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ORCIDShane T. Mueller
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- affiliation: Michigan Technological University, Houghton, Michigan, USA
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Journal Articles
- 2023
[j13]Gary Klein, Robert R. Hoffman, William J. Clancey, Shane T. Mueller, Florian Jentsch, Mohammadreza Jalaeian
:
"Minimum Necessary Rigor" in empirically evaluating human-AI work systems. AI Mag. 44(3): 274-281 (2023)- [j12]Robert R. Hoffman, Mohammadreza Jalaeian, Connor Tate, Gary Klein, Shane T. Mueller:
Evaluating machine-generated explanations: a "Scorecard" method for XAI measurement science. Frontiers Comput. Sci. 5 (2023) - [j11]Robert R. Hoffman, Shane T. Mueller, Gary Klein, Mohammadreza Jalaeian, Connor Tate:
Explainable AI: roles and stakeholders, desirements and challenges. Frontiers Comput. Sci. 5 (2023) - [j10]Robert R. Hoffman, Shane T. Mueller, Gary Klein, Jordan Litman:
Measures for explainable AI: Explanation goodness, user satisfaction, mental models, curiosity, trust, and human-AI performance. Frontiers Comput. Sci. 5 (2023) - [j9]Robert R. Hoffman, Tim Miller, Gary Klein, Shane T. Mueller, William J. Clancey:
Increasing the Value of XAI for Users: A Psychological Perspective. Künstliche Intell. 37(2): 237-247 (2023) - 2022
- [j8]Anne Linja, Tauseef Ibne Mamun, Shane T. Mueller:
When Self-Driving Fails: Evaluating Social Media Posts Regarding Problems and Misconceptions about Tesla's FSD Mode. Multimodal Technol. Interact. 6(10): 86 (2022) - 2021
- [j7]Lamia Alam, Shane T. Mueller:
Examining the effect of explanation on satisfaction and trust in AI diagnostic systems. BMC Medical Informatics Decis. Mak. 21(1): 178 (2021) - 2018
- [j6]Robert R. Hoffman, Tim Miller, Shane T. Mueller, Gary Klein, William J. Clancey:
Explaining Explanation, Part 4: A Deep Dive on Deep Nets. IEEE Intell. Syst. 33(3): 87-95 (2018) - [j5]Shane T. Mueller, Yin-Yin (Sarah) Tan:
Cognitive perspectives on opinion dynamics: the role of knowledge in consensus formation, opinion divergence, and group polarization. J. Comput. Soc. Sci. 1(1): 15-48 (2018) - 2017
- [j4]Robert R. Hoffman, Shane T. Mueller, Gary Klein:
Explaining Explanation, Part 2: Empirical Foundations. IEEE Intell. Syst. 32(4): 78-86 (2017) - 2015
- [j3]Shane T. Mueller, Brandon S. Perelman, Yin-Yin Tan, Kejkaew Thanasuan:
Development of the PEBL Traveling Salesman Problem Computerized Testbed. J. Probl. Solving 8(1) (2015) - 2011
- [j2]Shane T. Mueller, Benjamin Simpkins, George Anno, Corey K. Fallon, Owen Price, Gene E. McClellan:
Adapting the task-taxon-task methodology to model the impact of chemical protective gear. Comput. Math. Organ. Theory 17(3): 251-271 (2011) - [j1]Shane T. Mueller, Gary Klein:
Improving Users' Mental Models of Intelligent Software Tools. IEEE Intell. Syst. 26(2): 77-83 (2011)
Conference and Workshop Papers
- 2022
- [c18]Christopher Cischke, Shane T. Mueller:
Examining the Effectiveness of Different Assessments and Forecasts for Accurate Judgments of Learning in Engineering Classes. CSEDU (1) 2022: 497-503 - 2021
- [c17]Lamia Alam, Shane T. Mueller:
Assessing Clustering Methods to Establish Reliability and Consensus in Card Sorting Tasks. AHFE (17) 2021: 961-968 - [c16]Tauseef Ibne Mamun, Robert R. Hoffman, Shane T. Mueller:
Collaborative Explainable AI: A Non-algorithmic Approach to Generating Explanations of AI. HCI (44) 2021: 144-150 - [c15]Ashley F. McDermott, Elizabeth S. Veinott, Leonard Eusebi, Elizabeth T. Whitaker, Ethan Brantley Trewhitt, Shane T. Mueller, David A. Illingworth, Rick Thomas, Michael R. Dougherty, Sean L. Guarino:
Developing an Adaptive Framework to Support Intelligence Analysis. HCI (31) 2021: 550-558 - 2019
- [c14]Roberto Confalonieri, Tarek R. Besold, Tillman Weyde, Kathleen Creel, Tania Lombrozo, Shane T. Mueller, Patrick Shafto:
What makes a good explanation? Cognitive dimensions of explaining intelligent machines. CogSci 2019: 25-26 - [c13]Shane T. Mueller, Yin-Yin (Sarah) Tan, Isaac Flint:
Development and Evaluation of a Model of Human Comfort and Cognitive Ability for Moderate Differences in Thermal Environment. HCI (LBP) 2019: 395-411 - 2018
- [c12]Kaitlyn M. Roose, Elizabeth S. Veinott, Shane T. Mueller:
The Tracer Method: The Dynamic Duo Combining Cognitive Task Analysis and Eye Tracking. CHI PLAY (Companion) 2018: 585-593 - [c11]Shane T. Mueller, Elizabeth S. Veinott:
Testing the effectiveness of crossword games on immediate and delayed memory for scientific vocabulary and concepts. CogSci 2018 - [c10]Caden Sumner, Samantha Verran, Shane T. Mueller:
Equality in Dictator Games: Methodological Concerns in Interpreting Default-Mode Strategies and Norms for Equity. CogSci 2018 - 2017
- [c9]Brandon S. Perelman, Shane T. Mueller, Kristin E. Schaefer:
Evaluating path planning in human-robot teams: Quantifying path agreement and mental model congruency. CogSIMA 2017: 1-7 - 2015
- [c8]Kejkaew Thanasuan, Shane T. Mueller:
Improving Lexical Memory Access and Decision Making Processes Using Cognitive Word Games. CogSci 2015 - 2012
- [c7]Kejkaew Thanasuan, Shane T. Mueller:
An Exploration of Crossword Skill. CogSci 2012 - 2011
- [c6]Shane T. Mueller:
Tutorial on using the Psychology Experiment Building Language (PEBL) in the laboratory, the field, and the classroom. CogSci 2011 - 2010
- [c5]Corey K. Fallon, Anne K. G. Murphy, Laura Zimmerman, Shane T. Mueller:
The calibration of trust in an automated system: A sensemaking process. CTS 2010: 390-395 - 2009
- [c4]Alexei V. Samsonovich, David C. Noelle, Shane T. Mueller:
Preface. AAAI Fall Symposium: Biologically Inspired Cognitive Architectures 2009 - [c3]Winston R. Sieck, Shane T. Mueller:
Cultural variations in collaborative decision making: driven by beliefs or social norms? IWIC 2009: 111-118 - 2008
- [c2]Alexei V. Samsonovich, Shane T. Mueller:
Preface: Toward a Growing Computational Replica of the Human Mind. AAAI Fall Symposium: Biologically Inspired Cognitive Architectures 2008: 1-3 - [c1]Shane T. Mueller, Brandon S. Minnery:
Adapting the Turing Test for Embodied Neurocognitive Evaluation of Biologically-Inspired Cognitive Agents. AAAI Fall Symposium: Biologically Inspired Cognitive Architectures 2008: 117-126
Informal and Other Publications
- 2021
- [i5]Shane T. Mueller, Elizabeth S. Veinott, Robert R. Hoffman, Gary Klein, Lamia Alam, Tauseef Mamun, William J. Clancey:
Principles of Explanation in Human-AI Systems. CoRR abs/2102.04972 (2021) - 2020
- [i4]Shane T. Mueller:
Cognitive Anthropomorphism of AI: How Humans and Computers Classify Images. CoRR abs/2002.03024 (2020) - [i3]Robert R. Hoffman, William J. Clancey, Shane T. Mueller:
Explaining AI as an Exploratory Process: The Peircean Abduction Model. CoRR abs/2009.14795 (2020) - 2019
- [i2]Shane T. Mueller, Robert R. Hoffman, William J. Clancey, Abigail Emrey, Gary Klein:
Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI. CoRR abs/1902.01876 (2019) - 2018
- [i1]Robert R. Hoffman, Shane T. Mueller, Gary Klein, Jordan Litman:
Metrics for Explainable AI: Challenges and Prospects. CoRR abs/1812.04608 (2018)
Coauthor Index
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