Name
Abstract | ||
|---|---|---|
Using inappropriate datasets for data science tasks can be harmful, especially for applications that impact humans. Targeting data ethics, we demonstrate MithraLabel, a system for generating task-specific information about a dataset, in the form of a set of visual widgets, as a flexible "nutritional label" that provides a user with information to determine the fitness of the dataset for the task at hand.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3357384.3357853 | Proceedings of the 28th ACM International Conference on Information and Knowledge Management |
Keywords | Field | DocType |
accountability, data ethics, fairness, machine bias, transparency | Data science,Information retrieval,Computer science | Conference |
ISBN | Citations | PageRank |
978-1-4503-6976-3 | 2 | 0.36 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chenkai Sun | 1 | 3 | 0.71 |
| Abolfazl Asudeh | 2 | 60 | 19.05 |
| H. V. Jagadish | 3 | 11141 | 2495.67 |
| Bill Howe | 4 | 1520 | 94.44 |
| Stoyanovich Julia | 5 | 341 | 36.67 |