Building policy-aware research test beds : lessons from laboratory development for optical neuroimaging
Author(s)
Evans, Casey Gail.
Download1117774584-MIT.pdf (18.33Mb)
Other Contributors
Massachusetts Institute of Technology. Institute for Data, Systems, and Society.
Technology and Policy Program.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Megan H. Blackwell.
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Despite the prevalence of applications for compelling technologies, communication between scientists and policy makers is often obfuscated by conflicting philosophies concerning the role of science and technology in decision-making. Research test beds are here proposed and defended as a critical component of technologist-decision-maker communication. Approaches that enable a test bed to more effectively achieve such communication are enumerated, discussed and then compared with examples from the design, setup and validation process of a gated time-domain diffuse correlation spectroscopy (TD-DCS) test bed. Gated TD-DCS is a novel optical neuroimaging technique that can be used in applications that require higher spatial resolution than electroencephalograms (EEGs) but more portability than Magnetic Resonance Imaging (MRI). The gated TD-DCS test bed described here is the first of its kind for evaluating gated detector performance in a TD-DCS system and the methodology used for this test bed development is explored in depth. Lessons learned from test bed development in this wholly new field are then used to reassess the role of test beds in facilitating faithful policy applications of technology. This study highlights the significance of science-policy communication and illustrates through concrete example one promising method of improving such communication.
Description
Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2019 Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019 Cataloged from PDF version of thesis. Includes bibliographical references (pages 113-122).
Date issued
2019Department
Massachusetts Institute of Technology. Institute for Data, Systems, and Society; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science; Massachusetts Institute of Technology. Engineering Systems Division; Technology and Policy ProgramPublisher
Massachusetts Institute of Technology
Keywords
Institute for Data, Systems, and Society., Technology and Policy Program., Electrical Engineering and Computer Science.