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Data excellence for AI: why should you care?

Authors:

Lora Aroyo,

Matthew Lease,

Praveen Paritosh,

Mike SchaekermannAuthors Info & Claims

Interactions, Volume 29, Issue 2

Pages 66 - 69

https://doi.org/10.1145/3517337

Published: 25 February 2022 Publication History

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Abstract

This forum provides a space to engage with the challenges of designing for intelligent algorithmic experiences. We invite articles that tackle the tensions between research and practice when integrating AI and UX design. We welcome interdisciplinary debate, artful critique, forward-looking research, case studies of AI in practice, and speculative design explorations. --- Juho Kim and Henriette Cramer, Editors

References

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Sambasivan, N., Kapania, S., Highfill, H., Akrong, D., Paritosh, P., and Aroyo, L. "Everyone wants to do the model work, not the data work": Data cascades in high-stakes AI. Proc. of the 2021 CHI Conference on Human Factors in Computing Systems. ACM, New York, 2021, Article 39, 1--15.

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Google Scholar

[2]

Amershi, S. et al. Software engineering for machine learning: a case study. Proc. of the 41st International Conference on Software Engineering: Software Engineering in Practice. IEEE Press, 2019, 291--300.

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Aroyo, L. and Paritosh, P. Uncovering unknown unknowns in machine learning. Google AI blog. Feb. 11, 2021; https://ai.googleblog.com/2021/02/uncovering-unknown-unknowns-in-machine.html

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Reducing annotation artifacts in crowdsourcing datasets for natural language processing. Han, D., Kim, J., and Oh, A. 1st Data Excellence Workshop at HCOMP 2020.

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Christensen, J. and Watson, B. Machine learning training to support diversity of opinion. 1st Data Excellence Workshop at HCOMP 2020.

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Kapania, S., Sambasivan, N., Olson, K., Highfill, H., Akrong, D., Paritosh, P., and Aroyo, L. Data desiderata: Reliability and fidelity in high-stakes AI. 1st Data Excellence Workshop at HCOMP 2020.

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Olari VRomeike R(2024)Data-related practices for creating Artificial Intelligence systems in K-12Proceedings of the 19th WiPSCE Conference on Primary and Secondary Computing Education Research10.1145/3677619.3678115(1-10)Online publication date: 16-Sep-2024
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Yin YFeng YWeng SYao YLiu JZhao ZChristakis MPradel M(2024)Datactive: Data Fault Localization for Object Detection SystemsProceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3650212.3680329(895-907)Online publication date: 11-Sep-2024
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Data excellence for AI: why should you care?

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Information

Published In

Interactions Volume 29, Issue 2

March - April 2022

73 pages

ISSN:1072-5520

EISSN:1558-3449

DOI:10.1145/3522718

Editors:
Mikael Wiberg
Association for Computing Machinery, New York, NY
,
Alex Taylor
Association for Computing Machinery, New York, NY
,
Daniela Rosner
Association for Computing Machinery, New York, NY

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This work is licensed under a Creative Commons Attribution International 4.0 License.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 February 2022

Published in INTERACTIONS Volume 29, Issue 2

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Olari VRomeike R(2024)Data-related practices for creating Artificial Intelligence systems in K-12Proceedings of the 19th WiPSCE Conference on Primary and Secondary Computing Education Research10.1145/3677619.3678115(1-10)Online publication date: 16-Sep-2024
https://dl.acm.org/doi/10.1145/3677619.3678115
Yin YFeng YWeng SYao YLiu JZhao ZChristakis MPradel M(2024)Datactive: Data Fault Localization for Object Detection SystemsProceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3650212.3680329(895-907)Online publication date: 11-Sep-2024
https://dl.acm.org/doi/10.1145/3650212.3680329
Herrera-Poyatos DPoyatos ASoldado RDe Palacios PEsteban LIruela AFernández FHerrera F(2024)Deep Learning methodology for the identification of wood species using high-resolution macroscopic images2024 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN60899.2024.10650590(1-8)Online publication date: 30-Jun-2024
https://doi.org/10.1109/IJCNN60899.2024.10650590
Olari VRomeike R(2024)Data-related concepts for artificial intelligence education in K-12Computers and Education Open10.1016/j.caeo.2024.1001967(100196)Online publication date: Dec-2024
https://doi.org/10.1016/j.caeo.2024.100196
Mostofi FTokdemir OToğan V(2024)Leveraging Variational Autoencoder for Improved Construction Progress Prediction PerformanceProceedings of the 10th International Conference on Civil Engineering10.1007/978-981-97-4355-1_51(538-545)Online publication date: 20-Jul-2024
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Allison E(2024)Binary Classification of Medical Images by Symbolic RegressionAdvances in Computational Intelligence Systems10.1007/978-3-031-47508-5_40(516-527)Online publication date: 1-Feb-2024
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Yang JBozzon AGadiraju ULease M(2023)Editorial: Human-centered AI: Crowd computingFrontiers in Artificial Intelligence10.3389/frai.2023.11610066Online publication date: 15-Mar-2023
https://doi.org/10.3389/frai.2023.1161006
Balayn AYurrita MYang JGadiraju U(2023)“☑ Fairness Toolkits, A Checkbox Culture?” On the Factors that Fragment Developer Practices in Handling Algorithmic HarmsProceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society10.1145/3600211.3604674(482-495)Online publication date: 8-Aug-2023
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Priestley MO’donnell FSimperl E(2023)A Survey of Data Quality Requirements That Matter in ML Development PipelinesJournal of Data and Information Quality10.1145/359261615:2(1-39)Online publication date: 22-Jun-2023
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Jarrahi MMemariani AGuha S(2023)The Principles of Data-Centric AICommunications of the ACM10.1145/357172466:8(84-92)Online publication date: 25-Jul-2023
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New alliances and continuing excellence

Pursuit of Operational Excellence: A Systemic Approach

WSDM '19: Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining

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