People trust computer algorithms and AI more than fellow human beings: Study

People may be more willing to trust algorithms and computers over humans during more challenging problem-solving situations, according to the data scientists at the University of Georgia. In a new study published in Nature’s Scientific Reports journal, scientists found that in the digital age, technology-savvy people may have more biases towards the AI algorithms to perform a complex task more accurately than their fellow human colleagues or friends. Algorithms have replaced human actions such as replacing songs on the phone, streaming videos, and in fact, the simple household tasks with the digital assistance of AI-enabled machines such as Amazon's Alexa. 

"It seems like there's a bias towards leaning more heavily on algorithms as a task gets harder and that effect is stronger than the bias towards relying on advice from other people," researcher Eric Bogert, the lead author of the study, a Ph.D. student in the Terry College of Business Department of Management Information Systems said. He added, "Algorithms are able to do a huge number of tasks and the number of tasks that they are able to do is expanding practically every day.” Bogert worked in collaboration with management information systems professor Rick Watson and assistant professor Aaron Schecter on the paper. 

“This is a task that people perceive that a computer will be good at, even though it might be more subject to bias than counting objects,” Schecter said. “One of the common problems with AI is when it is used for awarding credit or approving someone for loans. While that is a subjective decision, there are a lot of numbers in there — like income and credit score — so people feel like this is a good job for an algorithm. But we know that dependence leads to discriminatory practices in many cases because of social factors that aren’t considered.”

Relying on computer algorithm for 'harder tasks'

In the study published on April 14, the data scientists asked 1,500 individuals to evaluate photographs. Scientists assigned the simple tasks to count the number of people in a photograph that consisted of a large crowd. They also provided suggestions that were generated by a group of other people and a computer algorithm. The number of people in the photograph increased drastically, making it harder for the evaluating group of people to count. It was then that the volunteers relied on AI rather than humans to determine the count in the photograph. According to Schecter, the counting trial task proved that as the task got harder and harder, the crowd generally expected the computers to be more reliable with information or the knowledge of how to solve the problem better than the human.