Work

MithraLabel

Year: 2019

Type: conference-paper

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.

Source: ACM International Conference on Information and Knowledge Management (CIKM)

DOI: 10.1145/3357384.3357853

Authors: Chenkai Sun, Abolfazl Asudeh, H. V. Jagadish, Bill Howe, Julia Stoyanovich

Institutions: University of Michigan, University of Illinois Chicago, University of Washington, New York University

Language: English

Topic: Ethics and Social Impacts of AI

Subfield: Safety Research

Field: Social Sciences

Domain: Social Sciences

Open Access status: bronze

Funder: National Science Foundation

Awards: BIGDATA: F: Collaborative Research: Foundations of Responsible Data Management, BIGDATA: F: Collaborative Research: Foundations of Responsible Data Management, BIGDATA: F: Collaborative Research: Foundations of Responsible Data Management