The Customer Service Journal

Volume 4 December 2018

Knowledge for the World of Customer Service & Support

ISSN: 2374-9296

AI Robotic Automation News & Commentary



Why Companies That Wait to Adopt AI May Never Catch Up


by Vikarm Mahidhar and Thomas H. Davenport, Harvard Business Review


"While some companies — most large banks, Ford and GM, Pfizer, and virtually all tech firms — are aggressively adopting artificial intelligence, many are not. Instead they are waiting for the technology to mature and for expertise in AI to become more widely available. They are planning to be “fast followers” — a strategy that has worked with most information technologies.

We think this is a bad idea. It’s true that some technologies need further development, but some (like traditional machine learning) are quite mature and have been available in some form for decades. Even more recent technologies like deep learning are based on research that took place in the 1980s. New research is being conducted all the time, but the mathematical and statistical foundations of current AI are well established."


Editor's Comment: The authors explore the different issues that need to be addressed in order to implement AI.  One gets the sense from reading the article that companies will face their own internal maturity curve which argues for early adoption to  fully realize the benefits.


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The AI Revolution That Was And Wasn't In 2018


Kalev Leetrau - Contributor - Forbes

"Looking back on 2018, this has been a year in which AI has continued its meteoric rise over the digital landscape, infusing its magical powers into almost every corner of every industry and revolutionizing how society uses data. Or so one might be forgiven for thinking this year as companies big and small have rushed to demonstrate how they are harnessing deep learning to upend their business processes. The reality is that while AI has truly transformed areas like audiovisual recognition, given us powerful new tools for understanding language and offered a first glimpse at algorithms that possess glimmers of intuition, the mundane reality of the overwhelming majority of commercial AI applications to date have frequently offered little improvement over the traditional approaches they replaced if those systems had been built properly to begin with."


Editor's comment:  Kalev offers a counter argument to those who applaud the rise of AI with interesting observations on the difficulty of applying deep learning to business challenges.


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Every Leader’s Guide to the Ethics of AI


by Vikarm Mahidhar and Thomas H. Davenport, MIT Sloan Management Review

"Ethical issues with AI can have a broad impact. They can affect the company’s brand and reputation, as well as the lives of employees, customers, and other stakeholders. One might argue that it’s still early to address AI ethical issues, but our surveys and others suggest that about 30% of large companies in the U.S. have undertaken multiple AI projects with smaller percentages outside the U.S., and there are now more than 2,000 AI startups. These companies are already building and deploying AI applications that could have ethical effects."


Editor's comment:  Interesting view point that isn't often discussed.


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