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Artificial intelligence is changing the world of work. How can HR professionals understand the variety of opportunities AI has created for the HR function and how best to implement these in their organization? This book provides the answers. From using natural language processing to ensure job adverts are free from bias and gendered language to implementing chatbots to enhance the employee experience, artificial intelligence can add value throughout the work of HR professionals. Artificial Intelligence for HR demonstrates how to leverage this potential and use AI to improve efficiency and develop a talented and productive workforce. Outlining the current technology landscape as well as the latest AI developments, this book ensures that HR professionals fully understand what AI is and what it means for HR in practice. Alongside coverage of employee engagement and recruitment, this second edition features new material on applications of AI for virtual work, reskilling and data integrity. Packed with practical advice, research and new and updated case studies from global organizations including Uber, IBM and Unilever, the second edition of Artificial Intelligence for HR will equip HR professionals with the knowledge they need to improve people operational efficiencies, and allow AI solutions to become enhancements for driving business success.
This cutting-edge Handbook offers a comprehensive introduction to the emerging research field of artificial intelligence (AI) in human resource management (HRM). Broadly mapping AI fields relevant for HR, it not only considers the more well-known areas of machine learning and natural language processing, but also lesser-known fields such as affective computing and robotic process automation.
Cover -- The New World of Human Resources and Employment: How Artificial Intelligence and Process Redesign is Driving Dramatic Change -- Contents -- CHAPTER 1: What Is Artificial Intelligence and What Is Its Impact Going to Be? -- CHAPTER 2: Human Resources-On the Front Line for a Change -- CHAPTER 3: How AI and Process Redesign Will Impact on Organizational Structures and Reducing Headcount-Rightsizing Your Organization -- CHAPTER 4: Aligning HR Processes with AI-Productivity Measurement and Performance Appraisal -- CHAPTER 5: Automating Training Needs Analysis and Training Evaluation -- CHAPTER 6: Digital Footprints and How They Can be Used to Upgrade Recruitment and Succession Planning-The End of Testing? -- CHAPTER 7: Pay and Rewards -- CHAPTER 8: New Skills Needed to Manage This Massive Paradigm Shift from Traditional HR To Artificial Intelligence Focused HR -- CHAPTER 9: Useful Formula and the Productivity Dashboard -- References -- About the Author -- Index -- Ad Page -- Back Cover
HR Without People? is a stimulating and confrontational challenge to conventional thinking on this people-centric profession’s role in the future of work.
There is no industry left where artificial intelligence is not used in some capacity. The application of this technology has already stretched across a multitude of domains including law and policy; it will soon permeate areas beyond anyone’s imagination. Technology giants such as Google, Apple, and Facebook are already investing their money, effort, and time toward integrating artificial intelligence. As this technology continues to develop and expand, it is critical for everyone to understand the various applications of artificial intelligence and its full potential. The Handbook of Research on Innovative Management Using AI in Industry 5.0 uncovers new and innovative features of artificial intelligence and how it can help in raising economic efficiency at both micro and macro levels and provides a deeper understanding of the relevant aspects of artificial intelligence impacting efficacy for better output. Covering topics such as consumer behavior, information technology, and personalized banking, it is an ideal resource for researchers, academicians, policymakers, business professionals, companies, and students.
This book directly addresses the explosion of literature about leveraging analytics with employee data and how organizational psychologists and practitioners can harness new information to help guide positive change in the workplace. In order for today’s organizational psychologists to successfully work with their partners they must go beyond behavioral science into the realms of computing and business acumen. Similarly, today’s data scientists must appreciate the unique aspects of behavioral data and the special circumstances which surround HR data and HR systems. Finally, traditional HR professionals must become familiar with research methods, statistics, and data systems in order to collaborate with these new specialized partners and teams. Despite the increasing importance of this diversity of skill, many organizations are still unprepared to build teams with the comprehensive skills necessary to have high performing HR Analytics functions. And importantly, all these considerations are magnified by the introduction and acceleration of machine learning in HR. This book will serve as an introduction to these areas and provide guidance on building the connectivity across domains required to establish well-rounded skills for individuals and best practices for organizations when beginning to apply advanced analytics to workforce data. It will also introduce machine learning and where it fits within the larger HR Analytics framework by explaining many of its basic tenets and methodologies. By the end of the book, readers will understand the skills required to do advanced HR analytics well, as well as how to begin designing and applying machine learning within a larger human capital strategy.
This book is a critique of Artificial Intelligence (AI) from the perspective of cognitive science - it seeks to examine what we have learned about human cognition from AI successes and failures. The book's goal is to separate those "AI dreams" that either have been or could be realized from those that are constructed through discourse and are unrealizable. AI research has advanced many areas that are intellectually compelling and holds great promise for advances in science, engineering, and practical systems. After the 1980s, however, the field has often struggled to deliver widely on these promises. This book breaks new ground by analyzing how some of the driving dreams of people practicing AI research become valued contributions, while others devolve into unrealized and unrealizable projects.
The book explains strategic issues, trends, challenges, and future scenario of global economy in the light of Fourth Industrial Revolution. It consists of insightful scientific essays authored by scholars and practitioners from business, technology, and economics area. The book contributes to business education by means of research, critical and theoretical reviews of issues in Fourth Industrial Revolution.