Algorithms now play a pivotal role in the economy and society. But their sheer prevalence mean that it’s all the more important that we know, understand, and trust their output. This is particularly pertinent when artificial intelligence is deployed to make critical decisions that can adversely affect individuals – such as banks and other financial services organisations using it to deny loans and credit card applications or misdiagnosing a disease or illness.
Complimentary insight paper:
Trust, Actually
She explains that trying to get trust in data and algorithms is not necessarily a matter of mind over heart.
Our working hypothesis was that testing was the way to increase trust in algorithms," writes Nicola. "That’s not incorrect but our research has established that it is inseparably a culture and user experience issue too. You’ve got to win people’s hearts, as well as minds – it really comes down to either working with, or understanding, the people who are going to be using them. Only then will trust take deep and permanent root across the digital landscape."
