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Investigating the Importance of First Impressions and Explainable AI with Interactive Video Analysis

Authors:

Mahsan Nourani,

Donald R. Honeycutt,

Jeremy E. Block,

Tahrima Rahman,

Vibhav GogateAuthors Info & Claims

CHI EA '20: Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems

Pages 1 - 8

https://doi.org/10.1145/3334480.3382967

Published: 25 April 2020 Publication History

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Abstract

We present research on how the perception of intelligent systems can be influenced by early experiences of machine performance, and how explainability potentially helps users develop an accurate understanding of system capabilities. Using a custom video analysis system with AI-assisted activity recognition, we studied whether presenting explanatory information for system outputs affects user perception of the system. In this experiment, some participants encountered AI weaknesses early, while others encountered the same limitations later in the study. The difference in ordering had a significant impact on user understanding of the system and the ability to detect AI strengths and weaknesses, and the addition of explanations was not enough to counteract the strong effects of early impressions. The results demonstrate the importance of first impressions with intelligent systems and motivate the need for improved methods of intervention to combat automation bias.

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References

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Cited By

Al-Ansari NAl-Thani DAl-Mansoori R(2024)User‐Centered Evaluation of Explainable Artificial Intelligence (XAI): A Systematic Literature ReviewHuman Behavior and Emerging Technologies10.1155/2024/46288552024:1Online publication date: 15-Jul-2024
https://doi.org/10.1155/2024/4628855
Humer CHinterreiter ALeichtmann BMara MStreit M(2024)Reassuring, Misleading, Debunking: Comparing Effects of XAI Methods on Human DecisionsACM Transactions on Interactive Intelligent Systems10.1145/366564714:3(1-36)Online publication date: 22-May-2024
https://dl.acm.org/doi/10.1145/3665647
Lu ZWang DYin M(2024)Does More Advice Help? The Effects of Second Opinions in AI-Assisted Decision MakingProceedings of the ACM on Human-Computer Interaction10.1145/36537088:CSCW1(1-31)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3653708
Show More Cited By

Index Terms

Investigating the Importance of First Impressions and Explainable AI with Interactive Video Analysis
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Empirical studies in HCI
    2. HCI design and evaluation methods
      1. User studies

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Information

Published In

cover image ACM Conferences

CHI EA '20: Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems

April 2020

4474 pages

ISBN:9781450368193

DOI:10.1145/3334480

General Chairs:
Regina Bernhaupt
Eindhoven University of Technology, Netherlands
,
Florian 'Floyd' Mueller
Monash University, Australia
,
David Verweij
Newcastle University, UK
,
Josh Andres
RMIT, Australia
,
Program Chairs:
Joanna McGrenere
University of British Columbia, Canada
,
Andy Cockburn
University of Canterbury, New Zealand
,
Ignacio Avellino
University of Maryland Baltimore County, USA
,
Alix Goguey
Grenoble Alpes University, France
,
Pernille Bjørn
University of Copenhagen, Denmark
,
Shengdong (Shen) Zhao
National University of Singapore, Singapore
,
Briane Paul Samson
Future University Hakodate, Japan & De La Salle University, Philippines
,
Rafal Kocielnik
University of Washington, USA

Copyright © 2020 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 April 2020

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Defense Advanced Research Projects Agency

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CHI '20

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SIGCHI

CHI '20: CHI Conference on Human Factors in Computing Systems

April 25 - 30, 2020

HI, Honolulu, USA

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Overall Acceptance Rate 6,164 of 23,696 submissions, 26%

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CHI 2025

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ACM CHI Conference on Human Factors in Computing Systems

April 26 - May 1, 2025

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Cited By

Al-Ansari NAl-Thani DAl-Mansoori R(2024)User‐Centered Evaluation of Explainable Artificial Intelligence (XAI): A Systematic Literature ReviewHuman Behavior and Emerging Technologies10.1155/2024/46288552024:1Online publication date: 15-Jul-2024
https://doi.org/10.1155/2024/4628855
Humer CHinterreiter ALeichtmann BMara MStreit M(2024)Reassuring, Misleading, Debunking: Comparing Effects of XAI Methods on Human DecisionsACM Transactions on Interactive Intelligent Systems10.1145/366564714:3(1-36)Online publication date: 22-May-2024
https://dl.acm.org/doi/10.1145/3665647
Lu ZWang DYin M(2024)Does More Advice Help? The Effects of Second Opinions in AI-Assisted Decision MakingProceedings of the ACM on Human-Computer Interaction10.1145/36537088:CSCW1(1-31)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3653708
Kolarik MSarnovsky MParalic JBabic F(2023)Explainability of deep learning models in medical video analysis: a surveyPeerJ Computer Science10.7717/peerj-cs.12539(e1253)Online publication date: 14-Mar-2023
https://doi.org/10.7717/peerj-cs.1253
Zhang RDuan WFlathmann CMcNeese NFreeman GWilliams A(2023)Investigating AI Teammate Communication Strategies and Their Impact in Human-AI Teams for Effective TeamworkProceedings of the ACM on Human-Computer Interaction10.1145/36100727:CSCW2(1-31)Online publication date: 4-Oct-2023
https://dl.acm.org/doi/10.1145/3610072
Kim AYang MZhang J(2023) When Algorithms Err: Differential Impact of Early vs. Late Errors on Users’ Reliance on AlgorithmsACM Transactions on Computer-Human Interaction10.1145/355788930:1(1-36)Online publication date: 18-Mar-2023
https://dl.acm.org/doi/10.1145/3557889
Rodolico GHirsu L(2023)Virtual Reality in education: supporting new learning experiences by developing self-confidence of Postgraduate Diploma in Education (PGDE) student-teachersEducational Media International10.1080/09523987.2023.226219560:2(92-108)Online publication date: 26-Sep-2023
https://doi.org/10.1080/09523987.2023.2262195
Himeur YAl-Maadeed SKheddar HAl-Maadeed NAbualsaud KMohamed AKhattab T(2023)Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalizationEngineering Applications of Artificial Intelligence10.1016/j.engappai.2022.105698119(105698)Online publication date: Mar-2023
https://doi.org/10.1016/j.engappai.2022.105698
Karran ADemazure THudon ASenecal SLéger P(2022)Designing for Confidence: The Impact of Visualizing Artificial Intelligence DecisionsFrontiers in Neuroscience10.3389/fnins.2022.88338516Online publication date: 24-Jun-2022
https://doi.org/10.3389/fnins.2022.883385
Nourani MRoy CBlock JHoneycutt DRahman TRagan EGogate V(2022)On the Importance of User Backgrounds and Impressions: Lessons Learned from Interactive AI ApplicationsACM Transactions on Interactive Intelligent Systems10.1145/353106612:4(1-29)Online publication date: 12-Dec-2022
https://dl.acm.org/doi/10.1145/3531066
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