Houston Claure

Societal Impact of AI Fairness

Exploring how robot decision-making drives human behavior

Algorithms are beginning to shape court decisions, whom we hire, who gets approved for a loan, or who is admitted into college. Recognizing the importance and urgency to build understanding about the increasing influence that machines have over our lives as individuals and societies, my goal is to investigate how human behavior is shaped by these machines' decisions. In my research projects, I build platforms that recreate standard machine behaviors (e.g., distributing resources across a team of humans) and collect large-scale data on human behavior.


Co-Tetris: The Multiplayer Tetris Game. I designed this multiplayer game to explore the influence of AI algorithms on group member perceptions through large-scale data collection, aiming to analyze the effects of fair or unfair AI decisions.

Publications:

  • Claure, H., Shin,I., Trafton, G., Vázquez M. 2024. The Fairness in Human-Robot Interactions Scale (F-HRI) Development and Validation. ACM/IEEE International Conference on Human-Robot Interaction (HRI). In Preparation.
  • Claure, H., Candon, K., Clark, O.,Vázquez, M. 2024. Multiplayer Space Invaders: A Platform for Studying Evolving Fairness Perceptions in Human-Robot Interaction. Companion of the ACM/IEEE International Conference on Human-Robot Interaction (HRI). Submitted.
  • Claure, H., Kim, S., Kizilcec, R., & Jung, M. 2023. The social consequences of machine allocation behavior: Fairness, interpersonal perceptions and performance. Computers in Human Behavior.
  • Claure, H., Jung, M. 2021. Fairness Considerations for Enhanced Team Collaboration. Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction (HRI)
  • Jung, M. F., DiFranzo, D., Stoll, B., Shen, S., Lawrence, A., & Claure, H. 2021. Robot Assisted Tower Construction - A Resource Distribution Task to Study Human-Robot Collaboration and Interaction with Groups of People. ACM Transactions on Human-Robot Interaction.

Designing Fair Algorithms

Investigating how we can develop fair AI algorithms for robots

In this line of work, I explore the use of reinforcement learning as a means to develop fair algorithms. I focus on contexts where robots would be integrated into human teams consisting of one or more humans. One approach includes using our developed upper confidence bound (UCB) algorithm to have a system adapt and regulate its allocation of resources. Additionally, I explored how perceived fairness influences a team member's performance within the group.


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Interactive Hardware Design

Building and Studying Hardware Designs on Human Experiences

In these projects I developed different hardware and software platforms as well as explored different aspects of human interaction with technology. For instance, the project image below was a collaboration with Dr. Robert Shepherd's Organic Robotics Laboratory (ORL) at Cornell University and NVIDIA. The goal was to develop a novel type of virtual reality controller sleeve that is capable of providing haptic feedback. We developed and tested a 12 DOF fluidically pressurized soft actuator for persistent and kinesthetic haptic sensations. We tested the controller through a user experience test after the development of a software interface with NVIDIA's game VR Funhhouse. Results demonstrated which haptic stimulations from the controller were more recognizable by human participants as well as how the controller sleeve influenced the game experience.


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