Diversifying Human-Centered Data Science through the Research and Design of Ethical Games


This interdisciplinary study explores the learning experiences of diverse undergraduates at two universities as they collaborate in the research and design of a simulation game that teaches ethical thinking in data science and artificial intelligence. Using ethnographic methods, researchers seek to answer the following questions:

  1. How do students individually and collectively position their views within data ethics and do these views change over time with increased exposure to technical concepts and norms?
  2. Does the collaborative design of an ethical simulation game facilitate diverse student learning experiences? If so, how does this inform theories on the science of learning in environments with conflicting norms?
  3. In what ways do underrepresented students see their personal relationship to the fields of data science, data ethics, and game design in the periods before, during, and after working on a related research team?

The project begins in year one with the formation of two undergraduate research teams, one at the Hispanic-serving institution University of North Texas (UNT), and one at the University of Washington (UW), with emphasis on recruiting students from underrepresented groups. Led by the PIs and supervised by a Ph.D. student in each location, the teams work together via internet technologies to collaboratively learn about data science methods, data ethics, and applications to game design. In year two, the two teams create and test a game prototype designed to teach ethical thinking about the uses of data science and artificial intelligence.