Browse 3 peer-reviewed papers from University Of California Los Angeles spanning Human-AI Interaction, Cognitive Aging (2024–2025). Research powered by Prolific's high-quality participant data.
This page lists 3 peer-reviewed papers from researchers at University Of California Los Angeles in the Prolific Citations Library, a curated collection of research powered by high-quality human data from Prolific.
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Authors: KO Alberts, AD Castel
Year: 2025
Published in: Experimental Aging Research, 2025 - Taylor & Francis
Institution: University of California Los Angeles
Research Area: Cognitive Aging, Associative Memory, Trustworthiness of Artificial Faces, Human-AI Interaction, Psychology, Trust in AI
Discipline: Psychology, Psychobiology, Aging Research
Older adults perceive artificial faces as equally trustworthy as real faces, unlike young adults who find artificial faces less trustworthy, and older adults show no difference in memory accuracy between face types.
Methods: Participants viewed real and artificial faces associated with scam or neutral conditions, then rated trustworthiness and were tested on associative memory.
Key Findings: Associative memory and perceived trustworthiness of real and artificial faces across young and older adults.
Citations: 1
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Authors: Y Yin, N Jia, CJ Wakslak
Year: 2024
Published in: Proceedings of the National Academy of ..., 2024 - pnas.org
Institution: University of Southern California Los Angeles
Research Area: Human-AI Interaction, Social Perception of AI, Media Effects
Discipline: Social Science
AI responses make people feel more heard and are better at emotional support compared to humans, but labeling responses as AI diminishes this effect.
Methods: Experiment and follow-up study to assess recipient reactions to AI vs. human-generated responses and determine emotional support efficacy.
Key Findings: The degree to which recipients feel heard, emotion detection accuracy, and third-party ratings of emotional support quality.
DOI: https://doi.org/10.1073/pnas.2319112121
Citations: 201
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Authors: D Guilbeault, S Delecourt, T Hull, BS Desikan, M Chu
Year: 2024
Published in: Nature, 2024 - nature.com
Institution: University of California Berkeley, Institute For Public Policy Research, Columbia University, University of Southern California Los Angeles
Research Area: Gender Bias, Computational Social Science, Online Media, AI Bias
Discipline: Computational Social Science
Online images significantly amplify gender bias compared to text, with biases in visual content impacting societal beliefs about gender roles.
Methods: Analyzed 3,495 social categories using over one million images from platforms like Google, Wikipedia, and IMDb, compared visual content to billions of words from the same platforms, and conducted a preregistered national experiment to assess the psychological impact on participants' beliefs.
Key Findings: The prevalence and psychological impact of gender bias in online images compared to text, including gender associations and representation disparities.
DOI: https://doi.org/10.1038/s41586-024-07068-x
Citations: 72
Sample Size: 3495
