Artificial Intelligence

Recent surveys, studies, forecasts and other quantitative assessments of the progress of AI, highlighted among other findings, disagreements about the impact of chatbots: Do purchase rates go down when people find out they are interacting with a chatbot? Or do chatbots actually increase customer satisfaction and loyalty? And are chatbots already successful in replacing human workers?

The promise of artificial intelligence (AI) improving our lives is enormous. In less than a quarter of a century, the Internet has grown from niche curiosity to a modern necessity for much of the world. Interpersonal communication has never been easier and social media has profoundly changed how people interact. This same technology that allows for a more efficient and communicative modern life also puts public and personal information at risk and creates new anxieties among the public and policymakers. These heightened concerns should not be a hinderance to the furtherance of technology, but rather, they should serve as a catalyst for necessary reflection and planning. To fully realize the benefits of these technologies, organizational goals must align with defined ethical values and the public interest.

From Sephora to Amazon to Dominos Pizza – major companies have employed chatbots to interact with millions of customers from around the world.

These artificial intelligent systems have been found to outsell human employees by four times and at almost zero marginal costs.

Big Data Analytics and Artificial Intelligence have moved from emerging technologies to become core tools in organizations today. These technologies enable enterprises to dive deeper into ever-growing volume of data to solve multifaceted business problems. In an interview with Analytics Insight, Melissa Bowers, PhD, Director of the Master’s in Business Analytics (MSBA) program at the Haslam College of Business, the University of Tennessee, Knoxville shares how the college offers a cutting-edge business analytics program to train the next generation of data scientists for today’s forward-thinking organizations.

Given the scale of the world’s food supply, there aren’t many industries that lend themselves to the power of data science and analytics than agriculture. This is the thinking behind a new research paper from a group of data scientists who make a case for finding new ways to use blockchain, AI and API management to enable “smart agriculture.”  The paper, “Agricultural Digital Transformation,” has been published in the OR/MS Today journal from the Institute for Operations Research and the Management Sciences (INFORMS).

Russell Allgor, chief scientist for Worldwide Operations at Amazon and INFORMS member, shares how the people who work in Amazon’s fulfillment centers work with the systems guided by artificial intelligence and machine learning to deliver customer orders in the most efficient way possible. 

INFORMS President Ramayya Krishnan shares how AI and automation are impacting the workforce. In particular, he addresses fears of job replacement by automation, stating, "What we have to remember is that a job is a role that consists of a bundle of tasks, so a job itself won't be replaced but some of the tasks may be."

The world is awash in data, and police departments are no exception. Now, they are beginning to make better use of that data. Police departments are starting to use machine learning and layering on artificial intelligence to make smarter, more informed policing decisions. Although the technology is still in its infancy, public safety agencies like the New York Police Department see significant potential in pattern recognition algorithms, AI and the ability to turn unstructured data into structured data that supports and informs police work.

The NYPD has developed new technology called Patternizr, an algorithmic machine-learning software that sifts through police data to find patterns and connect similar crimes. Developed by the New York Police Department, Patternizr is the first tool of its kind in the nation. It's been in use by NYPD since December 2016, but its existence was first disclosed by the department this month.