Lauren Hoffmann

Papers

Total Citations

H-Index

About

Lauren Hoffmann is a researcher focused on the human dimensions of autonomous systems, particularly the psychological and social barriers that impede trust in emerging technologies. Her work critically examines how users perceive and interact with future autonomy, bridging the gap between technical development and human acceptance. Her most-cited paper, "Exploring Trust Barriers to Future Autonomy: A Qualitative Look" (2017), has garnered 10 citations, establishing a foundational qualitative framework for understanding user skepticism and resistance to autonomous systems. This study highlights key factors such as transparency, control, and reliability that shape trust, offering actionable insights for designers and policymakers. Hoffmann’s contributions are notable for their emphasis on user-centered perspectives in a field often dominated by technical metrics. By prioritizing qualitative inquiry, she provides a nuanced understanding of trust dynamics that quantitative approaches may overlook. Her work is essential for researchers and students exploring human-robot interaction, ethics in AI, and the social implications of automation, positioning her as a thoughtful voice in the discourse on responsible innovation.