Data excellence for AI

Author:

Aroyo Lora1,Lease Matthew2,Paritosh Praveen1,Schaekermann Mike3

Affiliation:

1. Google Research

2. University of Texas at Austin

3. Amazon

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

Publisher

Association for Computing Machinery (ACM)

Subject

Human-Computer Interaction

Reference6 articles.

1. “Everyone wants to do the model work, not the data work”: Data Cascades in High-Stakes AI

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. 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.

3. 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 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

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

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

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