Chatbots, Humbots, and the Quest for Artificial General Intelligence

TLDR: The conversational agent space, difficulties in meeting user expectations, potential new design approaches, uses of human-bot hybrids, and implications for the ultimate goal of creating software with general intelligence are described.

Abstract: What began as a quest for artificial general intelligence branched into several pursuits, including intelligent assistants developed by tech companies and task-oriented chatbots that deliver more information or services in specific domains. Progress quickened with the spread of low-latency networking, then accelerated dramatically a few years ago. In 2016, task-focused chatbots became a centerpiece of machine intelligence, promising interfaces that are more engaging than robotic answering systems and that can accommodate our increasingly phone-based information needs. Hundreds of thousands were built. Creating successful non-trivial chatbots proved more difficult than anticipated. Some developers now design for human-chatbot (humbot) teams, with people handling difficult queries. This paper describes the conversational agent space, difficulties in meeting user expectations, potential new design approaches, uses of human-bot hybrids, and implications for the ultimate goal of creating software with general intelligence.