms of alienation
From the product (no control over product)
From the labor process (no contro over labor processl)
From oneself (him/herself becomes alien to self)
From other human (cannot connect with other people)
# De-alienation: abortion of private property
# Marx's theory of work and labor can be applied to online platforms like facebook
FB and online media makes profit by the exploitation's user's labor and commodification of personal data
# Marx - dual character of labour, as concrete work (produces use value), and abstract labour (generates value/exchange value)
# In FB, people write and their life and objectify their subjective experience
Works require information process, and information creation is itself a work process [book or gardening]
# Every work process requires cognition, communication, and cooperation as tools production
# According to Marx in order to speak of work, there must be an interaction of labour power with objects and instruments of work so that use-values are created as products
Digital Labour
Alienation of labout power: societal pressure
Alienation of instrument of labour: platform is not controlled
Alienation of object of labour: shared experience goes away
Alienation of product of labour: social need of community + profit for FB
# Fetish commodity takes on an inverted form
# Commodity character of FB is hidden behind social use value of FB (exchange value gets hidden)
# There is class relationship (exploitative relationship) between FB and its users (users have no control)
# Social media transform leisure time into labour and profit
Relationship between play, labour and pleasure
# In different social system, people's satisfaction is delayed
# But in capitalism, in the age of FB, people get immediate social satisfaction
# In other social system
Both labour (= use value) and work (= exchanhe value) at the same time
New media and culture identity
# Internet: from military to vox populi
# New media: broad array of modern information and communication technologies, including was media, social media, digital platforms for message delivery
# Internet exemolifies postmodern phenomenon disorganized, non-hierarchical information
New media
# Catchall term
# Remediation: appropriates the techniques, form and social significance of previous media
Reshaping cultural identity narratives
Global reach
Third culture: facilitates by exchange
Virtual communities - online gaming communities
Context - less culture
Media's Role in Cultural Change
Transformation: shifting cultural indentities
Global public sphere
# Moral panic and identity crisis
Threat of losing essential human existence
# Cultural assimilation and homogenization
Network individuals
# Commodification and commercial interest
Cultural festivals, global brands and consumersim
# Digital virtual culture and social isolation
Influencer culture
Future Outlook
Preservation and enrichment of cultural diversity
Smithonasian's digital archive
Culture industry concerns
Trusted media
30.05.24
LECTURE 11
New Social Movement
Objective: To discuss and learn about NSM
The nature of contemporary social movement Ricardo (1997), Markham (2014)
Social movement
A collective action to realize some kind of demand
In the industrial era, following a Marxist logic, social movements were believed to be centered in the working class
Working class movements were seen as actions concerned with matters of economic redistribution. Those were formal and organized
But NSM - collective action
Characteristics: informal, disorganized, fragmented, decentered, no organization, no central leader
The central claims of the NSM paradigms are–
NSMs are unique and, as such, different from those of the industrial age
i.e. contemporary movements are fundamentally different than movements of the past
NSMs are a product of the shift to a postindustrial economy
Ideology and Goals
Prioritize life and lifestyle concerns over economic redistribution
e.g. environmental movement
Challenge traditional domestic structures
Tactics
Often employ disruptive tactics and mobilize public opinion
Exticnciton rebellion uses non-violent direct action to draw attention to the urgency of climate change
High dramatic symbolic form
e.g. women’s march, wardrobe, slogan
Structure
Non-hierarchical, decentralized
No trust in the bureaucratic system
Participants
The new middle class in the service sectors
No class boundary, marked by social concern
Black lives matter
Origins of NSM
Objective school: stresses social structural factors that formed new social classes as an oppositional group
Change in capital accumulation
State intervention into civic life
Resistance to cultural domination; self-defense of society against the state and market economy
Mouffe (1984) links it to
The commodification of social life
Bureaucratization: a form of dominion
Cultural massification: against the pervasive influence of mass media, homogenization to preserve cultural spaces and identities
Subjective school:
Value shift hypothesis: origin is culture, centers on the notion that Western society after achieving economic and political security, shifts its focus to personal growth and self-actualization
The cycle of protest argument: nothing new, recent manifestation of old protests responding to changing cultural climate and social events
Social media and protests
How does social media facilitate movement?
# Wofsed et al. (2013) - new tech provides movements with powerful, speedy, low-cost tools for
Recruitment, fundraising, distribution of image and info
Collective discussion
Mobilization for action
Three types of people
Cyber enthusiasts
Optimistic view: optimistic about the potential of new media to empower individuals in nondemocratic societies and to help insurgents adopt new strategies creating new kinds of political selves
Cyber skeptics
Crucial perspective: new media provide a false sense of participation, discouraging actual physical protests. Also, it can be the tool of repression
Contextualists
Emphasize the impact that political, social, and economic variations have on the role of the social media in collective action
Anderson (2011): The key to arab spring was not technology but how the technology resonated in the various local contexts.
Hussain and Howard (2012): Gulf states show high levels of social media and low levels of protest
Social Media and Arab Spring
Markham (2014) argues the term stands problematic
Overestimation of social media’s agency
Emphasis on structurelessness in protest cultures
Resistance to over-determination and objectification: avoiding objectivity or historically situating protests
Argument
Schetman (2009) points out that Twitter revolution in Iran overestimates the role of Twitter in Western media
Belin (2012) says Arab Spring was not created by social media [contextualists]
Long-standing grievances
An emotional trigger
A sense of impunity
Access to new social media
LECTURE 12
■ Michael Kwet (2019) Digital colonialism, whereby foreign corporations undermine local development, dominate the market, and extract revenue from the Global South, with power obtained primarily through the structural domination of digital architecture, which leads to more general forms of imperial control.
■ Under digital colonialism, foreign powers, led by the US, are planting infrastructure in the Global South engineered for their own needs, enabling economic and cultural domination while imposing privatised forms of governance.
■ To accomplish this task, major corporations design digital technology to ensure their own dominance over critical functions in the tech ecosystem.
This allows them to accumulate profits from revenues derived from rent (in the form of intellectual property or access to infrastructure) and surveillance (in the form of Big Data).
■ It also empowers them to exercise control over the flow of information (such as the distribution of news and streaming services), social activities (like social networking and cultural exchange), and a plethora of other political, social, economic and military functions mediated by their technologies.
■ Sources of digital domination: Control over software, hardware and network connectivity
■ Digital forms of power are linked through the three core pillars of the digital ecosystem: software, hardware and network connectivity.
■ Software is the set of instructions that define and determine what your computer can do.. (Control over software, free, paid)
■ Hardware is the physical equipment used for computer experiences. (Control over hardware can take at least three forms: software run on third-party servers, centralised ownership of hardware, or hardware designed to prevent users from changing the software.)
The network is the set of protocols and standards computers use to talk to each other, and the connections they make. (Net neutrality regulation proposes that Internet traffic should be 'neutral' so that Internet Service Providers (ISPs) treat content flowing through their cables, cellular towers and satellites equally. Net neutrality prevents this form of discrimination and protects the end user's freedom to utilise the Internet as they wish, without third-party favouritism, blocking, or throttling.)
DATA COLONIALISM
■ Data colonialism: a new form of colonialism distinctive of the twenty-first century
■ Not an echo or simple continuation of historic forms of territorial colonialism.
■ Data colonialism combines the predatory extractive practices of historical colonialism with the abstract quantification methods of computing.
■ Capitalism currently depends on this new type of appropriation.
It works at every point in space where people or things are attached to today's infrastructures of connection.
■ Over the long-run historical colonialism provided the essential preconditions for the emergence of industrial capitalism,
■ The appropriation of human life through data will be central to data colonialism.
■ This provides the preconditions for a new stage of capitalism.
■ Data relations: new types of human relations that enable the extraction of data (allow data to be collected) for commodification (to turn into commodities).
■ "In all over the world, data relations have made social life a readily available resource for businesses to extract data and commodify.
■ These global flows of data are as expansive as historic colonialism's appropriation of land, resources, and bodies, although the epicenter has somewhat shifted.
■ Data colonialism involves two poles of colonial power: the United States and China. Complicates geographical understanding of global order.
DATA COLONIALISM- UNIQUE FEATURE
The new data colonialism works both externally-on a global scale-and internally on its own home populations.
■ The difference between the early form of colonialism and the current one is that, now, data colonialism is done both outside and inside. Benefits from both home people and world people [Baidu/Alibaba/Tiktok - China and the World]
■ The elites of data colonialism (think of Facebook) benefit from colonization in both dimensions, and North-South, East-West divisions no longer matter in the same way.
THE MECHANICS OF DATA COLONIALISM
THE NATURALIZATION OF DATA CAPTURE
■ Ideological Framing:
➤ Data is often referred to as the "new oil," suggesting that it is a valuable raw material that is simply waiting to be harnessed by corporations. This metaphor obscures the processes of data collection and appropriation.
■ The World Economic Forum (WEF) and other influential bodies promote the idea that personal data has intrinsic value, reinforcing its naturalization as a resource.
> Metaphorical Blurring: Data is often seen as "exhaust" from people's lives, implying it cannot be Metaphor owned by anyone.
➤ Social Rationality: Much of the labor involved in data extraction is considered valueless, merely "just sharing."
Practical Rationality: Corporations are seen as the only entities capable of processing and appropriating data.
Political Rationality: Society is positioned as the natural beneficiary of corporate data extraction, similar to how historical colonialism was justified as a "civilizing" mission for humanity's benefit.
■ Legal and Philosophical Frameworks:
➤ Historical analogies are used to justify data capture. For instance, the concept of terra nullius (land belonging to no one) was used to justify colonial land appropriation. Similarly, data is treated as "just there," available for exploitation without significant ethical or legal challenges.
THE MECHANICS OF DATA COLONIALISM
THE NATURALIZATION OF DATA CAPTURE
■ Discursive Practices:
Complex and often incomprehensible Terms of Service agreements are used to embed individuals in data relations. These documents make appropriative claims that most users do not fully understand, yet are compelled to accept. [Facebook, Google]
➤ The language and discourse around data capture emphasize its inevitability and benign nature, making it seem like a normal part of modern life.
In earlier times, colonizing countries took the consent of people to do things either by force or in other ways. Now, these companies do so by using a 'terms of services' agreement.
■ Reconfiguration of Social Relations:
The flow of everyday life is transformed to enable data capture. This involves designing social interactions, online behaviors, and even physical environments in ways that facilitate continuous data collection.
➤ Personal data is appropriated for purposes that are not personal, often serving corporate interests rather than the interests of the individuals from whom the data is collected.
MODES OF EXTRACTION IN DATA COLONIALISM
■ Data colonialism involves a profound shift in social relations, resembling historical colonialism in resource appropriation, ideology, and corporate profit concentration. This transformation integrates human life into capitalism through three main modes of extraction:
■ Digital Platforms: These platforms transform the social realm into data that can be tracked, captured, and valued. This process extends marketization into everyday life, transforming ordinary social interactions into data ready for appropriation and financialization. [Annexation of life to capital]
Data-driven logistics: The integration of continuous data collection and large-scale data processing into various areas of production and work. Continuous data collection and processing have redefined work management, incorporating digital platforms and underpaid labor (e.g., gig economy) into a broader system of data-driven logistics.
Self-tracking: Individuals monitor their own activities for data extraction, sometimes voluntarily (health metrics) or as a job requirement (Office info, Driving license, Passport). This self-data collection underpins new forms of discrimination and inequality.
RESULTS OF DATA COLONIALISM THE COLONIZED SELF
■ Data colonialism's pervasive tracking threatens personal autonomy and the integrity of the self.
■ This tracking invades personal privacy and transforms how individuals experience and understand their own lives.
■ It transforms the self into a constant data subject, risking the loss of personal identity and freedom.
This continuous data collection undermines the basic conditions for human autonomy. highlighting the need to defend personal integrity against these invasive practices.
As data collection becomes pervasive, individuals often have little control over how their personal information is used or interpreted. This constant surveillance can undermine their sense of self and personal freedom.
■ The self is seen as colonized because the very essence of personal identity is influenced by the data collected about an individual. The data-driven insights and judgments made by corporations or other entities affect how individuals are perceived and treated.
LENIN'S FIVE-POINT DEFINITION OF CAPITALIST IMPERIALISM
■ Concentration of production and capital: developed to such a stage that it creates monopolies which play a decisive role in economic life;
■ Merging of Bank Capital with Industrial Capital: creates a financial oligarchy. Finance capital becomes the dominant form of capital, wielding significant influence over economic and political decisions.
■ Importance of capital export over commodity export: Capitalist countries invest in foreign markets, seeking higher returns and new opportunities for exploitation.
■ Formation of international capitalist monopolies: These monopolies share the world among themselves. They collaborate and compete to control global markets and resources, leading to economic and political alliances.
Territorial division of the world among major capitalist powers: This division involves the struggle for colonies and spheres of influence, reinforcing the dominance of powerful capitalist nations over weaker regions. [In Imperial Age, World was divided into territories of England/Portugal/French]
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