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Introduction to Algorithms
Preview the lesson below, then register for free to access the entire lesson or assign it to students.​
Average Duration
> 60 min.
Difficulty Level
4
Lesson Host
Mia Sato
of The Verge
About

Dive into the world of algorithms and generative artificial intelligence as you weigh the civic and social impact of these technologies.

News literacy topics

Algorithms and personalization

Learning objectives

  • Describe how algorithms shape the information we see and find.
  • Explain how algorithms can be biased.
  • Analyze the benefits and costs of “free information” in the attention economy.
  • Argue the potential risks and benefits of generative AI.
  • Create a plan to avoid the pitfalls posed by algorithms and to train them to promote more balanced and credible information.

Essential questions

  • What are algorithms?
  • Why is the information found through search engines and on social media platforms different for different people?
  • Why do search engines and social media platforms use algorithms?
  • How much influence do algorithms have in my life? How much influence do they have on the national conversation?
  • What opportunities and challenges do generative AI chatbots and image generators present?

Excerpt

“How many times have you heard someone say they’re ‘addicted’ to social media? Maybe you’ve even felt that way? It makes total sense! These platforms are addicting by design. When people like and share our posts, it gives our brain a hit of dopamine. It feels good.

“Social media companies are all trying to keep us engaged and coming back. They are all vying for our time and attention, which they will convert into data about us, and into ad sales. Getting that attention means serving you the most relevant content at the right time. To do this, their algorithms compare and evaluate patterns from billions of users, looking for people whose interests are similar to yours.

“Short-form video platforms are constantly collecting data from you. When you stop and watch a video — even if it’s not all the way through — the algorithms notice. They also notice when you like a video, share it, save it or watch it more than once. And when you scroll right past something? They notice and learn from that too.”