At Google's annual developer conference this past week, CEO Sundar Pichai played a clip of what seemed to be a mundane human interaction: Someone calling to make an appointment with their hairdresser. The two voices negotiated the date and time, with the "assistant" providing the client's name for the reservation. Instead, Pichai said, it was Google's artificial intelligence making the call to the unwitting hair salon receptionist. The technology is called Google Duplex, a system that combines natural language processing and speech generation that allegedly allows Google to accomplish customer service tasks in a number of limited situations. Right now, the company is only testing the technology internally, focusing on booking reservations at restaurants and hair salons, as well as inquiring about holiday hours for businesses.

Explainable Recommendation refers to the personalized recommendation algorithms that address the problem of why -- they not only provide the user with the recommendations, but also make the user aware why such items are recommended by generating recommendation explanations, which help to improve the effectiveness, efficiency, persuasiveness, and user satisfaction of recommender systems. In recent years, a large number of explainable recommendation approaches -- especially model-based explainable recommendation algorithms -- have been proposed and adopted in real-world systems. In this survey, we review the work on explainable recommendation that has been published in or before the year of 2018. We first high-light the position of explainable recommendation in recommender system research by categorizing recommendation problems into the 5W, i.e., what, when, who, where, and why. We then conduct a comprehensive survey of explainable recommendation itself in terms of three aspects: 1) We provide a chronological research line of explanations in recommender systems, including the user study approaches in the early years, as well as the more recent model-based approaches. 2) We provide a taxonomy for explainable recommendation algorithms, including user-based, item-based, model-based, and post-model explanations. 3) We summarize the application of explainable recommendation in different recommendation tasks, including product recommendation, social recommendation, POI recommendation, etc. We devote a chapter to discuss the explanation perspectives in the broader IR and machine learning settings, as well as their relationship with explainable recommendation research. We end the survey by discussing potential future research directions to promote the explainable recommendation research area.

Amazon's Echo Dot and its accompanying version of Alexa for kids called FreeTime raised eyebrows and questions about children's privacy from the start. Now, Sen. Edward J. Markey (Massachusetts) and Rep. Joe Barton (Texas) want to know what the e-commerce giant is doing to ensure the privacy of kids who use the speaker and the voice assistant. The lawmakers have penned a letter to Amazon asking if kids' interactions with the speaker are saved and shared with third parties. They also want to know if the company worked with child development experts when they designed the device. The tech giant answered some of the lawmakers' concerns in a statement, telling CNET that "Amazon takes privacy and security seriously, and FreeTime on Alexa is no different."

Over the years of teaching and research, I have gradually standardized the notation that I use for describing the math of recommender systems. This is the notation that I use in my classes, Joe Konstan and I have adopted for our MOOC, and that I use in most of my research papers. If you haven't already settled on a notation, perhaps you would consider adopting this one. I have tried to strike a balance between clarity and clutter. I slightly overload the meaning of some symbols; in particular, I am loose with distinctions between sets and matrices, because it is generally clear from context which is being invoked; I do not overload external referents, however.

For wealth managers, losing clients can be detrimental. When longstanding client relationships dissolve, it can be a blow to advisors' revenue and reputation. Not to mention, replacing them can cost significant money and time. As financial advisors aim to strengthen relationships, retain valued clients and attract new business, artificial intelligence is an overlooked and underutilized tool. Emerging technology continues to dominate the conversation in the wealth management community, and the jury is still out on how the advent of robo advisors and similar technology will influence the advisory industry for better or worse.

Google's Duplex could make Assistant the most lifelike AI yet Richard Nieva, CNET Google has big plans for Assistant, and some of what it showed at I/O this week is equal parts fascinating and worrisome. CNET took a closer look at the so-called Duplex technology that will allow Google Assistant to do things like make phone calls on your behalf. The company has since said it will alert the person on the other end that they're speaking to AI, but for many, questions remain. If there's one thing I've learned over the last few years, it's that when Coates publishes something, it's going to be worth your time. This piece about the current state of Yeezus is no exception.

Health care is a $3 trillion a year industry, and tech companies such as Amazon are vying for a slice of it. In January, the e-commerce giant announced a partnership with JPMorgan and Berkshire Hathaway to "revolutionize health care." Chiefly, this joint partnership would work toward developing a less costly health care network for their employees, but the exact aims and methods are otherwise vague. It's also been rumored periodically that Amazon might enter the pharmaceutical business. Now, reports suggest Amazon is interested in building health care applications directly into its virtual assistant, Alexa.

Mother's Day is on Sunday, which makes this a great time to buy...well, a lot of things. Amazon's Mother's Day deals are still going on strong. So is this unbelievable deal on the Plantronics Voyager 8200 UC headphones, which our headphone connoisseur Jeffrey Van Camp loved, and which is still $135 off. You also still have time to pick up some Beats headphones from Apple. But even if you're not in the market for a Kindle or headphones, we've worked together with our pals at TechBargains to find other great tech deals for you this weekend.

BROADBAND BREAKFAST INSIGHT: I watched this video of Google CEO Sundar Pichai demonstrating Google Assistant, and I also was impressed. While I agree that there are some real social engineering issues raised by the assistant, I'm not sure that "disclosure" requirement called for by some of the technology's critics really meet the mark. Is there a need for "disclosure" that one is riding in a driverless car? Google Duplex was the talk of Google I/O, the company's annual developer conference that kicked off this week. Google CEO Sundar Pichai unveiled the new product himself on Tuesday: Basically, you can ask Google Assistant to call a business on your behalf, and Google's AI will schedule an appointment for you.

Google CEO Sundar Pichai took a giant leap in the wrong direction this week. At his company's I/O developer conference, Pichai wowed the crowd by using a virtual assistant to fool people, making unsuspecting humans the target of laughter and raising serious ethical questions about future uses for AI. Hair salon: Hello, how can I help you? Google Assistant: Hi, I'm calling to book a woman's haircut for a client. Hair salon: Sure, give me one second.