What Is Algorithm Aversion

Algorithm aversion refers to the tendency of decision makers to rely on human judgment instead of algorithms, even when the algorithms are known to be better. A study found that people are more likely to use imperfect algorithms if they have some control over the decision-making process. Even a small amount of control can increase algorithm usage and improve accuracy. The desire for control is a common human trait, and people feel more comfortable when they can exert some influence over a situation. This applies to various domains, including self-driving cars, where people prefer to have the option of manual control. The study also highlights the ethical dilemma of algorithmic decision-making, with the example of the trolley problem. In the case of autonomous vehicles, while there have been advancements, challenges remain in handling unexpected scenarios. Despite the potential benefits, any accidents involving self-driving cars are likely to have a significant impact on public perception. This is due to the tendency to irrationally penalize algorithms and robots for imperfections compared to human error. However, as technology continuously evolves, there is hope that algorithm aversion will gradually diminish and people will become more accepting of algorithms.