Imani N. Sherman

About

Imani N. Sherman is a researcher at the intersection of human-computer interaction and computer vision, with a primary focus on understanding the cognitive and social factors that shape trust in automated image analysis systems. Her most cited work, "Human Trust Factors in Image Analysis" (2018), has garnered 5 citations and lays foundational groundwork for examining how human biases, expectations, and prior experiences influence the acceptance and reliance on AI-generated interpretations of visual data. This research is critical as machine learning models become increasingly integrated into fields like medical imaging, security, and autonomous systems, where human oversight remains essential. Sherman’s contributions highlight the nuanced interplay between algorithmic outputs and human judgment, offering insights that can inform the design of more transparent and trustworthy AI interfaces. By bridging technical performance with user psychology, her work helps ensure that automated systems are not only accurate but also aligned with human decision-making processes. Her research is particularly valuable for students and practitioners seeking to build human-centered AI that fosters appropriate reliance and mitigates over-trust or under-trust in critical applications.

Research Focus

Key Achievements

Top Papers

1. 1
   Human Trust Factors in Image Analysis

   5 citations · 2018

Key Collaborators

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