A Question Of Trust: Consumer Confidence And Trust In Machine Learning Is Rising

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Consumer trust in Machine Learning is growing as adoption of services enabled with the technology becomes the norm.

We recently polled 2,000 UK consumers for the ‘Managing Consumer Anxiety In The Age Of Machine Learning’ Report, which showed that despite 40% of respondents finding the concept of Machine Learning ‘scary’, more than half (52%) valued the increased productivity and efficiency that it delivers and a third (32%) were confident about businesses using the technology.

These findings suggested that adoption of every day services, such as music, news, entertainment and travel recommendations generated by Machine Learning, are the gateway products that are building consumer trust for the technology.

Travel direction (38%), music suggestions (33%) and recommendation for entertainment (26%) were the three most trusted use-cases for Machine Learning, which has been born out of consumers becoming confident with trusted companies and brands, such as Google maps, Spotify, Netflix and Youtube, who were ‘first movers’ in using Machine Learning capabilities to serve up personalised recommendations.

Trust levels in younger demographics, who have had longer exposure to cultural curation services, were higher with nearly two fifths (37%) of 18-24 year olds trusting Machine Learning to make music suggestions – perhaps accounting for the fact that 72% of all Spotify’s streams come from Millennial audiences.

And, it seems UK adults are starting to trust Machine Learning with more than just directions or entertainment suggestions; 21% would trust it to secure their homes, 10% would trust medical advice delivered by Machine Learning, and 9% would trust legal advice powered by the technology. 7% would even trust Machine Learning to teach their children.

However, while consumer confidence and trust around Machine Learning is growing, to ensure that the technology continues to win favour with end-users, technology leaders need to devote varying levels of resources to building and maintaining this trust, depending where their customers are in their Machine Learning acceptance journey. And our research shows the best way to achieve this is by using a combination of consumer education, transparency of business process and consumer choice.

For instance, organisations will need to devote considerably more resources if they wish to offer legal advice and children’s education services compared to music recommendations and travel directions. However, the fact there are increasing numbers of consumers saying they would trust Machine Learning for crucial life decisions underlines its transformational potential.