Designing Data-informed Intelligent Systems to Create Positive Impact

Design Methods, Questions and Recommendations

J. Derek Lomas, Nirmal Patek, and Jodi Forlizzi

This paper explores several approaches for designing data-informed intelligent systems to create a positive impact. Two contrasting case studies in K12 education are used to illustrate design methods, questions and recommendations. The first case study addresses the poverty achievement gap in America and shows how product data can be used to identify areas of inequity in digital education. The second case study looks at the unintended consequences of automating data-driven optimization in the context of a digital math game. Together, the two case studies reveal generalizable knowledge that supports the design of intelligent feedback loops to create a positive impact. Further, this paper considers both the benefits and limitations of data feedback in complex social-technical systems.

Keywords: Smart Systems, Learning Organizations, Cybernetics, Poverty, Education, Artificial Intelligence, Goodhart’s Law

Posted September 2021 content is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. This permits anyone to copy and redistribute the material in any medium or form according to the licence terms.

Suggested Citation Format (APA)

Author(s) (20XX). Article title. Proceedings of Relating Systems Thinking and Design (RSDX) Symposium.