If the historical data used to train an AI system disadvantages certain minority groups, the system can be swayed to follow these patterns in its own decision-making process.
A-level students protest the use of algorithms to determine their grades.
Jonathan Brady/PA Wire/PA Images
A report calls for banning the use of emotion recognition technology. An AI and computer vision researcher explains the potential and why there's growing concern.
When algorithms make decisions with real-world consequences, they need to be fair.
R-Type/Shutterstock.com
A machine learning expert predicts a new balance between human and machine intelligence is on the horizon. For that to be good news, researchers need to figure out how to design algorithms that are fair.
Algorithms can reinforce existing biases in society.
Shutterstock
Technology firms should use more design fiction to explore and avoid potential negative consequences, such as AI bias.
Specialist machine learning and narrow AI could help us to start removing the “four Ds” - dirty, dull, difficult, dangerous - from our daily work.
from www.shutterstock.com
Artificial intelligence is predicted to contribute some US$15.7 trillion to the global economy by 2030. A new report looks at issues specific to New Zealand.
When algorithms are at work, there should be a human safety net to prevent harming people. Artificial intelligence systems can be taught to ask for help.
What do the Carlos Ghosn scandal, the rising power of algorithms and the "gilets jaunes" have in common? The need to extend the spatial and temporal definitions of responsibility.
What can an algorithm find when it reads a book?
Vasilyev Alexandr/Shutterstock.com
Artificial intelligence poses opportunities as well as dangers; understanding them – and regulating carefully – will help avoid harm to individuals and society as a whole.
Biometric Mirror is an interactive application that takes your photo and analyses it to identify your demographic and personality characteristics.
Shutterstock
Information on social media can be misleading because of biases in three places – the brain, society and algorithms. Scholars are developing ways to identify and display the effects of these biases.