![Lana Tikhomirov](/sites/default/files/styles/profile_large/public/profile-images/27679.png?itok=fP3oG9o2)
Lana Tikhomirov
Higher Degree by Research Candidate
School of Psychology
Faculty of Health and Medical Sciences
Advancements in AI-based technologies far outpace research that inform us of their influence on human decision-making. Traditional research on human-computer interaction demonstrates the challenges of effective decision-making when combining these two fundamentally different entities. As such, my work resides in the nascent field that combines AI safety, cognitive science, and human factors research for development of complementary and safe AI technologies. Specifically, I investigate the impact of medical AI systems in clinical radiology. Further, I am interested in ethical and safe AI development to ensure fairness and accountability practices.
I am jointly supervised by Associate Professor Carolyn Semmler (School of Psychology) and Dr. Lauren Oakden-Rayner (School of Medicine/Australian Institute for Machine Learning). I am based at the Australian Institute for Machine Learning.
Advancements in AI far outpace research that inform us of their cognitive and decisional influences on humans. Traditional research on human-computer interaction demonstrates the challenges of effective decision-making when combining these two fundamentally different entities. As such, my work resides in the nascent field that combines AI safety, cognitive science, and human factors research for development of effective decisional AI technologies. Specifically, I investigate the impact of medical AI systems from model development to implementation on clinical decision-making. Based at the Australian Institute for Machine Learning, my project is an interdisciplinary approach to the design and implementation of AI in high-risk settings. My research aims to inform human-computer interaction research from a cognitive science perspective and provide insight for industries in medical technology. Further, I am interested in ethical AI development to ensure fairness and accountability practices.
I am jointly supervised by Associate Professor Carolyn Semmler (School of Psychology) and Dr. Lauren Oakden-Rayner (School of Medicine/Australian Institute for Machine Learning).
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Appointments
Date Position Institution name 2022 - 2025 PhD Candidate University of Adelaide -
Education
Date Institution name Country Title Flinders University Australia Bachelor of Psychology (Honours) -
Research Interests
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Journals
Year Citation 2023 Tikhomirov, L., Semmler, C., & Searston, R. (2023). Medical AI for Radiology: The Lost Cognitive Perspective.
2023 Tikhomirov, L., Bartlett, M. L., Duncan-Reid, J., & McCarley, J. S. (2023). Identifying Inefficient Strategies in Automation-Aided Signal Detection. Journal of Experimental Psychology: Applied, 29(4), 869-886.
2022 Tikhomirov, L., Bartlett, M. L., Duncan-Reid, J., & McCarley, J. S. (2022). Identifying Inefficient Strategies in Automation-Aided Signal Detection.
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Report for External Bodies
Year Citation 2024 Semmler, C., Palmer, L., McCradden, M., Oakden-Rayner, L., & Tikhomirov, L. (2024). Submission to Senate Select Committee on Adopting Artificial Intelligence (AI) - Submission 95 (95). 2023 Semmler, C., & Tikhomirov, L. (2023). Responsible AI means keeping humans in the loop. -
Preprint
Year Citation 2024 Tikhomirov, L., Smith, L., Oakden-Rayner, L., Bird, A., Palmer, L., & Semmler, C. (2024). Large-Scale Evaluation of the Influence of AI-use on Radiologist Performance using Signal Detection Theory.
Connect With Me
External Profiles