Why is data not inherently objective?
Data is selected, filtered, interpreted, and visualized; it reflects choices in what to collect, how, and why.
Weather data collected only at noon in Brantford may give a biased view of daily temperatures if morning/evening data are ignored.
What is digital enclosure?
Means our everyday lives are increasingly captured and controlled through data.
Samsung Family Hub fridges collect data and display personalized ads on idle screens.
What is the promise of big data, and what are the potential issues?
Companies like Google or Meta claim big data brings convenience (e.g., auto-scheduled health checks, perfectly timed buses).
Issues:
Privacy loss
Dependence on companies
Loss of freedom and critical thinking because choices are predicted and shaped
A navigation app predicting your route and nudging you to take certain stores or restaurants based on your data.
What is digital enclosure in urban space?
Efforts to replicate the digital experience in physical cities (e.g., Google Sidewalk Labs) using AI, sensors, and connectivity, often funded by advertising and tracking citizens’ behaviors.
Cities use cameras, sensors, and GPS data to monitor traffic flow, public transport, and pedestrian movement.
Based on older “enclosure” ideas
First enclosure – taking common land and making it private (in medieval times).
Second enclosure – controlling knowledge through intellectual property.
Digital enclosure – controlling data and digital spaces, turning our online actions into profit.
What does Andrejevic’s “recession of the social” describe?
technology lets us connect more but also makes our interactions less clear, more distant, and controlled by companies and data tracking.
A doodle poll shares your info with 144 companies — small social act, big data capture.
How does the data divide relate to the recession of the social?
The data divide creates asymmetrical power: platforms know more about us than we know about them, reinforcing the distancing and control of social interactions.
Facebook/Meta collects behavioral data for advertising while users remain largely unaware of its scope or use
Examples of “Recession of the Social”
- RealPage (YieldStar):
Software that helps landlords maximize rent prices using data analytics.
Removes human empathy → raises rents → harms social fairness. - Skip-lagging (airline example):
People book cheaper connecting flights but skip the second leg.
Good for traveler, but messes up airlines’ planning, causes higher prices or bans.
Shows how algorithmic systems affect social trust and fairness.
- CityBike “Station Flipping”:
Program rewarded users for moving bikes to balance stations.
People gamed the system—moved bikes back and forth for money.
Result: System imbalance, not improvement → another example of tech eroding cooperation.
What does Google’s “Selfish Ledger” demonstrate about digital data?
Personal data can be used like a “digital genome” to guide and shape behavior, showing how platforms can control choices and create a form of digital enclosure.
“recession of the social” main idea
Digital tools make us more connected but also more controlled. Algorithms and platforms quietly shape what we do, eroding social trust, empathy, and autonomy
What does “If you’re not the customer, you’re the product” mean?
Users’ data becomes the product companies sell to advertisers or others.
What does “data is the new oil or gold” mean?
It compares data to a valuable raw material that fuels economic systems.
Why is data collected without a clear reason?
Because it might become valuable later — data has potential economic worth.
Capital vs Commodity
Commodities: C-M-C (Commodity → Money → Commodity for use).
Capital: M-C-M’ (Money → Commodity → More Money — continuous accumulation).
Data fits the capital model (M-C-M’) — collected to generate endless value.
What are the main ways companies derive value from data according to Sadowski?
- Profile and target people – e.g. Meta showing you ads for shoes after you browse them online.
- Optimize systems– e.g. Amazon using data to predict what products to restock or recommend.
- Manage and control things– e.g. Fitbit or Apple Watch tracking steps and health goals.
- Model probabilities– e.g. predictive policing forecasting where crimes might happen.
- Build new things– e.g. training generative AI or self-driving cars with huge datasets.
- Grow asset value – e.g. Tesla collecting data from cars to improve future models and software updates.
What is the “liquification of the physical world”?
physical assets are turned into data commodities that can be tracked, indexed, and traded digitally.
Smart thermostats (like Nest) or cars constantly send usage data to companies, turning real-world activity into digital information for profit.
What does “dark data” mean, and why do companies want it?
“Dark data” is unused or hidden data that’s collected but not yet analyzed — seen as a huge business opportunity.
Sensors in hospital beds or railway tracks collecting data that could later be sold or used to improve efficiency and maintenance.
What does Sadowski mean by data as extraction?
It means data is taken from people and systems without fair consent or compensation, creating power imbalances between users and corporations.
What is accumulation by extraction?
It’s the process of collecting as much data as possible from all sources to drive profits and control — regardless of user consent or awareness.
Smart home devices like Alexa or Ring gather voice and motion data continuously, which companies use to train AI models and target ads.
