Data Dialogue: Design intuition, ethnography, and data science
Sponsor(s): Information Initiative at Duke (iiD), Bass Connections-Information, Society & Culture, Biomedical Engineering (BME), Biostatistics and Bioinformatics, Computational Biology and Bioinformatics (CBB), Computer Science, Electrical and Computer Engineering (ECE), Mathematics, and Statistical Science
Data science's future as a profession faces two major challenges: on the one hand, the technical portions of the day-to-day work are being increasingly automated, while on the other hand, increasingly frequent stories of algorithmic bias make people reticent to trust decision automation. In the interest of future-proofing the profession of data science, this talk will address the need for increased attention to a critical non-technical skill: design. Incorporating lessons from anthropological research methods, and referencing recent professional work on shape validation and geolocation precision calibration, the presentation will make a case for a greater focus on design skills and the need for a question-generating toolset.
Contact: Ariel Dawn