How Intelligent Technologies Affect People and Practices

The Fourth Industrial Revolution has already arrived and is revolutionizing the landscape of organizational research (e.g., Brynjolfsson & McAfee, 2014; 2017; Brynjolfsson & Mitchell, 2017). In particular, as organizations worldwide are navigating through this new wave of industrial revolution (in which intelligent machines are increasingly becoming part of modern workplace), our conventional wisdom about work practices, interpersonal relationships, and the management of organizations needs to be refined. Each of the papers provides a new avenue to the implications of intelligent technologies on people and practices in organizations by emphasizing how the incorporation of such technologies may specifically affect individuals, managers, as well as other organizational stakeholders. Towards this end, the papers in this symposium take on the challenge to understanding more broadly on how intelligent technologies may affect people and practices across different levels of theorization and analysis. Overall, this symposium seeks to continue the societal conversation inspired by the uprise of intelligent technologies and provide answers to outstanding questions (raised by both organizational scholars and managers), while also setting a research agenda for the future. Interacting with Artificial Intelligence and Its Implications on Employee Work and Non-work Behavior Author: Pok Man Tang; U. of Georgia Author: Joel Koopman; Texas A&M U. Author: Haoyue Zhang; Nanyang Business School, NTU Singapore Author: Philipp Reynders; Cardiff U. Author: Chin Tung Stewart Ng; Institute of Human Resource Management, National Sun Yat-sen U. Author: I-Heng Chen; National Sun Yat-Sen U. Feedback from Artificial Intelligence: Reactions of the Stigmatized to Algorithm-driven Feedback Author: Ji Woon Ryu; Portland State U. Author: Roshni Raveendhran; U. of Virginia Darden School of Business Author: Cristiano L O Guarana; Indiana U. - Kelley School of Business Using Advanced Text Analysis to Increase Prediction and Reduce Subgroup Differences in Selection Author: Emily D. Campion; U. of Iowa Author: Michael A Campion; Purdue U. Author: James Johnson; United States Air Force Academy Author: Thomas Carretta; United States Air Force Author: Sophie Romay; United States Air Force Author: Bobbie Dirr; U.S. Air Force Author: Andrew Deregla; United States Air Force Author: Amanda Mouton; United States Air Force Hungry for Data: Examining How Developing AI Technology Reconfigures Organizations Author: Jodie Koh; Northwestern Kellogg School of Management Author: Hatim A. Rahman; Northwestern Kellogg School of Management Moral Spillover from Creators to Autonomous Technological Agents Author: Arthur S. Jago; U. of Washington, Tacoma