Why Google Duplex Did Not Pass the Turing Test

Recently, a lot of press was given to Google’s Duplex Artificial Intelligence (AI) bot. The Duplex bot calls businesses, such as a restaurant, on your behalf and makes a reservation. We’re going to save for another day the potential ethical issues raised by AI bots fooling people into believing they are talking to a person. Instead, let’s focus on whether or not Duplex has successfully passed the Turing test as some have suggested.

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Bill Franksbill franks
Will Data Scientist Continue to be the Sexiest Job?

Back in 2012 I wrote (with D.J. Patil, who went on to become the Chief Data Scientist in the White House) an article in Harvard Business Review called “Data Scientist.” Nobody remembers the title or much about the content of the article, but many remember the subtitle: “Sexiest Job of the 21st Century.” At the time (and still today), these jobs paid well, were difficult to fill, and required a very high level of analytical and computational expertise. But a more accurate subtitle might have been “Sexiest Job of the 2010-2019 Decade,” because I am not sure how much longer data scientists will be in great demand.

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84.51° Builds a Machine Learning Machine for Kroger

84.51°’s Chief Operations Officer, Milen Mahadevan, is a champion for automation of processes and products within the organization. 84.51°’s Shop, a custom-built BI platform that allows CPG customers to pull detailed reports about shopping behavior, is a successful example of BI automation.

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Why Analytics of Things Standards are Needed

As the Internet of Things (IoT) continues to explode, so does the need for the analysis of IoT data. At IIA, we call the analysis of IoT data the Analytics of Things (AoT). However, without some attention to standards of both IoT data itself and the analysis of it, organizations will struggle to achieve AoT’s potential. In this post, we’ll dig into several different areas where standardization must be pursued.

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Do You Need a Ph.D. to Run Analytics or Data Science?

While we are supportive of companies’ efforts to hire quantitative Ph.D.’s to practice data science, we believe that most firms are better off hiring people with other types of training and general management skills to manage analytics and data science groups. Why? Because there are a series of traits that make for effective managers of such groups, and most Ph.D.’s don’t tend to have them. We describe ten of those traits in this blog, and the reasons why they are unlikely to be found in the average doctoral degree holder. The list of traits may be useful for anyone seeking to hire a leader of analytics or data science functions-whether they are considering Ph.D.’s or not.

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Can Process Robots Deliver Digital Transformation?

One of the fastest-growing areas of artificial intelligence—at least if that term is defined broadly—is “robotic process automation,” a set of capabilities for the automation of digital tasks. RPA, as it is often called, has some valuable functions, but digital-centric companies may need more intelligence and process simplification to than RPA can currently provide.

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Why Blockchain and Analytics Don't Mix Well

The concept of a blockchain is quite a phenomenon in recent times. It has quickly risen from a relatively obscure idea known mostly within some small circles to one that is being discussed as having potential to literally change some of the fundamentals of the world’s economic systems.

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Bill FranksComment
Yes, Artificial Intelligence is Analytics

Is AI a form of analytics or is it a totally new discipline that is distinct from analytics? I firmly believe that AI is more closely related to predictive analytics and data science than to any other discipline. One might even argue that AI is the next generation of predictive analytics.

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Bill FranksComment
A Revolution in Analytical Technology

It’s been 10 years since Jeanne Harris and I published our book, Competing on Analytics, and we’ve just finished updating it for early-fall (2017) re-publication. We realized during this process that there have been a lot of changes in the world of analytics.

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Tom Davenport