Person:
Feigh, Karen M.

Permanent Link
https://hdl.handle.net/1853/71250
Associated Organization(s)
ORCID
ArchiveSpace Name Record

Filters

2012 - 2019 2 2020 - 2023 2
3 1
2 1 1
4
4
Reset filters

Settings
Author: Feigh, Karen M. × search.filters.applied.f.isOrgUnitOfPublicationTitle: Institute for Robotics and Intelligent Machines (IRIM) ×

Publication Search Results

Now showing 1 - 4 of 4
  • Thumbnail Image
    Item
    Expectations and Needs for Interaction in Human Robot Interaction
    (Georgia Institute of Technology, 2023-11-29) Feigh, Karen M.
  • Thumbnail Image
    Item
    The Importance of Shared Mental Models and Collaborative Judgment in Human-AI Interaction
    (Georgia Institute of Technology, 2022-08-24) Feigh, Karen M.
    IRIM hosts each semester a symposium to feature presentations from faculty and presentations of research that has been funded by our IRIM seed grant program in the last year. The symposium is a chance for faculty to meet new PhD students on campus, as well as a chance to get a better idea of what IRIM colleagues are up to these days. The goal of the symposium is to spark new ideas, new collaborations, and even new friends!
  • Thumbnail Image
    Item
    Human Teacher’s Perception of Teaching Methods for Machine Learning Algorithms
    (Georgia Institute of Technology, 2019-02-06) Feigh, Karen M.
    A goal of interactive machine learning (IML) is to create robots or intelligent agents that can be easily taught how to perform tasks by individuals with no specialized training. To achieve that goal, researchers and designers must understand how certain design decisions impact the human’s experience of teaching the agent, such as influencing the agent’s perceived intelligence. We posit that the type of feedback a robot can learn from effects the perceived intelligence of the robot, similar to its physical appearance. This talk will discuss different methods of natural language instruction including critique and action advice. We conducted multiple human-in-the-loop experiments, in which people trained agents with different teaching methods but, unknown to each participant, the same underlying machine learning algorithm. The results show that the mechanism of teaching has an impact on a human teacher’s perception of the agent, including feelings of frustration, perceptions of intelligence, and performance, while only minimally impacting the agent’s performance.
  • Thumbnail Image
    Item
    Development and Evaluation of an Automated Path Planning Aid
    (Georgia Institute of Technology., 2012-11) Watts, Robert ; Christmann, Hans Claus ; Johnson, Eric N. ; Feigh, Karen M. ; Tsiotras, Panagiotis
    Handling en route emergencies in modern transport aircraft through adequate teamwork between the pilot, the crew and the aircraft’s automation systems is an ongoing and active field of research. An automated path planning aid tool can assist pilots with the tasks of selecting a convenient landing site and developing a safe path to land at this site in the event of an onboard emergency. This paper highlights the pilot evaluation results of a human factors study as part of such a proposed automated planning aid. Focusing on the interactions between the pilot and the automated planning aid, the presented results suggest that a particular implementation of the pilot aid interface, which uses a simple dial to sort the most promising landing sites, was effective. This selectable sorting capability, motivated by the anticipated cognitive mode of the pilot crew, improved the quality of the selected site for the majority of the cases tested. Although the presented approach increased the average time required for the selection of an alternate landing site, it decreased the time to complete the task in the case of emergencies unfamiliar to the pilot crew.