Editing Human Centered Data Science (Fall 2019)/Schedule (section)

=== Week 6: October 31 ===
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;Data science and society: ''power, data, and society; ethics of crowdwork''

;Assignments due
* Reading reflection
* A3: Crowdwork ethnography

;Agenda
* Reading reflections
* Assignment 3 review
* Guest lecture: Stefania Druga
* In-class activity
* Introduction to assignment 4: Final project proposal

;Homework assigned
* Read both, reflect on one:
:* Baumer, E. P. S. (2017). ''[http://journals.sagepub.com/doi/pdf/10.1177/2053951717718854 Toward human-centered algorithm design].'' Big Data & Society.
:* Amershi, S., Cakmak, M., Knox, W. B., & Kulesza, T. (2014). ''[http://www.aaai.org/ojs/index.php/aimagazine/article/download/2513/2456 Power to the People: The Role of Humans in Interactive Machine Learning].'' AI Magazine, 35(4), 105.
* [[Human_Centered_Data_Science_(Fall_2019)/Assignments#A4:_Final project proposal|A4: Final project proposal]]

;Resources
* Lilly C. Irani and M. Six Silberman. 2013. ''[https://escholarship.org/content/qt10c125z3/qt10c125z3.pdf Turkopticon: interrupting worker invisibility in amazon mechanical turk]''. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '13). DOI: https://doi.org/10.1145/2470654.2470742
* Salehi, Niloufar, Lilly C. Irani, Michael S. Bernstein, Ali Alkhatib, Eva Ogbe, and Kristy Milland. ''[https://hci.stanford.edu/publications/2015/dynamo/DynamoCHI2015.pdf We are dynamo: Overcoming stalling and friction in collective action for crowd workers]''. In Proceedings of the 33rd annual ACM conference on human factors in computing systems, pp. 1621-1630. ACM, 2015.
* Hill, B. M., Dailey, D., Guy, R. T., Lewis, B., Matsuzaki, M., & Morgan, J. T. (2017). ''[https://mako.cc/academic/hill_etal-cdsw_chapter-DRAFT.pdf Democratizing Data Science: The Community Data Science Workshops and Classes]''. In N. Jullien, S. A. Matei, & S. P. Goggins (Eds.), Big Data Factories: Scientific Collaborative approaches for virtual community data collection, repurposing, recombining, and dissemination. New York, New York: Springer Nature. https://doi.org/10.1007/978-3-319-59186-5_9
* Ingold, David and Soper, Spencer. ''[https://www.bloomberg.com/graphics/2016-amazon-same-day/ Amazon Doesn’t Consider the Race of Its Customers. Should It?].'' Bloomberg, 2016.
* Julia Angwin, Jeff Larson, Surya Mattu and Lauren Kirchner. ''[https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing Machine Bias: Risk Assessment in Criminal Sentencing]. Propublica, May 2018.
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