Create Your Own Algorithm Activity

In this activity, you will simulate the process of creating an AI algorithm that curates news feeds. This hands-on experience will help you understand what factors are considered when deciding which news stories appear on your feed and how those decisions can influence public perception.

Objectives

• Understand the decision-making process used by AI in news curation.
• Recognize the factors that influence which news stories are prioritized.
• Analyze the potential impact of algorithmic decisions on the information you consume.

Instructions

1. Brainstorm Session (5 minutes):

   • In small groups (3-4 students), discuss what criteria you think are important when deciding which news stories should appear in a news feed. Consider factors such as user interest, credibility of the news source, timeliness, diversity of perspectives, and others.

2. Design Your Algorithm (10 minutes):

   • Each group will create a step-by-step outline of how their algorithm will work. Use the following guiding questions:
     • What criteria will your algorithm prioritize?
     • How will you measure the importance of each news story?
     • What data inputs will your algorithm use (e.g., user history, trending topics, etc.)?
   • Write down a flowchart or list to illustrate the decision process of your algorithm.

3. Simulation and Testing (10 minutes):

   • Imagine a sample set of news stories with different attributes (e.g., topic, reliability, timeliness).
   • Apply your designed algorithm to this sample, and determine which stories would be featured and why.
   • Record the results of your simulation.

4. Group Reflection (5 minutes):

   • Each group will briefly share their algorithm, the inputs they considered, and the outcomes of their simulation.
   • Discuss what changes might be necessary to improve the fairness or accuracy of your algorithm.

Questions for Reflection

• How do the chosen criteria affect the diversity of news stories that appear?
• Could bias be introduced inadvertently through the selection of criteria? If so, how might it be mitigated?
• In what ways could the algorithm you designed be improved to better serve a public audience?

Follow-Up Points for Discussion

• Compare your group’s algorithm with others. What similarities and differences do you notice?
• How do real-world AI algorithms compare to the one you've designed?
• Discuss how the transparency of algorithm decisions can impact user trust in news platforms.

Take a moment to think critically and be creative with your solutions! Enjoy building your own AI and see the impact of your design choices on shaping a balanced news feed.

Media Bias and AI Discussion

This discussion is an opportunity to explore how media bias can be influenced by AI technologies, specifically in the realm of news curation. The goal is to help students understand the potential for bias in algorithmic decision-making and how such biases can affect information consumption.

Discussion Guidelines

• Respectful Listening: Ensure everyone has an opportunity to share their views. Listen carefully and respectfully to others' opinions.
• Open-Mindedness: Consider multiple perspectives and challenge your own thinking.
• Evidence-Based Discussion: Support your arguments with examples or references to the material we've covered, such as the AI and News Curation lesson plan and the The AI Newsroom slide deck.
• Critical Thinking: Question how the design of AI algorithms might inadvertently introduce bias and explore ways to mitigate these issues.

Discussion Prompts

1. Understanding Bias in AI:
   
   
   

   • What do you think are the main sources of bias in AI algorithms that curate news feeds?
   • Can you provide examples of how such bias might manifest in real-world applications?

2. Impact on News Consumption:
   
   
   

   • How could biased news feeds affect the public's understanding of current events?
   • In what ways might an individual's perception be shaped by an algorithmically-curated feed?

3. Mitigating Bias:
   
   
   

   • What steps could be taken to reduce or counteract the effects of bias in AI curation?
   • How important is transparency in the algorithms used for news curation, and what measures could improve it?

4. Ethical Considerations:
   
   
   

   • How do you balance the benefits of personalized news with the risks of creating echo chambers or reinforcing biases?
   • What ethical responsibilities should tech companies have in addressing media bias?

Follow-Up Questions

• How do your perspectives compare with those of your peers during this discussion?
  
  
  
• Can you identify any real-world examples where media bias might have been influenced by AI, either positively or negatively?
  
  
  
• In what ways can increased media literacy help us become more critical of the news we read?

Let's dive into these questions and work together to uncover how AI and media bias intersect, and what this means for our understanding of news in today’s digital world.