dc.contributor.author | Bradley, Robin | |
dc.date.accessioned | 2020-05-19T00:03:28Z | |
dc.date.available | 2020-05-19T00:03:28Z | |
dc.date.issued | 2020-02-17 | |
dc.identifier.citation | Bradley , R 2020 , ' How to Solve AI Bias ' , Paper presented at Women in Tech - Bias in AI , London , United Kingdom , 17/02/20 - 17/02/20 . | |
dc.identifier.citation | workshop | |
dc.identifier.uri | http://hdl.handle.net/2299/22716 | |
dc.description | © 2020 The Author(s). This an open access work distributed under the terms of the Creative Commons Attribution Licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. | |
dc.description.abstract | Bias in AI is a topic that impacts machine learning and artificial intelligence technology that learns from datasets and its training data. While gender discrimination and chatbots showing bias have recently caught people’s attention and imagination, the overall area of how to correct and manage bias is in its infancy for business use. Further, little is known about how to solve bias in AI and how there could potent for malicious misuse at large scale. We explore this area and propose solutions to this problem. | en |
dc.format.extent | 7 | |
dc.format.extent | 252302 | |
dc.language.iso | eng | |
dc.subject | Artificial intelligence | |
dc.subject | AI artificial intelligence | |
dc.subject | bias | |
dc.subject | Machine Learning | |
dc.subject | Algorithm and data structure visualization | |
dc.subject | Algorithms | |
dc.subject | ethics and politics | |
dc.subject | Ethics Committees, Research | |
dc.subject | ethics; socially responsible investment | |
dc.subject | testing methodology | |
dc.subject | Artificial Intelligence | |
dc.subject | Computer Vision and Pattern Recognition | |
dc.title | How to Solve AI Bias | en |
dc.contributor.institution | School of Physics, Engineering & Computer Science | |
dc.contributor.institution | ECS Computer Science VLs | |
dc.description.status | Non peer reviewed | |
rioxxterms.type | Other | |
herts.preservation.rarelyaccessed | true | |