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Examining Age-Related Differences in Cognitive Biases in Acquiring Knowledge About AI
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Author(s): Adrienne Bethany Barretto (Parvatibai Chowgule College of Arts and Science, India), Pratiksha Gurudatt Mallya (Parvatibai Chowgule College of Arts and Science, India), Evira Daniela Pereira (Parvatibai Chowgule College of Arts and Science, India), Saloni Joanna Rodrigues (Parvatibai Chowgule College of Arts and Science, India), Vanessa Bonita Pereira (Parvatibai Chowgule College of Arts and Science, India), Shalyn Angel Cardozo (Parvatibai Chowgule College of Arts and Science, India)and Jeanne Marie Cotta (Parvatibai Chowgule College of Arts and Science, India)
Copyright: 2026
Pages: 44
Source title:
Examining Social Psychology in Virtual Environments
Source Author(s)/Editor(s): Ruqia Safdar Bajwa (Bahauddin Zakariya University, Pakistan), Sarwat Sultan (Bahauddin Zakariya University, Pakistan)and Asma Yunus (University of Sargodha, Pakistan)
DOI: 10.4018/979-8-3373-5896-3.ch002
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Abstract
The rise of artificial intelligence (AI) necessitates understanding how cognitive biases shape our perception of this evolving technology. This study examined the relationship between age and susceptibility to biases in acquiring AI-related knowledge. It addressed three objectives: to explore the influence of cognitive biases in AI knowledge acquisition, to identify the types of biases involved, and to examine age-related differences. Sixty participants were evenly divided across young, middle, and older adulthood. The findings indicated that younger adults demonstrated higher levels of confirmation bias (80%), middle-aged adults exhibited declinism bias (70%), and older adults displayed availability bias (75%). The least evident biases were distinction bias and authority bias among young adults (30% each), belief bias among middle-aged adults (20%), and belief bias and distinction bias among older adults (30% each). The overall findings provides an understanding of how biases influence AI knowledge acquisition across age groups, laying groundwork for future research.
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