We are on the precipice of a new era where physical and virtual autonomous systems become even more deeply entwined in our daily lives. These systems are going to fundamentally transform many aspects of society, from the transportation and service industries, to education and the health care sector. They will reshape the way we work, how we travel (driverless cars), recover from injury (aid in surgery and rehabilitation), take care of our loved ones (assistance in nursing and elderly care), think about intimacy (sex), and provide emotional and social support for those in need.

Critically, the smooth and successful assimilation of these systems into daily life requires that people’s attitudes, beliefs, and intentions are positively inclined towards these systems. This not only goes for the individual consumer but also politicians who will craft policies to regulate those systems and implement information campaigns to influence how those systems are used. Simply put, attitudes, beliefs, and intentions are likely powerful predictors of robotic and intelligent system adoption and use. We therefore need to ensure that the former are positive, where they are not, intervene and change them for the better.

Unfortunately, public opinion towards such systems is currently quite negative. In the USA and Europe people are often reluctant to embrace autonomous systems like driverless cars or robotic caregivers. If these negative attitudes persist they may slow the adoption of these systems. They may also influence stakeholders in politics and industry in ways that undermine the introduction and proliferation of those systems. Thus what is clear is that we need to combat misconceptions and negative attitudes towards robotic systems while simultaneously fostering positive attitudes, beliefs, and intentions in their place.

I am currently a visiting scholar at Cornell University working with Melissa Ferguson and Ross Knepper. Here I am interfacing my background in attitudes and behavior change with a new area for me (social robotics and human-robot interaction), in order to identify how (implicit and explicit) attitudes and robot related cognition can be altered in order to improve human-robot interaction and other behavior (e.g., adoption and interaction with robotic and virtual systems). Papers coming soon...