Tools for Identifying AI Biases for Machine Learning Models
| dc.contributor.author | Adchariyavivit, Patcharaporn | |
| dc.contributor.author | Crow, Austin | |
| dc.contributor.author | Golden, Victoria | |
| dc.date.accessioned | 2022-01-19T16:55:40Z | |
| dc.date.available | 2022-01-19T16:55:40Z | |
| dc.date.issued | 2021-04-28 | |
| dc.description.abstract | There is no doubt about the usefulness of machine learning in today’s data environment. Machine learning algorithms are used across many domains and across a variety of problems. These algorithms are seen in e-commerce such as Amazon’s recommendations , financing through loan applications, image processing, autonomous vehicles, and speech recognition among many others. Acknowledging the market penetration of machine learning and its relevance to many big data related challenges, it is important to address the effect of bias in machine learning. | |
| dc.identifier.uri | https://hdl.handle.net/1920/12197 | |
| dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/3.0/us/ | |
| dc.subject | Artificial intelligence | |
| dc.subject | Fairness | |
| dc.title | Tools for Identifying AI Biases for Machine Learning Models | |
| dc.type | Working Paper |