Computer Science
Grade 9
20 min
Data Collection and Surveillance: Understanding the Impact
Students will explore the ethical implications of data collection and surveillance technologies.
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Introduction & Learning Objectives
Learning Objectives
Define data collection, surveillance, and digital footprint.
Identify at least three different types of personal data collected by websites and apps.
Explain the difference between first-party and third-party data collection.
Analyze the benefits and drawbacks of data collection for individuals and society.
Evaluate the ethical implications of a common surveillance technology (e.g., targeted advertising, public cameras).
Propose two strategies to better protect their personal data online.
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In this lesson, we will explore how our digital information is gathered and monitored, a process known as data collection and surv...
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Key Concepts & Vocabulary
TermDefinitionExample
Data CollectionThe systematic process of gathering information about specific individuals or groups from various sources.A social media app collecting your name, birthdate, and location when you sign up for an account.
SurveillanceThe close monitoring of the behavior, activities, or data of a person or group.A school using software to monitor students' web browsing on school computers, or a city using public security cameras.
Digital FootprintThe trail of data you leave behind when you use the internet. This includes websites you visit, emails you send, and information you submit to online services.Your search history, social media posts, photos you've been tagged in, and online shopping history all form your digital footprint.
Personally Identifiable Infor...
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Core Syntax & Patterns
The Data Trade-off Principle
Convenience/Free Service <=> Personal Data
This pattern describes the common exchange in the digital world. Users get a 'free' service (like social media or a search engine), and in return, the company collects user data to sell ads or improve its products.
The Profiling Algorithm Pattern
Data Point A + Data Point B + ... => Inferred Profile
Algorithms combine multiple, seemingly harmless pieces of data to create a detailed profile about you. For example, your location data, search history, and 'liked' posts can be used to infer your interests, income level, and political views.
The Consent Pattern
Action -> Request for Consent -> Data Collection
Websites and apps are often required to ask for your permi...
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Challenging
How does the 'Data Trade-off Principle' strengthen the argument against the 'I Have Nothing to Hide' fallacy?
A.It proves that having something to hide is the only reason to want privacy.
B.It shows that 'free' services are a myth and that data collection is always harmful.
C.It highlights that you are giving up a valuable asset (your data) which can be used to influence you, making control over it important regardless of your actions.
D.It demonstrates that only paid services respect your privacy.
Challenging
When evaluating the use of public surveillance cameras with facial recognition, what is the most critical ethical balance to consider?
A.The cost of the cameras versus the cost of the electricity to run them.
B.The potential for increased public safety versus the erosion of individual privacy and potential for misuse.
C.The camera's video quality versus its data storage capacity.
D.The brand of the camera versus the brand of the software used for recognition.
Challenging
Based on the 'Ignoring Terms of Service' pitfall, if you were to skim a new app's privacy policy, which sentence would be the most critical to pay attention to?
A.'We may share or sell your data, including location and browsing history, with our third-party advertising partners.'
B.'We are committed to providing you with the best possible user experience.'
C.'This policy is effective as of January 1st and may be updated in the future.'
D.'Our service is intended for users who are at least 13 years of age.'
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