Future Performance Measurements in the Age of AI

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39 pages
Practical guidelines for measurements and ethics are discussed. Each chapter ends with thinking questions and a small business case.
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Sobre el autor

Frank is a former business leader and entrepreneur and recent academic, now turned author and researcher focused on Artificial Intelligence ethics and self-regulation.

Leading up to current engagements is a career path that started with civil engineering, then coding, Information...


Yesterday’s approaches to measuring must change to control emerging technologies in commerce, control meaningfulness of work-life, control ethics in AI. Responsibility lies with business leaders to set policy, managers to execute decisions, and workers to remain engaged. 

Practical guidelines for measurements and ethics are discussed. Each chapter ends with thinking questions and a small business case. 

The second edition of a companion book Measuring Performance at the Workplace addresses similar points for traditional industries.

About the author

Following a corporate career in Industrial Engineering with global US corporations, Dr. Wolf taught in the week-end MBA program at the H. Wayne Huizenga School of Business and Entrepreneurship, at NSU in Ft Lauderdale, Florida, for more than sixteen years until 2016. The courses were quantitatative such as Operations Management, Supply Chain Management, Best Practices and Business History, Quantitative Modeling, and Business Strategy. Currently, he is in private practice as an arbitrator/mediator for FINRA (Financial Markets Regulatory Autority) in the USA and pursues research in Artificial Intelligence related to society and ethics, and Board memberships as a public service.

Society Memberships

  • AAAI Association for the Advancement of Artificial Intelligence
  • APICS American Production and Inventory Control Society
  • FINRA Financial Industry Regulatory Authority (US), arbitrator, mediator
  • The Chemist Club, New York

Dr. Wolf can be reached at frkwlf@gmail.com, 828 989 9259 (US)

  • About the Author
  • Foreword 
  • Introduction 

  1. Meaningful Work 
  2. Measuring Artificial Intelligence (AI) Projects 
  3. Measurements for web-based- and Platform Businesses 
  4. Happiness, Cause & Effect, Indexing and Employee Self-Measurement 

  • References And Resources