Thesis: Ph. D., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2017. / Cataloged from PDF version of thesis. / Includes bibliographical references. / We live in a culture that depends on technologies to record our behavior and coordinate our actions with billions of other connected people. In this computational culture, humans and machines continue to perpetuate deep-seated injustices. Our abilities to observe and intervene in other people's lives also allow us to govern, forcing us to ask how to govern wisely and who should be responsible. In this dissertation, I argue that to govern wisely, we need to remake large-scale social experiments to follow values of democracy. Using qualitative and quantitative methods, I spent time with hundreds of communities on the social news platform reddit and learned how they govern themselves. I designed CivilServant, novel experimentation software that communities have used to evaluate how they govern harassment and misinformation. Finally, I examined the uses of this evidence in community policy deliberation. As we develop ways to govern behavior through technology platforms, we have an opportunity to ensure that that the benefits will be enjoyed, questioned, and validated widely in an open society. Despite common views of social experiments as scarce knowledge that consolidates the power of experts, I show how community experiments can scale policy evaluation and expand public influence on the governance of human and machine behavior. / by J. Nathan Matias. / Ph. D.
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/112527 |
| Date | January 2017 |
| Creators | Matias, J. Nathan (Jorge Nathan) |
| Contributors | Ethan Zuckerman., Program in Media Arts and Sciences (Massachusetts Institute of Technology), Program in Media Arts and Sciences (Massachusetts Institute of Technology) |
| Publisher | Massachusetts Institute of Technology |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 206 pages, application/pdf |
| Rights | MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission., http://dspace.mit.edu/handle/1721.1/7582 |
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