guest Article by Ming-Hui Huang and Roland T. Rust

Artificial intelligence (AI) is advancing rapidly, and its impact on service promises to be profound.  Although AI has not yet shown its full potential in business, scientific progress appears to be at an inflection point, and the number of AI applications in service is increasing rapidly.  It is useful to analyze AI as involving four distinct intelligence levels.  “In the order in which scientific development in AI is taking place, the four levels are mechanical (using AI for routine and repetitive tasks), analytical (using more complicated logic and analysis), intuitive (coming up with holistic understanding and sensing patterns), and empathetic (understanding and emulating human emotions)” says Huang.  “Many people still believe that AI is limited to mechanical, routine tasks, but scientific development in AI shows that this isn’t true–AI in service is likely to involve all four intelligence levels,” says Rust.  As AI masters more and more service tasks, human service jobs will be eliminated.  We already see this for many mechanical service tasks, for example, with customer service jobs being lost to automated phone menus.  Given that the order of AI development is roughly from mechanical to analytical to intuitive to empathetic, it is possible to predict that the next big wave of service job losses will be those that involve analytical tasks.  IBM’s Watson system, for example, already creates marketable products that perform analytical (and to some degree, intuitive) tasks.  Eventually analytical, intuitive and empathetic tasks will all be successfully performed by AI.  One firm is using AI for financial portfolio analysis.  An empathetic robot, Sophia, has already been named a citizen of Saudi Arabia.  Managers should be open to developing ways to use AI for all service tasks, starting with the most routine.  Service employees should seek to avoid jobs that will be easily taken over by AI.  These are mostly mechanical jobs today, but soon analytical jobs will be under threat. Our mathematical model shows how the relative importance of the four intelligence levels for service labor will change. The job skills that will take longest for AI to take over will be the “softer” people skills of intuition and empathy.  Our business schools should be emphasizing those skills the most.  Ultimately we may be faced with the “singularity” described by Ray Kurzweil, in which AI is smarter than humans for all four levels of intelligence.  In that scenario, we may need to be creative about how human service employees can remain relevant.  One possibility is that humans may need to become “trans-human” (extending human capabilities using AI).  Recently scientists in South Africa succeeded in connecting a human brain to the Internet.  In the extreme, we may have a network of human brains all connected to the Internet—a human analog to the Internet of Things that we call the Internet of Brains.  Such connectedness will greatly accelerate learning in the service environment—expanding service capability just as the beehive expands the capability of individual bees.

A forthcoming article in the Journal of Service Research, “Artificial Intelligence in Service,” by Ming-Hui Huang and Roland T. Rust, investigates how AI is likely to develop in the service economy, and what the likely implications are for service jobs and marketable job skills. A copy of the forthcoming article may be obtained from the authors.

Ming-Hui Huang (huangmh@ntu.edu.tw)

Distinguished Professor of Electronic Commerce at National Taiwan University

 

 

Roland T. Rust (rrust@rhsmith.umd.edu)

Distinguished University Professor and David Bruce Smith Chair in Marketing at the Robert H. Smith School of Business

Executive Director of the Center for Excellence in Service.

 

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