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Artificial Intelligence Has Yet To Break The Trust Barrier Posted on : Jan 13 - 2021

Trust is the glue that holds enterprises and processes together, and lately, more of that trust has being relegated to artificial intelligence. How much decision-making can and should be entrusted to the machines? We often trust AI recommendations for books related to the ones we have purchased. We are learning to trust AI to help guide our trucks and cars, applying warnings and brakings in traffic situations. Our call-center staff trust AI-generated recommendations to upsell the customers they have on the line. We let AI move more valuable customers to the head in line of queues. But how trustworthy is AI? Maybe more, maybe less trustworthy than we perceive it to be — it depends on the situation.

That’s the conclusion drawn by Chiara Longoni and Luca Cian in a recent analysis posted in Harvard Business Review. Consumers, for example, “tend to believe AI is more competent at making recommendations when they are seeking functional or practical offerings.” But they prefer human judgement “when they are more interested in an offering’s experiential or sensory features.”

In terms of corporate decision-making, at least one in four executives responding to a survey released by SAS, Accenture Applied Intelligence, Intel and Forbes Insights, report they had to manually intervene to override an AI-generated decision. Still, a majority are still happy with the results of their AI efforts and intend to keep moving forward. Close to three-fourths of executives, 74%, recognize that close oversight of AI is essential, the survey also shows. (I was part of the team that designed and analyzed the study, as part of my work with Forbes Insights.)

Longoni and Cian explored consumer trust with AI in a series of experiments involving 3,000 consumers. Among their conclusions: “Simply offering AI assistance won’t necessarily lead to more successful transactions. In fact, there are cases when AI’s suggestions and recommendations are helpful and cases when they might be detrimental.”

They call reliance on AI’s recommendations a “word-of-machine effect,” which stems from a belief that AI systems are more competent than humans in dispensing advice on “utilitarian qualities” — such as selecting hair-care products. However, the opposite is true, as humans are just as capable of assisting with such choices. “Vice versa, AI is not necessarily less competent than humans at assessing and evaluating ‘hedonic’ attributes” — involving sensory experiences. “AI selects flower arrangements for 1-800-Flowers and creates new flavors for food companies such as McCormick.” View More