Assessing the Impact of Automated Suggestions on Decision Making: Domain Experts Mediate Model Errors but Take Less Initiative
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Arvind Satyanarayan | David Sontag | Ariel Levy | Monica Agrawal | D. Sontag | Arvind Satyanarayan | Monica Agrawal | A. Levy
[1] Eric D. Ragan,et al. The Role of Domain Expertise in User Trust and the Impact of First Impressions with Intelligent Systems , 2020, HCOMP.
[2] Gwenn Englebienne,et al. How model accuracy and explanation fidelity influence user trust , 2019, IJCAI 2019.
[3] Benoît Sagot,et al. Influence of Pre-Annotation on POS-Tagged Corpus Development , 2010, Linguistic Annotation Workshop.
[4] Eric Horvitz,et al. Beyond Accuracy: The Role of Mental Models in Human-AI Team Performance , 2019, HCOMP.
[5] Ilaria Liccardi,et al. Misplaced Trust: Measuring the Interference of Machine Learning in Human Decision-Making , 2020, WebSci.
[6] Jeffrey Heer,et al. Agency plus automation: Designing artificial intelligence into interactive systems , 2019, Proceedings of the National Academy of Sciences.
[7] Kuzman Ganchev,et al. Semi-Automated Named Entity Annotation , 2007, LAW@ACL.
[8] Sunghwan Sohn,et al. Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications , 2010, J. Am. Medical Informatics Assoc..
[9] Thomas S. Morton,et al. WordFreak: An Open Tool for Linguistic Annotation , 2003, HLT-NAACL.
[10] Xiao Zeng,et al. A WEB-Based Version of MedLEE: A Medical Language Extraction and Encoding System. , 1996 .
[11] Sanna Salanterä,et al. Overview of the ShARe/CLEF eHealth Evaluation Lab 2013 , 2013, CLEF.
[12] D. Sculley,et al. Hidden Technical Debt in Machine Learning Systems , 2015, NIPS.
[13] Alan R. Aronson,et al. An overview of MetaMap: historical perspective and recent advances , 2010, J. Am. Medical Informatics Assoc..
[14] E. Salas,et al. Shared mental models in expert team decision making. , 1993 .
[15] Suresh Manandhar,et al. SemEval-2014 Task 7: Analysis of Clinical Text , 2014, *SEMEVAL.
[16] Hua Xu,et al. Research and applications: Assisted annotation of medical free text using RapTAT , 2014, J. Am. Medical Informatics Assoc..
[17] Louise Deléger,et al. Evaluating the impact of pre-annotation on annotation speed and potential bias: natural language processing gold standard development for clinical named entity recognition in clinical trial announcements , 2013, J. Am. Medical Informatics Assoc..
[18] Sampo Pyysalo,et al. brat: a Web-based Tool for NLP-Assisted Text Annotation , 2012, EACL.
[19] Lorenzo Strigini,et al. How to Discriminate between Computer-Aided and Computer-Hindered Decisions , 2013, Medical decision making : an international journal of the Society for Medical Decision Making.
[20] Christopher Ré,et al. Snorkel: Rapid Training Data Creation with Weak Supervision , 2017, Proc. VLDB Endow..
[21] Cláudio T. Silva,et al. HistoryTracker: Minimizing Human Interactions in Baseball Game Annotation , 2019, CHI.
[22] John T. Stasko,et al. Combining Computational Analyses and Interactive Visualization for Document Exploration and Sensemaking in Jigsaw , 2013, IEEE Transactions on Visualization and Computer Graphics.
[23] Philip V. Ogren,et al. Knowtator: A Protégé plug-in for annotated corpus construction , 2006, NAACL.
[24] Lauren Wilcox,et al. "Hello AI": Uncovering the Onboarding Needs of Medical Practitioners for Human-AI Collaborative Decision-Making , 2019, Proc. ACM Hum. Comput. Interact..
[25] Dayong Wang,et al. Deep Learning for Identifying Metastatic Breast Cancer , 2016, ArXiv.
[26] Yunfeng Zhang,et al. Effect of confidence and explanation on accuracy and trust calibration in AI-assisted decision making , 2020, FAT*.
[27] Jure Leskovec,et al. Human Decisions and Machine Predictions , 2017, The quarterly journal of economics.
[28] Scott R. Klemmer,et al. Early and Repeated Exposure to Examples Improves Creative Work , 2012, CogSci.
[29] Krzysztof Z. Gajos,et al. Providing Timely Examples Improves the Quantity and Quality of Generated Ideas , 2015, Creativity & Cognition.
[30] Nagarajan Natarajan,et al. Learning with Noisy Labels , 2013, NIPS.
[31] Anna Rumshisky,et al. MCN: A comprehensive corpus for medical concept normalization , 2019, J. Biomed. Informatics.
[32] Parth Pathak,et al. Annotation of a Large Clinical Entity Corpus , 2018, EMNLP.
[33] Mara Gorli,et al. What hinders the uptake of computerized decision support systems in hospitals? A qualitative study and framework for implementation , 2017, Implementation Science.
[34] Ming Yin,et al. Understanding the Effect of Accuracy on Trust in Machine Learning Models , 2019, CHI.
[35] L C Kingsland,et al. The ranking algorithm of the Coach browser for the UMLS metathesaurus. , 1993, Proceedings. Symposium on Computer Applications in Medical Care.
[36] Stuart J. Nelson,et al. Normalized names for clinical drugs: RxNorm at 6 years , 2011, J. Am. Medical Informatics Assoc..
[37] Daniel King,et al. ScispaCy: Fast and Robust Models for Biomedical Natural Language Processing , 2019, BioNLP@ACL.
[38] Sarit Kraus,et al. The Evolution of Sharedplans , 1999 .
[39] Tamara Munzner,et al. Overview: The Design, Adoption, and Analysis of a Visual Document Mining Tool for Investigative Journalists , 2014, IEEE Transactions on Visualization and Computer Graphics.
[40] Krzysztof Z. Gajos,et al. Proxy tasks and subjective measures can be misleading in evaluating explainable AI systems , 2020, IUI.
[41] Stéphane M. Meystre,et al. Evaluating the effects of machine pre-annotation and an interactive annotation interface on manual de-identification of clinical text , 2014, J. Biomed. Informatics.
[42] J. J. Higgins,et al. The aligned rank transform for nonparametric factorial analyses using only anova procedures , 2011, CHI.
[43] Iryna Gurevych,et al. Automatic Annotation Suggestions and Custom Annotation Layers in WebAnno , 2014, ACL.
[44] John D. Lee,et al. Trust in Automation: Designing for Appropriate Reliance , 2004, Hum. Factors.
[45] Jeffrey Heer,et al. Human Effort and Machine Learnability in Computer Aided Translation , 2014, EMNLP.
[46] Peter Szolovits,et al. MIMIC-III, a freely accessible critical care database , 2016, Scientific Data.
[47] Zahra Ashktorab,et al. Mental Models of AI Agents in a Cooperative Game Setting , 2020, CHI.
[48] Jie Yang,et al. YEDDA: A Lightweight Collaborative Text Span Annotation Tool , 2017, ACL.