Celeste Kidd

Research Expertise and Interest

attention, curiosity, learning, computational modeling, cognitive development, machine learning, belief formation

Research Description

The Kidd Lab studies the processes involved in learning and belief formation, starting in infancy, using a combination of computational and behavioral methods. The lab is one of few in the world that combine technologically sophisticated behavioral experiments with computational models in order to broadly understand knowledge acquisition. The Kidd Lab employs a range of methods, including eye-tracking and touchscreen testing with human infants, in order to show how learners sample information from their environment and build knowledge gradually over time.

Celeste Kidd's work has been published in PNAS, Neuron, Psychological Science, Developmental Science, and elsewhere. Her lab has received funding from NSF, DARPA, Google, the Jacobs Foundation, the Human Frontiers Science Program, and the Templeton Foundation. She is a recipient of the Hellman Fellows award, the American Psychological Science Rising Star designation, the Glushko Dissertation Prize in Cognitive Science, and the Cognitive Science Society Computational Modeling Prize in Perception/Action. Kidd was also named as one of TIME Magazines 2017 Persons of the Year as one of the "Silence Breakers" for her advocacy for better protections for students against sexual misconduct.

 

In the News

Coronavirus skeptics, deniers: Why some of us stick to deadly beliefs

Many young adults are defying the 6-feet-apart social distancing rules. What causes certain people to stick to their beliefs and act with skepticism despite overwhelming contradictory evidence? Berkeley News asked Celeste Kidd, a UC Berkeley computational cognitive scientist who studies false beliefs, curiosity and learning.

What we think we know — but might not — pushes us to learn more

If you think you know the farm animal most closely related to T-Rex, or the American president who inspired the creation of blueberry jelly beans — but aren’t quite sure — you’re more likely to bone up on the chicken-dinosaur connection or Ronald Reagan’s predilection for glazed, gel-filled candies.

Featured in the Media

Please note: The views and opinions expressed in these articles are those of the authors and do not necessarily reflect the official policy or positions of UC Berkeley.
May 28, 2019

What we think we know -- but might not -- pushes us to learn more

Science Daily
Doubt is the driver of curiosity and the urge to learn, suggests a new study by Berkeley researchers. "It's very in vogue to talk about curiosity as a strategy to increase learning, but it's unclear how to engage people's curiosity," says assistant psychology professor Celeste Kidd, the study's senior author. "Our study suggests it's the uncertainty -- when you think you know something and discover you don't -- that leads to the most curiosity and learning." Co-author Shirlene Wade, a visiting doctoral scholar in Professor Kidd's lab, says: "Asking students to explain how things work can be an effective learning intervention because it makes them aware of what they don't know and curious about what they need to know." This story originated at Berkeley News. A related story about Professor Kidd's research appeared in Study Finds. It stemmed from another story at Berkeley News.
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