November 22, 2021 - Podcast

Episode 206—Best times to invest, and the uncanny valley

If you are looking to invest in the next big startup, researchers from the IU Kelley School of Business and the University of Central Florida suggest consulting your circadian rhythm. In a new study, researchers looked at time-based factors – such as the time of day and whether you’re a morning or evening person – and discovered that those factors can influence our investment decisions and our ability to evaluate whether a startup will be successful. The researchers also studied how lack of sleep affects the cognitive skills we need to be successful in evaluating ideas and making better decisions. IU assistant professor Cristiano Guarana, a co-author on the study, says when individuals evaluated an investment opportunity at a time that conflicted with their body’s natural internal clock – for example, a morning person made a decision late in the evening – the person tended to make poor choices. Over time, decision making at the wrong time could result in substantial losses for people who, on average, don’t possess much investment knowledge, Guarana says. The researchers also found that night owls invested more in an unsuccessful venture in the morning, while morning people, or larks, invested more than night owls in an unsuccessful venture in the morning. And the same types of errors occurred, in the opposite direction, with successful ventures. Guarana says that, with websites making it easier than ever for amateur investors to jump into equity crowdfunding with the click of a button, determining when you are best equipped to make those decisions can really impact your success.

In other news, robots are becoming more realistic every day. But have you ever seen a video of a robot so realistic that it’s unsettling, and you don’t know exactly why? Karl MacDorman, a human-computer interaction expert from the IU School of Informatics and Computing at IUPUI, conducts research on that effect, called the uncanny valley. But when it comes to why people respond in this uneasy way to robots, MacDorman suspects there could be at least two dozen theories. Together with Alexander Diel, a researcher from Cardiff University, MacDorman recently organized current explanations into nine classes, ranging from category uncertainty to threat avoidance. They then tested the theories in an experiment. One leading theory behind the uncanny valley experience is perceptual mismatch. The uncanny valley effect is probably caused by some robot features appearing human and other features not appearing human, he says. As robotic designers work towards their ultimate goal of creating a robot or android that is indistinguishable from humans, MacDorman says they also need to develop models of human interaction that can be implemented in the android to see if they are true to life. And if they aren’t, he says, the designers will find out quickly because the impact of the resulting design will be uncanny. In that way, the uncanny valley is a good thing. It helps researchers better understand human interaction and helps designers create more lifelike robots and virtual characters.