Each lecture we give the students a Thought Experiment. Students discuss it privately first with the people around them and then we have a class discussion. I always wish these could go on longer because the students have such interesting ideas. The first couple weeks I posed the thought experiments, and then after that, the guest lecturers have. It’s a nice way to provide continuity between guest lecturers, and get the students started thinking about the themes of that evening’s lecture:
Week 1: Can we use data science to define data science? [Posed by Rachel Schutt]
Week 2: How would you simulate chaos? [Posed by Rachel Schutt]
Week 3: First, students were given a bunch of text, and asked what it was. They quickly were able to identify it as spam. How did you figure this out? Can you write code to automate the spam filter that your brain is? [Posed by Jake Hofman]
Week 4: How would data science differ if we had a “grand unified theory of everything”? [Posed by Brian Dalessandro]
Week 5: What do you lose when you think of your training set as a big pile of data and ignore the timestamps? [Posed by Cathy O'Neil]
Week 6: What are the ethical implications of a robo-grader? [Posed by Will Cukierski]
Week 6: (1) How might we design technology to support managing one’s social graph? (2)Privacy is important to users and in designing technology. What is the best way to decrease concern, and increase understanding and control?[Posed by David Huffaker]
