Events
Past Event
WED@NICO WEBINAR: Cristian Candia-Castro Vallejos, Universidad del Desarrollo, Chile "Digital footprints for collective intelligence"
Northwestern Institute on Complex Systems (NICO)
12:00 PM
Details
Speaker:
Cristian Candia-Castro Vallejos, Assitant Professor and Director of Master in Data Science at the Data Science Institute, Universidad del Desarrollo, Chile
Title:
Digital footprints for collective intelligence
Abstract:
In general words, Collective Intelligence (CI) is defined as the shared or group intelligence that emerges from the interaction between people and the ways of processing information. For CI to exist, groups of people must learn collectively and store what is learned in their collective memories; thus, the need to solve new problems allows collective intelligence to manifest. CI arises mainly in collaboration, collective efforts, competition between people, and decision-making by consensus (Pierre Levy, 1999). In this presentation, using an approach placed at the intersection between theories of human behavior and data science, we will take a tour of our ongoing research in three different aspects of collective intelligence: Tools that facilitate collective intelligence; Types of collective intelligence, such as cooperation and coordination; and one of the means that allow collective intelligence, collective memory.
Speaker Bio:
Cristian Candia is an Assistant Professor and Director of the Master Degree in Data Science at the Data Science Institute, School of Engineering, Universidad del Desarrollo, Chile. Besides, Dr. Candia is an external faculty at the Northwestern Institute on Complex Systems, Northwestern University. His work focuses on data science applied to socio-economic systems, and it has been published in journals such as Nature Human Behaviour, American Psychologist, and EPJ Data Science. Previously, Cristian held a Postdoctoral position at the Kellogg School of Management at Northwestern University. He conducted his Ph.D. research at the MIT Media Lab (Massachusetts Institute of Technology), the Center for Complex Networks Research (Northeastern and Harvard University), and the Center for Social Complexity (Universidad del Desarrollo).
Webinar:
https://northwestern.zoom.us/j/99954269710
Passcode: nico
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, October 20, 2021 at 12:00 PM - 1:00 PM
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)
No classes - Memorial Day - University offices are closed
University Academic Calendar
All Day
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No classes - Memorial Day - University offices are closed
Time
Monday, May 25, 2026
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Calendar
University Academic Calendar
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)
Spring 2026 Commencement
University Academic Calendar
All Day
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Spring 2026 Commencement
Time
Sunday, June 14, 2026
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Juneteenth - University Closed
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All Day
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Juneteenth - University Closed
Time
Friday, June 19, 2026
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University Academic Calendar
Independence Day (observed) - University Closed
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All Day
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Independence Day (observed) - University Closed
Time
Friday, July 3, 2026
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Fall 2026 Classes Begin
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All Day
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Fall 2026 Classes Begin
Time
Wednesday, September 23, 2026
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