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Designing Data-informed Intelligent Systems to Create Positive Impact

Design Methods, Questions and Recommendations

Conference Paper (2021)
Author(s)

J.D. Lomas (TU Delft - Industrial Design Engineering)

Nirmal Patel (Playpower Labs)

Jodi L. Forlizzi (Carnegie Mellon University)

Research Group
Form and Experience
URL related publication
https://rsdsymposium.org/towards-data-informed-system-design-for-good-methods-questions-and-recommendations-for-designers/ Accepted author manuscript
More Info
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Publication Year
2021
Language
English
Research Group
Form and Experience
Pages (from-to)
154-170
ISBN (electronic)
978-94-6366-507-0
Event
Relating Systems Thinking and Design 2021 Symposium (RSD10) (2021-11-02 - 2021-11-06), Faculty of Industrial Design Engineering, TU Delft, Delft, Netherlands
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Abstract

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.