-
A Beauty Contest was Judged by AI and the Robots Didn’t like Dark Skin
lnbressa
Author: Sam Levin; Publisher: The Guardian; Publication Year: 2016. The following article discusses how in 2016, the first artificial intelligence (AI) judged beauty contest was conducted. The objective factors included facial symmetry and wrinkles. Beauty.AI, created by Youth Laboratories and supported by Microsoft, received 6,000 submissions from over 100 countries to identify those who resembled…
-
How I’m Fighting Bias in Algorithms
lnbressa
Author: Joy Buolamwini; Publisher: TED; Publication Year: N/A. The following speech discusses how algorithmic bias, or the “coded gaze,” can lead to discriminatory practices. Machine learning is being used for facial recognition but a lack of Black and Brown faces in training sets has led to an inability to identify them. Joy suggests that we…
-
Human Bias in Machine Learning: How Well Do You Really Know Your Model?
lnbressa
Author: Jim Box, Elena Snavely, and Hiwot Tesfaye; Publisher: SAS Global Forum; Publication Year: 2022. The following paper discusses how it is a common consensus that artificial intelligence (AI) and machine learning (ML) are going to solve problems by letting an objective algorithm make decisions. The issue is that the algorithms are not always objective.…
-
4 Principles of Responsible AI and Best Practices to Adopt Them
2022, Bias, Blog Article, Code of Ethics, Communities of Practice, Diversity, Equity & Inclusion, Notable Peoplelnbressa
Author: Cem Dilmegani; Publisher: AI Multiple; Publication Year: 2022. The following article explores 4 principles for responsible AI design and recommends best practices. The 4 principles, along with best practices, include: 1). achieving fairness by ensuring the training data is representative of the population, analyzing outcomes among subpopulations, and continuous monitoring of the…
-
Bias in AI: What it is, Types, Examples & 6 Ways to Fix It in 2022
lnbressa
Author: Cem Dilmegani; Publisher: AI Multiple; Publication Year: 2022. The following article describes how in the imperfect world, AI can’t be expected to be completely unbiased. However, there are various ways to minimize bias by proper testing of algorithms and building AI systems with responsible AI principles. Fixing bias in AI systems can be summarized…
-
Inequality in the Data Science Industry
lnbressa
Author: Aisulu Omar; Publisher: Towards Data Science; Publication Year: 2022. The following article discusses how data scientists should be more cognizant of the role they play in organizations. Their skill set as a tool can be potentially used by malicious actors. One way to counter this is to ensure representation in the training dataset in…
Archive
Categories
- 1979
- 2002
- 2004
- 2006
- 2007
- 2010
- 2011
- 2012
- 2013
- 2014
- 2015
- 2016
- 2017
- 2018
- 2019
- 2020
- 2021
- 2022
- 2023
- Agriculture
- Automobiles
- Aviation
- Banking & Finance
- Bias
- Blog Article
- Book
- Cartography
- Code of Ethics
- Communities of Practice
- Criminal Justice
- Digital Media
- Diversity, Equity & Inclusion
- Education
- Education & Training
- Encyclopedia
- Environment
- Film, Arts & Entertainment
- Frameworks
- Glossary
- Healthcare
- Industry-Specific
- Insurance
- Legal & Policy
- News Article
- Notable People
- Oil & Gas
- Podcast
- Privacy
- Renewable Energy
- Research Article
- Social Justice
- Sports
- Tool
- Uncategorized
- Underrepresented Author
- Video
- Visualization
- White Paper