Designing Data-informed Intelligent Systems to Create Positive Impact

Designing Data-informed Intelligent Systems to Create Positive Impact: Design Methods, Questions and Recommendations

Lomas, J.D. (TU Delft Design Aesthetics)
Patel, Nirmal (Playpower Labs)
Forlizzi, Jodi L. (Carnegie Mellon University)

van der Bijl--Brouwer, Mieke (editor)

2021

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.

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

http://resolver.tudelft.nl/uuid:cccf716e-35f4-400f-871c-ffa2b932c4d8

978-94-6366-507-0

Proceedings of Relating Systems Thinking and Design (RSD10) Symposium

Relating Systems Thinking and Design 2021 Symposium (RSD10), 2021-11-02 → 2021-11-06, Faculty of Industrial Design Engineering, TU Delft, Delft, Netherlands

Institutional Repository

conference paper

© 2021 J.D. Lomas, Nirmal Patel, Jodi L. Forlizzi