In a 2015 Harvard Business Review article deputy editor Walter Frick discussed algorithm aversion, saying, “Even when an algorithm consistently beats human judgment, people prefer to go with their gut.”
Autonomous technology has advanced considerably since that article was written, but people are still struggling with placing their full trust in innovations driven by artificial intelligence (AI). For example, studies show that nearly 75 percent of Americans are afraid to ride in a self-driving vehicle.
So, what is it that prevents us from trusting in technology? A more recent HBR article, published in early June, delved into some of the underlying factors.
The authors conducted a study with participants in a simulation of typical organizational levels, i.e., employees, middle management, and top management. According to the article, “People think of humans and algorithms as good at providing different types of information, including about who to trust. Humans are seen as a better source of intuition, better at social skills, and better at taking another person’s perspective. But algorithms can provide information about who to trust in cases where that information is less intuitive and more factual.”
In various simulations, study participants accepted an algorithmic determination of another colleague’s trustworthiness, but this was in the early stages of their working relationship. As relationships develop further, the article points out, “People become more reliant on emotion-driven information, which AI is not able to provide yet.”
These and other takeaways from the study underscore that the social skills people rely on to gauge another’s trustworthiness are considered uniquely human and that the reliance on these skills increases as the relationship progresses.
The study’s authors offer a number of tips for organizations to address the trust factor when implementing autonomous technology, including training supervisors to recognize which tasks are more suited to an algorithm and which might be better for a human to perform.
For more on the use of algorithms in the workplace head over to this recent APEX of Innovation post on the topic.