Reviews:

“The world of workplace learning will be dominated by AI within a few years. Artificial Intelligence for Learning plots a clear and concise path through what is the biggest opportunity the industry has had for many years.”

—Paul McElvaney, CEO of Learning Pool

“Donald Clark has been at the leading edge of technology in learning for over 30 years. His take on tech is always informed by his detailed knowledge of learning theory. This book on AI is no exception - it’s bold, thorough, bang up to date, well-researched, evidence-based and practical.”

—Kirstie Donnelly MBE, CEO of City & Guilds Group

Description:

Artificial intelligence is creating huge opportunities for workplace learning and employee development. However, it can be difficult for L&D professionals to assess what difference AI can make in their organization and where it is best implemented. Artificial Intelligence for Learning is the practical guide L&D practitioners need to understand what AI is and how to use it to improve all aspects of learning in the workplace. It includes specific guidance on how AI can provide content curation and personalization to improve learner engagement, how it can be implemented to improve the efficiency of evaluation, assessment and reporting and how chatbots can provide learner support to a global workforce.

Artificial Intelligence for Learning debunks the myths and cuts through the hype around AI allowing L&D practitioners to feel confident in their ability to critically assess where artificial intelligence can make a measurable difference and where it is worth investing in. There is also critical discussion of how AI is an aid to learning and development, not a replacement as well as how it can be used to boost the effectiveness of workplace learning, reduce drop off rates in online learning and improve ROI. With real-world examples from companies who have effectively implemented AI and seen the benefits as well as case studies from organizations including Netflix, British Airways and the NHS, this book is essential reading for all L&D practitioners needing to understand AI and what it means in practice.

Critically assess the impact of artificial intelligence on the L&D function and understand how to use it to improve learning in the workplace.

Key features at a glance:

• Shows how to use AI to curate and personalize learning content to improve learner engagement
• Debunks the myths around AI and explains how to cut through the hype and critically assess the impact of artificial intelligence on L&D
• Provides guidance on how artificial intelligence can be used to improve the assessment, evaluation and measurement of learning in organizations
• Explains how AI can be used as an aid in employee learning and is not a replacement for L&D professionals
• Includes case studies and real-world examples from companies including Netflix, British Airways, Vision Express and the NHS

Contents:

About the author

About this book

Preface
Acknowledgements

List of abbreviations

PART ONE: Introduction

Chapter 01: Homo technus • Technological revolutions • Culture • Philosophy and mathematics • Learning technology • Conclusion • References

Chapter 02: What is AI? • AI as idiot savant • AI is many things • AI and intelligence • AI as competence without comprehension • AI as collective competence • AI learns • AI in learning • References

PART TWO: Teaching

Chapter 03: Robot teacher fallacy • Anthropomorphizing AI in learning • Reductive robot fallacy • Teaching versus technology • References

Chapter 04: Teaching • AI for teacher administration • AI for teaching activities • AI for enhancing teaching • AI and online learning make you a better teacher • References

PART THREE: Chatbots

Chapter 05: AI is the new UI • Invisible interface • Learning interfaces • Voice in learning • Future interfaces • Conclusion • References

Chapter 06: Chatbots • The tutorbot that fooled everyone • Chatbots and learning theory • Uses of chatbots in learning • References

Chapter 07: Building chatbots • Building or buying a chatbot • Chatbot abuse • Botched bots • Caution • Conclusion • References

PART FOUR: Learning

Chapter 08: Content creation • Learning science • Text • Natural language processing (NLP) • Content creation • Summarize text content • Adapt language content • Create content from existing resources • Open input content • Create content from scratch • Conclusion • References

Chapter 09: Video • What can we learn from YouTube? • What can we learn from Netflix? • Video and AI • AI turns video into deep learning • Retrieval • Conclusion • References

Chapter 10: Push learning • Peer learning • Nudge learning • Campaigns • Interleaving • Spaced practice • Conclusion • References

Chapter 11: Adaptive learning • Adaptive learning • Types of adaptation • Adaptive results • Conclusion • References

Chapter 12: Learning organizations • What can we learn from Amazon? • AI and informal learning • Moments of need • From LMS to LXP • Organizational learning • Conclusion • References

Chapter 13: Assessment • Recruitment and assessment • Digital identification • Plagiarism and AI • Automatic essay assessment • References

PART FIVE: Data

Chapter 14: Data analytics • Sources of data • Data pitfalls • Types of data • Learners and data • Learning analytics • Level 1 – describe • Level 2 – analyse • Level 3 – predict • Level 4 – prescribe • A/B testing • Learning analytics and organizational change • Conclusion • References

Chapter 15: Sentiment analysis • Social learning • Sentiment analysis • Digging deeper • Conclusion • References

PART SIX: Future

Chapter 16: Future skills • AI and learning design • AI and technology design • AI and data design • AI as agile production • AI and procurement • Conclusion • References

Chapter 17: Ethics and bias • Brains and AI • Human bias and AI • Common charges • AI as statistics • Avoiding bias • Pedagogic concerns • Doomsday is hot • Conclusion • References

Chapter 18: Employment • 47% of jobs will be automated… • 65% of today’s students will be employed in jobs that don’t exist yet… • Professions and AI • Learning jobs and AI • Under- and unemployment • Conclusion • References

Chapter 19: The final frontier • AI, AR and VR • Neurotech • Runaway learning • References

Chapter 20: Where next? • Technology • Utopian • Dystopian • References

Index

About the Author:

Donald Clark has over 30 years’ experience in online learning, simulations, virtual reality, mobile and artificial intelligence projects. He was a founding member of Epic Group plc and the Founder and CEO of Wildfire Learning. He is a frequent global speaker, blogger, advisor and researcher on AI in learning and is also a Visiting Professor at the University of Derby.

Target Audience:

Useful for HR and Learning & Development practitioners who need to understand AI and what it means in practice.