Events
Past Event
WED@NICO WEBINAR: Lorien Jasny, University of Exeter
Northwestern Institute on Complex Systems (NICO)
12:00 PM
Details
Speaker:
Lorien Jasny, Lecturer in Political and Environmental Network Analysis, University of Exeter
Title:
Can conversation change minds: applying mental models to the UC Davis Adaptive Rangeland Management study
Abstract:
This project combines networks of mental models and conversation dynamics to understand collaboration and deliberation in a small group. We brought interested stakeholders (ranchers, conservationists, and government rangeland managers) to visit a piece of UC Davis rangeland and develop a management strategy. Prior to group discussion, we surveyed 4 groups of respondents (a homogenous group from each category of ranchers, conservationists, and government rangeland managers as well as one mixed group) about the management decisions they would make. In particular, we were interested in how these respondents linked the methods they would use to the goals they set. We thus have bipartite networks for each individual respondent where the tie indicates that a given method should be used to achieve a given goal. After the group discussion, we then asked each individual to make any changes they felt were appropriate to their network of responses about goals and methods that they had given before discussion. We use Butts’ Informant Accuracy Model (2003) to look at the cultural consensus within groups and compare it to change over time. We find the most change in linkages between goals and methods (rather than new goals and methods), and we find in all cases that individuals do indeed change to be more like the rest of the group.
Speaker Bio:
Lorien Jasny is a computational social scientist in the Department of Politics at the University of Exeter. Her work focuses on questions of public involvement and engagement in environmental decision making. In my research I explore two related themes – how the structure and dynamics of inter-organizational networks affect policy change, and how the structure and dynamics of belief networks affect behavioral change. Substantively, she studies how people try to bring about societal change in response to political and environmental concerns. Methodologically, the need to grapple with these often complex phenomena requires the use and development of techniques for handling large, dynamic, and relational datasets.
Webinar:
Video of this talk can be found on our YouTube Channel.
About the Speaker Series:
Wednesdays@NICO is a vibrant weekly seminar series focusing broadly on the topics of complex systems and data science. It brings together attendees ranging from graduate students to senior faculty who span all of the schools across Northwestern, from applied math to sociology to biology and every discipline in-between. Please visit: https://bit.ly/WedatNICO for information on future speakers.
Time
Wednesday, February 24, 2021 at 12:00 PM - 1:00 PM
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)
Data Science Nights - MAY 2026 - Speaker: Xudong Tang, Computer Science and NICO
Northwestern Institute on Complex Systems (NICO)
5:30 PM
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M416, Technological Institute
Details
MAY MEETING: Thursday, May 28, 2026 at 5:30pm (US Central)
LOCATION:
ESAM Conference Room, Tech M416
2145 Sheridan Road, Evanston, IL 60208
AGENDA:
5:30pm - Meet and greet with refreshments
6:00pm - Talk with Xudong Tang, PhD Student, Computer Science, NICO, and the Human-AI Collaboration Lab, Northwestern University
TALK TITLE:
Human and Machine Perception of Voice Similarity
ABSTRACT:
Modern voice cloning systems generate synthetic speech that listeners frequently cannot identify as being synthetic. But a voice can sound natural without sounding like the intended person, and what determines whether a clone is heard as a particular person is an open question. Here we report a large-scale preregistered experiment in which we collected 92,239 responses from 175 participants on their perception of pairs of real recordings, voice clones, and continuously morphed voices drawn from 100 contemporary celebrities across 20 speaker groups. We find that voice clones do not reliably preserve perceived speaker identity, reducing same-speaker judgments by 12.7 percentage points even though the clones are produced by a state-of-the-art text-to-speech model, while leaving different-speaker judgments unchanged. Using continuously morphed stimuli, we find that speakers vary substantially in how much variation their perceived identity tolerates, and that this variation is not predicted by speaker demographics. Speaker embeddings account for 58.9\% (95\% CI = [55.7, 61.9]) of variance in identity judgments, which is more than acoustic features, social attributes, and clone status combined. Once all these observed features are accounted for, clone status adds no additional predictive power. These results shows that the perceptual impact of voice cloning is positional rather than categorical: we can model how listeners judge a voice by how close it falls to the perceptual boundary that defines each speaker's recognizable voice, applying the same criterion to real and synthetic speech alike.
DATA SCIENCE NIGHTS are monthly meetings featuring presentations and discussions about data-driven science and complex systems, organized by Northwestern University graduate students and scholars. Students and researchers of all levels are welcome! For more information: http://bit.ly/nico-dsn
FUTURE DATES:
Data Science Nights will return in September!
Time
Thursday, May 28, 2026 at 5:30 PM - 7:00 PM
Location
M416, Technological Institute Map
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)