In 2026, after nearly 90 years, the Institute of Design was folded into Illinois Tech's School of Design & Society.
This website is an archive of the impactful and inspirational work produced by the ID community before that transition.

László Moholy-Nagy opened the New Bauhaus in Chicago in 1937, treating design as a discipline that was teachable, testable, and consequential. Nine decades on, its scope had widened from the things people use to the systems they depend on: hospitals, government agencies, classrooms, supply chains, digital platforms. Along the way, ID community members developed the published research, methods, and frameworks that designers rely on every day.

Chief among them is human-centered design: close attention to how people actually live, and advocacy for what that research reveals. It shaped designers who are comfortable with complexity and ambiguity: curious, rigorous, inclusive, and stubbornly optimistic about design's ability to change the systems that shape our lives.

To every one of them, who taught, studied, built, critiqued, and stayed late in the studio: thank you, and keep designing.

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Human + Data Systems

Human + Data Systems

Designing the conditions that shape our behaviors, the data they generate, and the systems that manage, learn, and predict outcomes about us.

Objective & Outcomes

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.

Typical Schedule

  • 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

See all MDes Courses