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Why?

This lesson helps equip students with a nuanced understanding of how technology intersects with everyday life. It introduces them to key concepts in modern digital marketing, and fosters critical thinking about the ethical implications of AI, such as privacy, autonomy, and fairness. By engaging with real-world scenarios and ethical dilemmas, students develop a deeper awareness of the digital landscape they interact with daily, preparing them for informed and responsible digital citizenship. This provides a crucial combination for students growing up in a rapidly advancing digital age, ensuring they become thoughtful consumers and ethical users of technology.

Materials Needed

Materials Needed

Computers with internet access for students to use in the simulation

Time needed

Time needed

60 - 75 Mins

Objectives

  • Students will be able to identify and describe ethical concerns associated with personalized marketing, including privacy and data security.
  • Students will be able to evaluate the benefits and challenges of personalized marketing.
  • Students will be able to propose solutions or strategies to address ethical dilemmas in AI-driven personalized marketing.

Key Concepts & Vocabulary

  • Personalized Marketing: Tailoring marketing efforts to individual customer preferences and behaviors.
  • Echo Chamber: Exposure to information aligning with one’s existing beliefs, limiting diverse views.
  • Price Discrimination: In this context, using demographic data to market differently-priced products to different people.
  • Data Security: Protecting digital data from unauthorized access, corruption, or theft.
  • Data Transparency: Openness and clarity about processes or operations

Lesson Components

  1. Before You Watch: Connect lesson to background knowledge of AI-driven marketing and get students’ attention 
  2. Video: Show the pedagogy.cloud video explaining the ethical considerations in the topic of personal marketing
  3. Case Study: Detail a real-world scenario of Netflix using personal data to provide future viewing suggestions.
  4. Simulation: Lead students through an interactive activity exploring the idea of tracking web data.
  5. Discussion: Ask whole-class questions to reflect on experience and consider perspectives.
  6. Assessment: Verify student understanding with an exit ticket

Warm up

Mystery Shopping Bag Scenario

Tell the students you have a “Mystery Shopping Bag” (imaginary) that claims to know the perfect item for each student in the class. Ask students to “guess” what might be inside the bag for them. Then, lead them to ponder how the bag could possibly “know” their preferences.

Case Study

Distribute or read Case Study handout.

Summary:  Netflix’s personalized recommendation system, powered by AI, analyzes users’ watching habits to tailor content suggestions, offering convenience but raising concerns about privacy and the potential creation of echo chambers. This dilemma highlights the need for transparency in data usage and user control over personal data, as well as adjustments to the algorithm to introduce a wider range of content and prevent limiting viewers’ exposure to diverse material. While Netflix’s AI-driven personalization enhances user experience, it also prompts critical reflection on the balance between technological benefits and the preservation of privacy and content diversity.

Student Handout

Case Study: Netflix’s Personalized World

Imagine you’re settling down for a movie night. You turn on Netflix, and it suggests a list of movies and shows that perfectly match your taste. Sounds convenient, right? But have you ever wondered how Netflix knows so much about what you like? This scenario brings us to a fascinating dilemma: while personalized recommendations make our lives easier, they also raise questions about privacy and the influence of AI on our choices.

 

Background Information: Netflix, a popular streaming service, uses Artificial Intelligence (AI) to analyze your watching habits. Every show you watch, every rating you give, and even the time you spend on each title, feeds into a complex algorithm. This algorithm is like a smart assistant, constantly learning your preferences to suggest content you might enjoy. While this personalization is helpful, it’s essential to understand the implications of such extensive data collection and how it shapes our viewing habits.

 

Problem Analysis: The challenge revolves around two issues: privacy and the creation of “echo chambers.” On the privacy front, the concern is about how much personal information Netflix gathers and what they do with it. It’s like having someone who watches over your shoulder, taking notes on everything you watch! Then, there’s the echo chamber effect. By always suggesting things based on your past choices, Netflix might limit your exposure to diverse content, potentially narrowing your worldview.

 

Possible Solutions: One solution could be more transparency from Netflix about their data use. If users better understand what data is collected and how it’s used, they might feel more comfortable with the personalization. Another approach could be giving users more control over their data, like options to opt-out of certain types of data collection.

On the echo chamber issue, Netflix could tweak its algorithm to occasionally suggest diverse content outside of the user’s typical preferences. This way, viewers can discover new genres and ideas they might not have chosen on their own.

 

Conclusion: Netflix’s use of AI for personalized recommendations is a double-edged sword. It brings convenience, but also raises critical questions about privacy and the diversity of our entertainment choices. As we embrace the benefits of AI in services like Netflix, we must also consider and address these challenges.

 

Questions

  • Do you think the convenience of personalized recommendations is worth the potential privacy trade-off?
  • How might watching only similar types of shows and movies limit our understanding of different perspectives?
  • What other ways can AI be used responsibly to enhance our entertainment experiences without compromising our privacy or limiting our choices?

Simulation

Internet Search and Tracking

Through this simulation, students will learn about data tracking in online behavior and its implications for personalized marketing, emphasizing real-time observation and ethical considerations.

 

Scenario

Divide the class into pairs, with each student alternating roles between being an internet user and a tracker.

 

Roles

  • Internet Users: Students who conduct internet searches and read pages based on their interests.
  • Trackers: Simulating AI algorithms, the trackers quietly observe their partner’s search behavior and note down potential products or services that align with the interests shown.

 

Tasks

  1. Internet Users start by browsing the internet on topics that interest them. They can visit news sites, online stores, or any other websites they choose.
  2. Trackers discreetly observe and make notes on the types of websites visited, the content interacted with, and potential products or services that align with these interests. The Internet Users may forget that the tracker is there, which is ideal.
  3. After a set period of time (perhaps 10 minutes), roles are reversed, allowing each student to experience both sides of the data tracking process.
  4. Once both students have performed each role, have them compare notes on each others’ searching. Students should read the list of possible product or service tie-ins they noted for their partners’ web surfing.

 

Implementation Notes

  • To maintain privacy, Trackers should not record any personal or sensitive information; they should focus only on general interests and potential product alignments.
  • Internet Users should be instructed to avoid searching for sensitive or personal topics during the simulation.

Student Handout

Simulation: Internet Search and Tracking

Objective: Understand how your online behavior is tracked and how this data is used to tailor marketing strategies, focusing on real-time observation and ethical considerations.

Overview: You will be participating in a simulation where you’ll experience the roles of an internet user and a tracker. This will help you understand how online activities are monitored and how data is used in personalized marketing.

Procedure:

  1. Form Pairs: Each of you will pair up with a classmate. You will alternate roles between being an Internet User and a Tracker.
  2. Roles Explained:
    • Internet Users: You will conduct searches and read pages based on your interests, as if you were browsing the internet normally. You may visit news sites, online stores, or any websites of your choice.
    • Trackers: Your role is to simulate how AI algorithms track online behavior. Quietly observe your partner’s search behavior, noting the types of websites visited and the content interacted with. Write down potential products or services that align with the interests shown.
  3. Activity Steps:
    • Start the simulation with one student as the Internet User and the other as the Tracker.
    • The Internet User will browse freely on topics of interest for approximately 10 minutes. During this time, the Tracker will discreetly observe and take notes without interrupting.
    • When your teacher tells you, switch roles and repeat the process.
  4. Discussion and Reflection:
    • Once both of you have performed each role, compare your notes.
    • Discuss the list of potential products or services you noted for each other’s web browsing.
    • Reflect on what it felt like to be tracked and to track someone else’s internet behavior.

Ethical Guidelines:

  • Trackers: Do not record any personal or sensitive information. Focus only on general interests and potential product alignments.
  • Internet Users: Avoid searching for sensitive or personal topics during this simulation.

Learning Outcome: By the end of this simulation, you should have a better understanding of how online behaviors are tracked and used for personalized marketing, as well as the ethical considerations involved in data tracking.

Discussion

These questions are designed to be used in whole-class discussion. Ask questions that relate most effectively to the lesson.

  1. How did it feel to have your searches observed in person?
  2. How accurate were the trackers in identifying your interests? 
  3. Trackers, what challenges did you face in predicting products or services based on the searches?
  4. How much does this activity reflect real computer tracking for marketing purposes?
  5. What are the ethical boundaries of personal marketing in this way?
  6. How could privacy be intruded upon by tracking algorithms?

Assessment

Exit Ticket: Provide a prompt for students to reflect on their learning, such as: 

  • What are three new things you learned today about AI-driven personalized marketing and its impact on consumer behavior?
  • Do you have any remaining questions or areas of confusion about the ethical implications of AI in marketing? If so, what are they?
  • How do you think AI in personalized marketing will evolve over the next five years, and what impacts might this have on consumer experiences?

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