Robotics and Artificial Intelligence

Biography

Biography: Shannon D Bohle

Abstract

This paper is based on talks that included a demo of my new virtual humanoid embodied AI bot capable of autonomously expressing appropriate emotions using gestures, facial expressions and text-to- voice. It does this while engaging in natural language conversations or giving automated scripted lectures with a slide show presentation.The system employs a touch-interaction-based learning and communication system where the virtual bot responds and learns from touch sense feedback training-a poke (negative reinforcement) or swipe (positive reinforcement)-conveyed through a touch screen. The bot’s predecessor was part of an award-winning project in an international Artificial Intelligence competition advertised by The White House and sponsored by the U.S. Department of Defense. The talk and demo combination consists of a creatively scripted talk given by the AI bot that provides a counterargument to its critics (RAND and a variety of organizations aimed at slowing its progress). Using logos, ethos, and pathos, it argues for its legal and ethical rights for development and suggests specific technical guidance developing AI for their accompanying responsibilities. Embedded in the talk are theoretical foundations for an AI Hierarchy of Needs using landmark studies. These include the work of Maslow; advances in understanding the philosophical, psychological and neurological bases for consciousness and language; The Turing Test; Asimov’s Three Laws of Robotics; Chalmers’ hard problem of consciousness; Robert Plutchik's psychoevolutionary theory of emotion; Paul Ekman’s relationships between nonverbal communication (such as facial expressions) and emotions; classical and operant conditioning for learning (especially Pavlov and Skinner); and the roles of biology and social cognitive neuroscience (for sympathy and empathy capacity). Additionally, the presentation encroaches upon the development of new machine learning techniques based on affective experiences (learned through touch and conversation) for the improvement of human-computer interaction for potential use in a variety of AI- enabled robots.