week 8. data-driven culture as experience

 1. students present Project 1.

2. revisiting "Human-AI Interaction" in four levels:

   Yang, Q., Steinfeld, A., Rosé, C. and Zimmerman, J. 2020. Re-examining Whether, Why, and How Human-AI Interaction Is Uniquely Difficult to Design. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (New York, NY, Apr. 2020), 1–13. https://doi.org/10.1145/3313831.3376301

Level 1: fixed output, with statistics, 

              example

give simple examples:　

output = f(input)

new output = f(nearest_input)

What is Human-in-the-Loop?

Arts and Humanity: Human-in-the-Loop

Questions:

  what is the role of human in AI system?

  How to collect data? how to label?

3. Data-driven culture, Data Storytelling

Qian Yang, Alex Scuito, John Zimmerman, Jodi Forlizzi, and Aaron Steinfeld. 2018. Investigating How Experienced UX Designers Effectively Work with Machine Learning. In Proceedings of the 2018 Designing Interactive Systems Conference (DIS '18). Association for Computing Machinery, New York, NY, USA, 585–596. DOI:https://doi.org/10.1145/3196709.3196730

Questions:

 What are your Data Storytelling strategies? Practical, fictional, or communicative?

4.  Machine Learning as Monsters?

Graham Dove and Anne-Laure Fayard. 2020. Monsters, Metaphors, and Machine Learning. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (CHI '20). Association for Computing Machinery, New York, NY, USA, 1–17. DOI:https://doi.org/10.1145/3313831.3376275