Public Accountability: Understanding Sentiments towards Artificial Intelligence across Dispositional Identities

Abstract

Artificial Intelligence (Al) and Machine Learning (ML) have been influential across many industries. Companies, nearly every day, are finding new means and methods of benefiting from these technologies. Despite this prevalence, individuals still report a significant level of distrust towards Al and its applications. To rehabilitate the relationship between Al and its consumers, developers must expose these new technologies to consumers and include them in the process of critiquing and assisting in the improvement of such technologies. The goal of this work is to introduce a new initiative towards an Ethical Al society. Participants are given the opportunity to learn about modem applications of Al and the space to reflect on these technologies. It is found that across the exampled technologies, differences of opinions are significantly correlated to specific dispositional identities, such as gender and computing experience. Furthermore, trends of trust across the general public are compared to that of students enrolled in a computer science course. These results depict vastly differing opinions across technologies which validate the need for public exposure and critique. This work highlights the need for researchers and developers to investigate opinions across dispositional identities, including race, gender, socioeconomic status, etc. The study has shown to be beneficial, with over 70% of individuals reporting having learned about a new application of Al.