Superimposing Natural Intelligence on Artificial Intelligence: Optimizing Value

Posted June 23, 2020 | Leadership | Technology | Amplify
Tad Gonsalves and Bhuvan Unhelkar argue that while machine intelligence facilitates smart automation and autonomous operations, yielding benefits, it cannot handle decisions that need to account for subjective factors, such as satisfaction, perceived quality, or joy, which cannot be parameterized in an ML algorithm. The authors recommend judicious superimposition of human natural intelligence (NI) on machine intelligence as a better way to facilitate business decisions that factor in customer value. In their discussion of how to achieve this goal, they also present a few use cases that embrace this hybrid intelligence.
About The Author
Tad Gonsalves
Tad Gonsalves is a Professor in the Department of Information & Communication Sciences at Sophia University, Tokyo, Japan. His research interests include computational intelligence and machine learning algorithms as well as bio-inspired optimization techniques for engineering and business applications. Dr. Gonsalves is also actively engaged in designing image recognition and low-cost autonomous driving systems. As an educator, his passion is… Read More
Bhuvan Unhelkar
Bhuvan Unhelkar (BE, MDBA, MSc, PhD; FACS) is a Cutter Expert. He has decades of strategic as well as hands-on professional experience in the information and communi­cations technologies (ICT) industry. Dr. Unhelkar is a full Professor at the University of South Florida, Sarasota-Manatee campus. As a founder of MethodScience and PLATiFi, he has demonstrated consulting and training expertise in big data (strategies), business analysis (use cases… Read More
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