Human + Data Systems

Our interactions with digital products and services generate large amounts of data: data is created consciously by us or passively observed, and that data is used to learn and make inferences about us, and ultimately, inform subsequent actions. This course aims to extend interaction design beyond how we design interactions with discrete products and services, to how we approach the design of interactions with systems that capture, collect, and analyze data and make predictions. An alternative name for this course is designing interactions with data and predictions.

Upon completing this course, students will be able to demonstrate visually how human-data systems drive feedback loops, facilitate data capture and ask for consent, and explain how that differs between conscious data creation and passive data collection; analyze different human-data systems and be able to identify how feedback is captured, what that data is going to inform, and what actions are dependent on the insights derived from that data; and explore through making the opportunity for different data representation formats and mediums to facilitate data management and influence data awareness.

• Session 1: Understanding How We Got Here & Why Now: From HCI to ubiquitous computing
• Session 2: Defining Human-Data Systems, Inputs & Outputs
• Session 3: Consent Patterns for Data Capture & Collection
• Session 4: Friction in Human-Data Systems: Optimizing data capture vs legibility
• Session 5: Representing Data for Agency in Human-Data Systems
• Session 6: Representing Data for Management in Human-Data Systems
• Session 7: Final Presentations