by Alan Christensen
| ISBN | 9789372421941 |
|---|---|
| Publisher | Digital Drive Learning |
| Copyright Year | 2026 |
| Price | $256.00 |
Communication and artificial intelligence (AI) are closely related. It is communication – particularly interpersonal conversational interaction – that provides AI with its defining test case and experimental evidence. Likewise, recent developments in AI introduce new challenges and opportunities for communication studies. Technologies such as machine translation of human languages, spoken dialogue systems like Siri, algorithms capable of producing publishable journalistic content, and social robots are all designed to communicate with users in a human-like way. Artificial intelligence (AI) and people’s interactions with it—through virtual agents, socialbots, and language-generation software—do not fit neatly into paradigms of communication theory that have long focused on human–human communication. To address this disconnect between communication theory and emerging technology, this article provides a starting point for articulating the differences between communicative AI and previous technologies and introduces a theoretical basis for navigating these conditions in the form of scholarship within human–machine communication (HMC). Today, communication is the most influential factor in idea creation and productivity. Although AI appears most commonly when dealing with communication between businesses and consumers, it also transforms communication within the workplace. Applying AI and machine learning, an organization can shift monotonous, repeated jobs from its workforce to virtual robots, relieving employees to focus on more complex, value added pursuits. Robotic process automation can replace back-office tasks, such as those in finance, accounting, and sales operations. This book has been written keeping in view the requirements of undergraduate and postgraduate students and research scholars in the area of computer science and engineering in particular, and other branches of engineering which deal with the study of AI such as electronics engineering, electrical engineering, industrial engineering.