Mediacom 1020 quiz review

The Rise of the Information and Service Economy (Jan 27 & 29 — Hardt & Negri)

The Three Economic Paradigms

Economies historically move through three dominant systems:

  1. Agricultural Economy (Pre-modern)

    • Economy dominated by agriculture and resource extraction (farming, mining).

    • Most people work in food production or raw materials.

  2. Industrial Economy (Modernization)

    • Economy dominated by manufacturing and durable goods.

    • Modernization is often treated as industrialization.

    • Labour shifts from farms to factories.

  3. Information / Service Economy (Postmodernization or Informatization)

    • Economy dominated by services, information, knowledge, and communication.

    • Labour shifts from factories to service, communication, and knowledge work.

    • Important: Industrial production does not disappear; it is transformed, just like agriculture was transformed during industrialization.

Informatization

Informatization refers to the shift where information, communication, and knowledge become central to economic production.

Examples of Informatization:

  • Software development

  • Customer service

  • Social media management

  • Data analytics

Hardt & Negri argue that this shift changes how humans understand themselves. Instead of modeling ourselves after machines (industrial age), we now model ourselves after cybernetic systems, characterized by:

  • Feedback loops

  • Information processing

  • Communication systems

Production Changes: Fordism → Toyotism

Fordism

Fordism refers to mass production of standardized goods, with key characteristics including:

  • Assembly-line production

  • Large inventories

  • Little communication between production and consumers

  • Demand assumed in advance

  • Example: Ford Model T production.

    • Hardt & Negri state that Fordism had a "mute relationship" between production and consumption because factories did not need to constantly listen to the market.

Toyotism

Toyotism reverses Fordism, characterized by:

  • Just-in-time production

  • Minimal inventory

  • Constant communication with the market

  • Production responds immediately to consumer demand

  • Example: Modern car manufacturing where production changes based on real-time orders.

    • Key idea: Manufacturing becomes treated like a service.

Changes in Labour

Immaterial Labour

Immaterial labour produces intangible goods rather than physical objects.

Examples of Immaterial Labour:

  • Knowledge

  • Cultural products

  • Communication

  • Software

  • Media content

Impact of Computers on Labour:

  • Workers used to imitate machines.

  • Now workers interact with cybernetic systems and digital networks.

New Division of Labour within Immaterial Labour

Highest Value Tasks:

  • Problem-solving

  • Strategy

  • Innovation

  • Decision-making

Lowest Value Tasks:

  • Routine digital tasks

  • Data entry

  • Basic information processing

Affective Labour

Affective labour produces emotional experiences or feelings.

Examples of Affective Labour:

  • Healthcare workers providing care

  • Customer service representatives

  • Entertainment industry workers

  • Social media influencers

Product of Affective Labour:

  • Emotional experiences such as happiness, comfort, excitement, satisfaction.

The Surveillance Economy (Feb 3 & 5 — Zuboff)

Instrumental Rationality

Instrumental rationality is a way of thinking focused solely on the most efficient means to reach a goal, without considering ethics or human consequences.

Characteristics include:

  • Means-end calculation

  • Treats people and nature as resources to exploit

Example:

  • A company maximizing profit regardless of worker conditions.

Surveillance Capitalism

According to Shoshana Zuboff, a new economic system has emerged:

Industrial Capitalism

  • Raw material = natural resources and manufactured goods

Surveillance Capitalism

  • Raw material = human data and behavior

Key quote:

  • "We are not the users. We are being used."

  • Companies collect behavioral data and sell predictions about our actions.

Behavioral Surplus

Behavioral surplus refers to extra data collected beyond what is necessary for a service.

Example:

When using Google Search, data collected includes:

  • Location

  • Browsing habits

  • Typing patterns
    This extra data becomes the real commodity.

Metadata

Metadata is data about data.

Examples of Metadata:

  • Time you send messages

  • Typing speed

  • Punctuation habits

  • Location history

Value of Metadata:

  • Allows profiling and pattern analysis.

    • Example: Small behavioral patterns can predict personality traits or consumer preferences.

Behavioral Futures Markets

Companies sell predictions of future behavior.

Example:

  • Advertisers pay for predictions regarding:

    • Who will buy a product

    • Who will click an ad

    • Who is politically persuadable
      These predictions are traded in behavioral futures markets.

Smart Devices and Data Flows

Smart devices (smart homes, voice assistants) create massive data flows.

Example:

Installing a smart thermostat may send data to:

  • Manufacturers

  • Advertisers

  • Data brokers

  • Third-party partners
    What may appear simple is part of a hidden data supply chain.

Instrumentarian Power

Zuboff describes a new form of power characterized by control over behavior/malicious interaction without violence or coercion. Companies achieve this through:

  • Tuning

  • Nudging

  • Herding

  • Coaching

Goal:

  • Achieve predictable consumer behavior and guarantee profit outcomes.

Danger:

  • If algorithms replace political decision-making, democracy may weaken.

The Materiality of AI (Feb 10 & 12 — Crawford & Joler)

Dependence of AI

AI appears abstract but depends on massive physical systems.

Types of Artificial Intelligence

Top-Down AI

  • Rule-based AI systems characterized by:

    • Uses explicit rules

    • Symbolic reasoning

    • Pre-programmed knowledge

    • Example: Early chess programs.

Bottom-Up AI

  • Neural networks trained using examples, characterized by:

    • Machine learning

    • Iterative improvement

    • Pattern recognition

    • Example: Image recognition systems.

The Turing Test

Proposed by Alan Turing to determine if a machine can demonstrate human-like intelligence through conversation.

Criteria:

  • If a human cannot distinguish the machine from a human, it passes the test.

Anatomy of an AI System

Researchers Kate Crawford and Vladan Joler argue that AI systems involve huge hidden infrastructures and analyze AI through three stages:

  1. Birth — extraction of raw materials

  2. Life — data processing and algorithmic work

  3. Death — disposal and electronic waste

    • Even simple AI interactions rely on global supply chains.

Example:

  • Asking a voice assistant a question involves:

    • Mining metals

    • Factory labor

    • Software engineering

    • Data centers

    • Cloud infrastructure

Fractal Supply Chains

AI supply chains are nested systems of production.

Example Structure:

  • Mining raw materials

  • Processing metals

  • Manufacturing components

  • Assembling devices

  • Distributing products

  • Running cloud infrastructure

Each level produces profit and environmental/social costs.

Mechanical Turk

Originally a fake chess machine with a human hidden inside. Today, it refers to platforms where humans perform microtasks for AI systems.

Examples of Tasks:

  • Labeling images

  • Moderating content

  • Data tagging
    These workers are often hidden behind the appearance of automation, sometimes described as “artificial artificial intelligence.”

Biodata and Bias

AI systems collect various forms of personal data, including:

  • Biometric data

  • Behavioral data

  • Social data

  • Psychological data

Problems:

  • Datasets often reproduce historical biases and stereotypes.

    • Example: Image datasets labeling men as leaders and women as assistants.

Enclosure and Meta-Value

Companies capture human knowledge and activities to create AI systems, a process called enclosure.

  • Even if data is public, companies own the meta-value, which includes:

    • The trained AI model

    • The algorithm built from the dataset

Political Economy of Media (Feb 24 – Mar 5)

Political Economy of Media

This approach studies media within economic and political systems, shifting the focus from meaning to questions of:

  • Who owns media?

  • Who profits?

  • How power shapes communication?

Media Industries

Media industries operate like manufacturing systems characterized by:

  • Production-line structure

  • Dominance of large corporations

  • Smaller companies competing for leftovers

Dual Markets

Media companies sell to two markets:

  1. Audiences

  2. Advertisers

Conflict:

  • Content may prioritize advertisers over audiences.

    • Example: Social media platforms maximizing engagement to sell ads.

Dialectics

Dialectics explains change through conflict between opposing forces, represented as:

  • Thesis → Antithesis → Synthesis

Example:

  • Thesis: Industrial capitalism

  • Antithesis: Worker resistance

  • Synthesis: Labour regulations

Perspective:

  • According to Vincent Mosco, media must be analyzed through both power dynamics (corporations, governments) and resistance (workers, audiences).

Commodification

Commodification is the process of turning something valued for use into something valued for exchange (profit).

Example:

  • Telling a story to family = use value

  • Selling the story to a publisher = exchange value

Forces driving commodification include:

  • Corporations

  • Advertising industries

  • Government policies supporting markets

Quantification and the Commodified Self

Digital technology allows for enormous amounts of data to be collected, stored, analyzed, and monetized.

Example:

  • A voice assistant request has use value (playing a song) but becomes exchange value when companies monetize the data.

Audience Labour

Media companies sell audiences to advertisers, meaning audiences produce economic value simply by:

  • Watching

  • Clicking

  • Browsing

  • Engaging

Users are effectively unpaid workers.

Playbour

Playbour combines play and labour, where activities that seem like hobbies create economic value.

Examples:

  • Gaming communities

  • Fan content creation

  • Bug testing

  • Online feedback

Extreme example:

  • Gold farming in video games.

Myths of Technology and Progress

Myth (Roland Barthes)

A myth simplifies complex social systems, making them appear natural and inevitable.

Characteristics:

  • Myths remove politics and conflict.

Example:

  • “Technology automatically improves society.”

Technological Sublime (Leo Marx / David Nye)

The technological sublime refers to an overwhelming emotional awe toward technology.

Historically Applied To:

  • Railroads

  • Dams

  • Airplanes

Today Applied To:

  • AI

  • Cyberspace

  • Digital networks

Why Technology Myths Matter

Advertising and media promote myths about technology.

Example:

  • Predictions from 1949 claimed nuclear technology would eliminate poverty, war, famine.

    • Similar promises are now made about digital technology and AI.

Distinction:

  • Political economy explains how the system works, while myths explain why people believe in it.

Quick Key Term Definitions

  • Informatization: Shift to an economy centered on information, communication, and services.

  • Fordism: Mass production of standardized goods through assembly-line manufacturing.

  • Toyotism: Flexible production system based on just-in-time manufacturing and real-time market feedback.

  • Immaterial Labour: Work producing intangible goods like knowledge, communication, or cultural products.

  • Affective Labour: Work that produces emotions or experiences (care, entertainment, satisfaction).

  • Surveillance Capitalism: Economic system where companies collect behavioral data to predict and influence actions.

  • Instrumental Rationality: Efficiency-focused thinking that ignores ethical or human consequences.

  • Behavioral Futures Markets: Markets where predictions of human behavior are bought and sold.

  • Top-Down AI: Rule-based artificial intelligence systems.

  • Bottom-Up AI: Machine learning systems trained using data examples.

  • Mechanical Turk: Hidden human labor behind supposedly automated AI systems.

  • Commodification: Turning use value into exchange value for profit.

  • Quantification: Converting human behavior into measurable data.

  • Audience Labour: Economic value created by media audiences through attention and engagement.

  • Playbour: Hobby or entertainment activities that produce economic value.

  • Technological Sublime: A sense of awe and emotional power associated with new technologies.