The fundamental problem with AI is it is often riddled with society's existing biases and prejudices.
Technology firms should use more design fiction to explore and avoid potential negative consequences, such as AI bias.
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.
Social biases in digital tech create racist face recognition software and sexist hiring tools, but more data collection isn't the answer.
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.
An ethicist on why fixing algorithms may not be the best response to algorithmic bias.
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.
Some AI technologies aren't advanced enough to provide useful insights, but simpler tools can yield new opportunities to explore the humanities.
Expecting algorithms to perform perfectly might be asking too much of ourselves.
Artificial intelligence poses opportunities as well as dangers; understanding them – and regulating carefully – will help avoid harm to individuals and society as a whole.
A new tool called Biometric Mirror exposes the need for public debate about the ethics of AI.
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.