CSE 142

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Honors Section (CSE 390HA)

Wednesdays, 4:30-6:20pm, in CSE 403

Instructor: Brett Wortzman (brettwo@cs.washington.edu)

This quarter, we are offering an honors section for students who are interested in exploring additional topics related to technology and computer science. This is a one-unit, CR/NC course that will be offered in a seminar setting. Sessions will consist of group discussions about various topics and ideas along with some activities. There will be a small amount of homework prior to each session, primarily readings or videos that will be discussed in class. Students must attend seven (7) of the nine (9) scheduled sessions and participate in all discussions and activities to receive credit.

Each week, we will discuss various topics related to computer science. While we may cover some programming topics (such as non-Java programming languages, advanced techniques, applications of CS, etc.), our sessions will mostly relate to the societal and cultural impacts of technology and CS. This course is NOT an opportunity to learn more programming, but an opportunity to think about computer science and other related topics in a broader context.

Week 7 (2/27): Guest instructor: Zorah Fung

Interesting Links and related reading to what was mentioned in class:

Pre-work for next section:

None!

Week 6 (2/20): Impact of "Big Tech"

Discussion of Readings:

  • How does the existence of "Big Tech" companies impact society?
  • What are some of the ways, both visible and invisible, large technology companies impact our lives?
  • What would happen if certain companies collapsed? Are some large tech companies "too big to fail"?
  • How does the presence of a "Big Tech" campus or office impact the city and community in which it is located?

Interesting Links and related reading to what was mentioned in class:

Pre-work for next section:

None!

Week 5 (2/13): Machine Learning

Discussion of Readings:

  • How does machine learning work? What are some ways machine learning is applied?
  • What are the advantages and disadvantages to machine learning approaches?
  • Can algorithms (especially ML algorithms) be biased? What are the consequences of algorithms that reflect existing human biases?

Interesting Links and related reading to what was mentioned in class:

Pre-work for next section:

Week 4 (2/6): Artificial Intelligence

Discussion of Readings:

  • What is intelligence? What is artificial intelligence?
  • How should human intelligence and artificial intelligence be compared and evaluated?
  • What are the risks to continuing to develop artificial intelligence?

Interesting Links and related reading to what was mentioned in class:

Pre-work for next section:

Week 3 (1/30): Privacy and Security

Discussion of Readings:

  • What is privacy? What is security?
  • Whose responsibility is it to protect "your data"?
  • Are we willing to give up privacy in exchange for convenience? Or vice versa?

Interesting Links and related reading to what was mentioned in class:

Pre-work for next section:

Week 2 (1/23): Search Indexing, PageRank and Google's Impact on Our Beliefs and Behaviors

Discussion of Readings:

  • How do search indexing and PageRank work?
  • How are search results influenced by the search query?
  • What impact do search results have on people's beliefs and behaviors?
  • What does it mean for search results to be "unbiased"?
  • What responsibility does Google (or other tech companies) have to present "unbiased" search results?

Interesting Links and related reading to what was mentioned in class:

Pre-work for next section:

Week 1 (1/16): Welcome!

Course Overview; Get To Know; What is a computer? What is computer science?

Pre-work for next section: